FailingCompany - Back to the Basics

We've really covered some ground in the world of AI. Hopefully by now your eyes have been opened to the possibilities at your fingertips. There are a multitude of ways to either partially or fully automate nearly every major function of your business with this technology. If you're like me, then you're probably sitting there reading this with one big question in your mind.

You're probably scratching your head and thinking something like, "Geez, this AI stuff is cool and all, but how do I actually start using it? I'm not even sure where to start!" That's a fair statement. While each article has listed examples of tools and how they are used, we haven't spent enough time on looking at ways to get started. Yes, one of my first articles talks about starting with using AI for research and I stand by that, but perhaps you've done that and are ready to jump in feet first.

There's no one right way to jump into using AI. It's somewhat specific to your business and situation. Out of curiosity, I turned to ChatGPT. I asked ChatGPT to act as a top AI consultant for small businesses and to write an article about the top 5 to 10 things that a small business owner should do to learn about and implement AI in their business. I also asked it to be specific and to provide tangible things that a business owner can start learning or implementing today. There are other AI solutions to ask as well, but I'm partial to ChatGPT. Let's take a look at a Gen AI engine's advice for getting started with AI...

"Embracing Artificial Intelligence: A Guide for Small Business Owners
Artificial Intelligence (AI) has emerged as a transformative force across various industries, offering unprecedented opportunities for efficiency, customer engagement, and innovation. For small business owners, integrating AI can seem daunting due to its perceived complexity and cost. However, with the right approach and resources, even small businesses can harness the power of AI to gain a competitive edge. This article outlines the top steps small business owners can take to learn about and implement AI in their businesses, providing specific and actionable advice.

1. Start with Education and Awareness
The first step in integrating AI into a business is understanding what it is and how it can be applied. Business owners should begin by familiarizing themselves with basic AI concepts, such as machine learning, natural language processing, and computer vision. This can be achieved through:

• Online Courses and Webinars: Platforms like Coursera, edX, and Udacity offer courses on AI and machine learning tailored for beginners. Free resources like YouTube channels and blogs also provide valuable insights.


• Reading and Research: Books like "Artificial Intelligence: A Guide for Thinking Humans" by Melanie Mitchell or "Prediction Machines" by Ajay Agrawal provide a solid foundation.


• Networking and Conferences: Attend industry conferences, webinars, and local meetups to connect with experts and peers who are also exploring AI.

By building a foundational understanding, business owners can make informed decisions about how AI can benefit their operations.

2. Identify Business Needs and Pain Points
Before diving into AI implementation, it’s crucial to identify specific areas where AI can add value. Consider the following:

• Customer Service: AI-powered chatbots can handle customer inquiries, provide 24/7 support, and reduce response times. For example, a small e-commerce business can use chatbots to handle common questions about orders and products.


• Data Analysis: AI can analyze large datasets to uncover trends and insights. A retail business, for example, can use AI to analyze sales data and predict future inventory needs.


• Marketing: AI can optimize marketing campaigns by analyzing customer data and personalizing content. For instance, AI can help a small clothing store segment its audience and target specific demographics with tailored promotions.

3. Choose the Right AI Tools and Platforms
Once the needs are identified, selecting the appropriate AI tools and platforms is essential. For small businesses, it's important to choose cost-effective and user-friendly solutions:

• Chatbots and Virtual Assistants: Platforms like Tidio, ManyChat, and Intercom offer easy-to-implement chatbot solutions.


• Data Analytics Tools: Google Analytics, Tableau, and Microsoft Power BI are accessible tools for data visualization and analysis.


• Marketing Automation: HubSpot, Mailchimp, and Hootsuite provide AI-driven tools for email marketing, social media management, and customer segmentation.

When choosing tools, consider factors like ease of integration, scalability, and cost.

4. Start Small with Pilot Projects
Starting with small, manageable AI projects allows businesses to test the waters without significant investment. Pilot projects can help demonstrate the value of AI and identify potential challenges. For instance:

• A local restaurant might implement a chatbot to handle reservation inquiries and gather customer feedback.


• An online retailer could use AI to recommend products to customers based on their browsing history.

Pilot projects should have clear objectives, such as improving customer satisfaction or increasing sales, and should be monitored closely for performance and ROI.

5. Invest in Data Management
Data is the lifeblood of AI. Ensuring that your business has a solid data management strategy is crucial for successful AI implementation. Steps include:

• Data Collection: Gather relevant data from various sources, such as customer interactions, sales transactions, and social media.


• Data Cleaning: Ensure that the data is accurate, complete, and free from errors. This step is vital for effective AI analysis.


• Data Security and Compliance: Protect customer data and comply with regulations like GDPR. Tools like encryption and secure databases can help safeguard data.

For example, a small business using AI for personalized marketing must ensure that customer data is handled responsibly and in compliance with privacy laws.

6. Leverage Cloud Computing
Cloud computing offers scalable and cost-effective resources for AI development. By using cloud services, businesses can access powerful AI tools without the need for expensive hardware. Key benefits include:

• Scalability: Easily scale AI applications up or down based on demand.


• Cost Efficiency: Pay only for the resources used, which is ideal for small businesses with limited budgets.


• Access to Advanced Tools: Platforms like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud offer a range of AI services, including machine learning models, natural language processing, and image recognition.

A small business can, for instance, use AWS's machine learning services to develop a product recommendation system without investing in its own infrastructure.

7. Develop AI Skills Within Your Team
While not every team member needs to become an AI expert, having basic AI literacy within your team can be incredibly beneficial. Consider:

• Training and Workshops: Offer training sessions or workshops on AI basics, data analysis, and the use of specific AI tools relevant to your business.


• Hire or Outsource: If budget allows, consider hiring an AI specialist or working with a consultancy to help implement and manage AI projects.

A small retail business, for example, might train its marketing team on using AI-driven analytics tools to better understand customer behavior.

8. Monitor and Measure Impact
It's essential to track the performance of AI initiatives to ensure they are delivering value. Key performance indicators (KPIs) might include:

• Customer Satisfaction: Measure changes in customer satisfaction scores after implementing AI-driven customer service solutions.


• Sales and Revenue: Track increases in sales or conversion rates from AI-driven marketing campaigns.


• Operational Efficiency: Monitor improvements in efficiency, such as reduced time spent on manual data analysis.

Regularly reviewing these metrics helps refine AI strategies and demonstrates the value of AI investments to stakeholders.

9. Stay Informed and Adapt
AI is a rapidly evolving field, with new tools and technologies emerging frequently. Small business owners should:

• Stay Updated: Follow industry news, blogs, and journals to stay informed about the latest developments in AI.


• Experiment and Iterate: Be open to experimenting with new AI tools and approaches. Small businesses have the advantage of agility, allowing them to quickly adapt and implement new technologies.

10. Consider Ethical and Social Implications
As with any technology, AI comes with ethical considerations. Business owners should ensure that their use of AI aligns with ethical standards and social responsibilities:

• Transparency: Be transparent with customers about how AI is being used, particularly in areas like data collection and automated decision-making.


• Bias and Fairness: Work to eliminate biases in AI models and ensure fair treatment of all customers.

For example, an online lending company using AI to assess creditworthiness must ensure that its algorithms do not unfairly discriminate against any group.

Conclusion
Implementing AI in a small business can seem overwhelming, but by starting with education, identifying specific needs, choosing the right tools, and beginning with small projects, business owners can leverage AI to drive growth and efficiency. Investing in data management, cloud computing, and team training further supports successful AI integration. Monitoring the impact, staying informed, and considering ethical implications ensure that AI initiatives deliver value while maintaining trust and fairness. By taking these steps, small business owners can confidently navigate the AI landscape and unlock the full potential of this transformative technology."

I must admit that the ChatGPT response for learning about and implementing AI was more thorough that I expected. There is still opportunity to dig deeper on the "how", but for today we can focus on breaking this down a bit more. We'll see where this leads us and if we need another post to go deeper.

First on the list is education. Stop and take a moment to pat yourself on the back, as that's what you've been doing by follow this series on AI. Education is absolutely the key, and my posts are merely scratching the surface. There is so much free content out there that you could spend all your free time devouring it to learn more. Sometimes it's worth paying for education, such as courses, conferences or books, simply to have the material distilled down into a consumable package. Don't stop with these posts. Keep learning!

Courses offer another key benefit, which is hands on experience. If you're like me, you can watch videos or read books for months, but you don't really learn until you put fingers to keyboard and do it yourself. Good courses will offer this experience. It can be one of the fastest ways to get started. If you have an idea of the company/technology that you'd like to use, then check with them first to see if they have free or paid training. Perfect starting point!

Hopefully, by now you've identified your business needs. We talked about that early on in this series and you've seen several examples in each of the posts. Hopefully those examples inspired some ideas on where to focus in your own business. If you haven't narrowed down the business need to focus on first, then maybe look for trainings for AI capabilities that address the various needs that you have in mind and start with the best training first.

Making sure you pick the right AI platform for your business should be a no brainer. There are a lot of solutions out there and not all are right for you. This may take some time, so research their websites along with independent sources. Look for companies similar to you that have implemented that same solution and reach out to them. Put the same due diligence into this as you would picking a contractor for a construction project or hiring a new leader who will run your most critical operations. This can be the difference between having and amazing experience with AI or hating it!

Starting small is another great idea. Have you ever gotten a little too excited about a new hobby? You went out and bought all the most expensive gear or equipment and dove into the deep end. Only to realize a couple of weeks or months later that you're really not as interested as you thought. Is that stuff still out in the garage, down in the basement or tucked away in one of your closets?

Do yourself a favor and start small. Treat it like a proof of concept, similar to what you may do when testing the market before launching a new product or service. Really evaluate it thoroughly and work to maximize the capability within the predefined boundaries of the proof of concept. Become an expert in it and, if it proves valuable, you'll feel much more comfortable with scaling the solution.

That brings us to scalability. The last thing you want to do is set up some wiz bang POC that has amazing potential only to find out that it won't scale for your business. Starting over can be incredibly frustrating. Please be sure to do thorough homework when selecting an AI platform and ensure that it can scale to meet your needs. Double and triple check this by confirming with businesses your size or larger using that solution that it performs well and meets their expectations.

One way to ensure scalability is to start with a cloud-based solution. These vendors, like Amazon's AWS, offer the ability to start very small and only pay for what you use. If it proves out, then you can scale up for your current business needs. You'll also know that you can scale even more as your business grows.

One word of caution for you. Evaluate the pricing models for the cloud solution very well. Compare that with how you plan to grow your business over the next 3 - 5 years. Some cloud solutions have very cheap pricing models for a very small service level, but the price jumps significantly for larger service levels. You don't want to end up in a situation where the AI solution works really well, but the economics simply don't work for your business as the company grows!

Underlying any AI solution, whether cloud-based or on prem, is data. You must get your data in order. This has been a common theme throughout this series. This will take time and effort and is one area where it may pay dividends to hire an expert. Poor quality data can lead to inaccurate results which, if blindly acted upon, can have devastating results for your business! Maybe I'll do a deeper dive into data management and data governance in future posts??

AI capabilities are great, but you can't run them yourself. You need your employees to be adept at the technology. I'd recommend picking one or two key people early who will operationally run your AI systems. Get them involved with the early steps of implementing AI and definitely have them involved in the POC.

Training is key here. Your employees will need to be trained in AI just like you. This goes beyond those one or two key people. Some training can be free, but don't cheap out here. Pay for courses and send your employees to conferences. Conferences are great because employees also make connections with other using the same software. They can use that network as a resource when they run into questions or problems later on. Your employees will greatly appreciate your investment in them and that will pay dividends for you!

Training also supports sustainability. If you give your employees a solid education in AI, that will serve as a solid foundation for them to build upon. They can incrementally add onto that foundation as they gain new knowledge as AI evolves. This makes it so much easier to keep the AI solutions relevant to your company's needs.

Closely related to training is staying current in the world of AI. It's not something that you can just implement and forget about. The capabilities are advancing at an incredible pace, and you'll quickly fall behind if you don't make a conscious effort to stay current. Staying current in the trends also helps you to determine when and where to invest in continuing education and training for your employees. Moreover, as your business evolves, you'll be able to quickly determine how to augment your AI strategy to evolve with it.

The last thing that ChatGPT mentioned was ethical and social implications. Ethics in AI is an important topic. You want to use AI for the betterment of your company and your customers. You're still accountable for the outcome when you implement an AI solution. That means that you need to know if the AI solution has any bias that may explicitly or inadvertently discriminate or otherwise harm any of your customers or employees. Always make sure your operations, AI-enabled or not, are something that you would brag about on the front page of a newspaper.

Hopefully, this post helped to give you an idea of how to actually get started using AI. We'll continue to dig in, where possible, to make this as tangible as possible for you. Ultimately, however, it's up to you to take the first step. What course or conference are you going to sign up for today? What book are you going to order? Will you pick one or two employees to be your AI champions? Or will you write this off as too much work and quietly drift into obsolescence?

Do you feel like you are ready to get started with AI but need some help in implementing your solution? Maybe you have a few great ideas and need some help narrowing those down into a plan to move forward with implementation? Check out FailingCompany.com to find the help that you need. Go sign up for an account or log in to your existing account and start working with someone today.

#FailingCompany.com #SaveMyFailingCompany #ArtificialIntelligence #ImplementAI #EducateYourself #SaveMyBusiness #GetBusinessHelp

We touched on leveraging AI for demand management and inventory optimization last week. We saw that there are some pretty powerful capabilities that can help you dial in your demand forecasting and associated inventory levels, which can have a material impact to your bottom line. Let's tackle a related topic in this post.

Inventory isn't the only thing that a company has to buy. A company has to buy all sorts of things, from office supplies to trucks to professional services, to support daily operations. In most companies, the function that handles this is called procurement. It can be a complex job and, left unchecked, can be big source of wasted funds for a company.

People who work in procurement are often specialized. They have experience and expertise in negotiating contracts and discounts, estimating order sizes, timing of orders, etc. Sometimes the work is rather manual, relying on spreadsheets for calculations and tracking purposes and email for approvals. Other times, the company uses procurement management systems. Either way, is there room for AI to help support this function as well as it can support other functions? Let's ask ChatGPT again to find out.

"Leveraging AI to Automate Procurement for Small Businesses: Top 5 Strategies
In the rapidly evolving world of business, small enterprises often face the challenge of keeping up with larger competitors, especially in procurement. Procurement, the process of sourcing and acquiring goods and services, can be time-consuming and complex. However, the advent of artificial intelligence (AI) offers small businesses a powerful tool to streamline and automate their procurement processes. Here are the top five ways small businesses can leverage AI to automate procurement, along with specific examples for each.

1. AI-Powered Spend Analysis

Explanation
Spend analysis involves examining procurement data to understand spending patterns and identify opportunities for cost savings. AI can automate this process by analyzing large datasets quickly and accurately, identifying trends, and providing actionable insights.

Example
A small retail business uses an AI-powered spend analysis tool to review its procurement data. The AI system identifies that the company is spending significantly more on office supplies from multiple vendors. By consolidating purchases with a single vendor who offers volume discounts, the business can reduce costs by 15%. The AI tool also highlights seasonal variations in purchasing patterns, allowing the company to negotiate better terms with suppliers during low-demand periods.

2. Predictive Analytics for Demand Forecasting

Explanation
Predictive analytics uses historical data and machine learning algorithms to forecast future demand. Accurate demand forecasting helps businesses maintain optimal inventory levels, avoid stockouts, and reduce excess inventory costs.

Example
A small e-commerce company selling handmade crafts integrates an AI-based predictive analytics tool with its sales and inventory management system. The AI tool analyzes past sales data, market trends, and seasonal patterns to predict future demand for various products. This enables the company to adjust its procurement plans accordingly, ensuring they have the right amount of stock for upcoming peak seasons while minimizing overstock during slower periods. As a result, the company reduces inventory holding costs by 20% and improves customer satisfaction by consistently meeting demand.

3. Supplier Relationship Management (SRM)

Explanation
AI can enhance Supplier Relationship Management by automating the process of evaluating and selecting suppliers, monitoring supplier performance, and managing supplier communications. This ensures that small businesses work with the best possible suppliers, leading to better pricing, quality, and reliability.

Example
A small restaurant chain uses an AI-powered SRM system to manage its relationships with food and beverage suppliers. The AI system evaluates suppliers based on criteria such as price, delivery reliability, and product quality. It automatically flags suppliers who consistently deliver subpar products or miss delivery deadlines, enabling the restaurant to switch to more reliable suppliers. Additionally, the AI system sends automated reminders for contract renewals and negotiates better terms based on historical performance data. This results in improved supplier performance and a 10% reduction in procurement costs.

4. Automated Purchase Order (PO) Management

Explanation
Purchase order management involves creating, approving, and tracking purchase orders. AI can automate these tasks, reducing manual errors, speeding up the procurement cycle, and ensuring compliance with procurement policies.

Example
A small manufacturing firm implements an AI-driven PO management system. When a purchase requisition is submitted, the AI system automatically generates a purchase order based on predefined templates and procurement rules. The system routes the PO for approval to the relevant manager, who receives an automated notification. Once approved, the AI system sends the PO to the supplier and tracks its status until delivery. The firm experiences a 30% reduction in procurement cycle time and a significant decrease in manual errors, leading to smoother operations and better supplier relationships.

5. AI-Enabled Contract Management

Explanation
Contract management involves the creation, execution, and analysis of contracts to maximize operational and financial performance while minimizing risk. AI can automate the extraction of key terms and conditions, monitor contract compliance, and alert businesses to renewal dates and potential issues.

Example
A small IT consulting company uses an AI-based contract management platform to handle its vendor contracts. The AI system extracts key terms such as payment schedules, delivery timelines, and service level agreements from new contracts. It continuously monitors compliance with these terms, sending alerts for any deviations. For instance, if a vendor fails to meet a delivery deadline, the AI system notifies the procurement team, who can then take corrective action. Additionally, the AI platform provides automated reminders for contract renewals, ensuring that the company never misses a renewal deadline. This leads to better compliance, reduced legal risks, and improved vendor relationships.

Conclusion
AI offers small businesses a wealth of opportunities to automate and optimize their procurement processes. From spend analysis and demand forecasting to supplier relationship management, purchase order management, and contract management, AI can significantly enhance efficiency, reduce costs, and improve decision-making. By leveraging AI tools, small businesses can level the playing field and compete more effectively in the marketplace. Embracing these technologies not only streamlines operations but also positions small businesses for long-term success in an increasingly competitive business environment."

We hit on predictive analytics for demand forecasting last week, so we'll skip that one this week. With that out of the way, let's jump back up to the top of the list and look at using AI for spend analysis. I mentioned earlier that it's easy to let spending in procurement get out of control. Sometimes, small orders like office supplies can be approved by each individual manager or the admin has blanket approval to buy the supplies. Those small orders add up quickly when not monitored and money could be wasted.

It doesn't have to be office supplies. Perhaps the employees who are on the road have company credit cards and use them to buy fuel for the company vehicles. Each person just pulls into the closest station when they need fuel. Seems simple enough. However, the company could be missing out on fuel discounts if they had instead selected a single station to use for all its fuel needs.

Leveraging the power of AI can allow you to quickly discover where money is being wasted. You will need to keep detailed records of all purchases, but once that's done you can let AI do the heavy lifting. You can quickly find opportunities to make changes such as consolidating the order of office supplies both within the company and the vendors used to source the supplies. The same for fuel. AI can show you where you could potentially save money by consolidation or volume purchases.

It's not just about saving money, though. If you have robust enough data, you can use AI to find patterns in delays in the delivery of supplies, supply shortages, etc. This can help you to find back up suppliers for certain products to ensure you always have the supplies you need when you need them. This is where AI powered Supplier Relationship Management systems can shine. They can do all this work behind the scenes and make it feel effortless!

So, you've done your spend analysis and plugged the holes to save money. You've also implemented an AI-powered supplier management system to optimize your suppliers. What's next? How about streamlining the Purchase Order (PO) process?

Why rely on a human to create POs, track approvals by email and get them sent off in a timely manner? Enter automated PO systems. These systems can leverage AI to generate the POs automatically and handle the approval routing process seamlessly. This eliminates relying on a person to handle it and usually results in a reduced cycle time, helping to keep the business running smoothly. No more delays because somebody left early on a Friday and forgot to send the PO to the vendor.

Once you've found waste in your procurement process, optimized your suppliers and streamlined the PO process, you'll eventually need to deal with contracts. Not every order will need a contract, but bigger orders do. Sometimes it for large purchases but other times it's for services provided by another supplier, such as consulting, construction, painting, etc. Contracts can be complicated and time consuming. On top of that, you may not have the time or expertise to review contracts for operational, financial or legal impacts.

Enter contract management systems. These AI-powered systems can do the majority of the contract work for you. These systems can even help you monitor contracts to ensure compliance to the terms laid out in the contract. This means no more penalties for late payments, expired contracts and fewer missed deadlines by the vendor. All good things for your business!

Once again, we've seen that AI can add substantial value to a business. Adding artificial intelligence to the procurement process can save money, reduce cycle times, streamline suppliers and greatly improve the contracting process. Yes, there's work involved to implement all of these capabilities and there will also be upfront cost. You can choose to invest now and help take your business to the next level or you can choose to sit on this information and stick to business as usual. The choice is yours to make!

Has your procurement process felt like a wooden boat with lots of holes drilled in it? Perhaps you've dialed in your procurement process but would like to streamline a few key areas? Check out FailingCompany.com to find the help that you need. Go sign up for an account or log in to your existing account and start working with someone today.

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Last week I wrote a post on using AI to support the sales process. In that post I mentioned that I might do a follow up post on using AI to automate demand forecasting and inventory management. Let's dig into that one today.

One thing that plagues any small business that sells a physical product is inventory management. It often feels more like an art than a science to keep the right level of inventory on hand. You don't want to keep too little, sell out and leave your customers frustrated. You also don't want to keep too much on hand that ties up valuable capital, especially if it may become obsolete or expire.

Throw seasonality into the mix and managing inventory can feel like hitting a moving target. Over time, most become fairly adept at their "normal" business cycle. However, nothing stays "normal" for very long anymore. There has to be a way to get more precise at optimizing inventory levels without hiring executives from the big chain stores, right? Let's see what ChatGPT has to say about the topic:

"Leveraging AI for Sales Demand Forecasting and Inventory Optimization in Small Businesses

In today's competitive market, small businesses must leverage every tool available to stay ahead. One of the most transformative technologies available is Artificial Intelligence (AI). AI can significantly enhance sales demand forecasting and inventory management, enabling small businesses to operate more efficiently and effectively. Here are the top five ways to apply AI for these purposes, with specific examples illustrating each approach.

1. Predictive Analytics for Accurate Demand Forecasting
Predictive analytics is the use of data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data. For small businesses, predictive analytics can vastly improve the accuracy of sales forecasts.

Example:
A small bakery uses predictive analytics to forecast demand for various baked goods. By analyzing historical sales data, weather patterns, and local event schedules, the bakery can predict which items will be in high demand on specific days. This allows them to prepare the right amount of each product, reducing waste and ensuring fresh inventory.

Implementation Steps:

• Data Collection: Gather historical sales data, customer feedback, and external factors like weather and events.


• Algorithm Development: Develop machine learning models, such as regression analysis and time-series forecasting, to analyze the data.


• Continuous Improvement: Continuously update the models with new data to improve forecast accuracy.

2. Inventory Optimization through AI Algorithms
AI algorithms can analyze sales patterns and predict future demand, helping businesses maintain optimal inventory levels. This reduces carrying costs and minimizes the risk of stockouts.

Example:
A small electronics store uses AI algorithms to manage its inventory. The AI system analyzes sales data to predict which products will be popular during different times of the year. It then suggests optimal reorder points and quantities, ensuring the store is well-stocked without overstocking.

Implementation Steps:

• Integration: Integrate AI tools with existing sales and inventory systems.


• Pattern Recognition: Use AI to identify sales trends and seasonal variations.


• Automated Reordering: Implement automated reorder points based on AI-driven forecasts.

3. Dynamic Pricing for Competitive Edge
Dynamic pricing involves adjusting prices in real-time based on supply and demand. AI can help small businesses implement dynamic pricing strategies to maximize revenue and stay competitive.

Example:
A small online fashion retailer uses AI to adjust prices based on factors such as inventory levels, competitor pricing, and customer demand. During peak shopping periods, the AI system increases prices for high-demand items while offering discounts on slower-moving stock to encourage sales.

Implementation Steps:

• Data Integration: Combine data from sales, competitors, and market trends.


• Pricing Algorithms: Develop AI algorithms to adjust prices in real-time based on collected data.


• Monitoring: Continuously monitor the impact of dynamic pricing and refine algorithms as needed.

4. AI-Driven Personalized Marketing
AI can analyze customer behavior and preferences to create personalized marketing campaigns. By understanding what products are likely to appeal to individual customers, businesses can tailor promotions to drive sales more effectively.

Example:
A small bookstore uses AI to track customer purchases and browsing history. The AI system then recommends books based on previous purchases and sends personalized email promotions for upcoming releases in genres that interest the customer. This targeted approach increases the likelihood of repeat purchases and improves customer satisfaction.

Implementation Steps:

• Customer Data Analysis: Collect and analyze data on customer behavior and preferences.


• Recommendation Systems: Use AI to develop recommendation engines that suggest products to customers.


• Targeted Campaigns: Design personalized marketing campaigns and measure their effectiveness to refine strategies.

5. Automating Repetitive Inventory Tasks
AI can automate repetitive tasks involved in inventory management, such as stock counting, order processing, and inventory tracking. This saves time and reduces human error, leading to more accurate inventory management.

Example:
A small grocery store uses AI-powered robots to perform regular stock counts. These robots scan shelves, update inventory records, and alert staff when items need to be restocked. This reduces the manual labor required for inventory management and ensures real-time accuracy.

Implementation Steps:

• Robotics and IoT: Implement AI-powered robots or drones equipped with sensors and cameras.


• Software Integration: Integrate these AI systems with existing inventory management software for automated data entry and reporting.


• Error Reduction: Use AI to identify and correct discrepancies in inventory records.

Conclusion
AI offers transformative potential for small businesses in the areas of sales demand forecasting and inventory management. By leveraging predictive analytics, inventory optimization algorithms, dynamic pricing, personalized marketing, and automation of repetitive tasks, small businesses can improve efficiency, reduce costs, and better meet customer demands.

Next Steps for Small Businesses:

• Identify Needs: Assess specific needs and challenges in your business operations.


• Explore AI Tools: Research AI tools and solutions that align with your business goals.


• Implementation: Start with small-scale implementations and gradually expand as you refine your AI strategies.


• Continuous Improvement: Regularly update and improve AI models with new data to maintain accuracy and effectiveness.

Embracing AI can provide small businesses with a significant competitive edge, enabling them to operate more efficiently and effectively in an increasingly dynamic market."

Admittedly, we saw some of these examples before. However, not through the lens of inventory optimization. There are some new nuggets in here as well. Let's take a look at a few of those now.

I like the idea of using AI for both demand forecasting and inventory optimization together. You implement a checks and balances system by doing so. If the AI engine analyzed seasonality and tells you to order 100 widgets but the demand forecast engine shows you that the widget is the hot new trend, then you may want to adjust your inventory order up a bit to cover increased demand. If you had just used AI for inventory management alone, then you may sell out and miss out on the selling spree at increased prices.

Obviously, it's not some magical solution where you find an AI tool for Inventory optimization, and it just works. First, you really need an inventory management system of some sort. A notepad won't cut it here. If you don't have an inventory management system, you're in luck. You can do a little research and select one now with AI built in.

You also need a system to record and track sales data. Once again, a notepad won't work. If you have a decent sales system, then you have access to all your historic sales data. You will know what products were sold on what dates, days of the week and times. That means you'll also know the season of the year and associated info related to that season, such as holidays, major events, natural disasters, etc. For orders that are shipped, you'll know relevant geographic information.

Feed this information into an AI engine and you have a robust way to forecast future demand. This can work with the AI engine tied to your inventory management system to help develop accurate inventory order levels and timing to ensure just in time inventory. What are you going to do with all that capital that is freed up from excess inventory??

I also love the dynamic pricing ability. Technically this falls under the sales process, but dynamic pricing can also be used to optimize inventory. By managing inventory levels real time, an AI engine can automatically discount products that have been sitting in inventory too long and generate some sales. This helps free up space in the warehouse plus generates a profit, albeit less than originally planned. The AI engines can also monitor trends and discount products that seem to be falling out of trend to clear them out before they are old news!

Finally, there is automation of repetitive inventory tasks. I've actually hit on this one before. Why pay someone to do a physical inventory count when you can have an AI robot do it for you? It's faster and cheaper in the long run. If you have money to invest, you can even get robots to help move the stock around the warehouse like the retailing giants use. These robots can help stock the shelves when the delivery truck shows up and can pick the items for packaging when an order is received. All of this is done with a high degree of accuracy and speed.

It's pretty exciting to know that AI can help with nearly every aspect of inventory management and optimization. You now know that you can really dial in your inventory to ensure that you never run out of stock and rarely end up with excess inventory. Are you willing to invest the time and money in this technology to take your business to the next level? Or are you going to go watch some silly video on social media and forget all about this opportunity?

Is your inventory out of control and you need help getting things straightened out? Perhaps your inventory management is pretty solid but takes way too much of your precious time? Check out FailingCompany.com to find the help that you need. Go sign up for an account or log in to your existing account and start working with someone today.

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It's safe to say that we've covered all the major back-office functions and how AI can help with each. We covered legal last week, which means that we've now worked through using AI for research and to automate marketing, customer service, HR, Finance and legal. Today we'll venture out of the back-office and tackle one of the most important functions for any business.

What's arguably the most important function for any business? Sales! A business can't exist if it can't sell a product or service. Sales professionals are often some of the most highly paid employees of a company outside of the executives. Being able to maximize their effectiveness at turning leads into paying customers is critical.

Businesses often invest a lot of money in their sales team. Sending the team to trainings, sales seminars and conferences is very common and quite expensive. These people must also maintain a network of potential clients, so paying to attend networking events and trade shows is also common.

More established businesses also invest in technology to develop leads and convert them to paying customers online too. Can AI be added to the mix to make the process even more efficient? I asked ChatGPT and here is what it had to say:

"Top 5 Ways to Use AI to Automate the Sales Process for Small Businesses

In the fast-paced world of sales, small businesses often struggle to keep up with larger competitors due to limited resources. However, artificial intelligence (AI) is leveling the playing field by offering powerful tools to automate and enhance the sales process. Here, we explore the top five ways small businesses can leverage AI to streamline their sales operations and drive growth.

1. AI-Powered Lead Generation and Scoring

Overview
Lead generation is the cornerstone of any sales strategy. Traditionally, it involves identifying potential customers through various means and then manually sorting and prioritizing them based on their likelihood to convert. AI revolutionizes this process by automating lead generation and scoring, allowing sales teams to focus on the most promising prospects.

Implementation
Example: Using Chatbots and AI Analytics

• Chatbots for Initial Engagement: Implement AI-powered chatbots on your website to engage visitors in real-time. These chatbots can ask qualifying questions, gather contact information, and provide instant responses to common queries. For instance, a chatbot for a boutique digital marketing agency might ask visitors about their current marketing strategies and budget to gauge their potential as leads.


• AI Analytics for Lead Scoring: Use AI tools like HubSpot or Salesforce Einstein to analyze and score leads based on various factors such as their interaction with your website, social media engagement, and past purchase behavior. These tools utilize machine learning algorithms to rank leads, allowing your sales team to prioritize follow-ups with those most likely to convert.

Benefits

• Efficiency: Automates the tedious task of lead qualification.


• Accuracy: Ensures that sales efforts are focused on high-potential leads.


• 24/7 Operation: AI chatbots work around the clock, capturing leads even outside of business hours.

2. Personalized Customer Interactions

Overview
Personalization in sales can significantly enhance customer experience and increase conversion rates. AI helps small businesses deliver highly personalized interactions by analyzing vast amounts of customer data and predicting their needs and preferences.

Implementation
Example: Personalized Email Campaigns

• Customer Data Analysis: Utilize AI tools like Mailchimp's predictive analytics to analyze customer data, including past purchases, browsing behavior, and demographic information. This analysis helps segment your audience into distinct groups with shared characteristics.


• Tailored Content: Create personalized email campaigns tailored to each segment. For example, an online clothing store might send personalized recommendations to customers based on their previous purchases and browsing history. AI can predict which products each customer is most likely to be interested in, resulting in higher open and click-through rates.

Benefits

• Enhanced Customer Experience: Personalized interactions make customers feel valued and understood.


• Higher Conversion Rates: Tailored messages are more likely to resonate with recipients and drive sales.


• Efficient Campaigns: AI automates the segmentation and personalization process, saving time and resources.

3. Sales Forecasting and Demand Planning

Overview
Accurate sales forecasting is crucial for effective inventory management, resource allocation, and strategic planning. AI excels in analyzing historical data and market trends to provide precise sales forecasts and demand planning insights.

Implementation
Example: AI-Driven Forecasting Tools

• Historical Data Analysis: Use AI tools like IBM Watson or Microsoft Azure AI to analyze historical sales data, considering variables such as seasonality, market conditions, and promotional activities.


• Predictive Insights: Generate predictive insights that help you anticipate future sales trends and demand fluctuations. For instance, a small e-commerce business selling seasonal products like winter clothing can use AI forecasting to ensure they stock up appropriately before the winter season.

Benefits

• Improved Inventory Management: Prevents overstocking or understocking, reducing costs and increasing profitability.


• Strategic Planning: Helps in making informed decisions about marketing strategies, resource allocation, and sales targets.


• Risk Mitigation: Identifies potential sales slumps or surges, allowing for proactive measures.

4. Automated Customer Relationship Management (CRM)

Overview
Customer Relationship Management (CRM) systems are essential for managing interactions with current and potential customers. AI enhances CRM by automating tasks, providing valuable insights, and ensuring no opportunities are missed.

Implementation
Example: AI-Enhanced CRM Systems

• Automation of Routine Tasks: Implement AI-powered CRM systems like Zoho CRM or Pipedrive to automate routine tasks such as data entry, follow-up reminders, and meeting scheduling. For example, AI can automatically log customer interactions and set reminders for follow-up actions, ensuring no lead falls through the cracks.


• Predictive Analytics: Utilize AI to analyze customer interactions and predict future behavior. This can include identifying upsell and cross-sell opportunities or predicting which customers are at risk of churning. For instance, a software-as-a-service (SaaS) company might use AI to identify customers who have not logged in for a while and trigger a personalized re-engagement campaign.

Benefits

• Efficiency: Reduces the time spent on administrative tasks, allowing sales teams to focus on selling.


• Insightful Data: Provides actionable insights into customer behavior and preferences.


• Proactive Engagement: Enables timely and personalized follow-ups, enhancing customer satisfaction and retention.

5. Virtual Sales Assistants and AI-Driven Customer Support

Overview
Providing excellent customer support is vital for maintaining customer satisfaction and loyalty. AI-powered virtual assistants and customer support tools can handle a significant portion of support tasks, ensuring timely and effective resolution of customer queries.

Implementation
Example: Virtual Sales Assistants

• AI Chatbots for Customer Support: Deploy AI chatbots on your website and social media platforms to handle common customer queries. These chatbots can provide instant responses, troubleshoot issues, and escalate complex cases to human agents when necessary. For example, a small electronics retailer might use an AI chatbot to assist customers with product troubleshooting and warranty information.


• Virtual Sales Assistants: Use AI-driven virtual sales assistants like Conversica to engage with leads and customers via email or messaging platforms. These virtual assistants can send personalized follow-up emails, answer product questions, and schedule appointments, acting as an extension of your sales team.

Benefits

• 24/7 Availability: AI virtual assistants provide round-the-clock support, ensuring customers receive timely assistance.


• Scalability: Handles multiple queries simultaneously, making it scalable for growing businesses.


• Cost-Effective: Reduces the need for a large support team, cutting down on operational costs.

Conclusion
AI is transforming the sales landscape, offering small businesses the tools they need to compete with larger enterprises. By automating lead generation, personalizing customer interactions, improving sales forecasting, enhancing CRM, and providing robust customer support, AI enables small businesses to streamline their sales processes and drive growth. Implementing these AI-driven strategies can lead to increased efficiency, higher conversion rates, and improved customer satisfaction, ultimately contributing to long-term success.

Small businesses that embrace AI will not only enhance their sales processes but also gain a competitive edge in an increasingly digital marketplace. Now is the time to explore and integrate AI solutions to future-proof your sales strategy and achieve sustainable growth."

Much of what was provided overlaps with what we discussed about marketing or customer service. However, there are still some gems in here. The lead management capabilities are what I find to be really powerful!

Traditionally, for an online business, the goal was to get someone interested enough to go to your website. Once there, you may offer them a limited time offer or a free product in exchanged for their email address. You'd then add them to a mailing list to begin regularly mailing them helpful information. This was done with the goal of building a relationship and hopefully converting them into a paying customer.

Now we can use AI to begin actively engaging with the leads once they hit the website. The chatbot can be much more conversational than a traditional web form and will be more successful at capturing vital lead information. It can then analyze and score the leads to enable you to focus your attention on the most likely leads to convert to a paying customer. This greatly increased your conversion rate and reduces the time you'll waste on people who will never buy!

The CRM tools that are available now also make the existing sales team much more productive. These tools take the burden off of the salesperson to remember to send follow up emails on a periodic basis. It's done automatically. Also, scheduling meetings can be a huge time suck. Why not let an AI powered CRM tool do that for you too. Essentially, the AI powered CRM tool acts as a virtual assistant for the salesperson, so he or she can focus on building relationships and selling.

The inventory management detail is awesome too. You can't sell what you don't have. I think I'll do another article focused on demand and inventory management. For now, know that AI can help take the guess work out of what to order and when.

Did you find any of this useful or was it just a replay of what we've already covered? Have you already started down the AI journey since reading these posts? Will you investigate ways to improve your sales with AI? Or do you believe you already have the secret sauce and can't possibly make it any better? I challenge you to try!

Is your sales team completely overworked? Maybe your landing tons of leads but your conversion rate is embarrassingly low? Check out FailingCompany.com to find the help that you need. Go sign up for an account or log in to your existing account and start working with someone today.
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It's safe to say that we've now covered all the major back-office functions and how AI can help with each. We've worked through using AI for research and to automate marketing, customer service, HR and Finance so far. That doesn't mean that our journey has come to an end just yet. We still have some things that we can explore.

This week we'll dig into leveraging AI for legal needs. Every business has the occasional legal need. Some deal with legal stuff on a regular basis. Dealing with contracts, compliance issues in a regulated environment, researching new patents or patent infringement, lawsuits, etc. It's all time consuming, expensive and most business owners would rather avoid it at all costs. Sadly, legal stuff is a part of life if you're operating a business.

Luckily, this is yet another area where AI can help provide some relief. We've covered using AI for research at the beginning of this mini-series, so it's no surprise that AI can be used to help with legal research as well. That alone is amazing news, as much of the legal expense incurred when working with a lawyer is driven by stuff not really requiring a lawyer, such as legal research. How else can AI help with legal needs? I turned to ChatGPT again to see what it has to say. As always, it didn't disappoint:

"Leveraging AI for Legal Needs in Small Businesses: A Comprehensive Guide

Artificial Intelligence (AI) is no longer a futuristic concept confined to science fiction. It has rapidly integrated into various industries, transforming how businesses operate. For small businesses, AI presents an opportunity to streamline operations, improve efficiency, and reduce costs. One area where AI is making significant strides is in addressing legal needs. From contract management to compliance and beyond, AI tools can offer substantial support to small businesses, ensuring they remain competitive and legally sound. This blog post explores how small businesses can harness the power of AI to meet their legal needs effectively.

Understanding AI in the Legal Context

AI in the legal field, often referred to as LegalTech, encompasses a wide range of applications designed to automate, enhance, and streamline legal processes. These applications utilize machine learning, natural language processing (NLP), and other AI technologies to perform tasks that traditionally required human expertise. For small businesses, adopting AI for legal purposes can translate into significant cost savings, improved accuracy, and faster processing times.

Key Areas Where AI Can Support Legal Needs

1. Contract Management
Contracts are the backbone of any business operation, dictating terms, conditions, and obligations. However, managing contracts can be labor-intensive and prone to human error. AI-powered contract management systems can:

• Automate Contract Creation: Tools like Ironclad use AI to generate contracts based on predefined templates and specific inputs, reducing the need for manual drafting. For example, a marketing agency can quickly create standardized client agreements by inputting client details and selecting appropriate clauses.


• Review and Analysis: AI platforms like LawGeex can quickly review large volumes of contracts to identify key terms, potential risks, and compliance issues. A small software company can use such a tool to review vendor agreements, ensuring no unfavorable clauses are overlooked.


• Obligation Tracking: AI can monitor contract timelines using tools like ContractPodAi, alerting businesses to upcoming deadlines or renewal dates to ensure compliance. For instance, a retail business can keep track of lease agreements and payment schedules automatically.

2. Legal Research
Legal research is a time-consuming process that involves sifting through vast amounts of legal texts, precedents, and regulations. AI can expedite this process by:

• Advanced Search Capabilities: ROSS Intelligence uses AI to perform deep searches across legal databases, retrieving relevant information faster than traditional methods. A boutique law firm can utilize this to find case law and statutes more efficiently.


• Predictive Analysis: Tools like Lex Machina analyze past cases and legal trends to predict potential outcomes and suggest the best course of action. A small business involved in a patent dispute can use this to anticipate litigation outcomes and develop a more informed legal strategy.

3. Compliance and Regulatory Monitoring
Staying compliant with ever-changing laws and regulations is a significant challenge for small businesses. AI can help by:

• Real-Time Monitoring: Compliance.ai provides systems that continuously monitor changes in relevant laws and regulations, providing real-time updates. A financial services firm can use this to stay abreast of new regulatory requirements.


• Risk Assessment: AI tools like ComplyAdvantage assess a business’s current practices against regulatory requirements, identifying areas of non-compliance and suggesting corrective actions. An e-commerce business can ensure its operations align with international trade laws and avoid penalties.

4. Intellectual Property Management
Protecting intellectual property (IP) is crucial for small businesses, especially those in innovative industries. AI can assist in:

• Patent Searches: Tools like PatentPal conduct comprehensive searches to ensure that an invention is unique before filing a patent. A tech startup can verify the novelty of its new software algorithms efficiently.


• Trademark Monitoring: AI tools such as TrademarkNow monitor potential trademark infringements by scanning various databases and online content. A fashion brand can protect its logo and designs from unauthorized use.

5. Litigation Support
When facing legal disputes, AI can provide critical support through:

• Document Review: AI solutions like Everlaw quickly review and categorize large volumes of documents, identifying those most relevant to the case. A small manufacturer involved in a liability case can use this to handle discovery more efficiently.


• E-Discovery: Tools such as Relativity streamline the discovery process by finding and organizing electronic evidence. An online retailer can manage large sets of emails and digital records when involved in a legal dispute.

Benefits of AI for Small Business Legal Needs

Cost Efficiency
One of the most significant advantages of AI is its potential to reduce legal costs. By automating routine tasks, AI allows small businesses to handle many legal processes in-house, reducing the need for expensive legal services.

Time Savings
AI can perform tasks much faster than humans. This speed is particularly beneficial in areas like legal research and document review, where AI can rapidly sift through information and provide actionable insights.

Improved Accuracy
AI systems are less prone to human error, which can lead to more accurate and reliable outcomes. This precision is vital in legal matters where mistakes can have significant consequences.

Accessibility
AI makes sophisticated legal tools more accessible to small businesses that may not have the resources to hire a full-time legal team. This democratization of legal services allows smaller companies to compete on a more level playing field.


Implementing AI for Legal Needs: A Step-by-Step Guide

1. Identify Legal Pain Points
The first step is to identify the specific legal challenges your business faces. These could include contract management, compliance, intellectual property protection, or litigation support. Understanding your pain points will help you choose the right AI tools.

2. Research AI Solutions
Once you’ve identified your needs, research the available AI solutions. Look for tools that specialize in your area of need and compare their features, costs, and user reviews. Some popular LegalTech solutions include:

• Contract Management: Ironclad, LawGeex


• Legal Research: ROSS Intelligence, Lex Machina


• Compliance Monitoring: Compliance.ai, ComplyAdvantage


• IP Management: PatentPal, TrademarkNow

3. Pilot the AI Solution
Before fully integrating an AI tool into your operations, conduct a pilot test. This trial period allows you to evaluate the tool’s effectiveness and identify any potential issues. Gather feedback from your team and assess whether the AI solution meets your needs.

4. Train Your Team
Successful implementation of AI tools requires that your team understands how to use them effectively. Provide training sessions and resources to ensure everyone is comfortable with the new technology.

5. Monitor and Evaluate
After implementation, continuously monitor the AI tool’s performance. Evaluate its impact on your legal processes and make adjustments as needed. Regularly reviewing the tool’s effectiveness will help you maximize its benefits.


Case Studies: Small Businesses Using AI for Legal Needs

Case Study 1: A Startup’s Contract Management Transformation
A tech startup struggled with managing numerous contracts, leading to missed deadlines and compliance issues. By implementing an AI-powered contract management system like Ironclad, the startup automated contract creation, tracked obligations, and received alerts for upcoming deadlines. This transformation resulted in a 40% reduction in contract-related errors and a 30% increase in compliance.

Case Study 2: E-Commerce Business Enhances Compliance
An e-commerce business faced challenges in keeping up with regulatory changes across different regions. By adopting an AI-based compliance monitoring tool such as Compliance.ai, the business received real-time updates on relevant regulations and automated risk assessments. This proactive approach ensured the company remained compliant, avoiding costly fines and enhancing its reputation.


Future Trends in AI and LegalTech

As AI technology continues to evolve, its applications in the legal field are expected to expand. Some emerging trends include:

1. Enhanced Predictive Analytics
AI will become even more adept at predicting legal outcomes by analyzing extensive data sets and identifying patterns. This capability will help businesses make more informed decisions and develop better legal strategies.

2. Greater Integration with Other Business Systems
AI legal tools will increasingly integrate with other business systems, such as customer relationship management (CRM) and enterprise resource planning (ERP) software. This integration will create a more seamless workflow and improve overall efficiency.

3. Increased Customization
AI solutions will offer more customization options, allowing businesses to tailor the tools to their specific legal needs. This flexibility will make AI even more valuable to small businesses with unique requirements.

4. Ethical and Transparent AI
As AI becomes more prevalent in legal matters, there will be a greater emphasis on ethical considerations and transparency. Ensuring that AI systems are fair, unbiased, and transparent will be crucial in maintaining trust and compliance.


Conclusion

AI is transforming the legal landscape, offering small businesses unprecedented opportunities to streamline their legal processes, reduce costs, and improve accuracy. By understanding the potential applications of AI in the legal field and taking a strategic approach to implementation, small businesses can leverage this technology to meet their legal needs effectively. As AI continues to evolve, its role in the legal sector will only grow, making it an indispensable tool for small businesses aiming to stay competitive and legally compliant.

Embracing AI for legal needs is not just about adopting the latest technology; it's about creating a smarter, more efficient way of doing business. Whether it's through automated contract management, advanced legal research, or real-time compliance monitoring, AI can provide the support small businesses need to thrive in today’s dynamic environment."

Once again, we see that AI has lots of applications in the legal field. I particularly liked the help it can provide with contracts. Just about every business has to deal with contracts of some sort. Knowing that AI can help draft solid contracts is exciting.

You can literally have AI draft the contract then pay your lawyer to review and edit it. This saves you both time and a little money. I also liked how it can help with keeping track of contract performance. It's a hassle to keep going back to a statement of work or contract to review it and see if both parties are doing what they said they would. Letting AI track that eliminates a manual burden and saves time!

If your company works in a highly regulated industry, then you know that compliance issues can bring your company to its knees. Most companies need to have dedicated resources to manage compliance controls, ensure that compliance standards are met and to deal with issues. If audits are required, then it may require leaders from all over the company to work on producing audit artifacts and respond to audit findings. Knowing that AI can help with at least parts of the compliance process is a breath of fresh air. It may provide some much-needed relief for your compliance experts and, if lucky, may help to tighten things up to ensure better audit outcomes in the future.

For companies that develop products, understanding patent laws and researching patents is a big part of their world. You need to know the laws around patent infringement, understand how to patent something and do the research to see if something similar is already patented prior to applying for a patent. You may also need to know who owns a patent to approach them about buying the rights to use their patent in a business deal. Letting AI do the heavy lifting here can not only save valuable time but may just help you to avoid a lawsuit from a patent owner. AI can do a much more thorough job at the research than a human, resulting in a lower risk of overlooking an existing patent on a product similar to yours. What a win!

Once again, I'm just scratching the surface on how AI can help with the legal needs of the business. Please run with this and investigate how AI can help with your unique and specific legal needs. I bet you'll find some AI solution to help with at least part of your business need. However, the action to implement falls to you. Are you willing to put in the time to set everything up in order to reap future rewards? Or are you going to move on to read another blog post and forget all about AI for the rest of the day? Choose wisely!!

Has your business been heavily burdened by legal and/or compliance demands? Maybe you have some great ideas to develop new products but simply don't have the time or money for patent research? Check out FailingCompany.com to find the help that you need. Go sign up for an account or log in to your existing account and start working with someone today.


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We're quickly making our way through the major back-office functions and learning how AI can help automate them. We wrapped up a review of leveraging AI to help with HR last week. That checks off research, marketing, customer service and HR. What does that leave left to cover?

Finance is next up this week. A lot of business owners have great business ideas. They can sell their product with ease, but they despise dealing with the back-office finance aspects. Dealing with accounting transactions is like Chinese Water Torture. Building accurate forecasts is some sort of sorcery. They are more comfortable leaving that stuff to someone else, but the current state of business says otherwise!

There are a lot of naysayers out there who will say that there's not a lot of opportunity for AI use in Finance. I simply don't believe that. They are usually just gatekeeping and attempting to protect their craft! In reality, there are lots of opportunities. The budgeting and forecasting activities are low hanging fruit. Throw in financial analytics and you have lots of possibilities. To me, that's still just scratching the surface. Let's evaluate some other opportunities. We'll return to ChatGPT to see what it comes up with:

"Top 5 Ways for Small Businesses to Use AI in Finance

Artificial Intelligence (AI) has made significant inroads into various sectors, transforming how businesses operate and compete. One of the most promising areas where AI can make a substantial impact is finance, especially for small businesses. Here, we delve into the top five ways small businesses can leverage AI in finance, along with specific examples illustrating each method.

1. Automated Bookkeeping and Accounting

The Challenge
For small businesses, bookkeeping and accounting can be time-consuming and prone to human error. Keeping track of every financial transaction manually is not only tedious but also increases the risk of inaccuracies that can affect financial health.

The AI Solution
AI-powered accounting software can automate these tasks, ensuring accuracy and saving time. Tools like QuickBooks Online and Xero use AI to streamline bookkeeping processes.

Example
QuickBooks Online: This software uses AI to categorize expenses, reconcile transactions, and generate financial reports automatically. For instance, when a small retail business uses QuickBooks, the software can automatically categorize transactions from bank feeds, reducing manual data entry. It also provides real-time financial insights, helping business owners make informed decisions promptly.

2. Enhanced Financial Forecasting

The Challenge
Accurate financial forecasting is crucial for small businesses to plan their budgets, manage cash flow, and make strategic decisions. Traditional forecasting methods can be inaccurate due to their reliance on historical data and manual adjustments.

The AI Solution
AI can enhance financial forecasting by analyzing vast amounts of data, identifying patterns, and predicting future trends with greater accuracy. Machine learning algorithms can continuously learn from new data, improving their predictions over time.

Example
Fathom: Fathom integrates with accounting software to provide advanced financial forecasting and analysis. A small manufacturing business using Fathom can generate cash flow forecasts, scenario analysis, and visual financial metrics. The AI algorithms consider factors like seasonal trends, market conditions, and past performance, offering a more accurate and dynamic forecast than traditional methods.

3. Fraud Detection and Prevention

The Challenge
Fraud is a significant risk for small businesses, which often lack the resources and expertise to detect and prevent it effectively. Financial fraud can lead to substantial losses and damage to reputation.

The AI Solution
AI can enhance fraud detection and prevention by analyzing transaction data in real time, identifying unusual patterns, and flagging suspicious activities. Machine learning models can be trained to recognize various types of fraud, continuously improving their detection capabilities.

Example
Kount: Kount’s AI-driven platform helps small e-commerce businesses detect and prevent fraud. For example, an online clothing retailer using Kount can benefit from its real-time analysis of transaction data, identifying anomalies such as unusual purchasing patterns or mismatched shipping addresses. By flagging these transactions for further review, Kount helps the retailer prevent fraudulent activities before they result in losses.

4. Personalized Financial Advice

The Challenge
Small business owners often struggle to make informed financial decisions due to a lack of expertise and personalized advice. Hiring financial advisors can be costly, and generic advice may not address specific business needs.

The AI Solution
AI-powered financial advisors, or robo-advisors, can provide personalized financial advice at a fraction of the cost of traditional advisors. These tools analyze a business’s financial data, market conditions, and owner preferences to offer tailored recommendations.

Example
Botkeeper: Botkeeper combines AI with human expertise to offer personalized financial insights and advice. A small tech startup using Botkeeper can receive recommendations on managing expenses, optimizing cash flow, and identifying investment opportunities. The AI analyzes the startup’s financial data, providing actionable insights and suggesting steps to improve financial health.

5. Streamlined Loan Approval Processes

The Challenge
Accessing financing is often a hurdle for small businesses. Traditional loan approval processes are time-consuming and can be biased, leading to delays or rejections that hinder growth opportunities.

The AI Solution
AI can streamline loan approval processes by analyzing creditworthiness more efficiently and fairly. AI-driven platforms assess a broader range of data points, including transaction history, social media activity, and real-time business performance, to make faster and more accurate lending decisions.

Example
OnDeck: OnDeck uses AI to expedite the loan approval process for small businesses. A small restaurant seeking a loan for renovation can apply through OnDeck’s platform, where the AI evaluates the application based on various data sources. The AI assesses the restaurant’s daily sales, customer reviews, and overall market conditions to determine creditworthiness, often providing approval and disbursement within 24 hours.

Conclusion

AI has the potential to revolutionize finance for small businesses, making processes more efficient, accurate, and secure. By leveraging AI in automated bookkeeping, enhanced financial forecasting, fraud detection, personalized financial advice, and streamlined loan approvals, small businesses can overcome some of their most pressing financial challenges. As AI technology continues to advance, its applications in finance will only grow, offering even more opportunities for small businesses to thrive in a competitive landscape.

Implementing AI-driven financial solutions may require an initial investment, but the long-term benefits of improved accuracy, efficiency, and decision-making capabilities can significantly outweigh the costs. For small business owners looking to stay ahead of the curve, embracing AI in finance is not just an option—it’s a necessity."

As you can see, AI can definitely help with most, if not all, aspects of finance and accounting. This technology may not immediately replace the need for CPAs or other financial professionals, but it can certainly augment your staff. Perhaps one CPA can now oversee all of the bookkeeping activities and tax preparation. You may also get by with one finance professional to oversee the budgeting, forecasting and financial analytics for the business. That enables you to scale your business without adding significant back-office cost.

Fraud detection is an interesting one that most small businesses don't proactively think about. They are worried about launching and/or growing the business and fraud doesn't really come to mind until they are a victim of it. It can be devastating to a small start up if they sell a large volume of product to a customer on credit, deliver it and never get paid. There are always times when the customer simply hits a rough patch and becomes insolvent but being able to detect fraud prior to shipping the order can be a life saver!!

Finally, streamlining the loan process is a great idea! Small businesses often need to rely on loans to grow or simply keep operating until they turn a profit. The loan process can be very time consuming and unpleasant. Seeking out lending institutions that streamline the process can be a wise move. Likewise, if you happen to be in the lending business yourself, this can allow you to process many more loan applications with a higher degree of accuracy while using fewer people. That's a great way to scale your lending business!!

Like all the past articles, I'm just hitting some highlights. I encourage you to run with this and do your own research into other novel ways to leverage AI in finance. I think you'll see how AI will totally transform the finance function in the coming years. Finance professionals and accountants will transform from doers to advisors. Their value will be generated by how well they can guide the decision makers rather than how few errors occurred during the monthly close or forecasting processes. That should be exciting news for all!!

Have you been struggling with keeping up with the finance activities in your business? Maybe you have a plan to scale and know your finance team can't keep up without some help? Check out FailingCompany.com to find the help that you need. Go sign up for an account or log in to your existing account and start working with someone today.
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Hopefully you've been following my series on AI and are starting to understand it's power. We've now covered using AI in research as well as using it to automate marketing and customer service functions. What used to take days can be done in minutes. What used to require experts can now be done by someone with a little patience and an interest in learning AI. We're still just scratching the surface. Where should we go now?

The Human Resources function is both very necessary and one that many business owners wish they could avoid. Whether it's the time required to review resumes, performing interviews, dealing with payroll issues, keeping up with benefit packages, handling performance issues or terminations, or some other mundane task, the owner must make sure it happens. These things take a lot of time and, in some cases, may have legal consequence if not handled properly. What if you could automate some of these mundane tasks and reclaim some of your precious time.

If you've been following my series, then I'm sure you guessed my answer. Of course, AI can help with HR functions. Yes, things like performance evaluations, coaching poor performers or terminating an employee should be personally handled. Those things aside, there is still plenty of room to implement AI and see a benefit. Let's take a look 5 common ways according to ChatGPT:

"Top 5 Ways for Small Businesses to Use AI in HR

Artificial Intelligence (AI) is revolutionizing various sectors, and Human Resources (HR) is no exception. For small businesses, leveraging AI in HR can lead to significant improvements in efficiency, productivity, and employee satisfaction. Here are the top five ways small businesses can use AI in HR, complete with specific examples to illustrate their potential impact.

1. Recruitment and Talent Acquisition
Example: Resume Screening

AI-powered tools can streamline the recruitment process by automating the initial screening of resumes. Instead of manually sifting through hundreds of applications, AI can quickly identify candidates whose skills and experiences match the job requirements. For instance, AI tools like HireVue and Pymetrics use natural language processing and machine learning algorithms to analyze resumes and rank candidates based on their qualifications. This not only speeds up the hiring process but also reduces biases, ensuring a more diverse and qualified candidate pool.

Example: Chatbots for Initial Interviews

AI chatbots can handle initial candidate interactions, conducting basic interviews and answering common questions. This frees up HR personnel to focus on more complex tasks. For example, Mya, an AI recruitment assistant, can engage with candidates in real-time, ask preliminary questions, and schedule follow-up interviews. This enhances the candidate experience by providing instant feedback and updates, which can be crucial for maintaining a positive employer brand.

2. Employee Onboarding
Example: Personalized Onboarding Plans

AI can create personalized onboarding plans tailored to each new employee’s role and experience. Tools like Talmundo and Enboarder use AI to design onboarding journeys that include relevant training materials, introductions to key team members, and timelines for completing onboarding tasks. This personalized approach ensures that new hires are better prepared and more engaged from day one.

Example: Virtual Onboarding Assistants

AI virtual assistants can guide new employees through the onboarding process. These assistants can answer questions, provide resources, and offer reminders about important tasks. For example, an AI assistant named Amber can be programmed to check in with new hires regularly, ensuring they have everything they need to succeed in their new role. This support system can significantly reduce the feeling of overwhelm that often accompanies starting a new job.

3. Employee Engagement and Retention
Example: Sentiment Analysis

AI can help measure and improve employee engagement by analyzing communication patterns and feedback. Tools like CultureAmp and Glint use sentiment analysis to gauge employee morale and identify areas of concern. For instance, AI can analyze responses from employee surveys and highlight recurring themes related to job satisfaction, workplace culture, or management practices. This data-driven approach allows HR to proactively address issues and foster a more positive work environment.

Example: Predictive Analytics for Retention

Predictive analytics can identify employees who might be at risk of leaving. AI tools like Workday and Visier analyze various data points, such as job performance, engagement levels, and historical turnover trends, to predict which employees are most likely to resign. By identifying these at-risk employees early, HR can intervene with targeted retention strategies, such as offering professional development opportunities or adjusting workloads, thus reducing turnover rates.

4. Performance Management
Example: Continuous Feedback Systems

AI can facilitate continuous performance feedback, moving beyond the traditional annual review process. Platforms like BetterWorks and Reflektive use AI to collect and analyze real-time feedback from peers, managers, and direct reports. For example, an employee might receive instant feedback on a project they just completed, highlighting strengths and areas for improvement. This ongoing feedback loop helps employees stay aligned with company goals and improves overall performance.

Example: Objective Performance Evaluations

AI can help reduce biases in performance evaluations by providing objective data and insights. Tools like Synergita and Eightfold.ai analyze performance metrics, employee feedback, and project outcomes to generate unbiased performance reviews. This ensures that evaluations are based on actual performance rather than subjective opinions, leading to fairer and more accurate assessments.

5. Learning and Development
Example: Personalized Learning Paths

AI can tailor learning and development programs to individual employees based on their skills, job requirements, and career goals. Platforms like Degreed and LinkedIn Learning use AI to recommend courses and training materials that are most relevant to each employee. For instance, an employee looking to develop leadership skills might be directed to specific leadership training modules, webinars, and articles. This personalized approach to learning ensures that employees receive the most relevant and impactful training.

Example: Virtual Coaching

AI-powered virtual coaches can provide employees with on-demand support and guidance. Tools like CoachBot and Replika offer personalized coaching sessions that can help employees develop specific skills or overcome challenges. For example, an employee struggling with time management might interact with an AI coach that offers practical tips and strategies for improving productivity. This continuous support can lead to significant improvements in employee performance and satisfaction.

Conclusion
Incorporating AI into HR processes can offer small businesses numerous advantages, from streamlining recruitment to enhancing employee engagement and development. By adopting AI tools and strategies, small businesses can not only improve their HR efficiency but also create a more positive and productive workplace environment. As AI technology continues to evolve, its applications in HR will only become more sophisticated and integral to business success. Small businesses that embrace these innovations will be well-positioned to attract, develop, and retain top talent in an increasingly competitive market."

As you can see, AI can definitely help in the recruiting and onboarding processes. I know I personally dread sitting down to read resumes. Then, after reading a dozen or so, things begin to blur together. You might miss out on a great candidate, or you may not give a well-qualified person the due diligence they deserve due to resume fatigue. Letting AI make the initial pass on the resumes allows you to quickly and fairly narrow the field of candidates down from hundred to maybe a dozen well qualified people to interview.

Once you decide to hire someone, you have to onboard them. This is a time-consuming process, and some experts say that it takes approximately 3 months for someone to be fully up to speed. That's a substantial time commitment for whomever is handling the onboarding. Leveraging AI tools to augment the onboarding process sounds amazing to me! As a bonus, it's personalized for the new hire, so it may be a better experience for them!

Helping your employees keep current on their skills is critical too. There are lots of AI-based learning and development platforms that can be customized to each employee. This may be far cheaper than paying for them to go to conferences or to take professional development courses. Given the ability to customize the experience, they may end up learning quite a bit more than they would at a conference, which is a bonus for both of you!!

I'm a firm believer in having someone personally handle performance evaluations and coaching. However, that doesn't mean that you can't leverage tools to guide you through the process. You can leverage AI tools to evaluate your performance or coaching notes that were gathered throughout the year and recommend next best actions. This helps leaders who aren't particularly strong in doing performance evaluations and most leaders could use a little extra help in coaching a struggling employee. A good tool also helps with follow ups to make sure you and the employee stay on track and stick to your commitments! Definitely something worth checking you!!

It's great to hire employees when you're growing, but often times you have to hire someone to backfill. It takes lots of time and is a real setback to your business. Luckily, you can leverage AI capabilities to analyze employee data and predict who might be a flight risk. You then have the opportunity to take proactive steps to retain them. Maybe a promotion, role expansion or a much-deserved pay raise. Keeping a good employee is worth the cost and the employee gets to feel valued. Keep that in mind as your business grows!!

I just hit on a few of the ways that you can use AI in your business by mainly elaborating on what ChatGPT provided. These are the most common ways, but certainly not the only ways to leverage AI in the human resources function. I encourage you to do your own research to discover unique ways to leverage AI in your business. Have fun with it and try to find ways that will really engage your employees!!

Are you excited to start using AI to help with some of the burdensome HR tasks? Maybe you've suffered from high turnover and see how AI can help reverse the trend? Check out FailingCompany.com to find the help that you need. Go sign up for an account or log in to your existing account and start working with someone today.

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We dipped our whole foot in the water last week when we tackled using AI to automate marketing. We learned that there really isn't an aspect of marketing with which AI can't at least help. In many cases, AI can complete the entire task for you! We even used AI to generate a big part of the post to demonstrate how easily it can generate content. it's truly amazing! So, what's next?

For this post, I thought we'd tackle another very common way to implement AI in a small business, which is customer service. There are many similarities in the customer facing aspects of marketing and the customer service function, so we may see either overlapping or complimentary ideas in today's article. Without further ado, let's dig into it!

So, you set up shop and used AI to get your website and social media presence established. Customers are noticing and orders are rolling in. Sounds great, right? It is until a customer has a question or perhaps an issue with their order. Then what do you do? You're not staffed to handle that!!

Just like in marketing, AI can either help or fully automate the major functions of customer service. You'll have to do a little up-front work, but then AI can take over for you. The most common way to use AI is something we've all experience online in recent years. That's chatbots.

In case you don't know, a chatbot simulates a customer service representative during a chat session with a customer or prospect. In many cases, the person doesn't realize that they are chatting with a computer. You can set up a chat bot to handle the most common questions about your products or services and offer it as a 24x7 service. This is a real benefit to your customers without having to pay for a 24x7 call center!

The chatbot can also vet out the difficult questions and do a hand off to a live agent for follow up. This ensures that you don't lose a customer or prospect who might get frustrated if they can't get their difficult question answered. The cool thing is that the chatbot can get smarter if you regularly feed it the answers to these more difficult questions.

The same capability can be offered over the phone too. Integrate AI voice systems and you have 70-80% of a 24x7 call center covered. With everything integrated behind the scenes, customers will have a similar experience whether they are chatting with your company online or calling into an automated phone system. Over time, your customer service will become very sophisticated, and you won't have the expense of paying for a large call center to monitor phones and online chat systems around the clock.

You can also use AI to automate routine tasks for customer service representatives. By freeing up time spent on things like processing warranty claims or researching internal FAQs, they can spend more time with the customer. This allows them to build a better relationship and hopefully increase the lifetime value of that customer.

If you record your customer service calls and messages, then you can use AI to analyze those files and look for patterns. You may find commonly asked questions that you can put on a FAQ page of your website, making it easier for other customers to answer their own questions. Use it to determine heavy call / message days and times or if there is any seasonality to the types of calls you receive and schedule your customer service representatives accordingly. Heck, you can even discover product defects requiring a recall through this analysis. All things that would take days or at least hours for highly trained data analysts to perform their magic.

Rather than me sharing even more ways to leverage AI in customer service, I thought it would be good to demonstrate a different AI tool for you today. I decided to ask Microsoft's Copilot, which is similar to ChatGPT, to give me the top 5 ways that a small business can begin using AI in customer service. I can't say the answer is as robust as ChatGPT, but it was still a very fast and useful summary. Check it out:

"Top 5 Ways for Small Businesses to Begin Using AI in Customer Service
1. Improve Agent Efficiency and Productivity
AI Chatbots: Implement chatbots on your website or messaging channels to handle simple customer inquiries. These bots can greet visitors, answer common questions, and provide immediate assistance. For instance, a small e-commerce business could use a chatbot to guide customers through the checkout process or help them track their orders¹.

Sentiment Analysis: AI can analyze customer interactions to understand sentiment and intent. By detecting positive, negative, or neutral language, it can route tickets to human agents accurately. For example, if a customer expresses frustration, the system can prioritize their query for immediate attention¹.

2. Offer 24/7 Support
AI Voices: Use AI-powered voice assistants to respond to customer queries even after regular business hours. These virtual agents can handle verbal questions over the phone, providing consistent and efficient support. Imagine a small hotel business using an AI voice system to assist guests with room reservations or check-in inquiries².

3. Personalize Customer Interactions
Natural Language Processing (NLP): Leverage NLP to understand customer messages and tailor responses accordingly. For instance, an online clothing store could use NLP to recommend personalized fashion items based on a customer’s preferences and browsing history³.

4. Automate Routine Tasks
Automated Processes: AI can take care of repetitive tasks, freeing up human agents to focus on complex issues. For instance, a small insurance agency could automate claims processing, reducing paperwork and speeding up resolution times¹.

5. Enhance Self-Service Options
Voice Search and FAQs: Implement AI-driven self-service options. When customers use voice search on their mobile devices, AI can quickly look up information and provide relevant answers. Additionally, create an extensive FAQ section on your website, where AI-powered search tools help users find solutions independently².

By adopting these strategies, small businesses can harness the power of AI to improve customer experiences, streamline operations, and boost satisfaction. Remember that successful AI implementation requires thoughtful planning, ongoing monitoring, and continuous optimization. Start small, measure results, and gradually expand your AI initiatives to create a seamless customer service experience! ????????

1: Zendesk - 9 ways businesses use AI in customer service 2: Microsoft - AI for Small Business: A Beginner’s Guide 3: Yellow.ai - AI in Customer Service - Benefits and Examples"

By just asking a simple question, I have some really solid ways to incorporate AI into my customer service function. Personally, I really liked the sentiment analysis ability. Can you imagine the power of being able to have insight into someone's anger level or mood prior to connecting them with one of your live agents? How much more quickly could you diffuse the situation and help that customer resolve their problem?

Also, think about employee retention. If you can head off angry customers and reduce the number of times your customer service representatives are yelled at or rudely spoken to in any given day, I bet they'd be more willing to stick around! They'll have a better work experience while you get to retain experienced employees and save money on recruiting and training. Definitely a win!!

Did something in this post resonate with you? Ready to get some help rolling out customer service AI? Check out FailingCompany.com to find the help that you need. Go sign up for an account or log in to your existing account and start working with someone today.

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If you read last week's post and took action, then you've started using AI to do some business research. Good for you! That's just the tip of the iceberg. Basically, it's a way to dip your toe in the water. Let's see if we can take it up a notch today. Get ready to put your whole foot in the water today!

You can't mention AI in a business context without mentioning marketing. AI is an incredible tool to advance your marketing strategy, so let's dig into that this week. I'll only be scratching the surface in this post, so your homework will be to go investigate all the other ways to use AI in your marketing efforts for your own business. Implement what you learn and experience the power for yourself.

Let me start by saying that, no matter what marketing task you need to perform, AI can either help with the task or actually complete the task for you. For example, what's one of the first marketing-related things you do when setting up a new business nowadays? Build your website, right? AI can help with that. There are AI powered website building tools that make things a breeze. You answer some questions, and it builds the website template for you.

Once you have your website template, it's time to add the content. It may be narrative about your business, your products or it may be images and videos. All of that is incredibly time consuming to put together, and it often shows in websites when people try to cut corners. It's also been historically expensive to get high quality content created by a professional, which was prohibitive to many business owners with a tight marketing budget. What if AI could help with the content for your website too? Guess what, it can!!

AI tools can literally generate images and videos relevant to the topics on your website and they are pretty amazing. You no longer have to pay for content creators or graphic artists to just get your website up and running. Save that for when you want truly original and unique content after you've established yourself a bit more. You literally have no excuse not to have a digital presence today.

A lot of companies also like to run a blog for their followers. The blog provides added value for existing customers, provides a way to build a relationship with prospective customers and may just be the key to converting a prospect into a paying customer. The challenge is that it's tough to keep coming up with new ideas for regular blog posts. Then there's the time spent writing the post and editing it. Did you know that AI can write entire blog posts for you? It can even do so based on trending topics for the subject that you're writing about.

To demonstrate how powerful AI can be in helping with content creation, I went to ChatGPT and asked it to please write me a 1000-word blog post for small business owners about the top 5 ways to begin using AI to automate their marketing functions. I also requested that it include specific examples for each of the top 5 ways. Below is what was generated:

"The Top 5 Ways Small Businesses Can Begin Using AI to Automate Marketing Functions

In today’s fast-paced digital world, small business owners face the challenge of staying competitive with limited resources. One powerful solution to this problem is leveraging artificial intelligence (AI) to automate marketing functions. AI can help streamline processes, reduce costs, and improve customer engagement. Here are the top five ways small businesses can begin using AI to enhance their marketing efforts.

1. Personalized Email Marketing
Example: Using AI-driven email marketing platforms like Mailchimp or SendinBlue.

Personalized email marketing is one of the most effective ways to engage customers, and AI can take it to the next level. AI algorithms analyze customer data to determine preferences, behaviors, and purchase history. This allows businesses to send highly targeted emails that resonate with individual recipients.

For example, an online clothing store can use AI to analyze past purchase data and send personalized recommendations to customers. If a customer frequently buys sportswear, the AI system can automatically send them emails showcasing new arrivals in that category. This level of personalization increases the likelihood of customer engagement and sales.

2. Chatbots for Customer Support
Example: Implementing AI-powered chatbots through platforms like Intercom or Drift.

Customer support is a critical aspect of marketing, as it directly impacts customer satisfaction and loyalty. AI-powered chatbots can handle a wide range of customer inquiries 24/7, providing instant responses and freeing up human agents to tackle more complex issues.

For instance, a small e-commerce business can deploy a chatbot to answer common questions about order status, shipping times, and return policies. By integrating the chatbot with the company's CRM system, it can provide personalized responses based on the customer's order history. This not only enhances the customer experience but also reduces response times and operational costs.

3. Social Media Management
Example: Utilizing AI tools like Hootsuite Insights or Sprout Social.

Social media is a vital marketing channel for small businesses, but managing multiple platforms can be time-consuming. AI tools can automate content scheduling, monitor brand mentions, and analyze engagement metrics to optimize social media strategies.

For example, a local restaurant can use AI to schedule posts across platforms like Facebook, Instagram, and Twitter. The AI tool can analyze which types of posts perform best at certain times of the day and automatically adjust the posting schedule accordingly. Additionally, AI can track and analyze customer interactions, helping the restaurant understand what content resonates most with its audience and adjust its strategy to increase engagement.

4. Predictive Analytics for Customer Insights
Example: Employing predictive analytics platforms like HubSpot or Salesforce Einstein.

Predictive analytics uses AI to analyze historical data and predict future customer behavior. This can help small businesses make data-driven decisions about marketing strategies, product offerings, and customer segmentation.

For instance, a small online bookstore can use predictive analytics to identify which books are likely to become bestsellers based on past sales trends and customer preferences. By understanding these patterns, the bookstore can stock up on popular titles, create targeted marketing campaigns, and offer personalized recommendations to customers, thereby increasing sales and customer satisfaction.

5. Content Creation and Curation
Example: Leveraging AI content generation tools like Copy.ai or Jarvis (now Jasper).

Creating high-quality content consistently can be a challenge for small businesses. AI can assist in generating and curating content, ensuring a steady stream of relevant and engaging material.

For example, a small travel agency can use AI tools to generate blog posts, social media updates, and email newsletters. The AI tool can analyze trending topics in the travel industry and create content that resonates with the agency’s target audience. Additionally, AI can curate content from various sources, providing a mix of original and third-party content that keeps the audience informed and engaged.

Conclusion
Integrating AI into your marketing strategy can seem daunting, but starting with these five areas can significantly improve your efficiency and effectiveness. Personalized email marketing, AI-powered chatbots, social media management, predictive analytics, and content creation are all accessible ways for small businesses to harness the power of AI. By adopting these technologies, you can enhance customer engagement, streamline operations, and ultimately drive growth for your business.

Embrace the future of marketing with AI and watch your small business thrive in the competitive digital landscape."

Not bad, huh? This article would have taken me quite a bit of time to research, write and edit. It took longer to type in my prompt than it did to generate the article. How much time can you save by leveraging AI in your marketing tasks? What other projects can you start advancing in your company with that newly found time?

Did this article spark some ideas on how to set up AI to automate your marketing processes? Need some help developing the plan to execute smoothly? Check out FailingCompany.com to find the help that you need. Go sign up for an account or log in to your existing account and start working with someone today.

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We covered a lot of the foundation work that must be done to get started with AI last week. It was a lot of info to throw at you, so hopefully you took some time to digest that. If you have, then you're probably curious about some ways to really test out AI. Refer back to last week's articles for details, but we'll start taking a look at some of the easier ways to start using AI this week.

Research has to be one of the easiest ways to begin using AI. I demonstrated in a few different posts how powerful ChatGPT is at distilling down into useful summaries. Why not try it in your business. Need to do some market research for a new business location or potential new product launch? Start with AI and let it do the heavy lifting for you. Let's turn this into a live example and test it out together.

Let's say you own several businesses around the country and want to try your luck in the laundromat business. You're interested in opening or buying a laundromat in the Louisville, KY area. We want to know how many Laundromats currently exist and, on average, how many customers does a single laundromat typically serve per week. This type of information used to require time to research on your own. Let's see what ChatGPT can tell us in a matter of seconds.

So, asking ChatGPT how many laundromats are in the Louisville, KY area quickly revealed that there is approximately 40 - 50 facilities. A caveat was given that it could change, as businesses open and close every day. I also learned that the average laundromat, not specific to Louisville, serves approximately 300 - 400 customers per week. That tells us that we have a total target market of somewhere around 12,000 - 20,000 people per week in the Louisville, KY market.

Should we try to open a new facility and buy an existing business? Perhaps we should investigate how loyal the target customers are to their current laundromat. It looks like, on average, about 54.8% of laundromats offer some sort of loyalty program. That might be a barrier to entry or incentive to buy an existing facility.

However, customers tend to value convenience, flexible pricing options and the use of modern technology like cashless / mobile payments and these may trump a loyalty program. If many of the laundromats are older and haven't been updated, then it might be possible to attract customers to a new facility with state-of-the-art accommodations. If we can find an area of Louisville that is mainly served by antiquated laundromats, then a new facility may be a solid choice.

Well, Louisville is a big city. How can we begin to focus in on some promising areas for deeper research? Basically, where is the best area of town to open or buy a laundromat? I simply asked ChatGPT. It's a good answer, so let me just quote it below:

"When considering the best location to open a new laundromat in Louisville, KY, several key factors and specific neighborhoods should be taken into account to ensure the business's success.

Key Factors for Location Selection
Demographics: Ideal locations typically have a high concentration of renters, lower to middle income levels, and multi-family housing units. Look for areas where at least 35% of households are renters, and a significant portion of the population earns less than $35,000 annually​ (Laundry Solutions Company)​​ (Open A Laundromat)​.

Visibility and Accessibility: Locations along major roads with high visibility and easy access are crucial. Ensure there is ample parking to accommodate customers, particularly those who will be arriving with large loads of laundry​ (Laundry Solutions Company)​​ (Open A Laundromat)​.

Proximity to Complementary Businesses: Being near grocery stores, convenience stores, and other high-traffic retail areas can drive more foot traffic to your laundromat. Customers appreciate the convenience of running multiple errands while doing their laundry​ (Laundry Solutions Company)​​ (Open A Laundromat)​.

Market Saturation: Analyze the competition in potential areas. Avoid locations that already have a sufficient number of laundromats to serve the local population. Visiting existing laundromats to understand their offerings can help identify gaps that your business can fill​ (Laundry Solutions Company)​​ (Open A Laundromat)​.

Suggested Neighborhoods in Louisville
Smoketown: This historic neighborhood has shown promise with new businesses aiming to revitalize the area. Smoketown Laundromat, for example, has become more than just a laundry service, acting as a community gathering space​ (Spectrum News)​.

West Louisville: Areas such as the vicinity of 2600 W Broadway are promising due to the mix of residential and commercial properties. This area benefits from significant foot traffic and community activities, making it a suitable location for new services like laundromats​ (Chamber of Commerce)​​ (Chamber of Commerce)​.

South Louisville: Neighborhoods around Preston Highway and Dixie Highway have a good mix of residential and commercial spaces, with a high density of renters and families. These areas also offer ample parking and visibility from major roads​ (Chamber of Commerce)​.

Conducting a thorough market analysis and considering these factors will help in choosing a location that maximizes the potential for a successful laundromat in Louisville."

Some of this is common sense or just good guidance, but there are some real nuggets here:

• First, we get guidance to look for an area with at least 35% renters where the population earns less than $35,000 annually.


• We then get suggestions for specific areas or neighborhoods to consider with some useful info about each area. More specifically, to look in Smoketown, West Louisville or South Louisville.


• Finally, we're given the suggestion to locate close to a complimentary business. We can use this to pinpoint a location within Smoketown, West Louisville or South Louisville if we decide to open a new facility.

With very little effort, we now have some preliminary market research data that would have taken days or weeks not that long ago.

In a matter of a few minutes, we've researched our target market and narrowed it down to a handful of locations to scout out. We can do further research on how many laundromats are in each of the locations, the percent of renters, average income, crime rates, etc. I think there are limits to how many questions you can ask ChatGPT per day if you use the free service, but you can always spread your research out a bit.

Can you see how easily you can incorporate AI research into your business? It can save you a tremendous amount of time and arm you with data and insights that can be put into action rather quickly. This helps level the playing field when you're dealing with bigger competitors with deep pocket and more resources. With access to powerful information at your fingertips, the advantage goes to the company that acts first. Now, you can be that company!

Ready to use some AI research to grow your business? Maybe you've identified some opportunities and need some help implementing them? Check out FailingCompany.com to find the help that you need. Go sign up for an account or log in to your existing account and start working with someone today.

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Hopefully last week's review of AI categories was helpful. The goal is to demystify AI to the point where you are comfortable with it. We naturally tend to avoid things that make us uncomfortable, so the quicker you can get comfortable with AI, the quicker you'll actually use it!

So, how do you actually get started down the path of using AI in your business? Do you just go find an AI tool and start using it? You could, but probably won't get you the results that you want. Like anything else in business, a little up-front planning and organization goes a long way. Get ready to roll up your sleeves and get to work!

The first thing to do is an assessment of your operations. Evaluate your sales process, marketing program, customer service approach, finance & accounting departments, etc. For each area, take note of what isn't working so well and needs improvement, what's working really well and could go to the next level, where do you spend far too much money with very little return and where do you need more people. Now spend some time evaluating and prioritizing the inventory from most impactful to least impactful.

For most of us, the key will be to start small. Pick one item from your list and focus solely on that. Focus on one where the AI is readily available, proven and affordable. It may not be your highest priority item and that's ok. You can always come back to that later.

You've picked the area of your business that you'd like to focus on. Now what? Well, you need a strategy. Lay out on paper how you want to improve, grow, reduce cost or augment people. Laying it out in stages might help. However you build your strategy, you need two items at the end. The first is a clearly defined end goal, which will serve as your north star. The second is a set of measures or KPIs to use to track your progress with AI. This is critical to know if you're moving in the right direction.

AI is heavily dependent on data, so now is the time to build a data strategy. Don't worry, it's not as complex as it sounds. Basically, you'll inventory all of the data that is involved in the process or function to which AI will be applied. For example, if you're automating accounting entries and processes, it would be all of the accounting transaction data used to make accounting entries, the subledger & general ledger data, balance sheet and income statements, etc.

After you know what data will be involved, it's time to assess your data quality. Do you have missing information, errors in the data, inconsistencies or other items that need to be corrected before feeding it into an AI engine? Now is the time to do that. This is the tedious part of the process that most people don't like to do, but it's crucial to success. It also may require upstream process changes to gather more complete and accurate data going forward.

Once your data is clean, it's time to pick a place to store all of the data together. This may be a cloud solution or a local database. Using the accounting example, this may include creating tables for transactional data, accounts receivables and accounts payables, charts of accounts info general ledger data, etc. Data should be structured well and labeled clearly. Certain AI technologies, such as machine learning, really depend on solid labels, so don't skip this step.

Once your data is clean, centralized, structured and labeled, you'll want to keep it that way. Enter Data Governance. That's a fancy name for a set of processes and rules that you'll put in place to be very intentional about how you handle data in the future. Doing so ensures that the data remains useful to the AI engine. This is sort of like a cleaning your house, condo or apartment. You don't just do a deep cleaning once and forget about it. Things will get filthy fast. Rather, you deep clean then put in place a routine cleaning regimen to ensure that the place stays clean. Data Governance is that routing cleaning regimen.

Now you can finally get to using the first AI solution that you picked. Getting going with the solution will be tool specific, so you're on your own there. However, regardless of the solution, don't expect immediate results. Most AI models, whether generative or predictive AI, require training using your pristine data. These models get more accurate over time, so be patient and monitor your key measure or KPIs to see how if things are progressing.

Admittedly, this is a very high-level approach to getting started with AI. There are many other factors, some specific to your business, which may need to be considered. The goal of this article was to shed some light on a few important first steps that most everyone will need to take as they embark on their AI journey. It's a new data-centric world out there, so now is the time to get comfortable with that fact!!

Excited about a new AI project and need some data experts to get things ready? Maybe things are in disarray, and you need some process help to improve the data you capture? Check out FailingCompany.com to find the help that you need. Go sign up for an account or log in to your existing account and start working with someone today.

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We dove into the types of artificial intelligence last week. The types were still a bit ambiguous but helped us to narrow our focus some to learn about the types of AI that would be most beneficial to us. This week we're tackling part two of the discussion and taking a look at the various categories of AI.

As I mentioned above, the types of AI may not be that meaningful to you yet. Don't worry, as that's normal. Luckily, artificial intelligence is also broken into categories. You'll likely recognize one or more of the categories as we go through them next. To get the discussion going, let's go back to ChatGPT for the answer. Again, this is just one way to categorize the capabilities. Different sources may have different categories.

According to ChatGPT, the major categories of artificial intelligence are:

"Machine Learning (ML): Machine learning is a subset of AI that focuses on developing algorithms and techniques that allow computers to learn from and make predictions or decisions based on data without being explicitly programmed for every task. It includes various types of learning paradigms such as supervised learning, unsupervised learning, and reinforcement learning.

Deep Learning: Deep learning is a subfield of machine learning that deals with algorithms inspired by the structure and function of the brain's neural networks. Deep learning algorithms, particularly neural networks with many layers (hence "deep"), have demonstrated remarkable success in tasks such as image and speech recognition, natural language processing, and autonomous driving.

Natural Language Processing (NLP): Natural language processing focuses on enabling computers to understand, interpret, and generate human language in a way that is both meaningful and contextually relevant. Applications of NLP include language translation, sentiment analysis, chatbots, and text summarization.

Computer Vision: Computer vision involves enabling computers to interpret and understand the visual world, including images and videos. It encompasses tasks such as object detection, image classification, facial recognition, and video tracking. Computer vision algorithms are widely used in fields like autonomous vehicles, surveillance, healthcare, and augmented reality.

Robotics: Robotics combines AI with mechanical engineering and computer science to design, build, and operate robots capable of performing tasks autonomously or with minimal human intervention. AI techniques such as machine learning and computer vision are essential components of modern robotics systems, enabling robots to perceive their environment, make decisions, and manipulate objects.

Expert Systems: Expert systems are AI systems designed to mimic the decision-making abilities of human experts in specific domains. They utilize knowledge representation techniques and rule-based reasoning to solve complex problems and provide recommendations or solutions. Expert systems have applications in areas such as medicine, finance, engineering, and troubleshooting.

Reinforcement Learning: Reinforcement learning is a type of machine learning where an agent learns to make decisions by interacting with an environment to achieve a certain goal. The agent receives feedback in the form of rewards or penalties based on its actions, allowing it to learn optimal strategies over time. Reinforcement learning has been successfully applied in areas such as game playing, robotics, and autonomous systems."

Hopefully many of the above categories sound familiar to you. Machine learning and Natural Language Processing are both terms that have been around for a while. Robotics is obviously a common term too. Deep Learning may be a new term for you, but get used to it. It's the hot topic recently, as Deep Learning has been important to the recent advancements of artificial intelligence.

Robotics may not be of much use to you unless you actually plan to manufacture robots or try to use them in a warehouse or for inventory control. Machine Learning and Deep Learning, however, have lots of applications. This is the AI technology that you'd want to focus on if you want to get really good a predicting market trends, building sales forecasts, evaluating risk profiles, etc.

Usually, data scientists with strong math backgrounds build machine learning models. These models are incredibly powerful and can incorporate many different data points that would otherwise be too cumbersome to work with.

For example, let's say you run an ecommerce site and want to build a product recommendation engine similar to Amazon. You can use machine learning to analyze the buying patterns and demographic data for all other people who bought a product to determine what other products will have the highest chances of also being added to the shopping cart. You can then show those products on the screen right below the product that they are looking at, similar to what Amazon does. This would be far too much data to analyze without Machine Learning!

Deep learning, a subset of machine learning, is helping to power artificial neural networks. These networks simulate the human brain and aim to replicate the decision-making ability of the brain. The networks are based on probabilities and must be trained on large data sets to produce the correct answer. That's where deep learning comes into play. Keep an eye on this one, as it's going to be crucial for the advancement of AI.

Natural Language Processing is another category of AI that can help automate your business. As an example, this technology helps to automate customer service interactions by employing a chatbot that can understand the spoken language and interact with a human. The chatbot can handle all of the easy to answer questions and issues and do a warm handoff to a human to handle the more complex issues. This allows you to provide robust customer service without having to employ a large call center.

Computer Vision is a confusing term, but I bet you've heard of some its uses. This is where facial recognition software comes into play. If you run a business that offers physical security solutions for businesses, then you'll see an increased trend in the move to facial recognition over things like biometrics or RFID access badges. Facial recognition is much more accurate and much harder to bypass than older technologies. This is critical for those who maintain trade secrets, confidential or classified information, etc.

Computer vision is also important in improving online search capabilities. Have you ever used Google's image search, where you can search for a specific image online? That uses computer vision technology. If you run a large ecommerce site with lots of products, you could offer a similar search capability to help customers find a product they are looking for if they don't know the name or correct keywords. This could be incredibly useful feature if you sell clothing online and someone wants to see if you carry a specific sweater but doesn't know the brand name.

If you have clients who are always looking for the edge in decision making or simply have too many decisions to make in a day, then you may want to familiarize yourself with expert systems. These systems are incredibly advanced at answering question. They have been used in the medical field to diagnose patients based on their symptoms. Another example is IBM's Watson, which is a question answering system that famously defeated the human champions on Jeopardy.

Finally, there is reinforcement learning. Reinforcement learning is used in a lot of things. One example is it's used in optimizing trading strategies to maximize profits. Agents learn to make buy or sell decisions based on market data and historical trends while aiming to maximize returns. If you're in the investment business, then you may want to check this out.

Wow, that was a lot of categories! So, what do you think? Do any of these categories of AI make more sense to you. Is AI starting to see a little less mysterious yet? Can you see any uses for your business? Hopefully you'll stick around as we start to explore different ways that you can implement AI in your business.

Is AI starting to click now and you need an expert to help you implement a specific type or category of AI? Maybe you just need some help getting things back on track so you can finally have time to learn more? Check out FailingCompany.com to find the help that you need. Go sign up for an account or log in to your existing account and start working with someone today.

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Last week we started our journey into learning a bit more about artificial intelligence, or AI for short. We went walked through a primer on AI and even let ChatGPT, a popular AI engine, tell us what must be present for something to be considered AI. We'll continue to ease into the subject again this week by further demystifying the subject. This will be a two-part article, so stick with me.

Now that we know a little more about what AI is, let's take a look at some of the major types of AI. It's a broad continuum spanning from mundane tools that are easy to overlook to truly amazing capabilities. With the ever-changing landscape, how you know which to watch and which to ignore? Luckily, all of these capabilities fall into a handful of types and categories of AI, and that's what we'll start exploring today.

Let's keep testing ChatGPT to see what it says about the types of AI. According to ChatGPT, the major types or AI include the following:

"Narrow AI (Weak AI): Narrow AI, also known as weak AI, refers to AI systems that are designed and trained for specific tasks or narrow domains. These systems excel at performing specific functions within a limited context but lack general intelligence. Examples include virtual personal assistants like Siri and Alexa, recommendation systems, and image recognition software.

General AI (Strong AI): General AI, also known as strong AI or artificial general intelligence (AGI), refers to AI systems that possess the ability to understand, learn, and apply knowledge across a wide range of tasks, similar to human intelligence. General AI would have the capacity for reasoning, problem-solving, creativity, and adaptability across various domains. Achieving true general AI remains a theoretical goal and is the subject of ongoing research.

Reactive AI: Reactive AI refers to AI systems that can react to specific inputs or stimuli but do not have memory or the ability to learn from past experiences. These systems produce responses based solely on the current input and predefined rules or algorithms. Reactive AI is often used in tasks such as game playing (e.g., chess-playing programs) and automated systems (e.g., autopilot systems in aircraft).

Limited Memory AI: Limited memory AI systems have the ability to learn from historical data or past experiences to make decisions in real-time. Unlike reactive AI, these systems can retain a limited amount of information about past interactions or observations, which influences their decision-making process. Examples include autonomous vehicles that learn from past driving experiences to improve navigation and decision-making.

Theory of Mind AI: Theory of mind AI refers to AI systems that have the ability to understand and interpret the mental states, beliefs, intentions, and emotions of other entities, such as humans or other AI agents. This type of AI is still largely theoretical and remains an area of active research, particularly in fields like human-robot interaction and social robotics.

Self-Aware AI: Self-aware AI, also known as consciousness AI, refers to AI systems that possess self-awareness or consciousness, similar to human beings. This level of AI would have subjective experiences, emotions, and a sense of self-awareness. Self-aware AI is currently purely speculative and remains a topic of philosophical debate rather than a practical reality."

What's important to note is that the above six types of AI are simply one way to define the types. AI is ever evolving and if you check five sources as to how they define the types of AI, you'll likely get five different answers. It's most beneficial for us to focus on Narrow, Reactive, and Limited Memory AI. General, Theory of Mind and Self-Aware AI are too theoretical for practical application for most businesses.

Focusing on Narrow, Reactive and Limited AI certainly narrows down the field a bit and makes things slightly more bite sized. Can you think of some ways that one or more of these types of AI can be applied to your business? I'll give you a few quick examples to get the gears in your mind turning.

Bouncing around a bit, let's start with Reactive AI. Do you happen to create games or other software where the computer needs to simulate a player or user? Or, perhaps you'd like to offer your customers a simple decision support system, where they enter some pre-defined criteria and the AI engine provide the best recommendation. If so, then you may wish to explore Reactive AI in much more depth.

Maybe you plan to become the industry leader in providing autonomous driving software to the auto industry. If so, then you'd definitely want to study Limited Memory AI. You'd likely want to study some of the existing autopilot systems within the realm of Reactive AI as well. Combining best practices from both of these types of AI should get you far down the road of creating a marketable autonomous driving software product for the industry.

As for the rest of us, we'd probably want to spend our time learning about Narrow AI. The capabilities being developed in this space can definitely help us automate our back-office processes. From the application of chatbots for our customer service systems to leveraging image recognition software to improve online product searches, this type of AI has a lot to offer the small business owner!

Admittedly, the above types are broad and may not be that meaningful to you yet. Don't worry, as that's normal. Luckily, artificial intelligence is also broken into categories. We'll tackle the common categories next week. You'll likely recognize one or more of the categories as we go through them. Until then, this is plenty to digest for this week.

Did you see the value that one or more types of AI could bring to your business and want some expert help? Maybe you just need some help digging your business out of it's hole so you can begin thinking about how to leverage AI? Check out FailingCompany.com to find the help that you need. Go sign up for an account or log in to your existing account and start working with someone today.

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I mentioned in last week's post that I'll be spending the next few weeks on artificial intelligence, or AI for short. Particularly, how it can be applied to back-office operations. It's natural if you feel a little fear about AI, as some may have flashbacks to the Terminator movies. Is it all bad or can we find some good in AI?

For this week's post, I think a primer will be in order. Just about everyone has heard of AI, but many don't really know what it means. For some, it brings up images of robots walking around and doing stuff that humans can do. Those do exist and certainly fall into the category of AI, but AI is much broader than that example.

I'll start by breaking the words downs and defining them, then we'll look at the actual definition for AI. AI, or Artificial Intelligence, is two common words put together. The first word, Artificial, means humanly contrived often on a natural model according to the Merriam-Webster dictionary. Essentially the word artificial means man-made. Think about artificial sweeteners. There are man-made and are intended to mimic real sugar, it's natural model.

Intelligence, according to the Merriam-Webster dictionary, means the ability to learn or understand or to deal with new or trying situations. Intelligent people can both learn new things and apply that learning to various scenarios in life. Putting the two words together, artificial intelligence means a man-made ability to learn or understand or to deal with new or trying situations. Not so scary, right?

The official definition of artificial intelligence, according to the Merriam-Webster dictionary, is the capability of computer systems or algorithms to imitate intelligent human behavior. That's a pretty broad definition. It's also why it's so intimidating to many. If the computer has the ability to imitate intelligent human behavior, then humans will become obsolete, right? Not exactly. The definition says to imitate intelligent human behavior, NOT to imitate ALL human behavior. That distinction is really important.

The majority of artificial intelligence applications cannot think and reason like a human in every capacity. They are usually specialized to perform a specific function. Think about Alexa or Siri for a moment. They use AI to interpret human speech and perform some action in response. Perhaps it will play a song, retrieve some information from the internet or maybe even turn off the lights in a connected smart home. It CANNOT walk over and adjust the old-fashioned manual thermostat or taste the milk, realize that it has gone bad and pour it out. It can only operate intelligently in the capacity for which it was designed.

At its core, AI is software written by humans that has some ability to store and/or interpret data, detect patterns and probabilities, perform some action based on that interpretation and learn from the data and/or outcome of the action to become more accurate in the future.

I thought it would be fun to demonstrate an AI system in action. I went to ChatGPT, a well know AI system, and asked the question, "What basic capabilities must any system have to be considered artificial intelligence?" Below is the answer:

"To be considered artificial intelligence, a system must possess certain basic capabilities that enable it to mimic or exhibit some aspects of human intelligence. Here are some fundamental capabilities typically associated with artificial intelligence:

Perception: AI systems should be able to perceive and interpret data from their environment, which may include inputs such as text, images, audio, or sensor data. Perception can involve tasks such as image recognition, speech recognition, and sensor data processing.

Reasoning: AI systems should be capable of reasoning and making logical deductions based on available information. This includes tasks such as problem-solving, planning, and decision-making. Reasoning enables AI systems to draw conclusions, generate solutions to problems, and take appropriate actions.

Learning: AI systems should be able to learn from data or experience and improve their performance over time. Learning can take various forms, including supervised learning (learning from labeled data), unsupervised learning (finding patterns in unlabeled data), and reinforcement learning (learning from feedback). Learning enables AI systems to adapt to new situations and improve their ability to perform tasks.

Adaptability: AI systems should be adaptable and able to respond to changes in their environment or task requirements. This includes the ability to generalize knowledge learned from one task to perform well on related tasks, as well as the ability to learn new tasks or concepts efficiently.
Natural Language Understanding: Many AI systems need to understand and generate human language to interact effectively with users. Natural language understanding involves tasks such as language parsing, semantic analysis, and language generation. This capability enables AI systems to process and generate text or speech in a way that is meaningful and contextually relevant.

Autonomy: AI systems should be able to operate autonomously, making decisions and taking actions without constant human intervention. Autonomy enables AI systems to perform tasks independently and can range from simple decision-making in rule-based systems to complex decision-making in systems using machine learning or other AI techniques.
Interaction: AI systems should be capable of interacting with humans or other systems in a manner that is natural and intuitive. This may involve interfaces such as graphical user interfaces, voice interfaces, or chatbots. Interaction enables users to communicate with AI systems effectively and provides feedback to the system to improve its performance."

This answer was returned back in a couple of seconds. Not that many years ago, I would have spent hours reading AI websites and books to gain the knowledge, then additional time distilling it down into the above summary. Now, I have this information at my fintertips within seconds. I spent more time writing the input question than it took to generate the answer. Can you see how powerful this can be for your business?

Now, let's dig into the the response a bit. An AI system must be a be able to perceive and interpret data, make some deductions based on that that data, learn from the data or experience to get better, adapt as the environment or task changes, and run with little human intervention. That sounds more like a fancy computer program than some scary robot race trying to take over the world. Basically, AI is a really smart computer program, or set of algorithms, that can interact with various types of data and learn from it to get better at it's task. It mimics human intelligence, but does not clone or replace it.

I hope you're starting to see how AI shouldn't be feared. Yes, it will replace certain jobs in the future. People doing those jobs should begin training now to switch careers. However, AI can provide tremendous benefit to a company. The possibilities are endless. From insanely fast market research to automating accounting entries, AI can help.

In the past, if you wanted to grow your business, you had no choice but to hire more people. Now, a person can compete with much larger competitors by setting up AI models for things that used to require adding headcount. That means that you can run leaner and adapt quicker to changing market conditions and become a real force in your industry. Not that long ago you may have been locked out of that same industry due to high barriers to entry. This is powerful!

AI levels the playing field. True, very sophisticated AI capabilities take huge investments to develop, but very few companies with that much investment capital available are spending it on AI right now. That means that the small competitor, who hasn't already hired a small army to perform back-office functions, can employ cheaper and less sophisticated AI capabilities and see HUGE gains in efficiency and effectiveness!

Do you still want to run from AI? Hopefully, you're ready to at least learn a little more about it rather than just ignore it. Don't be Blockbuster and ignore the emergenging trends. AI is here to stay and the quicker you adopt it, the quicker you'll benefit from it.

Are you interested in getting some help implementing AI in your company to achieve your growth strategy? Perhaps you hit some hard times and would like to see how AI might fit into the plan of getting your company back on track? Check out FailingCompany.com to find the help that you need. Go sign up for an account or log in to your existing account and start working with someone today.

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We wrapped up The Unconventional Wisdom of Jesus mini-series last week. It's always hard to figure out where to go when you wrap up something long-term like that mini-series. I spent some time pondering the right next step and realized that the answer was in the dilemma. Rather than keeping you guessing, let's dig into it!

What do you do when you spend months or years working towards some big goal and it doesn't pan out? How do you move forward from that? Months or years gone without anything to show for it. It's easy to throw up your hands and give up, to let depression sink in or to simply quit pushing towards your other goals.

We've all had something that didn't pan out for us despite our best efforts. Have you ever worked for years at a job to earn a promotion only to be told that you'll never get it? It's a punch in the gut for sure! You begin to spend a lot of time questioning why you invested so much time for nothing. That gets you questioning the time and effort that you're putting into your other goals. It totally messes with your confidence. Why not just quit now and be done with it?

The harsh reality is that we don't always win, and we don't always get what we want. Putting in lots of time on a goal only to not achieve it is a reality sometimes. It's also a reality that you're not a failure when that happens. It happens to the most successful people in world, only their mistakes probably have more zeros at the end. With that perspective, welcome to the club!!

What separates the successful people from the failures is what we do after we don't achieve our goals. Successful people learn from their mistakes, adjust course and keep going. They actually try to fail fast so they can learn faster. They also always have other goals waiting in line to be achieved. Failure is simply one step closer to their ultimate success, as they learned one more thing NOT to do when going after the next goal.

People who are "failures" habitually just quit after a big failure. They tuck their tails between their legs and run. They see the failure as the end of the road and internalize that failure. It becomes a part of them and dramatically affects their lives for quite some time. They don't take the time to find the lesson in their failure and, as a result, never see it as a steppingstone to some bigger achievement. It's simply too final in their mind to see it that way!

As you can see, it's all about mindset. Your mindset can work for you, or it can work against you. Mindset can also help you to see opportunity in change or drive you to be resistant to change. Not achieving a goal that you expected to achieve is definitely one example of a change. However, change is all around us in many different forms. For example, technological change is occurring at a faster rate now than ever before. Does your current mindset let you look for opportunity in technology advancement or do you resist it because the old ways work better??

Even if you're someone who looks for opportunity in change, it can still be a scary proposition. Probably the most fear-provoking technological development in recent times is the advancement of artificial intelligence, or AI for short. Mention AI and many react like AI will bring about doomsday. It'll eliminate just about all jobs and eventually take over the world.

That's fear talking. We tend to exaggerate those things that we fear and don't understand. It's important to educate yourself on those changes, technological or otherwise, which generate tremendous fear for you. Then you can move forward and truly embrace the opportunity, be an early adopter and gain the competitive advantage!

As such, I think I'll dedicate the next few weeks to exploring AI a little more. Particularly, the application of AI to back-office automation in the corporate setting. Let's see if we can help shine a spotlight on what's causing the fear and help you look past that to begin exploring the opportunities. Like it or not, AI is here to stay. Let's see if we can get you to embrace it and maybe even profit from it!!

Have you recently hit a dead end on a major goal and are looking for where to go from here? Perhaps you love being the early adopter and need some experts to help you capitalize on a big opportunity? Check out FailingCompany.com to find the help that you need. Go sign up for an account or log in to your existing account and start working with someone today.

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