Embracing AI: A Comprehensive Guide for Middle Market Leaders

It's no longer a question of whether Artificial Intelligence (AI) will survive. It’s a question of how your business can survive without AI. The short answer is that it won't, at least not in the long term. Middle market executives leading organizations valued between $10 million and $1 billion face the challenge of finding the right balance between early adopters and being the last ones to the party.?

Given the pressure on financial, human, and technological resources unique to middle-market companies, the impact on revenue, profitability, productivity, and customer and employee experience will be amplified. Move too fast, and you’ll waste precious resources. Move too slowly, and you'll miss your window to gain the edge AI can provide. So, how do you find the sweet spot for your organization??

Keep reading to find out.??

AI has moved beyond sci-fi fantasy and is now a real game-changer for businesses today. If you're a middle-market leader—AI presents thrilling opportunities and serious challenges. Let’s dive into how you can tackle AI, from navigating ethical and legal issues to setting goals and leveraging strategic benefits. We’ll cover how to integrate AI into your business in a thoughtful, forward-thinking way and provide insights to determine if AI is helping or hurting your overall business.?

Understanding AI in the Middle Market Context

AI encompasses a wide range of technologies that enable machines to perform tasks typically requiring human intelligence. For middle-market companies, integrating AI can streamline operations, enhance decision-making, and offer competitive advantages. However, successful AI integration demands careful planning and consideration of several factors.

There are four primary ways to apply AI.?

1. Robotics in industrial and residential settings have been around for a long time.?
2. Natural Language Processing (NLP) addresses the need for language translation and virtual assistants. Siri and Alexa answer over a billion questions a day. Does anyone write anything without using ChatGPT or Gemini anymore??
3. Computer Vision Technology is used for facial recognition, image tagging, and recognition.?
4. Machine Learning is the element I’m most excited about due to predictive analysis and pattern recognition. These babies can chew through data at lightning speed and, when appropriately applied, can help leaders make data-driven decisions significantly faster with far more precision.?

Diving right into the technology is akin to taking a ‘ready-shoot-aim’ approach that will not serve you or your business in the long run. As leaders, we need to think about the less sexy yet essential elements of AI before we can begin playing with the tools and toys that help us move faster. With AI, you will move faster. You want to make sure you’re moving faster in the right direction!

Moral and Ethical Considerations

1. Bias and Fairness

AI systems are trained on data; if this data contains biases, the AI can perpetuate or even exacerbate these biases. For example, if an AI tool is used in recruitment, it may unintentionally favor certain demographics over others if its training data reflects historical biases. Middle market leaders must ensure that their AI systems are developed and tested to be fair and unbiased. This involves:

• Diverse Data Sets: Using diverse and representative data to train AI systems.
• Bias Audits: Regularly audit AI outputs for signs of bias and implement corrective measures.
• Transparency: Being transparent about how AI decisions are made and ensuring human oversight is part of the process.

How can you be sure your organization is eliminating bias and unfairness to the best of its ability? If your organization is developing new technology or using third-party software, ensure you or your vendor of choice are following these best practices:

1. Diverse Data Collection

Gather Inclusive Data: Ensure the training data represents diverse demographics, contexts, and scenarios. This helps create more representative models less likely to favor any particular group.

Audit Existing Data: Regularly review and audit datasets for any imbalances or biases. Address underrepresented groups or scenarios that could lead to skewed outcomes.

1. Implement Fairness Checks

Use Fairness Metrics: Employ metrics and tools designed to measure fairness in AI models. These can help identify biases and disparities in predictions or decisions.

Regular Testing: Continuously test AI systems against various demographic groups and scenarios to ensure fair outcomes.

1. Incorporate Ethical Guidelines

Follow Ethical Standards: Develop and adhere to ethical guidelines and frameworks for AI development that emphasize fairness and equity. More information and guidance are being made available daily.

Engage Stakeholders: Include diverse voices in the development process, including ethicists, domain experts, and representatives from affected communities.

1. Transparent Algorithms

Promote Transparency: Ensure that the algorithms and decision-making processes are transparent. Understand how decisions are made and what factors are influencing outcomes. If (or when) you don’t understand something, make the team slow down and explain it until you do. If they can’t explain it in kitchen English, chances are they don’t understand it, and you are headed for trouble.?

Explainability: Implement AI solutions that offer explainable results so stakeholders can understand and challenge decisions if needed. Here’s where assuming the computer is always right is the wrong approach. Test, challenge, and use your instincts. They will serve you well.?

1. Bias Mitigation Techniques

Algorithmic Adjustments: Apply techniques to reduce bias, such as re-weighting data, modifying algorithms, or incorporating fairness constraints.

Bias Audits: Conduct regular bias audits and updates to AI systems to identify and correct any emerging biases.

1. Training and Awareness

Educate Teams: Train AI development teams on ethical considerations and bias mitigation strategies. This goes beyond your technology team. Business leaders, legal, HR, compliance, and customer service teams must be in the loop.?

Foster a Culture of Fairness: Promote a company-wide culture prioritizing fairness and ethical considerations in AI projects. Don’t just encourage but require team members to adopt a policy of ‘if you see something, say something.’ When everyone is looking out for the greater good, you are more likely to succeed.?

1. Third-Party Reviews

External Audits: Engage third-party experts to review AI systems for bias and fairness. Independent assessments can provide valuable insights and ensure objectivity.

Partnerships: Collaborate with organizations and institutions specializing in AI ethics and fairness to stay informed about best practices and emerging standards.

1. Feedback Loops

Gather User Feedback: Collect end-user feedback to identify unintended consequences or biases in AI outputs.

Iterative Improvements: Use feedback to continuously improve and refine AI systems to address fairness concerns better.

If you want to geek out and dive deeper into the topic, check out Science Direct’s Literature Review, which offers a plethora of resources to guide you on your journey.?

2. Privacy

AI often relies on large amounts of data, which can raise privacy concerns. Middle-market companies must prioritize data protection and comply with regulations such as the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and countless other privacy regulations if your business is global.?

Keeping up with privacy requirements alone is enough to make even the bravest leader quit before they even get started. With the proper guidance, practices, and a heavy dose of common sense in favor of the consumer, your organization will do the right thing.?

This is not an area where you can take a shortcut and is a significant factor to consider before moving forward. Many middle market organizations need a more robust infrastructure to manage the ever-changing world of privacy properly. Include this as you factor your Total Cost of Ownership (TCO) for every initiative.?

Key practices include:

• Data Anonymization: Anonymizing personal data wherever possible.
• Informed Consent: Obtaining explicit consent from individuals before collecting or using their data.
• Data Security: Implementing robust security measures to protect data from breaches.

3. Job Displacement

This has been such a hot topic lately. People are afraid AI will take away their jobs. The reality is that AI can (and will) dramatically impact jobs. Maureen Metcalf, the founder of the Innovative Leadership Institute and podcast host, has an interesting point of view. She believes that people who ignore AI won’t lose their jobs to AI; they’ll lose their jobs to people who know AI, at least in the near term.

The potential for automation, improved decision-making, curated customer experiences, and other efficiencies and enhancements could lead to job displacement. As a middle market leader, you can approach this challenge by investing in:

• Reskilling Initiatives: Invest in training and reskilling programs to help employees transition into new roles. In most cases, you don’t have to throw the baby out with the bathwater. Team members who understand the organization and your customers or create products and services are the company's lifeblood. Upskill your dedicated team members, and your company will thrive.?
• Job Creation: Explore how AI can create new job opportunities within the organization. In addition to hiring people with shiny new AI skills, another exciting thing happens. When more work gets done, that often leads to more work being generated. For example, you turn on machine learning to analyze the past five years of customer data, and a flurry of new products, services, and organic growth campaigns is now possible. Leverage this as an opportunity for significant growth.?

Legal and Intellectual Property Concerns

1. Intellectual Property (IP) Protection

This area continues to become increasingly murky and warrants close attention. A client of mine works for a major cosmetics company and is the executive overseeing their influencer media strategy. AI is massively effective and widely used in social media and organic marketing. The problem is that the outputs provided regurgitate everything else out there. This raises complex questions about who owns the image rights, the marketing copy, IP, etc. Add 25 countries to the mix, and you are deep into complexities you haven’t bargained for.?

IP is an essential element to the value of every company, and AI technologies and solutions can be patentable or subject to copyright. Protect your ideas and innovations by:

• Filing Patents: Securing patents for unique AI algorithms or applications.
• Copyrights: Using copyrights to protect proprietary AI code and software.
• Getting External Counsel: Keeping up with the fluid landscape of IP and AI is nearly impossible, and your time is better spent elsewhere.?

2. Data Ownership

Data is a critical asset in AI development. Companies must clearly define data ownership rights and ensure that they have legal access to the data used in training their AI systems. This involves:

• Data Agreements: Establishing clear agreements regarding data usage and ownership with partners and third parties.
• Contractual Clauses: Including specific clauses in contracts to protect data rights and ensure compliance with data protection regulations.
• Third-Party Software: Clarity on who owns what is essential when using third-party AI systems in your business. Be sure to read the fine print.?

3. Compliance

Compliance is the least sexy legal concern. Yet, it is essential to provide guardrails so that employees can do the right thing and you can sleep at night without worrying about the next audit or being subject to headline risk in the media.?

AI applications must comply with various legal regulations, including data protection, discrimination, and consumer rights. Middle market leaders should make sure your internal and third-party applications are continuously in compliance:

• Regulatory Awareness: Stay informed about relevant regulations and ensure AI systems comply. Regulations can be vague and difficult to understand. The critical element here is consistency. Get the best guidance you can, decide how this applies to your company, and stick to it.?
• Legal Consultation: Seek legal advice to navigate complex regulatory environments and mitigate legal risks. Most middle-market companies cannot afford to have this in-house. Your best bet is to partner with a firm specializing in this area so you know you have the best and most current legal advice available.
• Three Lines of Defense: Align your strategy to monitor this from various points within your organization: the teams closest to the customer (1st line), the teams processing the work (2nd line), and the teams overseeing that work is being done properly (3rd line).

Setting Strong Goals Before Using AI

Now we’re getting to the fun stuff. Once you've done the necessary work to establish your strong foundation, it might be tempting to dive right into all the tools and toys and see what works best for your company.?

Getting your leadership team and those closest to the work involved in setting your goals is essential to your success. Your visionaries, finance, and customer service teams will be invaluable here.?

1. Define Clear Objectives

Before implementing AI, it’s crucial to define clear objectives and outcomes. Middle market leaders should:

• Identify Business Problems: What are you solving for? Are you trying to fix something broken or amplify a unique opportunity in the marketplace? What are your customers saying? What are your five-year goals, and what are the most significant things standing in the way of your success? What do your team members feel they need? Determine specific business problems or opportunities that AI can address.
• Set Measurable Goals: The shiny object syndrome AI offers makes it even more important to be relentless when defining success and how to measure it. Establish measurable goals for AI implementation, such as improving operational efficiency, increasing revenue, or enhancing customer satisfaction. It's so easy to get sucked into the fun of AI if you have the right mindset. A cool avatar is just an expensive toy if it doesn’t improve your customer experience and productivity.?

2. Assess Feasibility

The last thing you want to do is get half-pregnant with a solution to find out you’ve bitten off more than you can chew. Leverage a systematic approach to evaluate whether AI is the right solution for the goals you just defined. Think about what you need today and where your needs will be years down the line as your business expands and the dynamics shift. If you happen to have someone who is or has been trained as a futurist, keep them close to this part of the process. This involves:

• Technology Assessment: Assessing whether existing AI technologies can meet the company’s needs and the difficulty of implementation and maintenance.?
• Ethical and Legal Complexity: How many rabbit holes will you need to go down, and what level of external advisors will you need??
• Resource Evaluation: Evaluating the resources required for successful AI implementation, including the talent needed for strategic thinking, development, implementation, operations, infrastructure, and budget.

3. Develop a Roadmap

Roadmaps are a mainstay in most organizations, but you need to alter the playbook a little when it comes to AI. Iterative approaches will be your lifeline. Adopt an open mindset to get the organization to experiment, crawl, walk, and run. Have a bailout plan before you start, and account for approximately 30% of the initiatives to fall short of results you expect for one reason or another. Below are 5 new things to implement above and beyond how you usually run your projects.

• Project Phases: Create micro-phases with frequent checkpoints to ensure everyone is on track. Leave considerably more time for experimentation before you decide how to proceed.?
• Experimentation: This goes way beyond the usual vendor bake-offs and beauty contests we typically do as a process of choosing technology. New players are emerging daily, and much is to be said about experimentation. Have various team members literally “play” with the different solutions being considered for a few months. When multiple people do this concurrently, they can come back with first-hand experience and help guide the overall strategy and tool selection.?
• Expanded Teams: This will require all hands on deck because it will impact many aspects of your organization, and it’s new. This is not the time for silos, so be inclusive and go more expansive than usual with team involvement.?
• Timelines: Set realistic timelines for each project phase and then double them. Your team may be new at this, and you may be leveraging new external resources. Delays and surprises are inevitable, so plan and budget for them ahead of time.?
• Budgeting: When allocating a budget for AI development, implementation, and maintenance, remember to include the extra project time and resources required to maintain the solid ethical and legal foundation you’ve built. Leverage your teams' fantastic work establishing goals and metrics to have more confidence in that ROI. You don’t want to chase a pipe dream that can lead your company in the wrong direction.?

Leveraging AI for Competitive Advantage

One of my clients is the CEO of a security detection device manufacturer. They develop, manufacture, and sell bomb detection devices and similar products used globally. Staying one step ahead of the bad guys is a never-ending process. It took 6-months for something to go from R&D to production. With the use of AI and 3D printing, the process is now three weeks. This has been a game changer for the organization, and the engineering team is churning out better ideas faster than ever. Their customers are thrilled with the turnaround time and ability to keep pace with changing technology. Revenue and profit margins are soaring.?

How can you get in on the action???

1. Enhance Operational Efficiency

The upside of AI can be significant. Whether your opportunities lie in Robotics, NLP, Computer Vision, or Machine Learning, there is an upside almost everywhere you turn. AI can automate routine tasks, streamline processes, and improve operational efficiency. Here are the first opportunities middle market leaders should be looking to capitalize on.?

• Automate Repetitive Tasks: Use AI to handle repetitive and time-consuming tasks, freeing employees for more strategic work.
• Optimize Operations: Implement AI-driven analytics to optimize supply chain management, inventory control, and other operational areas.
• Accelerate Data-Driven Decisions: Your organization has terabytes of pure gold lying untapped. Leverage AI to crunch this once elusive and disparate data and turn it into powerful knowledge you can act upon.

2. Improve Customer Experience

AI can dramatically enhance customer experience through personalization and efficient service. Gone are the days of inefficient chatbots and believing that putting someone's first name on an email counts as personalization. Someone in your market will crack the code to customize their experience, predict what your customers want, and capitalize on it.? Consider:

• Personalized Marketing: Using AI to analyze customer data and deliver personalized marketing messages and recommendations.
• Predictive Experiences: Leveraging every ounce of data to anticipate your customers' needs and be there for them exactly when they need you.?
• Chatbots and Virtual Assistants: Implementing AI-powered chatbots and virtual assistants to provide 24/7 customer support and resolve queries quickly.

3. Drive Innovation

How many great ideas have you and your team had over the years that fell by the wayside because it was too expensive, complicated, or unproven? AI can be a catalyst for innovation, enabling companies to develop new products and services. Middle market leaders can:

• Explore New Markets: Use AI to identify emerging market trends and opportunities for new products or services.
• Enhance Product Development: Leverage AI in the R&D process to accelerate product development and enhance product features.
• Faster Market Testing: You no longer need to wait six to twelve months before deciding whether an idea is a winner or loser. Get more actionable data faster to tweak and adjust as you learn more.?

Foresight and Strategic Planning

As you dive into the world of AI, you will see that this requires a steady hand on the rudder at all times. Technology, ethical, legal, and business landscapes are evolving rapidly, and your organization must keep pace. Welcome to the new normal!??

The need to maintain pace will change how you forecast expenses, where you align your resources, how you choose the strategic partners you use, and how you think about your business growth.?

1. Continuous Learning

Most of your organization will need to keep on top of the latest and greatest in their particular area of focus. Again, this isn’t just a technology play. This involves:

• Ongoing Education: Professional development is required for employees across the entire business involved in AI projects.
• Industry Trends: Stay abreast of industry trends, including legal, ethical, and technological advancements, will help ensure your AI strategies remain relevant and practical.
• Changes in the regulatory and ethics environment: Monitor the latest regulations, best practices, and technological advances to ensure AI is used responsibly. ?

2. Adaptability

The rate of change has never been faster, and the impact of your decisions will be amplified. Keep your AI strategies flexible and adaptable to changing conditions. Don’t over-commit to a specific technology; keep your processes agile and design for flexibility to modify policies and compliance rules as needed.? As you navigate your new normal, middle market leaders should:

• Monitor and Evaluate: Regularly monitor AI performance in all impacted areas of your business and evaluate its effect on your customers, employees, and financial results.
• Iterate and Improve: Approach everything with an experimental mindset so you are prepared to iterate on AI solutions and improve based on performance data and feedback.

3. Ethical Considerations

As AI technology advances, new ethical challenges continue to arise. If you build a solid foundation to maintain ethics and limit bias, keeping pace with these changes will be less daunting. Here are two things that will help keep your organization on track:

• Ethical Framework: Develop an ethical framework for AI use, considering emerging ethical issues and incorporating best practices. Be fully transparent with your framework throughout the organization, and require your teams to report anything headed off course.?
• Stakeholder Engagement: Engage with stakeholders, including customers, employees, suppliers, futurists, and regulators, to address ethical concerns and build trust. No one can keep track of everything, especially with the rapid rate of change. Build a strong bench of trusted advisors and keep them close.??

Conclusion

Incorporating AI into your middle-market business isn’t just about keeping up with the latest tech trends—it's a chance to drive innovation, boost efficiency, and sharpen your competitive edge. But getting it right means more than just jumping on the AI bandwagon. You must think carefully about ethical issues, legal matters, and strategic planning.

To make the most of AI, set clear goals, use the technology wisely, and keep an eye on the future. Navigating the complexities of AI can be challenging, but with the right approach, you can unlock its full potential and steer your business toward greater success.

If you are looking for more resources on leading in the age of AI, check out my article in Coaching Life Magazine on 7 Secrets to ‘Keeping it Human” in an Increasingly AI-Driven World.’ Another book I love is Innovative Leadership & Followership in the Age of AI: A Guide to Creating Your Future as a Leader, Follower, and AI Ally.?

Are? you ready to take the next step? Don’t go it alone—reach out to CWC. We’re here to help you integrate AI thoughtfully and effectively, ensuring you harness its benefits while addressing potential challenges. Let’s work together to make AI a powerful asset for your business and shape a brighter, more equitable future. Book your free AI readiness discussion with me today!