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By John Ryan
It’s difficult to have a business conversation today without discussing Artificial Intelligence. Whether it’s automating routine tasks, analysing large volumes of information, generating reports, or supporting decision making, AI is becoming part of everyday working life in many organisations.
Naturally, this has led to questions about the future of professional skills. If technology can analyse data faster than humans, what role will people play in solving business problems? If AI can generate recommendations, where does that leave improvement professionals?
From my perspective, AI will undoubtedly change the way organisations work, but it doesn’t reduce the need for structured problem-solving. If anything, it increases its importance. The organisations that achieve the greatest value from AI will be those that understand how to apply it effectively, where to apply it and how to turn insight into action.
One of AI’s greatest strengths is its ability to process and analyse information quickly. Tasks that previously required significant amounts of time can now be completed in seconds. Patterns can be identified faster, data can be summarised more efficiently and potential solutions can be generated almost instantly. These are impressive capabilities and organisations should absolutely look for opportunities to benefit from them.
However, access to more information does not automatically create better decisions. Before any organisation can implement a solution, it must first understand the problem it is trying to solve. It needs to determine whether the issue is important, whether it aligns with strategic priorities and whether solving it will deliver meaningful value. These are not technology questions. They are business questions.
This is where structured improvement methodologies continue to play an important role. Lean Six Sigma has always provided organisations with a framework for understanding problems, evaluating opportunities and focusing effort where it will have the greatest impact. The availability of better tools does not remove the need for that discipline. If anything, it makes it more important.
As AI becomes more capable, organisations will have access to more data, more analysis and more recommendations than ever before. The challenge will not be finding information. The challenge will be deciding what matters, what should be prioritised and what actions are most likely to deliver meaningful results.
One of the biggest misconceptions surrounding AI is that more answers automatically lead to better outcomes. In reality, the quality of the outcome still depends heavily on the quality of the thinking behind it. AI can identify patterns and generate recommendations, but organisations still need people who can evaluate evidence, assess risks, challenge assumptions and understand the wider context surrounding a decision. I’ve always viewed Lean Six Sigma as a discipline that develops critical thinking. It encourages people to ask better questions, test assumptions, examine evidence and avoid jumping to conclusions.
Those capabilities become even more valuable when information is abundant. The challenge is no longer finding answers. The challenge is determining which answers are relevant, reliable and worth acting upon.
Throughout my career, I’ve worked with organisations that had plenty of data but still struggled to solve important business problems. The reason is simple. Data tells us what is happening. It doesn’t always explain why it is happening. Nor does it tell us how people, processes, customers, suppliers, or organisational culture might be affected by a change. This is where human judgement remains essential.
A Lean Six Sigma practitioner understands not only the numbers, but also the process behind the numbers. They understand the operational reality surrounding a problem. They understand the people involved, the risks associated with change and the practical challenges that can affect implementation. AI can provide valuable insight. Experience and judgement help turn that insight into effective action.
One of the most important lessons I’ve learned over the years is that improvement projects succeed or fail because of people. That was true before AI. It’s true today and I believe it will remain true in the future. Even when an organisation identifies a clear opportunity, implementation requires communication, engagement, leadership and stakeholder commitment. People need to understand why a change is being made. They need confidence in the proposed solution. They need to believe the change will create value.
Introducing AI into an organisation doesn’t remove those requirements. In many cases, it increases them. As new technologies become part of everyday operations, organisations need people who can help others understand the benefits, address concerns, build trust and guide teams through change. Those are precisely the kinds of skills that successful Black Belts develop.
When many people think about Lean Six Sigma, they focus on analytical tools. Those tools are important. However, the role of a modern Black Belt extends well beyond analysis. Black Belts help organisations identify opportunities, evaluate risks, facilitate decision making, align projects with strategic goals, manage stakeholders and lead change. Increasingly, they also need to understand how emerging technologies can support improvement efforts. That doesn’t mean becoming an AI specialist. It means understanding how to apply structured thinking to new opportunities and ensuring technology is used to solve meaningful business problems. In many organisations, Black Belts are becoming the bridge between technology, operations and people.
Rather than viewing AI and Lean Six Sigma as separate disciplines, I believe they are highly complementary. AI can help organisations work faster, Lean Six Sigma helps organisations work smarter.
One accelerates analysis. The other provides structure. Together, they have the potential to create significant benefits for organisations that are prepared to develop both capabilities.
The organisations that will benefit most from AI won’t simply be those with access to the latest technology. They will be the organisations that develop people who can think critically, solve problems systematically, evaluate evidence and lead change effectively. Those capabilities have always mattered.
Today’s environment makes them even more important. This is one of the reasons the SQT Lean Six Sigma Black Belt Programme focuses on much more than tools and techniques. Alongside structured problem solving and advanced analysis, participants develop the leadership, stakeholder management, systems thinking and decision-making skills required to lead improvement in increasingly complex environments.
Technology will continue to evolve. The ability to identify meaningful opportunities, make sound decisions and help people embrace change will remain invaluable. Those are exactly the capabilities that strong Lean Six Sigma professionals bring to every organisation.
ChatGPT was first launched in November 2022. That means that todays graduates have grown up with AI and are going to bring it into every organisation they work in. Those of us in CI leadership positions need to embrace AI and be ready to learn from this new workforce. Embracing AI is not that easy as AI is constantly evolving. At SQT we’ve taken the approach that AI is to be treated like any other improvement tool. It is up to the user to ensure the tool is appropriate for the use selected. The user must evaluate how well the tool is working and ultimately the output from the tool is the responsibility of the user.
In SQT’s Black Belt programme, we’ve started by educating learners on the strengths and weaknesses of AI, strategies to get the most out of AI and good ways to use AI effectively to support their decision making. For example, when it comes to root cause analysis, we show how AI can be used to evaluate the analysis. How deep did it go? How strong is the logic? How effective are the proposed counter-measures likely to be? What wasn’t considered in the analysis? Beyond that we encourage our students to use AI to explore possible solutions, particularly for problems that are not necessarily new. Most problems faced by organisations fall into this category. While everyone thinks “we’re different”, in reality we see the same problems being addressed again and again both within and across industries. Therefore, if the problem you are looking to solve is not necessarily new, the use of AI to identify solutions others may have considered can only be a good thing. Similar to brainstorming for solutions, the critique of proposed solutions doesn’t happen until all possible solutions have been identified.
It will still be up to the user to evaluate proposed solutions, assess the risks and understand the assumptions and constraints associated with the proposed solution. We’ve recently incorporated more ‘systems thinking’ techniques into our Black Belt training, so that learners are not simply following a narrow path of root cause analysis, but thinking of the bigger picture. This can help learners to take a broader, more holistic approach to problem solving.
As AI continues to evolve and offer more potential applications for improving business performance, we will continue to encourage our learners to find more ways to apply it in their projects. What won’t change is the focus on following a structured approach, critical thinking and engaging with people across the organisation.
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2026