This exclusive interview with Maarten Verschuere was conducted by Tabish Ali of the Motivational Speakers Agency.
Effective AI transformation requires a defined business problem, reliable process data, controlled testing and trust from the people expected to use the system. Agentic AI adds urgency by allowing software to pursue high-level missions across business tools with less step-by-step direction.
Maarten Verschuere is a technology speaker, AI researcher at VIVES University of Applied Sciences and author of AI Will Replace You. He has more than 15 years of experience in AI and data science, founded the conversational AI company Clever and later served as Managing Director of Zoovu.
In this exclusive interview with the AI Speakers Agency, Maarten explains why AI programmes fail, which foundations determine whether a company is AI-ready, how leaders can test value before committing to large projects, and how his AI Navigator Framework moves organisations from exploration to deployment at scale.
Question 1: Why should AI transformation begin with the company’s vision and a clearly defined business problem?
Maarten Verschuere: “A lot of companies fail at AI transformation because they consider it as an IT problem. They say, “This is new technology. We need it. We know we need it. Let’s get it involved and let’s make sure everybody has access to AI.”
“Actually, it’s not really an IT problem. It’s a people problem. Technology is an enabler for achieving our missions.
“Especially when you’re talking about a transformation of this size, the first thing you need to do is start to think about your company’s vision. What problems are you trying to solve? And then consider AI as the key enabler of the future to solve that problem.”
Question 2: Which operational foundations determine whether a company is genuinely AI-ready?
Maarten Verschuere: “The companies that are really AI-ready have defined that vision and know which problem they’re solving. They also know what ecosystem of technology and tools they need to implement AI.
“If you’re thinking about more narrow AI, if you’re looking at computer vision or forecasting or trying to optimise efficiency in the organisation, you probably need information or data about your processes.
“If you don’t have the data, you can’t feed the AI, so it can’t learn your patterns. If you don’t have that, then it becomes a difficult exercise.
“If you haven’t got the vision right, the processes right and the data collected, then it becomes much harder.”
Question 3: How can leadership teams test where AI creates value before committing to large transformation budgets?
Maarten Verschuere: “When I talk to leadership teams, I hear a lot of excuses. Most of the time, it’s, “We don’t have the time, we don’t have the budget, we don’t have the knowledge.” Those are the three main excuses why companies failed to get started with AI.
“You feel the anxiety of not making the wrong bet. You can’t spend, let’s say, 500k and six months on a project that’s going to fail.
“What I see is with companies that are a lot more agile, that say, “Okay, let’s not take six months or 500k to do this, but let’s take a 20-20-20 approach,” which means 20 days, 20k and 20 days of external expertise.
“This means that you can execute and set up pilot projects and discover what AI could offer to you in a very short amount of time with limited funds. You learn.
“The key elements of good leadership is setting aside a little bit of budget to learn how AI could help your company. Once you’ve learned that in 20 days, that’s really all it takes: 20 days of external expertise and 20 days of internal expertise.
“You will learn where the real added value is for your company. When you go on your big transformation projects, you will skip a lot of the issues companies have and make it in time, within budget, and make it a success.”
Question 4: How does the AI Navigator Framework move organisations from initial exploration to trusted deployment at scale?
Maarten Verschuere: “I’ve spent my entire career as a data scientist in AI. I’ve worked all over the world. I’ve seen hands-on how the big AI projects win or lose and where they add value.
“I’ve bundled 20 years of experience into a book, which is called AI Will Replace You, where I describe the AI Navigator Framework. This framework offers you a very intuitive way to understand how you can implement AI without failing.
“I set it up in three phases, and it’s all about aligning the people, the processes and the technology.
“The first phase of the AI Navigator Framework is inspire, which means that you have to look outside. You can’t stay within your own little bubble with the knowledge you have and the people you have. You need to look outside.
“All of the questions you have about how can I use AI for my company, how can I create value and how can I solve problems have been asked before by other companies in the world.
“By looking outside and being inspired, you will learn from others and skip a lot of the learning phases. You will be able to identify, “These guys have done the same thing with success, so we can apply it too.”
“The second phase is enabling. Once you know what you’re going to do, you can invest the resources to do it: the people, the tools, the time and the budget. You can set up the pilots where you believe we can learn something here and see how AI will be able to help us.
“From that phase, you will learn what works and works not. The last phase is scale. When you scale, AI has to work 100% of the time.
“Once you found that one solution that works 100% of the time, you can start scaling it. Scaling means decent governance, decent training and building trust of the people who are going to use it.
“You could build the entire pipeline and have the perfect AI solution, but if people are afraid to use it or customers do not trust it, then it’s all been for nothing.
“In this final phase, setting up the right governance and doing the right methods to build trust with your people is key for implementation. That is the AI Navigator Framework: inspire, enable, scale.”
Question 5: What does the shift from generative AI to autonomous agents mean for the way organisations execute work?
Maarten Verschuere: “This technology has fuelled a new generation of technology, which is agentic AI. You don’t just give exact orders of, “Do this now, then do that, then do that.” You just give them a mission.
“You say, “We want to create marketing content,” or, “We want to follow up with customers,” or, “We want to do research and find new prospects.” You can define it on a high level.
“Then give AI agents access to your tools you will use in this process. AI agents will autonomously, independently start working to achieve this mission.
“It sounds like science fiction today. It’s incredible. You just give an order, and this AI machine does whatever you ask it to do.
“It’s clear that this is the future. By the end of next year, I am sure companies will have operating AI agents that are delivering value and doing work in companies.
“The internet transformed the way we live and work. Agent AI will do the same. Once we get used to how AI agents work for us, it’s the inevitable future.
“That’s why it’s so important for companies to look into this and understand the impact on their business because it will happen for sure.
“Today is the right day to take action because now you’re on time. You have time to learn. You have time to experiment at a low cost, at low risk.
“In a year’s time or two years’ time, you will have to do it. There will be no margin for error. There will be no time left. That’s why agentic AI is so important as a topic today for all leadership teams.”
