We are happy to introduce Mark Passtoors, who leads AI Client Strategy at Valtech.
Mark spends most of his time working with manufacturers and industrial companies on how AI can help them grow, and what it takes to get from idea to real result inside large organizations.
Intro and personal background
Can you tell us a little about yourself and your role at Valtech?
Honestly, I’ve got one of the best jobs in the industry right now. I work with leaders of some of the largest industrial and manufacturing businesses in Europe on what AI means for their company, and what they should do about it on Monday.
Not the theoretical version. The real one. Which decisions change. Which parts of the business get reshaped. Where the new growth is.
Across the clients I work with, the pattern I keep seeing is this: The best ideas almost never come from the boardroom. They come from people in the organization. The people that see the pain every day. The ones who know exactly where things should change. They have the ideas.
What they don’t have is air. They get blocked by governance, politics, budgets, roadmaps, “that’s not in the strategy,” “let’s park this for next year.” The corporate jungle.
So, a big part of my work with leadership is clearing that path. Because the boardroom doesn’t produce the breakthrough. It produces the cover that lets the breakthrough happen.
What first sparked your interest in the industrial/manufacturing world?
The stakes. These are companies moving real things around the world. Food, materials, products people depend on every day. When you help them get something right with AI, it’s not a marginal improvement on a dashboard somewhere. It’s tons of waste avoided. Hours given back. Decisions made faster. Real money on the line.
That kind of impact is addictive. And I love that the problems are physical. When a manufacturer talks about a bottleneck, you can stand next to it. Nothing’s abstract here.
Outside of work, what’s something that inspires you or keeps you curious?
CrossFit. But for me it’s more a mindset thing than a fitness thing. The best place to be is somewhere uncomfortable, because that’s where you learn.
It took me a year and a half to get a proper ring muscle-up. There were plenty of moments I thought I should just stop. The day I finally got one was the same day I’d told my coach it wasn’t going to happen. I think about that a lot at work. Innovation is the same discipline. Try, fail, adjust, try again and keep going past the point where it feels reasonable to stop.
Daily work and perspective
In your day-to-day work with clients, what part do you enjoy the most?
Working with leaders who actually commit. Most boardrooms talk about AI. A much smaller number commit for real.
Those are the most interesting conversations I have all year because suddenly we’re not debating whether AI matters. We’re working out where to point it first and what to learn from it. Those clients move quickly, push back hard and hold us to a high bar. That’s exactly the kind of partnership I want.
What’s one lesson you’ve learned from working with manufacturers that surprised you?
How much of the work is internal, not technical. Coming in, you assume the hard part will be the data, the model, the integration. The actual hard part is almost always the corporate jungle. Whose budget is this? Which roadmap does it sit on? Who decides? Who blocks? Who gets credit, who gets exposed?
I’ve seen genuinely great ideas die in a steering committee while weaker ones get funded, just because someone knew how to play the politics. That surprised me at first. Now, I plan for it. A big part of an AI transformation isn’t the AI. It’s helping the organization give its own best ideas permission to happen.
From your experience, what’s the biggest challenge manufacturers face when starting their digital transformation journey?
People often say it’s about picking the right first bet. I don’t think that’s true anymore. Two years ago, sure. You planned, allocated budget and teams, 20 weeks of work, and your outcome was usually exactly what you’d written down at the start.
That world is gone. The technology has caught up. You can now learn in weeks what used to take quarters. The real skill isn’t betting right. It’s learning quickly.
Trying things, getting honest feedback from reality, killing what doesn’t work, doubling down on what does. Across every transformation I’ve been part of, the companies winning aren’t smarter at picking. They’re faster at finding out.
Spread your effort across a few directions, see what the market actually tells you, then invest hard where the signal is strongest.
Thought leadership and impact
What excites you most about the opportunities data and AI bring to industrial and manufacturing companies right now?
AI is collapsing the cycle time of strategy. What used to be a five-year capability build can now happen in 18 months. What used to take a quarter to learn, you can learn in a sprint.
That changes everything about how companies compete. For decades, manufacturers competed on scale, efficiency and operational excellence. The next decade is going to be different. Companies will compete on intelligence. On how fast they learn, how fast they adapt, how fast they turn what they know into something the whole business can act on.
That gap, between companies moving now and companies still planning, is widening every quarter. And once it’s wide enough, it’s very hard to close. That’s the thing I genuinely get excited about, and honestly a little impatient about. The window to get ahead is open right now.
If you could give one piece of advice to industrial leaders navigating rapid change, what would it be?
The technology is ready. Your data is ready. The thing that isn’t ready is the decision to start.
So, pick that thing that’s been bugging you for years. The decision your team keeps making on gut feeling. The data sitting in three different systems that nobody has ever combined. And start. Not with a strategy. With a sprint. You’ll learn more in six weeks of doing than in six months of planning. I’ve seen it again and again.