Scaling AI in Belgium: Moving from Pilot to Production with Microsoft

Your AI pilots worked. The proof of value is in the slide deck, GitHub Copilot is in the IDE, and leadership is asking what comes next. Getting from pilot to production means solving 3 problems the pilot never tested: architecture, token costs and data governance. 

Gill Cleeren has led Xebia's Microsoft practice in Belgium since 2018. Since then, he's seen the same pattern across the market. Companies move fast on AI, hit predictable problems, and find out too late that the skills that got them to the pilot won't get them to production. "The pace of change isn't just fast," he says. "It's so fast, it might even be outpacing Moore's Law. A lot of companies now realize they need to shift gears faster." 

The pressure is real. Boards now want AI to deliver measurable outcomes. Architecture, governance, security, and model costs are now production concerns, not future problems. And the window to get ahead of competitors who are already scaling is narrowing fast. 

Why do AI pilots stall before production? 

Here's a pattern Xebia's team has seen play out repeatedly: a client starts with agentic coding, builds a proof of value, and celebrates. Then reality sets in. A working prototype is not a production system. 

The following situation often happens: teams start with agentic coding, build several proof-of-value projects, and then hit the wall every enterprise hits: they cannot simply deploy a prototype. They need to re-architect it as a proper AI-based solution, decide how to host it, and plan for it to run reliably in production. 

That shift surfaces three problems most teams underestimate: 

None of these problems is exotic. They are predictable. And predictable problems are exactly what a specialist partner should help you avoid, not react to after the fact. 

What to do before you go live: 

What should you expect from your AI partner?  

Large enterprises face a related but different problem: speed. Bigger organizations tend to move slower, often locked into approved toolsets and frameworks that make sense for stability but slow down AI adoption at the exact moment competitors are accelerating. Cleeren puts it plainly: "A lot of companies now realize they need to shift gears faster. A consultancy like Xebia can help to set the pace and lead by example." 

Speed under pressure is where the difference between a generalist and a specialist shows up most clearly. 

"Whenever we receive an ask from an organization, we assess whether what they are asking for would really solve their problem," says Freddy Aben. "We always dig deeper into the problem or challenge that is shared with us. Often, we provide a little push back, ask some deep questions, and help the client to scope the request as well as possible before they start.” 

Sometimes, we go even further. Instead of relying solely on theoretical input, Xebia also does its own research by visiting clients’ offices or locations and speaking with the people who ultimately will be using the solution. It’s this input that, in some cases, shapes the architecture in ways a requirements document never would have. 

That is the specialist posture: challenge assumptions, talk to end users, and own the outcome. A generalist executes the brief. A specialist tells you when the brief is incomplete. 

What Microsoft expertise does Xebia Belgium bring? 

Xebia Belgium is not a distant, anonymous consultancy. It's a team of 27 architects, team leads, and engineers who have spent years inside Microsoft's cloud, data, and AI stack, and who now sit at the center of a formalized Microsoft partnership that positions the team as the go-to specialist for Microsoft's target accounts in Belgium. 

That depth shows up in three places:

This breadth matters because Xebia Belgium is not a one-trick pony. The client base spans pharma, automotive and manufacturing, healthcare organizations like Rode Kruis, and labor unions. Large enterprise and mid-market clients alike. The common thread is not an industry. It's a problem that requires someone to think past the request. 

The catalyst: a managed Microsoft partnership 

Xebia's Microsoft partnership in Belgium has move to the next level. For years, the relationship existed through deep individual connections. Now, with a managed plan in place, there is a structure to bring even more value to clients.

"The new partnership with Microsoft gives us a catalyst to grow alongside them and get in front of their target accounts," says Finn Michielssens. "It means Microsoft can now put forward a specialist that goes deep, rather than a generalist that covers everything at a surface level." 

For a Belgian technology leader, that translates into something concrete: when Microsoft's own account teams hit a complex problem at a client site, there is now a direct, formal path to Xebia's specialists. Not a cold introduction. A standing relationship built for exactly that moment. 

Stop settling for generalists 

Belgian enterprises have a rare window: enough runway to learn from what has already happened in more mature AI markets, and a clear signal of what's coming next. Closing that gap takes more than tools. It takes a partner who has already solved the architecture, governance, and cost problems that production AI surfaces, and who will tell you when your plan needs to change. 

Xebia Belgium's 27 specialists have spent years building that expertise inside the Microsoft stack, and the firm's newly formalized Microsoft partnership puts that expertise directly in reach of Belgian enterprises ready to move past experimentation. 

Explore our Microsoft cloud, data, and AI-first engineering capabilities. 

Connect with Xebia Belgium to discuss how we can help you move from AI experimentation to production-ready solutions.