This blog post is Human-Centered Content: Written by humans for humans.

Over the past 12 months, I’ve sat in more exec meetings, virtual strategy sessions and innovation labs than I can count. The message is crystal clear: AI is no longer a futuristic ambition — it’s a strategic imperative.

Yet many organizations across Mainland Europe are still asking: “Where do we even start with AI?”

The answer isn’t as complicated as you think. But it does require something many overlook: a real, practical strategy — not hype.

Let me share what’s working, what’s not and how we’re helping organizations move from confusion to clarity.

Step 1: Don’t Start With AI, Start With Your Business

This surprises people. But when someone says, “We want to use AI,” my first question is:

Why? What problem are you solving?

AI is not a goal. It’s a tool. If you can’t link your AI initiative directly to:

• Revenue growth
• Operational efficiency
• Customer experience
• Regulatory resilience

…you’re likely just experimenting, not strategizing.

For one global client in manufacturing, we didn’t start by building a model. We started by asking: Where are your margins under pressure?

That led to an AI-powered predictive maintenance solution that saved them €4 million in downtime in year one.

Step 2: If Your Data Isn’t Ready, Neither Are You

Here’s a tough truth: Bad data kills good AI.

I see it every day — companies eager to jump into AI, but their data is siloed, inconsistent or worse: invisible. In the DACH region especially, we’re culturally rigorous when it comes to data privacy (as we should be), but that can’t be an excuse to avoid foundational work.

Clean, well-governed data is the bedrock. Don’t skip it. Invest in it.

If you need help, we have team of expert Architects and Engineers who can support.

Step 3: Prioritize the Right Use Cases (Hint: Not the Coolest Ones)

Everyone wants to talk about ChatGPT or generative AI (and yes, it’s exciting). But your first use case should be:

• Easy to measure
• Technically feasible
• Clearly valuable to the business

In BENELUX, one of our clients automated document classification across their legal department — a use case that’s far from flashy. But it saved 10,000 hours annually and gave the team breathing room for higher-value tasks.

That’s a win. And it builds momentum.

Step 4: Align Your People Early

Your AI strategy is doomed if it’s only owned by IT.

We embed business stakeholders from day one. Why? Because adoption doesn’t happen through technical brilliance alone — it happens when people trust the system and understand its value.

In both Germany and the Netherlands, where process discipline and stakeholder consensus are deeply valued, this step is non-negotiable.

Step 5: Build Ethically, Scale Responsibly.

We’ve entered the age of AI ethics, and rightly so. The EU AI Act is no longer theoretical — it’s here. If you want to read more about the EU AI Act, my colleague Barbara Hartmann published this brilliant overview.

We work closely with our clients to build in transparency, explainability and fairness from the ground up. I tell every executive:

Compliance is not a constraint. It’s a competitive advantage.

Especially in our region, where consumer and societal trust matters deeply, responsible AI isn’t optional — it’s the brand.

The Bottom Line

A great AI strategy isn’t just about algorithms. It’s about clarity, ownership, trust and value. And in DACH and BENELUX, where precision, pragmatism and purpose matter, we’re in a unique position to lead.

If you’re wondering where to begin, start with your biggest business challenge — and a partner who won’t sell you hype, but will help you build results.

Because in 2025 and beyond, AI strategy isn’t optional. It’s survival.

Let’s get to work.

Want to learn more about the use cases working best in your sector? I’m happy to share insights — reach out or connect with me on LinkedIn.