Global Partner & Head of AI Strategy
(EMEA)
AI transformation in enterprises isn’t just about adding another internal chatbot or running another pilot in customer service. It’s about rethinking how your organization works at a fundamental level. And right now, too many companies are playing small. They’re testing use cases in isolation, staying in “pilot mode,” and failing to scale.
The real opportunity is making AI part of the way your business operates, not just something your innovation team experiments with.
Here are 8 provocations to help you reframe how AI can actually drive scalable change in your organization:
Most companies treat AI like a tool to plug into existing processes. But true transformation comes when you shift that mindset: AI isn’t a product, it’s a capability. That means investing in internal knowledge, building infrastructure, and aligning teams around what AI can unlock for your business.
Instead of asking “Where can we use AI?”, start asking “How will AI change what we do and how we do it?”
⸻ Vincent Pirenne
Too often, AI is layered on top of messy legacy systems and processes. That leads to patchy results. Real impact comes when you reimagine workflows around AI from the ground up. Where can AI remove friction? Automate low-value steps? Give experts more leverage?
This is what OpenAI calls “embedding AI into the way people actually work.”
⸻ Open AI: AI for the Enterprise
You shouldn’t fall into the trap of chasing what’s feasible instead of what’s valuable. To scale AI with impact, leaders need to distinguish between high-leverage initiatives and well-intentioned distractions. The matrix below helps prioritize use cases based on two critical dimensions: their ability to differentiate your business and their potential to scale across the enterprise.
This is what OpenAI calls “embedding AI into the way people actually work.”
⸻ Open AI: AI for the Enterprise
AI transformation is not a one-off. The earlier you start, the more value compounds over time. Each use case makes the next one easier. Each success builds buy-in. And every time you unblock a team or clean up a dataset, you make the next wave of AI stronger.
Duolingo launched 148 courses created with AI after sharing plans to replace contractors with AI.
⸻ TechCrunch, 2025
You can’t transform by buying or licensing external tools. You need internal muscle. That means hiring and training people who can think and build with AI, and giving them tools that don’t require deep ML expertise to get started. In a recent podcast episode with the VP AI go-to-market & Head of GenAI from Bayer, we dove into how the company successfully launched a new business model by selling AI licenses, as referenced by the WSJ.
Many companies automate tasks, but few automate outcomes. If your automation goals stop at eliminating low-level work, you’re leaving value on the table. What would it look like to automate end-to-end processes? Decision cycles? Customer journeys?
Microsoft CEO Satya Nadella recently revealed that AI now generates approximately 20–30% of the company’s internal code, a clear sign that AI agents are no longer experimental, but essential to modern enterprise workflows.
⸻ TechCrunch, 2025
Some leaders are holding back, waiting for AI to be flawless before they commit. But here’s the reality: human work isn’t flawless either. The goal isn’t perfection, it’s progress. What matters is improving output versus the status quo, with guardrails and human oversight in place. LLM performance is improving fast, and the longer you wait, the further behind you fall. You don’t need to go all-in on day one, but you do need to get in the game.
Every iteration teaches you more than another month of debating use cases.
⸻ Vincent Pirenne
AI transformation won’t happen without executive ownership. Leadership needs to do more than support, they need to lead. That means being actively involved, setting the ambition, and making sure AI isn’t confined to IT. It also means raising the baseline understanding: if your executive team can’t speak fluently about AI’s opportunities and risks, it’s a liability. Build that literacy, make it part of the leadership culture, and don’t delegate it away.
Enterprise AI transformation isn’t easy. But it’s no longer optional either. The companies making real progress are doing more than testing ideas, they’re building the systems, talent, and habits that let AI scale. They’re embedding it into the way work gets done, from code generation to product launches. And they’re learning faster than the rest.
This shift isn’t about flashy demos. It’s about building momentum, shaping culture, and enabling your teams to move with confidence.
If you’re serious about AI, it’s time to stop experimenting at the edges and start embedding it into how your business runs.
Vincent is a senior leader in AI strategy and business transformation, helping Fortune 500 organizations unlock the full potential of artificial intelligence. As a Global Partner at Board of Innovation, he specializes in shaping AI-driven growth strategies for consumer goods, retail, and technology leaders across the USA and Europe. His expertise lies at the intersection of AI, business strategy, and enterprise transformation, helping senior executives navigate AI adoption and scale AI-driven decision-making. He’s focussed on helping organizations build future-ready AI strategies that deliver real business outcomes.
