AI in 2026: Why This Year Is Decisive

In conversations with executives, I'm seeing two reactions to AI right now: anxiety, because they don't know where to start. Or complacency, because ChatGPT seemed so easy.

Both are wrong. But the complacent ones have the bigger problem.

AI has something almost no technology before it had: an extremely low barrier to entry. Anyone can open a chat window, ask a question, and often gets a remarkably good answer — but sometimes also complete nonsense that sounds equally convincing. Both create a false impression: the good answer makes AI seem trivial, the bad one makes it seem useless. The truth is more complicated — especially for enterprises.

Between "I asked ChatGPT something" and "AI reliably delivers results in my organisation" lies a technical and organisational effort that most people underestimate. AI needs access to the right data — and in most companies, that data sits in silos, in outdated formats, with permissions nobody has cleaned up in years. AI needs clearly defined processes — and those are often documented nowhere. AI needs an infrastructure that goes far beyond a chat window.

Where these prerequisites are in place, remarkable things are already happening. In software development, 85% of developers work with AI tools — projects that used to take months are built in weeks. For clearly defined, recurring tasks, AI agents deliver results that were unthinkable two years ago.

My assessment after more than 30 years in digitalisation: AI will fundamentally change businesses and the way we work. But not through a chat window.

The companies that will successfully deploy AI in 2027 are not primarily investing in AI right now. They are investing in the things they have been putting off for years.