AI Strategy

Without a strategy, this is what happens: IT experiments with ChatGPT. Sales buys a tool. The executive team asks for results. Nobody can deliver. An AI strategy prevents exactly that: it defines where artificial intelligence creates the most value and how the organization prepares for it.

Four elements that work

First, the AI ambition: where should AI be in 12 months? Clear goals, not "let us do something with AI." Second, data infrastructure: what data exists, what quality does it have, what is missing? Third, use case prioritization: business value weighed against feasibility. Not the most exciting case first, but the most impactful one. Fourth, organizational anchoring: skills, governance, change management.

37% of German companies already use AI (Bitkom, 2025). But only 5% of global AI investments make it to production with measurable value. The gap? Missing strategy.

Regulation as a framework, not a blocker

The EU AI Act has required risk assessments and documentation since 2025. Anyone developing an AI strategy now builds compliance in from the start. That is not an obstacle. It is a quality signal toward customers and regulators.