Glossary Strategy & implementation
AI strategy
What is an AI strategy?
An AI strategy determines which business goals AI should serve, which applications deliver the most and in which order you introduce them.
A good AI strategy fits on a few pages and answers five questions: which goals, which use cases (ranked by value and feasibility), which data and systems must be in order, how you cover risks and the AI Act, and who owns it.
How do you approach an AI strategy?
Start with your business goals, not with the technology. Then list the processes with the most volume, lost time or risk of errors, score them on value and feasibility, and check for each candidate whether the data, the systems and an owner are in place. If you are a software company, you go through this twice: once for your own operations and once for the AI features that belong in your product.
The roadmap puts that into phases: first one or two applications that deliver results within weeks, then the broader setup. Without that order, it stays a set of loose experiments.
A strategy only pays off when it is executed. How we combine strategy and building is covered under AI consultancy.
Last updated: 20 October 2026