AI strategy” has become a boardroom buzzword, but very few organisations pause to ask a more basic question first: are we actually ready? Readiness isn’t about picking a tool — it’s about data quality, staff capability, existing workflows, and whether a use case solves a real operational problem or just sounds impressive in a deck. In this post, we break down a practical readiness framework covering four areas: data and systems maturity, team skill gaps, process fit, and governance/risk considerations specific to regulated sectors. We also share what a proper AI readiness assessment looks like in practice — from initial research and stakeholder interviews to a phased adoption roadmap — so leadership teams can move past the hype cycle and make a grounded decision about where AI genuinely adds value to their organisation, and where it doesn’t.