An AI strategy is not a list of AI projects - it's a clear articulation of how AI supports your business goals. The starting point is understanding where AI can create the most value in your specific context, which requires honest assessment of your data assets, technical capabilities, and organisational readiness. Too many organisations skip this step, jumping straight to tools and pilots without establishing why they're doing it or how they'll know if it's working. A strong strategy answers practical questions: which problems are worth solving with AI versus simpler approaches, what capabilities you need to build internally versus buy from vendors, how you'll measure success beyond "we're using AI now", and how individual initiatives connect to broader business priorities. Common pitfalls include chasing technology trends without clear business cases, underestimating the data and infrastructure foundations required, and launching too many pilots simultaneously without a plan for scaling the ones that work. The organisations that get this right treat AI strategy as an ongoing practice, not a one-off document.