AI is not a strategy

AI is not a strategy, it’s a tool. This isn’t a matter of semantics, it’s an important distinction.

AI use cases are often demonstrated as something to announce rather than something to implement. Externally, this might mean a loosely aligned concept in a proposal or a mention on a capabilities page. Internally, this often means AI sitting within an operational roadmap that is likely under-resourced.

In both cases, it’s the same problem: no specificity about what it does, for whom and why it matters. “AI-powered” has become the new “data-driven” (both literally and figuratively). It sounds impressive (and being succinct is always aspirational), but it doesn’t actually mean anything. Objectively, it fails to pass the “so what?” test.

AI becomes a strategy when it solves a specific problem in a specific workflow. The question is not whether your business uses AI - after all, everybody does, or at least says they do. It’s whether you can explain what it actually does for the people you serve.

How is your use of AI making workflows measurably better, for you, for your clients, for your team? If the answer isn’t immediate and takes more than a couple of sentences (or, heaven forbid, an entire deck), you haven’t sufficiently contemplated about the question.