If your AI strategy feels like it could be applied to any other company simply by changing the logo on the slide deck, it’s not a strategy. It’s a set of tactical table stakes, ready to be exchanged for the next new thing at a moment’s notice.
Yet, across the globe, in polished boardrooms and freshly painted coworking spaces, most AI strategies look eerily identical. The same buzzwords appear on repeat: AI first. AI Center of Excellence. Data Democratization. AI-Ready Data. Responsible AI. Explainable AI. Embedded AI. This is how companies convince themselves they are adopting AI, embracing cookie-cutter plans with the same structures, the same promises, and the same vague commitment to “embedding AI across the enterprise.”
Now, these concepts aren't wrong. But they are grossly insufficient on their own. They deliberately skip the hardest, most important questions—the ones that unearth a company’s soul:
▶️ Why are you truly doing this, and what fundamental business problem, unique to your organization, are you trying to solve?
▶️ What does success actually look like for you? Is it another percentage point of efficiency, a new market created, or a promise to your clients fulfilled in a way that was never before possible?
The real work of AI strategy begins where the template ends. It lives in the hard, messy, and deeply human decisions about trade-offs, timing, and trust. It requires a philosophy, not just a framework.
AI, if done right, is a foundational strategic capability that touches product, people, brand, and regulation all at once. This means your company’s unique context isn’t just a variable in the equation. It is the entire equation.
To be clear, there is a role for standardization, but that's operations, not strategy. Shared infrastructure, common workflow patterns, or a centralized process for evaluating models can save time and reduce friction. A cookie-cutter approach isn’t inherently bad, but it’s dangerous when treated as an end, not a means.
The organizations that thrive will be the ones that start with a blank page and ask not “How do we do AI?” but “How do we do our business—better, faster, differently?” Those still following templates, on the other hand, will be left wondering why their billion-dollar AI investments feel so remarkably unremarkable.