What Real Scale Looks Like: AI Beyond the IT Department

Too many AI strategies stall inside the data team. They’re scoped, tested, and “delivered” — but never adopted, and almost always suck up money, unchecked forever. Business units nod, smile, and quietly move on. And the AI ends up stuck in a dashboard that no one opens.

This is the illusion of progress. Executives fund AI, see a prototype, and assume the job is done. But AI doesn’t scale through demos. It scales when it becomes part of how work gets done — across functions, not just inside IT.

Real scale looks different. It’s not about model count — it’s about operational reach. Marketing uses AI to target leads. Sales uses it to qualify them. Customer success loops insights back. Product development reads those signals to shape roadmap. That’s not tool adoption — that’s a new system of execution.

The danger is that without this coordination, AI delivers only local value. Worse, it fragments the organisation — each function building isolated solutions, each competing for attention, and none of it compounding.

The fix is straightforward, but not easy: start where decisions live. Find the points where action gets taken — not just where data is stored. Design from those decision points backward. Cross-functional AI doesn’t mean everyone uses the same tool — it means every team is aligned around the same insight.

The companies pulling ahead don’t scale tech. They scale clarity. And that only happens when AI gets out of the lab — and into the loop.