Core question
How do we move from disconnected AI projects to a company-wide strategy?
Short answer
Get everything into one view first. Find what is actually in use, connect each item to a business priority, cut the duplication, set common guardrails, and then prioritize. Strategy begins when scattered departmental experiments become coordinated decisions. It does not begin with a plan written before anyone knows what is running.
Almost nobody starts with a strategy. They start with people experimenting, which is the right instinct. Marketing tries a tool. Operations runs a pilot. Someone in finance has quietly been doing their analysis in a personal account for a year. That is normal and it is not a failure of discipline.
The strategic step is assembling those activities into a single picture, and it is usually the first time anyone has one. What is working. What is duplicated. Where the risk sits. Which experiments connect to something leadership actually cares about. What shared infrastructure would make several of these easier at once. That inventory is frequently the most surprising thing in an assessment, because what is running is rarely what leadership believed.
From there you can decide. Some things expand. Some consolidate. Some stop, and stopping should be a normal outcome rather than a defeat. Guardrails become consistent instead of varying by department.
The specific failure to fix is ownership. When AI is everyone's responsibility it becomes nobody's accountability, and initiatives live in the space between departments and die there. Put a name on each priority. Not a committee, not a working group. One person who will stand up next quarter and say what was done and what it produced.
An AI strategy is not one large AI project. It is the coordination of many decisions around a shared view of where value actually is.