AI Adoption Archetype
Real pockets of use, no map
At a glance
A few teams have quietly figured out how to make AI work here. The rest of the business doesn't know it yet, and neither does anyone responsible for what data those teams are sending where.
The Tinkerer has proof that AI works here. A few teams have quietly figured it out. The question is whether that good practice spreads on purpose, or the risk spreads first.
Somewhere in the business, a team has already found a genuinely good AI use case and made it part of how they work. Nobody planned that. It happened because someone was curious and nobody stopped them. That's proof the value is real, it just hasn't been given anywhere to go.
Ad hoc pockets of good practice are easy to miss precisely because they're pockets. There's no shared inventory of what's in use, so the business can't tell the difference between a well-run experiment and an unmanaged one just by looking.
Every month without a baseline policy makes the eventual retrofit harder, because more tools, more habits and more informal norms get set in the meantime. The fix is cheap now and gets more expensive the longer good practice is left to spread on its own.
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By the numbers
Only 31% of organisations have a formal, comprehensive AI policy in place.
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The team using AI well rarely gets asked to teach anyone else, so the business ends up with one pocket of expertise and several teams reinventing a worse version of it independently.
Leadership usually hears about the successful pocket anecdotally, in a meeting or a hallway conversation, rather than through anything that resembles a report. There's no structure yet for good practice to travel upward.
Tool choices get made team by team, often without anyone comparing notes, so the business ends up quietly paying for three overlapping subscriptions that do roughly the same job.
If one or two teams have genuinely figured out AI on their own, while most of the business has not started or uses something completely different, you are almost certainly a Tinkerer.
A simple, company-wide policy baseline, before the next team adopts a tool on its own initiative. It is the cheapest fix available at this stage and gets more expensive to retrofit every month it is delayed.
A Sprinter has AI embedded everywhere with no governance. A Tinkerer has it working well in a couple of pockets with no governance and no adoption everywhere else. Same missing policy, much smaller footprint to fix.
Recommended engagement
AI Policy Baseline & Tool Rationalisation: a focused engagement to get ahead of governance before ad hoc use scales further.
Six archetypes, from least mature to most. See where the others sit and where you could head next.
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