Most executives expect an AI strategy to deliver transformation from day one. But those first three months are where we dig deep and move slowly and intentionally.
That means assessing where you are today, what risks exist, and how ready your team and processes are for AI. We document the bottlenecks, map where departments are misaligned, and lay out a short list of pilot projects worth trying first. Without it, implementation is just guesswork, and you end up with chaos instead of transformation.
What to expect
Days one through 30 are for understanding the business, not fixing it. That means in-depth conversations with leadership, a first pass at educating them on what AI can and can’t do, and getting day-to-day processes documented.
Days 30 through 60 are for triage. Which problems can wait, which ones can’t, and which one or two are worth turning into pilots. Most leadership teams want to fix everything at once, but going slow now means you can go faster later.
The final 30 days are execution. Testing the pilot, reporting on it weekly, adjusting when it doesn’t work the first time, and training the people who’ll actually use it going forward.
It’s supposed to feel slow. But rushing it means potentially wasting money or making already broken processes even messier.
The most common mistake
Before jumping to an AI tool, you need to analyze the actual problem first: what’s the end goal, where exactly does the current process break, and only then ask what a tool could replace or speed up.
One of my clients is a field-based services company with a recurring bottleneck. A technician on site would run into a problem, say a missing part or a site condition that needed sign-off before work could continue, and getting that resolved meant a chain of phone calls. The technician calls his supervisor. The supervisor is supposed to loop in purchasing. Purchasing is supposed to check with a manager if something’s out of the ordinary. In practice, the technician skips three steps and calls whoever answers first, and nobody upstream finds out there was ever a problem until the job is already behind.
Nobody had mapped that process. They just knew, vaguely, that communication was bad. Communication wasn’t the actual problem. The absence of a defined path for a routine exception was.
Map the process first, then let AI fix the mapped process. Skip the mapping, and you’re just giving a broken workflow a faster engine.
Why most AI initiatives stall after four to six months
When a new initiative loses steam, it happens for boring reasons. People lose interest. Something else on the calendar always feels more urgent. Someone decides it’s faster to just do the task themselves than to use the new tool correctly.
Usage climbs for a few weeks, flattens, spikes briefly when a new feature gets introduced, then flattens again. This is why you need someone who owns the AI strategy running the initiative day to day. A tool doesn’t sustain its own adoption. A person has to.
The businesses that keep momentum share a few habits. A consistent weekly meeting that doesn’t get skipped, even when it has to move. A small group, call it an AI council, actually responsible for testing and reporting back. A usage policy that exists in writing, even in the roughest form, rather than nothing at all. And probably most important, a way to measure results.
The metrics worth tracking are simple:
- Hours saved per week, by person or by team
- Dollars saved, once hours are converted to a real number
- Errors reduced in whatever process got automated or cleaned up
- Consistent adoption over time, not just a spike after launch
None of these require complicated tooling to track. Just someone to look at them on a fixed schedule and report what they find, good or bad.
Regulated industries need a different starting point
Everything above holds for any business. Regulated and compliance-heavy industries need one more layer on top of it.
AI governance and use policies are not optional. Understanding risk and potential exposure is critical. That is why I always recommend that any business, but especially one that has regulatory or compliance obligations, start with a FREE AI Exposure Audit. It will quickly reveal where your biggest risks are hiding, and what you can do to mitigate them.
Learn more about the FREE AI Exposure Audit, or book a time with Steve to talk about your business.
