Start with one thing, and measure whether it worked
Use cases ranked by likely return rather than novelty, a pilot with a success measure agreed before it starts, and an honest path from one working pilot to production.
45 min · Free · No commitment
Six experiments, none of them finished
The common failure isn't picking the wrong AI tool. It's picking eight of them — a pilot in marketing, something in support, a license somebody expensed, a proof of concept that stalled — with nobody measuring any of it and no way to tell which is worth keeping.
The businesses that get value from AI tend to do the boring version instead: pick the single most repetitive, text-heavy, measurable task in the business, record how long it takes today, try one tool against it with a defined group, and check the number after a fixed period.
That approach produces an answer either way. It either scales into production with evidence behind it, or it gets stopped after weeks rather than quietly consuming budget for a year.
What the roadmap engagement covers
Use-case inventory
We work through where AI could plausibly help in your operation — with the people doing the work, not just leadership. The useful candidates are almost always repetitive, text-heavy tasks with a clear right answer, and they're rarely the ones that came up in the board meeting.
Prioritization by return
Each candidate scored on time saved, error reduction, implementation effort, and risk. Ranking is what stops an AI program from becoming six half-finished experiments — most businesses can support one pilot at a time, done properly.
Pilot design
A defined group, a defined scope, a defined period, and a number that decides the outcome in advance. Pilots without a stated success measure never conclude; they just quietly persist until someone stops paying.
Measurement & baseline
Recording how long the work takes today, before anything changes. Without a baseline you can't tell improvement from enthusiasm, and enthusiasm fades within weeks.
Change management & training
Adoption is the hard part. People need to know what the tool is for, what it's bad at, and when to check its work. Tools that get rolled out without this get used twice and abandoned.
Pilot to production
If the pilot clears its bar: expanding scope, extending licensing, folding the tool into standard onboarding, and handing over documented processes. If it doesn't clear the bar, we say so and stop.
Quarterly review
AI tooling changes faster than any other category of business software. What was impossible last quarter may be routine this one, so the roadmap gets revisited rather than written once and filed.
What you end up with
- One prioritized roadmap instead of six competing experiments
- A pilot with a success measure agreed before it starts
- A baseline that shows whether anything actually improved
- Adoption support, so tools get used past the first few weeks
- A defensible answer to "what are we doing about AI?"
Deliberate beats enthusiastic
We rank by return, not novelty.
The impressive demo and the valuable use case are rarely the same thing. Prioritization is where most of the value in this engagement sits.
We design pilots that can fail.
A pilot that cannot produce a negative result isn't a pilot, it's a purchase. Agreeing on the bar in advance is what makes the outcome mean something.
It connects to your wider IT strategy.
AI adoption isn't a standalone program — it belongs in the same roadmap as the rest of your technology planning, which is where our vCIO service picks it up.
AI roadmap questions
How many AI use cases should we pilot at once?
Usually one. Most businesses do not have the attention to run several pilots properly at the same time, and running them badly produces no usable answer. One well-measured pilot tells you more than five unmeasured ones, and the next candidate on the roadmap is ready to go when it concludes.
How long does a pilot run?
A fixed period agreed before it starts — long enough to get past the first few weeks of novelty, when everyone is enthusiastic, and short enough that a failing pilot is stopped quickly. The exact length depends on how often the task being measured actually happens.
What if the pilot does not work?
Then it stops, and that is a useful result rather than a failure. You find out in weeks instead of a year, we record why it missed the bar, and the roadmap moves on to the next candidate with that lesson built in.
Do we need the readiness assessment first?
Usually, yes. A roadmap assumes your permissions, data, and AI policy can already take the weight of a pilot. If you have done that groundwork, we can start at the roadmap; if you are not sure, the assessment is the faster route to finding out.
Ready to take this off your plate? Six questions.
Spend 90 seconds answering. We'll spend a few hours putting together a written assessment of where your IT stands — and a 45-minute call with one of our engineers.