AI adoption
Find your best AI use cases
Score each AI idea for value, clarity and readiness, then run a 30-day pilot on the best one.
By Amalgam
Reviewed by Ryan WardFirst published Revised 3 min read
The short version
- Start from recurring work that costs your team time or quality every week.
- Score each candidate on the three questions below, pick one with a backup, and run a 30-day pilot with an owner and stop criteria.
Most teams have more AI ideas than evidence. Every idea sounds promising, so the choice comes down to opinion and whatever feels most urgent.
You end up with lots of experiments and no outcome you can defend.
Narrow the list to one or two use cases your team can carry out this quarter.
Score each idea on three questions
Ask these before you commit time or money.
- Value: does it remove a costly bottleneck or produce output that matters?
- Clarity: is the workflow clear enough that success and failure are obvious?
- Readiness: do your data, ownership and guardrails support a rollout now?
Score each from 1 to 5. For the guardrails part of readiness, NIST’s AI Risk Management Framework is a useful checklist of what to have in place.
From a long list to one pilot
Plan on a 90-minute workshop, then 30 minutes to review the scores.
- List 10 workflow bottlenecks where your team loses time or quality every week. Bring in someone who does the work every day, so the list starts with what slows them down.
- Pick the top three by business impact and how often they recur. Note whether each would save time, raise quality or cut cost.
- For each one, write the before and after in one sentence a new hire would understand.
- Score the three, and drop the weak fits.
- Choose one primary use case and one backup. Name a single owner who can make the call to scale, change course or stop.
- Run a 30-day pilot with a baseline, a weekly review and stop criteria agreed in advance.
Who should own it
Give the playbook to a product or operations lead who can pick one pilot and keep a weekly review going.
The pilot itself needs an owner who can unblock decisions, such as a founder, a general manager or the head of the function.
Common mistakes
- Starting with what a tool can do instead of where a workflow hurts.
- Choosing a use case nobody clearly owns.
- Calling a pilot a success when no metric moved.
- Scaling before review habits and trust are stable.
When to wait
Wait if your team is in the middle of an incident, or if nobody can give the pilot weekly decision time.
Wait too if the data the workflow depends on is unreliable. Fix the data first, then come back to the list.
How many pilots to run
One serious pilot and one backup is usually enough. More than that splits attention and makes the results hard to read.
