A clinical AI pilot works best when it answers one clear question. Without that focus, your team can stay busy without learning enough to expand, adjust, or stop.
The work begins before anyone receives access. A strong plan connects the problem being solved, the people participating, the safeguards required, and the evidence leadership will use afterward.
Frame the decision
Write a concise pilot statement that identifies the workflow, intended outcome, participants, time period, and decision to be made. For example, the question may be whether a defined group can use a new documentation workflow consistently enough to justify a broader implementation review.
Avoid combining too many goals. If the pilot is simultaneously expected to transform productivity, quality, clinician experience, patient experience, and financial performance, the project team may struggle to interpret mixed results.
Choose a group you can support well
The first group should be large enough to reveal meaningful workflow variation but small enough to support closely. Include participants with different levels of comfort and experience—not only enthusiastic early adopters.
- Choose workflows that are important and observable.
- Include participants who can commit to onboarding and feedback.
- Document exclusions and edge cases for later phases.
- Confirm that managers and support teams can accommodate the pilot.
Capture a useful baseline
Collect baseline information before the workflow changes. The exact measures will vary, but they should reflect the original problem and be practical to gather again. Combine system data where available with structured user feedback.
Baseline questions might cover when documentation is completed, how much rework users experience, where support is required, and how confident participants feel in the current process.
Keep measurement proportionate
A smaller set of reliable measures is more valuable than a long scorecard the team cannot maintain. Every measure should have a source, an owner, and a reason it matters to the final decision.
Decide how the pilot will run
Before go-live, confirm onboarding, access, support, incident handling, communication, and feedback routines. Define what requires immediate escalation and what can wait for the next project check-in.
Create a simple responsibility map. Participants should know where to take workflow questions, technical issues, and concerns about output quality or data handling. Project leaders should know who has authority to change scope or pause use.
Use a staged go-live
Begin with orientation and realistic practice before introducing the workflow into live activity. If possible, stagger activation so the project team can learn from the first participants and improve support for the next group.
During the first days, prioritize rapid feedback and visible support. Capture issues in a shared log, assign owners, and distinguish between configuration, training, workflow, and product questions.
Review evidence throughout the pilot
Do not wait until the final meeting to assess progress. Short, regular reviews help the team identify adoption barriers, update guidance, and decide whether the pilot remains within its approved boundaries.
- Review usage and support trends.
- Gather structured feedback from participants and affected teams.
- Track unresolved risks, assumptions, and dependencies.
- Record changes so results can be interpreted in context.
Choose the next step together
Close the pilot with a decision record. Summarize outcomes against the original criteria, unresolved risks, lessons learned, and the resources required for the proposed next step. Expansion should be a deliberate new phase with its own scope—not simply the absence of a stop decision.
Our professional services and Getting Started are designed to help teams turn evaluation questions into an actionable plan.