The clearest opportunities for AI in clinical research are often tasks that consume skilled people’s time: finding information, preparing drafts, checking documents, and moving work between systems. To measure its value, start with one of those tasks and determine whether AI helps the team complete it with less effort, fewer corrections, or a better result.
Choose a specific outcome before introducing the tool. “Reduce the time coordinators spend reviewing records” gives you something to test; “improve recruitment with AI” leaves too much room for interpretation.
Find Where AI Can Remove Work
Start by asking the people doing the work where they repeatedly search, copy, reconcile, or reformat information. Then identify which parts AI could support and which decisions still need their expertise.
Four applications offer practical starting points:
Patient identification: AI can help surface potentially relevant records and organize supporting information. Track review time, the proportion of matches confirmed by staff, and staff effort per patient who advances to screening.
Document drafting: AI can help turn approved source material into a structured first draft. Track total drafting and review time, substantive corrections, and whether the final document meets the same quality expectations.
Trial document management: AI can support classification, filing, reconciliation, and follow-up. Track filing accuracy, unresolved exceptions, and the time staff spend correcting or locating documents.
Budget preparation: AI can help extract protocol activities and organize a first-pass budget. Track preparation time, missing or misinterpreted activities, and the effort required to produce a usable budget.
These measures connect the tool to a recognizable job. They also reveal whether faster output creates additional work for someone else.
Count the Whole Task
Consider an illustrative document-drafting workflow. Before AI, a team spends four hours preparing a draft and two hours reviewing it, for six hours total.
With AI, source preparation and draft generation take one hour, while review and correction take three hours. The complete task now takes four hours, saving two hours rather than the three suggested by drafting time alone.
That is still a useful improvement, provided quality is maintained. But the calculation should include everyone’s effort, especially when work shifts from a writer to a more specialized reviewer.
For a fair comparison, use similar tasks and record:
Preparation and processing time.
Review, correction, and approval effort.
Work required to move the result into the next system.
Errors, omissions, and unresolved exceptions.
Measure several examples so one unusually easy task does not become the basis for the business case.
Show What the Saved Time Makes Possible
Time savings become more meaningful when teams can explain what they enable. Two hours saved on an occasional task may have limited operational impact, while the same saving across a recurring workload could help clear a backlog or free capacity for more demanding work.
Distinguish staff effort from elapsed time. A draft might require fewer working hours but still wait a week for approval. If the objective is faster delivery, examine the waiting periods and handoffs as well as the task itself.
Also separate capacity gains from cash savings. Giving an existing team more time does not automatically reduce spending, but it can allow the team to support additional work without equivalent increases in staffing.
Check Whether the Benefit Survives Everyday Use
Include licensing, integration, training, validation, and ongoing support when evaluating financial value. A modest improvement may be worthwhile in a frequent task, but harder to justify when substantial setup supports only occasional use.
Check whether staff actually use the tool for the intended work. If they routinely recreate outputs manually or maintain a parallel process, investigate why before expanding deployment.
A practical decision should rest on three findings: the workflow improved, quality remained acceptable, and the benefit justified the full cost. Where results fall short, use the evidence to adjust the process, narrow the application, or stop that use case.
Explore More Ideas From SCOPE
Practical questions about AI, trial design, patient engagement, and clinical operations continue across the SCOPE community. Explore more ideas emerging from SCOPE events, with guidance you can apply to your own teams and studies.
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