How to Collect Useful Staff Feedback During a Laboratory AI Pilot

Decide whether you are investigating clarity, workload, handover or a particular administrative step. Name the workflow, software version and approved pilot scope. A general question such as do you like the AI produces comments that are difficult to act on.

Qualified laboratory leadership must approve the feedback process and its boundaries. Feedback collection is not validation, a clinical study or permission to expand the system's use.

Use a short form that records the task attempted, where difficulty occurred and what the user expected. Ask for an observation before asking for a suggested improvement. This helps distinguish a confusing label from an unsupported requirement.

Use approved non-sensitive references rather than copying sample details or identifiable information into comments. Direct any incident or consequential output concern to the established escalation route immediately.

Record the relevant role, training stage and task context where appropriate. Explain who will see the feedback and how it will be handled under the organisation's approved arrangements.

Do not collect names or sensitive free text simply because a form allows it. Ask the responsible privacy and quality roles to determine necessary fields, access and retention. Do not upload feedback to an unapproved AI service.

Ask what was clear, what required extra checking and whether an existing workaround was needed. Avoid wording that assumes the new workflow is faster or more accurate. Allow users to report that a task was not attempted.

A satisfaction score can support discussion, but it cannot demonstrate output quality. Keep user experience, technical performance and professional acceptance as separate evidence streams.

Group observations by the actual workflow step and distinguish requests, usability findings and issues requiring escalation. Assign an owner and record the decision to investigate, clarify, defer or reject a proposal.

Do not silently turn a popular suggestion into a production change. Any approved modification still needs the applicable change control, risk review, testing and authorisation.

Tell participants which issues were considered and what will happen next without disclosing another person's private comments. Keep a traceable summary linked to the pilot version and decision record.

BioInsight Labs can support controlled laboratory operations and AI-assisted workflows. Qualified professionals remain accountable for validation, quality decisions and authorised use. This guide provides no diagnosis, treatment or clinical instructions.

Does positive feedback validate AI output? No. Should incidents wait for the survey review? No; follow the approved escalation process. Can a requested improvement be released immediately? Only through the required controlled approval process.