Taking AI from a pilot into everyday operations
Start with workflows, data and evaluation criteria to build a meaningful proof of concept.
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Choose a decision to improve
Identify who uses the AI output, when they need it and what action follows. In safety monitoring, the output can be an event for an operator to review, confirm and respond to. Describe this workflow before choosing a model.
Evaluate on representative data
Pilot data should reflect camera angles, shifts, lighting and difficult on-site conditions. Separate tuning data from evaluation data. Agree how missed events and false alerts will be counted for each scenario.
Design the operating process too
A PoC should test event flows, access controls, retention and API integration alongside detection results. Document acceptance criteria, alert ownership and post-deployment quality monitoring. Expand when the evaluation evidence and response process support it.
