Safety leaders should compare AI video analytics on which risks it detects, how accurate it is in their own lighting and layout, how quickly alerts arrive, whether an alert can trigger an action such as a light or a slowdown, and whether it runs on the plant's existing cameras. They should also compare privacy controls, where footage is stored and who can see it, and how findings reach supervisors in a form they can act on. The fair test is a pilot on the plant's highest-risk camera views, measured on confirmed detections, false alerts and the changes that followed.
Two set-ups are common. Analytics running on existing CCTV cover large areas at low hardware cost and suit trend analysis, but alerts usually arrive after the moment has passed. Purpose-built edge cameras process video on site and can drive a warning or interlock in time to matter, at the cost of new hardware. Many plants use both. Ask each supplier to state measured latency from event to alert on your network, and which detections are trained for your work, such as forklift interactions, PPE, line-of-fire and exclusion zones. The AI forklift safety guide explains where the category tends to fail, and the manufacturing guide covers plant-floor traffic.