One signal

Geotab’s Abhinav Vasu argues that fleet AI is most useful when it turns operational data into decisions, from spotting vehicles that need maintenance to identifying risky routes. His practical advice: start with one defined problem, set a baseline, measure results and ask suppliers to explain their recommendations.

Vasu cites Go-Ahead as having prevented more than 10 breakdowns in its first month using the technology, and HATS Group as having cut road incidents by 78% after pairing AI-enabled dashcams with in-cab coaching. Those are examples in a sponsored Geotab opinion piece, not independently assessed results. He also warns that poor data can produce confident but misleading answers, and that driver monitoring needs a clear purpose and careful handling. Fleet managers may get help with repetitive work, but Vasu argues the consequential calls still belong to people.

Discuss: If AI flags a risky driver or recommends a vehicle decision, should the fleet manager remain accountable for acting on it, or should responsibility be shared with the supplier?

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