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Predictive care for energy workers
Can AI improve safety without compromising privacy?
Ed Crooks
Vice Chair Americas and host of Energy Gang podcast
Ed Crooks
Vice Chair Americas and host of Energy Gang podcast
Ed examines the forces shaping the energy industry globally.
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Energy companies use sensors and AI to anticipate equipment failure. Can the same predictive approach protect the people operating that equipment, without turning safety systems into a new form of workplace surveillance? As AI moves from screens into robots, control rooms and industrial sites, that question is becoming practical, not theoretical.
Host Ed Crooks is joined by Olivier Oullier, a neuroscientist, investor and AI entrepreneur whose work focuses on how people and machines interact. Olivier argues that AI can improve operator safety and productivity at once through neuroadaptive systems that use signals such as brainwaves, facial expression, eye movement and voice to detect fatigue, stress, distraction or cognitive overload.
In energy operations, those systems could adapt control-room dashboards to foreground the information that matters, or help collaborative robots respond when an operator is tired or distracted. Olivier says pilots are already underway in energy operations in Mexico, Australia and the UAE. Drawing on lessons from surgery and transport, he describes this as an extension of predictive maintenance: moving from monitoring equipment to anticipating human needs, or what he calls predictive care.
That promise rests on a sensitive trade-off. Continuous physiological monitoring could support safer work, but it also raises concerns about consent, autonomy and employee surveillance. Olivier says programs should be voluntary, transparent and compliant with regulation; the discussion tests what responsible deployment needs to look like and whether better outcomes can justify collecting such intimate data.
The conversation also ranges from the risks of poorly supervised AI agents and the skills needed to use AI well to the next phase of physical AI. Olivier points to world models, which aim to help robots understand and act in physical environments, while cautioning against precise long-range predictions about jobs. For energy companies, the near-term challenge is to deploy systems that improve safety and performance without losing sight of the people they are meant to serve.
This episode of the Energy Gang is brought to you by ADIPEC, the world's largest energy event, taking place in Abu Dhabi from 2-5 November.
As demand rises and global energy markets evolve, ADIPEC 2026 brings together governments, industry, investors and technology leaders to accelerate investment, advance technology and build the partnerships needed to meet today's energy needs while building a more resilient system for tomorrow.
Discover more at adipec.com

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Energy Gang is a bi-weekly podcast. Join Ed Crooks and the gang for their take on the biggest energy stories shaping the world, with sharp analysis from top experts in climate, policy and the energy industry.