Major oil and petrochemical companies are deploying AI systems to predict equipment failures and safety hazards in refineries before they occur.
In October 2024, Chevron and Honeywell announced a collaboration to create AI-assisted alarm management solutions that guide operators through operational responses.
Companies like ExxonMobil, Phillips 66, and Marathon Petroleum are using machine learning and computer vision to monitor facilities in real time, catching potential safety risks and equipment leaks with greater accuracy than traditional inspections and human surveillance.
What happened
Major energy companies including ExxonMobil, Chevron, Phillips 66, and others are implementing AI systems for predictive maintenance, alarm management, and video monitoring in refineries and petrochemical plants. In October 2024, Chevron and Honeywell announced a collaboration to create AI-assisted alarm management solutions with an Alarm Guidance application that provides operators with specific actions to respond to alarms and operational events.
Why it matters
AI systems analyze vast datasets and sensor inputs to predict maintenance needs and safety hazards before they occur, shifting operations from reactive repairs to preventive interventions. This reduces lost profit opportunities, process safety incidents, and environmental risks. The technology monitors surveillance feeds and equipment data with greater sensitivity and accuracy than human observers alone can achieve, helping protect workers and critical infrastructure.
What to watch
The Chevron-Honeywell solution is expected to help operators increase efficiency, safety, and reliability of process operations. Separately, Marathon Petroleum uses Flyscan, an AI-driven technology that scans pipeline rights of way from aircraft to detect hydrocarbon leaks and mechanical threats with greater sensitivity than manual patrols.
People increasingly rely on AI tools like ChatGPT and Copilot for everyday tasks, but the technology is also reshaping critical safety operations in energy production. Refining and petrochemical companies are leveraging AI's ability to process massive data streams, identify subtle patterns, and forecast operational risks—not merely to improve efficiency, but to safeguard workers, protect the environment, and secure essential infrastructure.
In October 2024, Chevron and Honeywell announced a collaboration to build a new generation of AI-assisted alarm management solutions. The system includes an Alarm Guidance application designed to provide operators with guided and specific actions in response to alarms and operational events. By helping operators respond more effectively, the application aims to reduce lost profit opportunities and process safety incidents. AI's capacity to analyze vast datasets and detect emerging trends is transforming how facilities handle maintenance as well. Rather than following fixed schedules or conducting manual inspections alone, leading operators now deploy AI systems that continuously monitor sensor inputs and historical performance data to precisely predict where and when maintenance is needed. This shift from reactive repairs to predictive interventions prevents incidents before they occur—saving time, money, and reducing the risk of emissions or worker injury.
Industry adoption is broad. ExxonMobil, Chevron, Phillips 66, Flint Hills Resources, LyondellBasell, and BASF have all rolled out AI-enabled predictive maintenance at their facilities. Beyond maintenance, AI strengthens safety through advanced video and camera monitoring. ExxonMobil uses machine learning and computer vision to analyze real-time refinery footage, alerting staff to potential hazards and unsafe behaviors to prevent incidents before escalation. Marathon Petroleum deploys Flyscan, an AI-driven technology that scans pipeline rights of way from patrol aircraft, detecting hydrocarbon leaks and equipment threats with greater sensitivity and accuracy than human observers can achieve.
According to Lara Swett, Vice President of Technical and Safety Programs at the American Fuel & Petrochemical Manufacturers (AFPM), "AI is helping us move from reactive to proactive safety — identifying risks before they escalate and guiding proven responses." She emphasized that intelligent systems alone are not sufficient; rather, "the combination of intelligent systems and skilled people — those who bring insight, empathy, and accountability — that creates a truly resilient safety culture."
The oil and petrochemical industries are undergoing a significant operational shift as AI systems take on roles traditionally reserved for human inspection and reactive maintenance. Rather than waiting for equipment to fail or relying on fixed maintenance schedules, companies now deploy AI to continuously monitor sensor data, surveillance footage, and historical performance patterns to identify problems before they become incidents. This transition from reactive to predictive safety represents a fundamental change in how industrial assets are managed.
The collaboration announced by Chevron and Honeywell in October 2024 exemplifies how AI is being embedded into core operational decision-making. The Alarm Guidance application they developed addresses a specific pain point: helping operators respond correctly to the constant stream of alerts and operational events in a refinery. By automating parts of this guidance, the system can reduce both human error and the operational friction that sometimes leads to delays or missed safety opportunities.
The technology stack deployed across the industry is diverse. ExxonMobil combines machine learning and computer vision to analyze live refinery footage; Marathon Petroleum uses aerial drone-based threat detection; and multiple operators rely on predictive maintenance engines that synthesize sensor and historical data. What unites these applications is the idea that AI can process information faster and more consistently than human observation alone, freeing skilled operators to focus on judgment and accountability rather than routine surveillance.
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