Woodside pushes AI deeper into energy operations

Woodside Energy’s AI strategy has grown from predictive analytics and optimization into more agentic systems designed for complex industrial operations. The company has applied analytics, optimization and predictive models since around 2015 across exploration, drilling, maintenance and plant operations, using large volumes of data from equipment, plants and assets.

Maintenance intelligence is one example of that foundation at work. The system combines historical maintenance records with equipment performance data to recommend better timing for maintenance activity, with the opportunity to reduce maintenance hours by up to 15% over five years on one piloted asset. Woodside is also using its Startup Advisor, an AI copilot for operators managing LNG plant startups, to support faster and more informed decisions in high-stakes environments.

Woodside says it now has around 50 AI agents in production across operating assets and enterprise workflows. Its approach emphasizes standardized platforms, repeatable deployment patterns, structured assessments for privacy and cyber controls, and an AI council for higher-risk use cases. The company’s long-term goal is an autonomous enterprise where agents interact deeply with core workflows while people remain accountable for decisions.