Woodside Energy, a global energy producer, is embedding agentic AI more deeply into its operations, emphasizing governance, data quality, and human accountability. The company has spent over a decade building predictive analytics, optimization systems, and machine learning tools across its energy operations. According to Andrew Melouney, vice president for digital at Woodside Energy, the company has always had large volumes of operational data from its equipment and assets, which have created high-value use cases. This long-term investment in infrastructure and governance is now enabling a broader shift toward agentic AI systems that support complex industrial workflows. Source: mittr
Woodside’s approach to AI is centered on augmenting human expertise in high-stakes environments rather than replacing it. A prime example is its “Startup Advisor,” an AI copilot that helps operators manage the complex process of starting liquefied natural gas (LNG) plants. Melouney explains that the company is focused on empowering employees to make better and faster decisions. This strategy reflects a wider evolution in industrial AI, transitioning from isolated experiments to enterprise-wide systems built on standardized platforms and repeatable deployment patterns. Source: mittr
The energy sector’s AI journey differs from consumer-facing applications due to its focus on safety, reliability, and physical systems. Woodside has applied traditional AI techniques since around 2015, including analytics, optimization, and predictive models. With the advent of generative AI, the company has built on this foundation to solve problems that improve safety, environmental protection, and organizational returns. Melouney emphasizes that the technology is important, but it must be aligned with people, processes, and purposeful adoption. Source: mittr
