The opening keynote set a grounded and confident tone for the conference, positioning AI not as a future aspiration, but as an operational reality already reshaping how energy companies work. Drawing on Chevron’s long standing investment in data science and analytics, Justin Lo framed today’s AI moment as an inflection point where executive sponsorship, mature capability, and business relevance have finally converged.
The keynote traced how Chevron has spent more than a decade embedding advanced analytics across the value chain, from subsurface and engineering workflows through to trading, downstream operations, and corporate functions. What has changed, Lo argued, is not the ambition, but the ability to scale impact. Generative AI and agent based systems are lowering barriers to entry, allowing insights that once required specialist teams to be accessed directly within everyday workflows.
Real world examples from the Permian Basin illustrated how AI is being used to accelerate learning, standardise best practice, and improve safety and efficiency across highly complex operations. By ingesting vast volumes of structured and unstructured data, Chevron is able to automate playbooks, prioritise high value interventions, and respond faster to operational signals that would otherwise be lost in noise.
A central theme was the shift from bespoke models to reusable intelligence. Rather than repeatedly solving the same problems, the keynote outlined how AI foundations and orchestration layers allow organisations to capture institutional knowledge and make it available on demand. The message was clear: AI delivers value when it is woven into how work gets done, freeing people from repetitive effort and enabling them to focus on higher value decisions. The keynote concluded with a forward looking view of AI as a normalised business capability, one that will continue to evolve, but is already changing the industry’s operating model today.
Speakers
