Philippe Daroux

As asset intensive organizations embrace AI and digital transformation, the concept of the "assisted worker" is rapidly evolving into a core pillar of intelligent asset management. Moving beyond traditional connected worker initiatives, this session will explore how Chevron is building the digital and data foundations required to enable agentic AI, where AI not only provides insights, but begins to support autonomous decision making and task execution in the field.

• Why real time location services are foundational to intelligent asset management, enabling visibility of assets, people, and mobile equipment
• Building toward agentic AI to support autonomous decision making and task execution in field operations
• Integrating RTLS, IoT, and operational data to deliver contextual, real time insights that improve maintenance and turnaround performance [Discuss Sp
• Designing scalable architectures, including hybrid approaches combining RF and vision based AI, to operate effectively in complex environments
• Establishing strong data foundations and governance to enable AI driven asset performance while ensuring security and control