SLB and Shell Want AI to Run the Oilfield

SLB and Shell are co-developing agentic AI on the Lumi platform to unify upstream data and power autonomous oilfield decisions

1 Apr 2026

Two of the energy industry's most consequential players have joined forces to reshape how artificial intelligence is deployed across oil and gas operations. SLB and Shell signed a strategic collaboration agreement in December 2025 to co-develop agentic AI solutions built on SLB's Lumi data and AI platform, targeting the fragmented data infrastructure that has long impeded AI adoption across upstream operations.

The partnership addresses a structural problem that has persisted for years. Subsurface models, drilling records, and production metrics typically reside in disconnected systems, slowing decisions and obscuring emerging risks. Lumi is designed to unify those data streams into a single secure environment, providing the connected foundation that AI systems require to function continuously and reliably across the upstream value chain.

What sets this collaboration apart is its emphasis on agentic AI, technology capable of executing complex, multi-step tasks on its own rather than simply responding to prompts. For technical teams managing large asset portfolios, AI that can independently surface insights, flag developing problems, and support real-time operational decisions represents a meaningful departure from existing practice. According to company statements, SLB's president of digital framed the partnership as part of a broader effort to reshape industry workflows through automation and autonomy.

Shell's involvement is intended to serve purposes beyond its own operations. Solutions developed through the collaboration are designed to be commercially deployable across the broader sector, positioning Lumi as a platform other operators could eventually adopt. In the Middle East, where national oil companies have committed significant capital to their own AI programs, a proven enterprise-grade upstream platform could reduce redundant development and accelerate the shift from isolated pilots to scaled deployment.

The initiative extends an earlier arrangement in which SLB standardized Shell's global subsurface infrastructure using its Petrel software. Moving from data standardization to autonomous operational intelligence marks a significant escalation in scope. Yet the distance between architectural ambition and field-level performance remains to be measured, and how the platform holds up under real-world operational complexity will ultimately determine whether the connected, intelligent oilfield arrives as quickly as its architects suggest.