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HOW AI WILL RESHAPE THE FRONTLINES OF UPSTREAM OIL & GASReasoning, Agentic Orchestration, and Multimodal VisionPedro AlcalaJordi SerraNadim HaddadTommy InglesbyAI has crossed from the back o¾ce into the ¼eld© Oliver Wyman3How AI Will Reshape the Frontlines of Upstream Oil & GasEXECUTIVE BRIEFINGArtificial Intelligence (AI) is moving beyond back-oޱce automation into the operational core of upstream oil and gas. The new wave — reasoning-capable models, agentic orchestration, and multimodal vision — goes past dashboards and predictive analytics to deliver actionable recommendations in the field.This is not incremental improvement; it is an operating-model shift. The leadership challenge is no longer whether to use AI, but how to scale from pilots to governed, safe deployment across core workflows.WHAT’S NEWReasoning-capable models: AI that can work through problems step-by-step — like an engineer — testing options, weighing trade-oޮs, and updating its recommendations as conditions change.Agentic orchestration: Software “agents” that coordinate drilling, subsurface, production, and logistics across existing tools, collapsing silos and optimizing to asset-level value — operating under policies that enforce human approvals, safety limits, and full audit trails.Multimodal AI (vision + data): Systems that combine live video, sensor data, and engineering schematics to understand field environments in context and provide real-time recommendations.IMPLICATIONS FOR UPSTREAM LEADERSShift metrics: Move from discipline-only measures (such as feet drilled or equipment uptime) to system-level performance anchored to the profit and loss (P&L).Governance ࢉrst: Keep human-in-the-loop oversight with safe operating envelopes, tiered approvals, and auditable actions to meet safety and regulatory requirements.Early movers lead: Reduce operational risk, accelerate time to first oil, and shape industry standards for digital-physical convergence.© Oliver Wyman4How AI Will Reshape the Frontlines of Upstream Oil & GasWHERE IT APPLIES NOWExploration — AI agents accelerate seismic interpretation, connecting legacy software and tools with no intermediaries, and contextualizing responses for fully automated and more accurate workflows.Drilling — Reasoning models and multimodal vision to complete automation cycles with current drilling equipment and to provide enhanced responses that consider all context factors: such as hydraulics, ROP (rate of penetration), hole cleaning, and formation target positional accuracy. Drilling centers are evolving from monitoring and alarms to automated engineering analysis and prescriptions.Production — Agentic layers optimize gas lift, surface equipment performance, and field production, optimizing P&L while operating within subsurface model envelopes.Logistics — AI agents integrate marine routes, weather, and demand forecasts for optimal dispatch, considering all potential factors, and with no requirement for specific instructions. They act on requests an