AI Energy Demand, Shell’s 160 Projects, SLB Upstream Deal, and 7 GW of US Data Center Delays (2025-2026)

AI Adoption Risks, Shell’s 160 Projects Face AI’s Growing Energy Demand

Energy majors like Shell are rapidly scaling artificial intelligence to optimize operations, but this strategy is colliding with the physical constraint of power grid capacity, which is strained by the collective energy demand of AI itself. This dynamic creates a dual role for firms like Shell, positioning them as both major consumers of AI-dependent services and potential solutions providers for the underlying energy deficit, a challenge also being navigated by competitors like Exxon Mobil and Chevron.

Shell’s AI-First Operational Pivot

By 2025, Shell‘s use of AI moved from experimentation to a core operational strategy, deploying over 160 active AI projects to enhance efficiency and safety across its value chain. This “AI-first” approach is not a single initiative but a broad integration of machine learning and advanced analytics into fundamental business processes. It targets everything from optimizing upstream exploration with reinforcement learning to monitoring safety at 44, 000 retail stations with its VADR computer vision system.

The Data Center Power Constraint

The aggressive scaling of AI by Shell and others is contributing to a significant market-level risk: the immense power demand of AI data centers is creating grid bottlenecks. The market’s explosive growth, valued at USD 5.1 billion in 2025, comes with a high energy cost. Projections for 2026 indicate that up to 7 GW of planned U.S. data center projects may be delayed or canceled specifically due to power infrastructure constraints, a critical dependency for Shell‘s digital ambitions.

A Dual Role for Energy Majors

This energy deficit presents both a risk and a significant commercial opportunity. While Shell‘s AI programs depend on stable power, the company is also uniquely positioned to supply the required energy, whether through natural gas, its growing renewables portfolio, or other grid services. This situation forces a strategic question: will Shell primarily be a consumer of AI, subject to rising energy costs and infrastructure instability, or will it become a key energy provider to the trillion-dollar AI industry, as seen in market moves by companies like Next Era.

AI in Oil & Gas Market Set for 13% CAGR Growth
The AI in Oil and Gas market is projected to more than double from USD 3.79 billion in 2025 to USD 7.91 billion by 2031, growing at a robust 13.03% CAGR. This signifies a rapid acceleration in AI adoption across the sector.

(Source: Mordor Intelligence — via State of AI in Operations)

Shell’s 4 Key AI Agreements with SLB and Yokogawa (2025)

In 2025, Shell accelerated its AI deployment not by building everything in-house, but by formalizing a partner ecosystem to co-develop solutions for specific operational challenges, from upstream efficiency to robotic asset management. This strategy allows the company to leverage specialized expertise and scalable platforms, mitigating the high cost of internal development while speeding up the integration of new technologies.

Deepening Upstream Digitalization with SLB

A central pillar of this strategy is the deepened collaboration with SLB. A December 11, 2025, agreement focuses on co-developing agentic AI solutions on SLB‘s Lumi™ platform to augment the capabilities of technical experts in upstream operations. This builds upon an earlier 2025 partnership to standardize Shell‘s global operations on SLB‘s Petrel™ subsurface software, creating a unified digital environment for exploration and production data.

Piloting Automation and Safety Tech

Beyond software, Shell is using partnerships to pilot physical automation. A June 18, 2025, collaboration with Yokogawa initiated the deployment of robotics and drones at two facilities to test their value in improving operational efficiency. Separately, an August 22, 2025, initiative was launched to use AI and data analysis to improve safety measures on its Floating Production Storage and Offloading (FPSO) units.

Industry-Wide Platform Building

Shell‘s strategy extends to shaping industry-wide standards through its role as a founding member of the Open AI Energy Initiative. Announced on October 23, 2025, this partnership with Baker Hughes, C 3.ai, and Microsoft aims to foster collaborative development of AI solutions for the entire energy sector, signaling a move toward interoperability and shared innovation.

Table: Shell’s Key AI Partnerships and Projects (2025)

Global Deployment, Shell’s AI Strategy Moves From Pilots to Enterprise Scale

Shell‘s AI initiatives in 2025 reflect a global-first deployment strategy, moving beyond geographically isolated pilots to standardized, enterprise-wide rollouts across its diverse operational footprint in upstream, downstream, and retail. This marks a shift from testing AI’s potential to actively integrating it as a standard business tool to drive performance and efficiency worldwide.

Global Asset Standardization

A key feature of the 2025 strategy was the push for global standardization on partner platforms. The decision to expand the use of SLB‘s Petrel™ software and the continued rollout of the C 3 AI Reliability suite across thousands of assets indicate a deliberate move away from fragmented, site-specific solutions. This approach enables Shell to apply learnings, enforce best practices, and scale AI-driven insights across its entire portfolio.

Retail Network as a Global Proving Ground

The VADR (Video Analytics for Detection and Ranging) system is a prime example of achieving global scale with a single AI application. Built on Microsoft Azure, the system is deployed across Shell‘s network of 44, 000 retail stations worldwide. It uses computer vision to detect safety hazards in real-time, demonstrating how a standardized AI solution can be effectively managed and scaled across a vast and geographically dispersed asset base.

US Renewables and Grid Integration

In the U.S., Shell subsidiary Savion’s joint venture involving five solar projects highlights another dimension of its global AI strategy. While not exclusively an AI project, the efficient operation, forecasting, and grid integration of these renewable assets are heavily dependent on AI and machine learning. This aligns with Shell‘s broader digitalization goals and connects its AI activities to the challenges of the energy transition, including its hydrogen business.

SWOT Analysis, Shell’s AI Strengths and External Energy Threats

Shell‘s primary strength in 2025 lies in its ability to leverage its vast operational data and partner ecosystem for AI-driven efficiencies, but it faces a significant external threat from the very energy and infrastructure constraints that the AI boom is creating. The company’s future success depends on its ability to navigate this paradox by capitalizing on its opportunities while mitigating the substantial risks of a power-constrained digital economy.

Table: SWOT Analysis for Shell’s AI Initiatives (2025)

Shell’s Next Move: Powering the AI Boom or Getting Consumed By It?

Looking to 2026, the critical question for Shell is whether it will strategically pivot to become a primary energy supplier for the AI data center boom, or if its own AI-driven efficiency gains will be eroded by rising energy costs and infrastructure bottlenecks. The expansion of its reliability program with C 3 AI to cover over 13, 000 pieces of equipment signals a doubling down on efficiency, but this internal focus must be balanced with a strategy for the external energy challenge.

• If Shell intends to capitalize on the AI energy demand, watch for announcements of direct power-purchase agreements with data center operators or technology firms like Nvidia, similar to strategies being pursued by competitors like Saudi Aramco.
• A key signal of this pivot would be direct investments in assets that support data centers, such as gas-fired peaker plants for reliable power or battery energy storage systems (BESS) for grid stabilization.
• Conversely, if Shell remains primarily focused on internal use, watch for increased commentary on the rising cost of energy as a business risk in its financial reporting and investor calls.
• The release of its Enterprise Technology Analysis Report, anticipated in February 2026, will be a critical indicator, potentially offering the first public quantification of ROI from its 2025 AI projects and its strategic view on the AI energy paradox.

The questions your competitors are already asking

This report covers one angle of Shell’s AI strategy. The questions that matter most depend on your work.

• Exxon and Chevron AI energy strategy
• Energy companies selling power directly to data centers
• US data center projects delayed by power shortages
• Data centers buying power directly from producers

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