Middle East Crisis Forces Oil Companies to Pivot Toward Power and AI Value Chains
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Middle East Crisis Forces Oil Companies to Pivot Toward Power and AI Value Chains
The report contends that the closure of the Strait of Hormuz will permanently elevate oil price risk premiums, urging oil companies to extend downstream into power, data centers, and even AI infrastructure to capture higher valuations.
- The closure of the Strait of Hormuz has disrupted approximately 15 million barrels per day of supply, marking the largest energy crisis in history.
- Oil price risk premiums are set to rise permanently, triggering a new wave of M&A activity outside the Middle East.
- Power has become the primary bottleneck in the energy market; oil companies should shift their investment focus toward the power value chain.
- AI services can generate gross margins up to 100 times those at the generation level, offering immense downstream value.
- Lessons from the failed diversification efforts of oil companies in the 1970s—slowing demand and misallocation of capital—underscore the risks involved.
- Oil companies that take early steps to deploy power, data centers, and nuclear energy may see their valuations reassessed.
Report interpretation
Overview
Using the strategic adjustments following the Middle East war as its starting point, the report notes that the closure of the Strait of Hormuz has interrupted roughly 15 million barrels per day of crude oil supply, constituting the largest energy crisis in history. Institutions believe that geopolitical factors will permanently raise oil price risk premiums and spark a fresh wave of mergers and acquisitions; meanwhile, surging demand for AI computing power has made electricity the biggest bottleneck in the energy system. Oil companies face two paths: continue expanding production in high-cost regions or extend downstream into power, data centers, and even AI infrastructure. Drawing on examples of failed diversification attempts by oil companies in the 1970s, the report warns of potential risks but emphasizes that this round of “electrification + AI” trends is irreversible, with pioneering firms likely to enjoy valuation reevaluation.
Core views
Demand side: AI and data centers are driving rapid growth in electricity demand, making power the primary driver of incremental end-use energy consumption. Supply side: The closure of the Strait of Hormuz has cast doubt on Persian Gulf energy security, prompting Europe, Australia, Canada, and other high-cost basins to become key sources of additional supply; Qatar’s 20% share of global long-term LNG contracts is also considered high-risk. M&A direction: Shell’s $16.4 billion acquisition of Canada’s ARC Resources is just the beginning, with more small- and medium-sized E&P companies expected to become targets. Transformation cases: - Chevron and Engine No 1 plan to build a 4 GW gas-fired power plant directly connected to a data center by 2027; - Exxon is experimenting with a 1.5 GW non‑utility data center powered by CCS technology; - TotalEnergies aims to generate 100–120 TWh annually by 2030 and has already signed a major power supply agreement with Czech EPH; - PetroChina has set a goal of having electricity account for one-third of its total energy output by 2035, equivalent to about 1,000 TWh—a record-high publicly stated target worldwide. Valuation comparison: Traditional oil companies typically trade at EV/EBITDA ratios of only 0.8–1.5x, whereas data center/AI value-chain firms generally command multiples of 5–10x, with AI service segments sometimes exceeding 10x. Historical lessons: Following the 1973 oil embargo, oil companies aggressively expanded into unrelated sectors such as nuclear power, coal, metals, and animal feed, ultimately suffering significant write-downs due to a sharp drop in electricity demand growth from 7% to 3% and poor capital allocation. The report argues that this time around, the difference lies in the fact that AI-driven electricity demand growth is far more predictable than the traditional slowdown experienced back then, leading to the conclusion that transformation will unlock valuation premiums.
Analysis framework
The report employs a four-step framework—‘Geopolitical Shock → Supply Chain Restructuring → Value Chain Extension → Valuation Reassessment’—to dissect the situation: 1. Using the current Strait of Hormuz incident as a proxy for the 1973 oil embargo, it quantifies supply gaps and price elasticity; 2. Through M&A case studies (e.g., Shell/ARC), it illustrates capital flows toward high-cost, non-Middle Eastern regions; 3. A visualized AI value chain diagram highlights the escalating profit margins from power generation through data centers to AI services, underscoring the economic rationale behind downstream expansion; 4. By contrasting historical failures from the 1970s, it stresses that today’s demand drivers (AI-powered electricity) differ fundamentally from past trends (traditional electricity deceleration), thereby concluding that transformation will yield valuation uplift.
Methodology notes
Profit distribution and transmission across the industry chain
The report uses the ‘power generation–data center–AI service’ chain to demonstrate how gross margins per kWh escalate from $0.03 to $1–$3, helping readers understand why oil companies are willing to extend downstream.
Historical comparative methodology
By comparing the 2026 Middle East crisis with the 1973 oil embargo, the report assesses industry turning points based on three main threads: supply gaps, price increases, and corporate behavior.
Cross-sector valuation comparisons
Through EV/EBITDA, P/S, and other metrics, the report contrasts oil companies with data center and AI firms, demonstrating the potential for valuation expansion resulting from transformation.
Asset mapping & comparison
Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).
- ChevronHas announced collaboration with Engine No 1 to build a 4 GW gas-fired power plant directly linked to a data center, exemplifying downstream extension
- Strengths
- Strong financial resources; already implemented large-scale gas-fired power plus data center projects
- Weaknesses
- -
- Comparison
- -
- Risks
- -
- Exxon MobilFirst attempt at powering a data center with a 1.5 GW gas-fired plant equipped with CCS technology, exploring unconventional pathways
- Strengths
- Deep technical expertise; bold experimentation with CCS and data center integration
- Weaknesses
- Project scale remains small; still in experimental phase
- Comparison
- -
- Risks
- -
- TotalEnergiesMost aggressive European player, aiming to generate 100–120 TWh by 2030 and already securing major data center power supply agreements
- Strengths
- Leading pace of transformation; well-established presence in European power markets
- Weaknesses
- -
- Comparison
- -
- Risks
- -
- Equinix / Digital RealtyRepresentative of data center “shell” assets; oil companies could directly benefit through self‑construction or partnerships
- Strengths
- Highly validated valuation model (P/S ratio around 10x)
- Weaknesses
- Far smaller in scale compared to oil companies; vast room for cooperation or M&A
- Comparison
- -
- Risks
- -
- CoreWeaveNeocloud representative showcasing AI value chain profit multipliers; oil companies extending into GPU cloud services could benchmark against this model
- Strengths
- High-margin GPU leasing model
- Weaknesses
- Capital-intensive; high technical barriers
- Comparison
- -
- Risks
- -
Key data
- Scale of Supply Disruption15 million barrels per dayApproximately 15% of global supply, representing the largest energy crisis in history
- 1973 Oil Price Increase300%From $3 per barrel to $12 per barrel (nominal price), never returning to pre-crisis levels
- Shell’s M&A Amount$16.4 billionAcquisition of Canada’s ARC Resources, signaling the start of a new wave of M&A activity
- Gross Margin at Power Generation$0.03 per kWhReflects basic electricity sales profits
- Gross Margin at AI Service End$1–$3 per kWhCalculated based on token or API fees, roughly 100 times higher than generation-level margins
- Oil Companies’ P/S Range0.8–1.5xSignificantly lower than the 5–10x range seen in data centers and AI value chains
- PetroChina’s Electricity Target1,000 TWhElectricity output projected to comprise one-third of the group’s total energy mix by 2035
Impact & implications
The report concludes that under the dual forces of geopolitics and AI demand, traditional oil companies clinging to upstream extraction risk missing out on the substantial valuation gains offered by power and AI infrastructure. Companies that proactively invest in gas-fired power generation, renewable energy, small modular reactors (SMRs), or even data center “shell” assets stand to benefit from revaluation in capital markets. Conversely, enterprises that merely ramp up high-cost oil and gas projects while neglecting downstream expansion may face prolonged valuation discounts.
Risks
- Repetition of the 1970s oil company diversification failure: If AI-driven electricity demand growth falls short of expectations, large-scale capital expenditures could result in write-downs.
- Data center, nuclear power, and SMR technologies remain in early stages, with significant uncertainties regarding policies, permits, and construction timelines.
- Simultaneous advancement of high-cost oil and gas projects may lead to fragmented capital allocation and declining returns.
What to watch
- Upcoming 2030–2035 power capacity and data center investment guidance announcements from major oil companies
- The progress of the first oil company to announce entry into small modular reactor (SMR) development and related projects
- The pace and premium levels of the latest round of oil and gas M&A deals in North America, Australia, and Canada
- Whether actual AI computing demand and electricity load growth align with projected expectations.