Research preview. Independent expert review is pending. The worked analyses are hypothetical.
Method and corrections Interactive field model
Inspect the system around the AI system. The model is organized by the clauses of the definition: societies, the four objects, the benefits and harmful patterns governance aims at, and the conditions it races against. Apply a cross-cutting test, narrow by lifecycle stage or level, and inspect how definitions, claims, relationships and sources travel together.
Apply a cross-cutting test Whole model Power Legitimacy Distribution Adaptability
Narrow by lifecycle stage or level Lifecycle stage Any stage Research Data collection Model development Evaluation Procurement Deployment Monitoring Incident response Retirement Level Any level Community and organisational use Corporate Sectoral National Regional International Loading interactive controls. Concept links remain available. Field model · whole model
Groups follow the clauses of the definition; they are not a sequence or causal chain. Actual relationships appear in the inspector.
Jump to selected entity Societies …how societies should shape…
actor AI developer or provider actor Deploying organization actor Affected people actor Civil society and independent researchers Incentives …the incentives…
incentive Deployment pressure incentive Competitive race dynamics incentive Liability exposure incentive Procurement leverage
Institutions …institutions…
institution Regulator or public authority institution Internal safety and governance team institution Standards body institution International institution
Infrastructures …infrastructures…
infrastructure Evaluation capacity infrastructure Compute infrastructure Data, language resources, and data labor infrastructure Energy, water, and minerals infrastructure Data work and content moderation Safeguards …and safeguards around AI…
safeguard Risk management process safeguard Impact assessment safeguard Traceability safeguard Audit record safeguard Meaningful human oversight safeguard Supervision and regulatory review safeguard Pre-deployment evaluation and red teaming safeguard Incident reporting and post-deployment monitoring safeguard Complaint and appeal routes safeguard Review and sunset provisions safeguard Compute controls Benefits and harmful patterns …so that its benefits are broadly shared and harmful patterns are addressed…
principle Accountability principle Safety principle Broadly shared benefit pattern Contestable decision pattern Concentration of power pattern Systematically unreliable provenance pattern Over-reliance and deskilling pattern Sycophancy and engagement-driven agreement pattern Homogenisation and loss of authorship Choices and conditions …while they are still choices rather than conditions.
condition Lock-in condition Governance lock-in condition Reversibility window
Infrastructure · Infrastructures established
Energy, water, and minerals The physical inputs to compute: electricity, cooling water, and critical minerals, whose demand shapes siting, grids, and climate commitments.
Where do the electricity and water come from, who pays, and who decides where capacity is built?
Tests Distribution Power
Lifecycle Model development Deployment
Levels National Regional Recorded relationships Read each statement from its first entity to its second. Status describes our mapping, not certainty of cause.
Energy, water, and minerals — constrains the siting and growth of → Compute
Mapping: asserted
Data centre electricity demand is projected to more than double by 2030 and is clustered in a few regions, so grid and water capacity shape where compute can be built.
Inspect evidence · 1 passage Passage summaries are paraphrases, not quotations. Open the source to read the full passage.
Energy and AI (opens in a new tab) Executive summary — data centre electricity consumption and regional shares
Data centres accounted for around 1.5% of world electricity consumption in 2024, about 415 TWh, growing around 12% a year since 2017. Consumption is projected to more than double to around 945 TWh by 2030. The United States accounted for 45% of 2024 consumption, China 25% and Europe 15%; nearly half of US capacity sits in five regional clusters.
Scope note: Projections are scenario-based estimates, not observations; the 2024 consumption figure is an estimate published in 2025.
Passage checked 2026-09-06 · iea-datacentre-electricity
Claims and evidence · 1 source-assertion Confidence: high Contestability: low
Data centres consumed roughly 1.5% of global electricity in 2024, and their consumption is projected to more than double by 2030, concentrated in the United States, China and Europe.
Our reading: The 2024 figure is an estimate and the 2030 figure a base-case projection. Data centres serve more than AI; the report attributes the growth surge to AI.
Inspect evidence · 1 passage Passage summaries are paraphrases, not quotations. Open the source to read the full passage.
Energy and AI (opens in a new tab) Executive summary — data centre electricity consumption and regional shares
Data centres accounted for around 1.5% of world electricity consumption in 2024, about 415 TWh, growing around 12% a year since 2017. Consumption is projected to more than double to around 945 TWh by 2030. The United States accounted for 45% of 2024 consumption, China 25% and Europe 15%; nearly half of US capacity sits in five regional clusters.
Scope note: Projections are scenario-based estimates, not observations; the 2024 consumption figure is an estimate published in 2025.
Passage checked 2026-09-06 · iea-datacentre-electricity