- AI and Agentic Systems 2026
- Annex B
Data appendix
The indicator set with its sources, the source registers, the licences of every kind of material and the formats of the edition.
Contents
- ·Edition home
- ·Executive summary
- 1AI is infrastructure, not only software
- 2Key findings
- 3Systems and sectors at baseline
- 4Risks and capability
- 5Chip supply disruption under grid constraint
- 6Lenses and readings
- 7The 2027 agenda
- 8Systems in depth
- AMethodology
- BData appendix
- CReferences and record
- ·Complete edition, for print
B.1The indicator set
| Indicator | Value | Unit | Year | State | Source |
|---|---|---|---|---|---|
| Data-centre electricity use | ≈415 | TWh | 2024 | Reported | 1 |
| Share of world electricity | ≈1.5 | % | 2024 | Reported | 1 |
| Projected data-centre use | ≈945 | TWh | 2030 | Scenario | 1 |
| US data-centre share of electricity | 4.4 | % | 2023 | Reported | 15 |
| Frontier training compute growth | 4–5× | a year | 2010–2024 | Reported | 14 |
| Fall in cost of fixed-level use | >280× | fold | 2022–2024 | Reported | 2 |
| Organisations using AI | 78 | % | 2024 | Reported | 2 |
| Corporate AI investment | ≈252 | US$ billion | 2024 | Reported | 2 |
| Reported AI incidents | 233 | incidents | 2024 | Reported | 2 |
| Leading-edge logic capacity in Taiwan | 92 | % | 2019 | Reported | 17 |
| Jobs exposed to AI, IMF | ≈40 | % | 2024 | Reported | 16 |
| Jobs exposed to generative AI, ILO | ≈25 | % | 2025 | Reported | 32 |
| Jobs created by 2030 | 170 | million | 2025–2030 | Reported | 20 |
| Jobs displaced by 2030 | 92 | million | 2025–2030 | Reported | 20 |
| People offline | 2.6 | billion | 2024 | Reported | 34 |
B.2Global source register
The governed source set behind this edition. Each source keeps its authority, coverage, cadence and role; categories describe origin, not truth.
Domains bound by the register
- WAT
- ENE
- FOO
- HLT
- BIO
- CLI
- FIN
- TRD
- MIN
- AIC
| Source | Category | Coverage | Period | Cadence | Role |
|---|---|---|---|---|---|
| Energy and AI1 | intergovernmental | global | 2024–2030 | periodic | ENE |
| AI Index 20252 | university | global | 2024 | annual | adoption |
| International AI Safety Report3 | expert panel | global | 2025 | periodic | safety |
| Data-centre energy report15 | national laboratory | United States | 2023 | periodic | ENE |
| Compute trends14 | research institute | global | 2010–2024 | continuous | compute |
| Semiconductor supply chain17 | industry · consultancy | global | 2019 | one-off | chips |
| Critical Minerals Outlook18 | intergovernmental | global | 2024 | annual | MIN |
| Labour exposure1632 | IMF · ILO | global | 2024–2025 | periodic | labour |
| Facts and Figures34 | UN agency | global | 2024 | annual | access |
| Incident databases2728 | civil society · OECD | global | continuous | continuous | safety |
B.3Regional reading, AI across ten clusters
Regional plates follow with the regional editions. This page gives the regional reading of AI infrastructure and exposure in table form, and ranks no region.
| Region | Principal hazards | Systems most exposed | Baseline evidence |
|---|---|---|---|
| North America | largest data-centre load; grid queues | power, water, labour | LBNL15; IEA1 |
| South America | early adoption; clean-power potential | energy, skills | assessments33 |
| Europe | binding AI law; grid constraints | governance, power | AI Act4 |
| Eurasia | limited public data | access to chips | export controls29 |
| Middle East and North Africa | new data-centre investment; water stress | water, power | IEA1 |
| Africa | connectivity gaps | access, skills | ITU34 |
| South Asia | large workforce exposure | labour, skills | ILO32 |
| East Asia | chip manufacturing concentration | supply chain | SIA–BCG17 |
| ASEAN | fast-growing data-centre hubs | power, water | IEA1 |
| Oceania-Pacific | small-island access gaps | connectivity | ITU34 |
B.4Cluster card, leading-edge chip manufacturing
- supply chain
- single region
- chips
- minerals
- Systems in view
- compute, electronics, trade, finance
- Defining fact
- about 92% of leading-edge logic capacity in one region in 201917
- Couplings
- MIN → AIC chips; ENE and WAT → fabs; TRD → AIC export controls
- Capability evidence
- new fabs announced in several regions; stockpiles limited
- Gaps
- current capacity shares; time to recover from disruption
- Agenda items
- X-02
Leading-edge chips depend on a handful of fabs, tool makers and mineral refiners. Each is efficient; together they form a chain with few alternatives.
SUPPLY
One region, one chain
Chip fabrication uses large volumes of ultra-pure water and reliable power, coupling chip supply to droughts and grid events.
PHYSICAL INPUTS
Fabs need water and power
Export controls on chips, tools and minerals since 2022 add policy risk to physical risk.
TRADE
Controls tighten
B.5How countries appear in the AI edition
Countries enter the AI edition through the readiness chapters of their own national editions, on one card grammar. They are read against peer distributions and thresholds, never ranked.
| Card field | What it shows | Source |
|---|---|---|
| WEFH+B state | each core system against peer distribution bands | national edition |
| Couplings | the national dependency matrix | national edition |
| Risk objects | the national risk portfolio | national edition |
| Capability rungs | the national capability ladder | national edition |
| Evidence age | oldest and newest source dates | national source register |
Editions in the 2026 Baseline programme
26national
countries and unions
10regional
clusters
16global
flagship and sector
20frontier
technology reports
How to read a country card
- Each system is shown against the distribution of its peers, with thresholds where they exist
- Couplings and risk objects come from the country’s own national edition
- Capability rungs record evidence, not a judgement of institutions
- Evidence age is printed, so older national data are visible as such
| Wave | Countries and unions | State |
|---|---|---|
| W0 | Canada | ISSUED |
| W1 | United States, United Kingdom, France, Germany, Italy, Japan, European Union, Switzerland | PLANNED |
| W2 | Mexico, Brazil, Argentina, Türkiye, Russian Federation, Saudi Arabia, United Arab Emirates, South Africa, Senegal, Kenya, African Union, India, China, Republic of Korea, Indonesia, Singapore, Australia | PLANNED |
B.6Licences
| Material | Licence |
|---|---|
| Text | CC BY 4.0 |
| Data | on the licence of each source; Nexus tables CC BY 4.0 |
| Figures | Nexus figures CC BY 4.0; third-party as credited |
| Maps | boundary source and licence printed on each plate |
| Metadata | CC0 1.0, as Zenodo publishes it |
| Third-party data, figures and text | The source’s own licence, credited where it is used; never relicensed |
| Nexus-authored text, tables and figures: CC BY 4.0 (SPDX CC-BY-4.0). Map plates print their boundary source and licence. | |
B.7Formats and provenance
| Format | Kind | State | What it is | Identifier |
|---|---|---|---|---|
| Web edition | HTML | On this site | Draft in stewardship review; every value resolves to its source. | NR-XTECH-AI-GLOBAL-2026-BASELINE-v1.0.0 |
| Print edition | At release | A4 portrait · screen, print and archival PDF, signed with the web edition at release. | NR-XTECH-AI-GLOBAL-2026-BASELINE-v1.0.0 | |
| Indicator data | CSV · JSON | On this site | 15 indicators with unit, year, status and source; the machine-readable copy ships with the evidence bundle at release. | NR-XTECH-AI-GLOBAL-2026-BASELINE data release v1 |
| Figures | SVG · PNG | On this site | 4 on the web edition: headline figure, figure 1.3, coupling instrument, capability ladder. | FIG-XTECH-AI-GLOBAL-2026-BASELINE-* |
| Slides | Not recorded | No slide deck is recorded for this edition. | ||
| Evidence brief | HTML · PDF | Not recorded | No evidence brief is recorded for this edition. | |
| Dataset with DOI | DataCite | At release | Concept and version DOI are minted at deposit; none is recorded yet. |
Provenance
- Edition pack
- The edition’s content pack (JSON), from which the print and web editions are built
- Evidence cut
- DC-XTECH-AI-GLOBAL-2026-B0, closed 30 September 2026
- Reproducibility
- sourced values cited; analytical values reproducible from stated parameters
- Self-check
- 14 of 23 at evidence close; a fail on any item blocks release
- Review
- five passes scheduled before release
- Publisher of record
- The Global Centre for Risk and Innovation (GCRI) for the Nexus Consortium
- Corrections
- Registry correction pathway; upheld corrections are published as notices with a new version
Notes
Numbers are the edition’s reference numbers, so a note reads the same in every chapter. The full list, with every source and its licence, is in Annex C. Annex C, references
- 1International Energy Agency (ed.), Energy and AI. World Energy Outlook Special Report. IEA, Paris, 2025.back
- 15A. Shehabi, S. J. Smith, A. Hubbard et al., 2024 United States Data Center Energy Usage Report. Lawrence Berkeley National Laboratory, Berkeley, CA, December 2024.back
- 14J. Sevilla and E. Roldán, “Training compute of frontier AI models grows by 4–5x per year.” Epoch AI, 2024.back
- 2Stanford Institute for Human-Centered Artificial Intelligence (ed.), Artificial Intelligence Index Report 2025. Stanford HAI, Stanford, 2025.back
- 17Semiconductor Industry Association and Boston Consulting Group (eds.), Strengthening the Global Semiconductor Supply Chain in an Uncertain Era. SIA and BCG, Washington, DC, 2021.back
- 16M. Cazzaniga, F. Jaumotte, L. Li et al., “Gen-AI: Artificial Intelligence and the Future of Work,” IMF Staff Discussion Note SDN/2024/001. IMF, Washington, DC, 2024.back
- 32International Labour Organization (ed.), Generative AI and Jobs: A Refined Global Index of Occupational Exposure. ILO, Geneva, 2025.back
- 20World Economic Forum (ed.), Future of Jobs Report 2025. WEF, Cologny/Geneva, January 2025.back
- 34ITU (ed.), Measuring Digital Development: Facts and Figures 2024. International Telecommunication Union, Geneva, 2024.back
- 3Y. Bengio (ed.), International AI Safety Report. Department for Science, Innovation and Technology, London, January 2025.back
- 18International Energy Agency (ed.), Global Critical Minerals Outlook 2025. IEA, Paris, 2025.back
- 27Responsible AI Collaborative (ed.), AI Incident Database. incidentdatabase.ai, retrieved 2026-09-30.back
- 28OECD (ed.), OECD AI Incidents and Hazards Monitor. OECD.AI, retrieved 2026-09-30.back
- 33UNCTAD (ed.), Technology and Innovation Report 2025: Inclusive Artificial Intelligence for Development. UNCTAD, Geneva, 2025.back
- 4European Parliament and Council of the European Union (eds.), Regulation (EU) 2024/1689 laying down harmonised rules on artificial intelligence (Artificial Intelligence Act). Official Journal L, 12 July 2024, as amended.back
- 29U.S. Department of Commerce, Bureau of Industry and Security (ed.), Implementation of additional export controls: certain advanced computing and semiconductor manufacturing items. Federal Register, October 2022, as updated.back