License & Attribution — GAIA: Global AI Adoption Index

License

GAIA Copyright & License

CC BY 4.0

© 2026 Leila Aghabarari. The GAIA (Global AI Adoption Index) dataset, composite scores, country panel, and associated documentation are licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).

You are free to share (copy and redistribute in any medium or format) and adapt (remix, transform, and build upon the material for any purpose, including commercially) — provided you give appropriate credit, include a link to the license, and indicate if changes were made.

The underlying source datasets (Anthropic Economic Index, OpenAI GPT-4 exposure ratings, Brynjolfsson SML scores) carry their own licenses and attribution requirements, detailed in the Citations section below.

Required Citations

How to Cite the Data Sources

When using GAIA data in published work, please cite GAIA itself and the underlying source(s) you draw on. APA and BibTeX formats are provided below.

1

GAIA — Global AI Adoption Index

Leila Aghabarari

Zenodo · Version 1.0 · 2026

APA

Aghabarari, L. (2026). GAIA — Global AI Adoption Index (Version 1.0). Zenodo. https://doi.org/10.5281/zenodo.20320112

BibTeX

@misc{aghabarari2026gaia,
  author    = {Aghabarari, Leila},
  title     = {{GAIA}: {G}lobal {AI} {A}doption {I}ndex},
  year      = {2026},
  version   = {1.0},
  publisher = {Zenodo},
  doi       = {10.5281/zenodo.20320112},
  url       = {https://doi.org/10.5281/zenodo.20320112}
}

2

The Anthropic Economic Index

Anthropic

Dataset · Hugging Face · 2025

APA

Anthropic. (2025). The Anthropic Economic Index [Dataset]. Hugging Face. https://huggingface.co/datasets/Anthropic/EconomicIndex

BibTeX

@misc{anthropic2025economicindex,
  author  = {{Anthropic}},
  title   = {The {A}nthropic {E}conomic {I}ndex},
  year    = {2025},
  url     = {https://huggingface.co/datasets/Anthropic/EconomicIndex},
  note    = {Observed Claude.ai task-level usage data aggregated
             by occupation and country}
}

3

GPTs are GPTs: Labor market impacts of language models

Tyna Eloundou · Sam Manning · Pamela Mishkin · Daniel Rock

Science · Vol. 384 · 2024

APA

Eloundou, T., Manning, S., Mishkin, P., & Rock, D. (2024). GPTs are GPTs: Labor market impacts of language models. Science, 384(6702), 1306–1311. https://doi.org/10.1126/science.adj0998

BibTeX

@article{eloundou2024gpts,
  author  = {Eloundou, Tyna and Manning, Sam and Mishkin, Pamela
             and Rock, Daniel},
  title   = {{GPT}s are {GPT}s: {L}abor market impacts of language models},
  journal = {Science},
  year    = {2024},
  volume  = {384},
  number  = {6702},
  pages   = {1306--1311},
  doi     = {10.1126/science.adj0998}
}

4

What Can Machines Learn, and What Does It Mean for Occupations and the Economy?

Erik Brynjolfsson · Tom Mitchell · Daniel Rock

NBER Working Paper 24196 · 2018

APA

Brynjolfsson, E., Mitchell, T., & Rock, D. (2018). What can machines learn, and what does it mean for occupations and the economy? (NBER Working Paper No. 24196). National Bureau of Economic Research. https://doi.org/10.3386/w24196

BibTeX

@techreport{brynjolfsson2018sml,
  author      = {Brynjolfsson, Erik and Mitchell, Tom and Rock, Daniel},
  title       = {What Can Machines Learn, and What Does It Mean
                 for Occupations and the Economy?},
  institution = {National Bureau of Economic Research},
  year        = {2018},
  type        = {Working Paper},
  number      = {24196},
  doi         = {10.3386/w24196}
}

Terms of Use

What You May Do with GAIA Data

✓

Permitted uses

Academic research and peer-reviewed publication
Educational use in courses and curricula
Policy analysis and non-profit reporting
Journalism and data visualization
Building derivative datasets with attribution

!

Required with all uses

Cite GAIA and applicable upstream sources
Link to gaiaindex.org or the license
Indicate if data was modified or subsetted
Do not imply endorsement by the author or IFC/World Bank

✕

Requires prior permission

Commercial products or SaaS platforms
Redistribution as a standalone commercial dataset
Integration into proprietary indices for sale
Use in ways that violate upstream source terms

Suggested attribution text

"Data from the GAIA (Global AI Adoption Index), Aghabarari, L. (2026, Version 1.0), Zenodo, https://doi.org/10.5281/zenodo.20320112, licensed under CC BY 4.0. Underlying sources: Anthropic Economic Index (Anthropic, 2025); Eloundou et al. (Science, 2024); Brynjolfsson, Mitchell & Rock (NBER WP 24196, 2018)."

Disclaimer

Views & Representations

The GAIA dataset and this website are personal research outputs. They do not represent the views, positions, or endorsement of the International Finance Corporation, the World Bank Group, or any affiliated organization.

GAIA data is derived from third-party sources (Anthropic, OpenAI, ICPSR, ILO, IMF, Gallup/OWID, OECD.Ai, Eurostat) and is provided "as is" without warranty of any kind. Users are responsible for verifying fitness for their specific purpose and for compliance with the terms of each underlying source.

Country-level usage data reflect behavioral signals from API and consumer products and should not be interpreted as representative surveys of national AI adoption.

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