# How Early Adopters Used Generative AI Worldwide: Variation by Country Income and Language

arXiv: https://arxiv.org/abs/2605.30685 · HTML: https://mlsanity.com/paper/2605.30685/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 16 of its 48 references that are in the map.
- First posted on arXiv 29 May 2026.

## Builds on (most cited first, 16 of 16)

- [Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference](https://mlsanity.com/paper/2403.04132/) (2024)
- [The State and Fate of Linguistic Diversity and Inclusion in the NLP World](https://mlsanity.com/paper/2004.09095/) (2020)
- [WildChat: 1M ChatGPT Interaction Logs in the Wild](https://mlsanity.com/paper/2405.01470/) (2024)
- [Which Economic Tasks are Performed with AI? Evidence from Millions of Claude Conversations](https://mlsanity.com/paper/2503.04761/) (2025)
- [MMLU-ProX: A Multilingual Benchmark for Advanced Large Language Model Evaluation](https://mlsanity.com/paper/2503.10497/) (2025)
- [All Languages Matter: Evaluating LMMs on Culturally Diverse 100 Languages](https://mlsanity.com/paper/2411.16508/) (2024)
- [Investigating Affective Use and Emotional Well-being on ChatGPT](https://mlsanity.com/paper/2504.03888/) (2025)
- [Using Large Language Models to Generate, Validate, and Apply User Intent Taxonomies](https://mlsanity.com/paper/2309.13063/) (2023)
- [The Adoption and Usage of AI Agents: Early Evidence from Perplexity](https://mlsanity.com/paper/2512.07828/) (2025)
- [Gender, Age, and Technology Education Influence the Adoption and Appropriation of LLMs](https://mlsanity.com/paper/2310.06556/) (2023)
- [Please Translate Again: Two Simple Experiments on Whether Human-Like Reasoning Helps Translation](https://mlsanity.com/paper/2506.04521/) (2025)
- [Shifting Work Patterns with Generative AI](https://mlsanity.com/paper/2504.11436/) (2025)
- [Measuring AI Diffusion: A Population-Normalized Metric for Tracking Global AI Usage](https://mlsanity.com/paper/2511.02781/) (2025)
- [Characteristics of ChatGPT users from Germany: implications for the digital divide from web tracking data](https://mlsanity.com/paper/2309.02142/) (2023)
- [The Emerging Generative Artificial Intelligence Divide in the United States](https://mlsanity.com/paper/2404.11988/) (2024)
- [AI Diffusion in Low Resource Language Countries](https://mlsanity.com/paper/2511.02752/) (2025)

## Abstract (arXiv)

AI is being used by people globally, but not everyone is using it in the same ways. Using a large-scale dataset of anonymized, de-identified, and privacy-scrubbed interactions with a widely available and free AI chatbot, we empirically characterize differences in early adopters' usage across countries. Schooling is the most common domain of use in most countries, particularly low-income countries, with a strong inverse association evident between schooling and country-level GDP. Leisure-related use, by contrast, is positively associated with country-level income. Language, we find, also shapes use: English-language interactions are overrepresented in places where the predominant languages were not well-served by existing models during the period of the study. Improving performance across languages may be a key factor, our work suggests, in whether this technology expands digital divides or enables leapfrogging.