Google ATLAS Reports Global AI Use Patterns and Scientist Time Savings

ATLAS data show India's creative industry uses AI at a higher rate than the rest of the world, with arts, design, and media occupations accounting for 19 percent of work-related AI usage, 1.6 times the global average. The United States leads in technical AI adoption, with computer and mathematical occupations accounting for 30 percent of work-related AI usage, double the share in the rest of the world.

Google said the new tool allows users to examine AI use rates by occupation, from electricians to purchasing managers, explore how people use AI at home, and compare adoption rates across countries.

The ATLAS findings also show regional differences by profession. In OECD countries, computer and mathematical occupations and business and financial operations lead in AI usage. In non-OECD countries, office and administrative support; arts, design, entertainment, sports, and media; and educational instruction and library occupations take the top spots.

AI adoption generally correlates with a country's income level, but Brazil and the United Arab Emirates stand out with higher adoption rates than their GDP per capita would predict, according to the post. Use of AI for manual tasks such as real-time equipment diagnostics and troubleshooting varies by region. Brazil and Germany direct 7 percent of work AI usage toward manual tasks, 1.4 times the global average, compared with 4 percent in Japan.

The new scientific research draws on ATLAS data, an analysis of 2,600 specialized AI models, and a survey of more than 600 scientists in the United States and the United Kingdom. It uses a taxonomy from MIT FutureTech that maps what scientists do. The research says scientists use AI at a higher rate than many other occupations, with nearly half of surveyed scientists using some form of AI every day.

Scientists use both specialized models and large language models, the research says, and the two are applied in mutually reinforcing ways. LLMs such as Gemini are used widely across scientific fields and task categories, while specialized AI models are relatively more common in health and life sciences and in domain-specific data prediction, generation, and simulation tasks.

Scientists report saving just under seven hours a week with AI, freeing time for more research. The research also finds evidence of significant time spent validating AI outputs, an increased backlog of hypotheses yet to be tested, and bottlenecks in areas such as physical experimentation and clinical validation. Google said science is similar to most other occupations: AI offers significant potential to increase productivity, but large-scale impact on outputs and discoveries may require redesigning scientific processes and workflows.

Google said many questions about the future of AI and the economy remain. It described ATLAS as a long-term research project and said it will work with partners in academia and elsewhere to identify new areas of research and deliver insights into how AI is transforming the economy.