India's creative professionals are adopting AI at a rate 1.6 times the global average, according to new data from Google's AI & Economy ATLAS. Arts, design and media occupations account for 19% of all work-related AI use in the country, putting the sector ahead of most other professions in AI adoption.
The interactive platform, which Google launched as an open-access tool, tracks AI usage across occupations and countries. It reveals sharp differences in how artificial intelligence is being put to work depending on where you look. In the United States, computer and mathematical occupations dominate, making up 30% of work-related AI use - twice the global share.
The pattern shifts again when comparing richer and developing economies. Across OECD countries, computer, mathematical, business and financial operations lead AI adoption. In non-OECD nations, office and administrative support, education, library roles, and creative fields such as arts, design, entertainment and media take larger shares.
AI's footprint in physical and manual work
The ATLAS data also captures AI use beyond desk jobs. In Brazil and Germany, 7% of work-related AI usage connects to real-time equipment diagnostics and troubleshooting - 1.4 times the global average. Japan records 4% in the same category. Brazil and the UAE both show adoption levels that exceed what their GDP per capita would predict.
Google said it plans to work with academic and other partners to expand the research. The ATLAS project is intended to track how AI adoption changes work and the wider economy over time.
Scientists save hours but hit validation bottlenecks
Separate research from Google, Google DeepMind and MIT FutureTech examined how scientists are using AI. The study analysed 2,600 specialised AI models and surveyed more than 600 scientists in the U.S. and U.K. Nearly half said they use some form of AI every day.
Scientists reported saving just under seven hours a week through AI tools. Large language models such as Gemini are used across disciplines for a broad range of tasks, while specialised models appear more often in health and life sciences for domain-specific prediction, generation and simulation.
Those hours saved are being redirected into research, but the productivity gains do not automatically produce more discoveries. Scientists still spend substantial time checking AI-generated results. The faster pace of idea generation is also creating a growing backlog of hypotheses waiting to be tested. Physical experimentation and clinical validation are emerging as particular bottlenecks, and Google's research partners said converting AI's gains into larger scientific output may require changes to existing research workflows.
Why this matters for creatives
The 19% figure from India is not an outlier - it signals that creative fields are early and active adopters of AI tools globally. For designers, artists and media professionals, AI is already part of daily workflows, from generative art to content production. The ATLAS data confirms that adoption in creative occupations is not waiting for permission. It is happening, and the gap between those using AI and those who are not will shape hiring, freelance rates and project budgets in the near term. For anyone in a creative role, familiarity with AI for creatives is moving from optional to expected.
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