EY Ripples published this survey of 2,515 people aged 60 to 85 across 16 countries, conducted between October 29 and November 13, 2025. Named contributors include Gillian Hinde (EY Global Corporate Responsibility Leader), Alex Glazebrook (OATS from AARP), Gina Neff (Minderoo Centre for Technology and Democracy, University of Cambridge), Takashi Maeno (Professor Emeritus, Keio University), and Lisa Reppell (Microsoft). The report, Understanding Older Generations’ Adoption of AI, covers five regions: North America, Latin America, Europe, Asia-Pacific, and the Middle East, Africa and India. The survey was conducted online; the authors acknowledge this may overrepresent older adults who are already digitally active.
About 40% of respondents have never used AI or have tried it only once or twice. Around 21% use it multiple times per week or almost daily. Among Baby Boomers, 24% describe themselves as quite or very familiar with AI; 38% are actively learning about it through online resources, videos, and social media; only 15% expressed no interest in learning.
When respondents do use AI, reported experience is largely positive. Among those who tried AI tools, 79% cited learning as their top use case. Health and everyday tasks ranked next. Among respondents still working, 84% reported positive experiences using AI at work; creative uses drew 80% positive ratings.
Employment status is the strongest predictor of usage. Respondents still working use AI at roughly three times the rate of retired respondents. A gender gap is also present: 31% of women report never having used AI, compared to 20% of men.
Barriers: data privacy concerns (41%), not knowing which tools to use (34%), not knowing where to start (23%), not seeing personal relevance (20%), lack of support (19%), tools too difficult (17%), cost (11%), device access (5%), physical limitations (4%). Nineteen percent report no barriers. Eighty percent of respondents agree that not everything produced by AI has been checked for accuracy.
EY frames the policy challenge as a “just transition” and calls for age-appropriate AI literacy programmes in libraries, adult education centres, and healthcare settings, alongside accessible and lower-cost tools. The report does not quantify the cost of inaction or model the reach of proposed literacy programmes.
Relevance to the AI Gap thesis: The EY survey is the first large-scale evidence base for age as a distinct axis of AI exclusion. The 40% non-usage rate among people aged 60 to 85 is driven primarily by structural factors — lack of suitable access points, support, and guidance — rather than by resistance. The employment-status gap (3x usage differential) indicates that retirement removes the primary mechanism through which most adults currently acquire AI skills. The data directly supports the case for publicly funded adult AI literacy programmes (scoring dimensions 1 and 4) and for inclusion policies that extend beyond gender and socioeconomic status to cover age and employment status (dimensions 10 and 11).