59%
of organisations named knowledge and training gaps a main obstacle to implementing responsible AI in 2025, up from 51% in 2024

What the chart shows

Knowledge and training gaps were the obstacle to implementing responsible AI measures that organisations named most often in both years: 59% in 2025, up from 51% in 2024. Resource or budget constraints came second at 48% (45% in 2024).

Technical limitations rose from 32% to 38%, and regulatory uncertainty held steady at 41% (40%). Lack of executive support was the least cited obstacle, falling from 16% to 14%.

Key numbers

MeasureValue
Knowledge and training gaps, 202559%
Knowledge and training gaps, 202451%
Resource or budget constraints, 202548%
Regulatory uncertainty, 202541%
Technical limitations, 202538%
Technical limitations, 202432%

How to read it

  • Survey of business leaders by the AI Index and McKinsey & Company in 2024 and 2025, across several regions and industries; it has no respondents from China.
  • Respondents could name several obstacles, so shares add up to more than 100%.
  • ‘Other’ (2% in 2024, 0% in 2025) is not shown; the data file labels both ‘Other’ rows 2024, and the report’s chart shows the second as 2025. The report also leaves out ‘Unknown’ and ‘None’.
Source: McKinsey & Company Survey, 2025, via the AI Index Report 2026 (Stanford HAI), figure 3.3.9: Main obstacles to the implementation of responsible AI measures, 2024 vs. 2025. Chart and text by AI Adoption.
Numbers checked against the published data on 20 October 2026.
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