THE ADOPTION of ARTIFICIAL INTELLIGENCE IN FIRMS

New Evidence for Policymaking

by OECD/BCG/INSEAD (2025)

This study combines several types of data and information to explore the adoption of artificial intelligence (AI) in enterprises and how governments can support this. The core of the study is a policy-oriented survey of 840 enterprises implemented in the Group of Seven (G7) countries – the 2022-23 OECD/BCG/INSEAD Survey of AI-Adopting Enterprises - plus 167 enterprises in Brazil. The survey includes novel questions on topics such as enterprises’ views on the value of public policies relevant to AI uptake, and their priorities for future AI policy. Other novel questions seek information on familiar topics, such as enterprises’ use of cloud computing, but with new emphases – such as probing why cloud computing, an important adjunct to AI, might be underutilised. Complementing the survey, this book also contains studies of public sector institutions that help technology diffusion, along with interviews with enterprises.

Achieving higher rates of AI adoption could raise labour productivity and have other desirable outcomes, such as lower defect rates in production, reducing the need for material inputs. Policy insights from this and other comparable studies will likely become more important as more enterprises seek to become active users of AI.

It is widely reported that a scarcity of skills – particularly specialised talent – hinders AI uptake, even in many large firms. This study shows that policies and programmes to develop human capital are among the most valued and used by businesses. Many enterprises express a desire to better understand how to identify and use the right AI skills. However, academic certifications may not provide all the information employers seek. Updated qualification frameworks could help. Public sector providers should collaborate with industry to design relevant training materials, and training programmes should be tailored to industry or business-specific needs (such as using AI to optimise supply chain management). Training on real-world projects, using AI systems and datasets common in specific areas of business, is particularly valuable.

Source: OECD/BCG/INSEAD (2025), The Adoption of Artificial Intelligence in Firms: New Evidence for Policymaking, OECD Publishing, Paris, https://doi.org/10.1787/f9ef33c3-en.

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