Policy brief

What is holding back artificial intelligence adoption in Europe?

To accelerate the roll-out of AI technology across the European Union, policymakers should alleviate constraints to adoption faced by firms, both in t

Publishing date
30 November 2021

Artificial intelligence (AI) is considered a key driver of future economic development, expected to increase labour productivity and economic growth worldwide. To realise these gains, AI technologies need to be adopted by companies and integrated into their operations. However, it is unclear what the current level of AI adoption by European firms actually is. Estimates vary widely because of uneven data collection and lack of a standard definition and taxonomy of AI.

What is clear is that AI adoption in Europe is low and likely running behind other parts of the world. Discussions on the barriers to AI advancement often mix up different stages of innovation – research, development and adoption. Each stage is constrained by the availability of skills, data and financing in the European market, but there are nuances in how these barriers arise in each of the three stages.

This policy contribution focuses on the final stage, AI adoption. We discuss theoretical and empirical evidence of the drivers of AI adoption. We outline the relevant barriers to adoption for European firms in terms of human capital, data availability and funding, and make international comparisons where possible.

To accelerate the roll-out of AI technology across the European Union, policymakers should alleviate constraints to adoption faced by firms, both in the environmental context – labour market, financial market and regulation – and in the technological context – data availability, basic digitisation of businesses and technological uncertainty.

 

Recommended citation
Hoffmann, M. and L. Nurski (2021) ‘What is holding back artificial intelligence adoption in Europe?' Policy Contribution 24/2021, Bruegel

This policy contribution was produced within the project “Future of Work and Inclusive Growth in Europe“, with the financial support of the Mastercard Center for Inclusive Growth.

About the authors

  • Mia Hoffmann

    Mia worked at Bruegel as a Research Analyst. She studied International Economics (BSc) at University of Tuebingen, including one semester at the Università di Torino, and holds a Master’s degree in Economics from Lund University.

    Before joining Bruegel Mia worked in the international development sector. As a Bluebook Trainee she worked at the European Commission’s Directorate-General for International Cooperation and Development and previously interned at the German development bank DEG, working on credit analysis and restructuring.

    Her previous research focused on the impact of migration on economic growth and analyzed the effects of childcare policy on household bargaining. Her current research interests involve issues related to trade, labor markets and inequality.

    Mia is a German native speaker, is fluent in English and has good working knowledge in French and Italian.

  • Laura Nurski

    Laura Nurski leads the Future of Work and Inclusive Growth project which analyses the impact of technology on the nature, quantity and quality of work, welfare systems and inclusive growth.

    Before joining Bruegel, she investigated the impact of job design and organisation design on wellbeing and productivity at work. This inherently multidisciplinary domain has left her with a broad social science background, encompassing psychology, sociology and economics.

    Laura is passionate about data and technology. As a former data scientist in the financial and retail sector, she developed machine learning models and big data analytics. She is also a skilled statistical programmer, survey developer and open-source aficionado.

    Laura holds a Ph.D. in Industrial Organization, a M.Sc. in Economics and a M.A. in Business Engineering from KU Leuven.

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