The Proof Is in the Eating: Lessons Learnt from One Year of Generative AI Adoption in a Science-for-Policy Organisation
This paper presents the key results of a large-scale empirical study on the adoption of Generative AI (GenAI) by the Joint Research Centre (JRC), the European Commission’s science-for-policy department. Since spring 2023, the JRC has developed and deployed GPT@JRC, a platform providing safe and comp...
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| Format: | Article |
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MDPI AG
2025-06-01
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| Series: | AI |
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| Online Access: | https://www.mdpi.com/2673-2688/6/6/128 |
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| author | Bertrand De Longueville Ignacio Sanchez Snezha Kazakova Stefano Luoni Fabrizio Zaro Kalliopi Daskalaki Marco Inchingolo |
| author_facet | Bertrand De Longueville Ignacio Sanchez Snezha Kazakova Stefano Luoni Fabrizio Zaro Kalliopi Daskalaki Marco Inchingolo |
| author_sort | Bertrand De Longueville |
| collection | DOAJ |
| description | This paper presents the key results of a large-scale empirical study on the adoption of Generative AI (GenAI) by the Joint Research Centre (JRC), the European Commission’s science-for-policy department. Since spring 2023, the JRC has developed and deployed GPT@JRC, a platform providing safe and compliant access to state-of-the-art Large Language Models for over 10,000 knowledge workers. While the literature highlighting the potential of GenAI to enhance productivity for knowledge-intensive tasks is abundant, there is a scarcity of empirical evidence on impactful use case types and success factors. This study addresses this gap and proposes the JRC GenAI Compass conceptual framework based on the lessons learnt from the JRC’s GenAI adoption journey. It includes the concept of AI-IQ, which reflects the complexity of a given GenAI system. This paper thus draws on a case study of enterprise-scale AI implementation in European public institutions to provide approaches to harness GenAI’s potential while mitigating the risks. |
| format | Article |
| id | doaj-art-e8c414a532b84c33b17ecfaefe33c1b0 |
| institution | Matheson Library |
| issn | 2673-2688 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | AI |
| spelling | doaj-art-e8c414a532b84c33b17ecfaefe33c1b02025-06-25T13:21:11ZengMDPI AGAI2673-26882025-06-016612810.3390/ai6060128The Proof Is in the Eating: Lessons Learnt from One Year of Generative AI Adoption in a Science-for-Policy OrganisationBertrand De Longueville0Ignacio Sanchez1Snezha Kazakova2Stefano Luoni3Fabrizio Zaro4Kalliopi Daskalaki5Marco Inchingolo6European Commission—Joint Research Centre, CDMA Building, 21 Rue du Champ de Mars/Marsveldstraat 21, B-1050 Brusselss, BelgiumEuropean Commission—Joint Research Centre, Via Enrico Fermi 2749, I-21027 Ispra, VA, ItalyEuropean Commission—Joint Research Centre, CDMA Building, 21 Rue du Champ de Mars/Marsveldstraat 21, B-1050 Brusselss, BelgiumEuropean Commission—Joint Research Centre, Via Enrico Fermi 2749, I-21027 Ispra, VA, ItalyEuropean Commission—Joint Research Centre, Via Enrico Fermi 2749, I-21027 Ispra, VA, ItalyEuropean Commission—Joint Research Centre, CDMA Building, 21 Rue du Champ de Mars/Marsveldstraat 21, B-1050 Brusselss, BelgiumEuropean Commission—Joint Research Centre, CDMA Building, 21 Rue du Champ de Mars/Marsveldstraat 21, B-1050 Brusselss, BelgiumThis paper presents the key results of a large-scale empirical study on the adoption of Generative AI (GenAI) by the Joint Research Centre (JRC), the European Commission’s science-for-policy department. Since spring 2023, the JRC has developed and deployed GPT@JRC, a platform providing safe and compliant access to state-of-the-art Large Language Models for over 10,000 knowledge workers. While the literature highlighting the potential of GenAI to enhance productivity for knowledge-intensive tasks is abundant, there is a scarcity of empirical evidence on impactful use case types and success factors. This study addresses this gap and proposes the JRC GenAI Compass conceptual framework based on the lessons learnt from the JRC’s GenAI adoption journey. It includes the concept of AI-IQ, which reflects the complexity of a given GenAI system. This paper thus draws on a case study of enterprise-scale AI implementation in European public institutions to provide approaches to harness GenAI’s potential while mitigating the risks.https://www.mdpi.com/2673-2688/6/6/128Artificial IntelligenceGenerative AILarge Language ModelsLLMsAI governanceorganisational transformation |
| spellingShingle | Bertrand De Longueville Ignacio Sanchez Snezha Kazakova Stefano Luoni Fabrizio Zaro Kalliopi Daskalaki Marco Inchingolo The Proof Is in the Eating: Lessons Learnt from One Year of Generative AI Adoption in a Science-for-Policy Organisation AI Artificial Intelligence Generative AI Large Language Models LLMs AI governance organisational transformation |
| title | The Proof Is in the Eating: Lessons Learnt from One Year of Generative AI Adoption in a Science-for-Policy Organisation |
| title_full | The Proof Is in the Eating: Lessons Learnt from One Year of Generative AI Adoption in a Science-for-Policy Organisation |
| title_fullStr | The Proof Is in the Eating: Lessons Learnt from One Year of Generative AI Adoption in a Science-for-Policy Organisation |
| title_full_unstemmed | The Proof Is in the Eating: Lessons Learnt from One Year of Generative AI Adoption in a Science-for-Policy Organisation |
| title_short | The Proof Is in the Eating: Lessons Learnt from One Year of Generative AI Adoption in a Science-for-Policy Organisation |
| title_sort | proof is in the eating lessons learnt from one year of generative ai adoption in a science for policy organisation |
| topic | Artificial Intelligence Generative AI Large Language Models LLMs AI governance organisational transformation |
| url | https://www.mdpi.com/2673-2688/6/6/128 |
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