Overcoming the Challenges of Collaboratively Adopting Artificial Intelligence in the Public Sector

Averill Campion, Mila Gasco-Hernandez, Slava Jankin Mikhaylov, Marc Esteve

Research output: Indexed journal article Articlepeer-review

42 Citations (Scopus)

Abstract

Despite the current popularity of artificial intelligence (AI) and a steady increase in publications over time, few studies have investigated AI in public contexts. As a result, assumptions about the drivers, challenges, and impacts of AI in government are far from conclusive. By using a case study that involves a large research university in England and two different county councils in a multiyear collaborative project around AI, we study the challenges that interorganizational collaborations face in adopting AI tools and implementing organizational routines to address them. Our findings reveal the most important challenges facing such collaborations: a resistance to sharing data due to privacy and security concerns, insufficient understanding of the required and available data, a lack of alignment between project interests and expectations around data sharing, and a lack of engagement across organizational hierarchy. Organizational routines capable of overcoming such challenges include working on-site, presenting the benefits of data sharing, reframing problems, designating joint appointments and boundary spanners, and connecting participants in the collaboration at all levels around project design and purpose.

Original languageEnglish
Pages (from-to)462-477
Number of pages16
JournalSocial Science Computer Review
Volume40
Issue number2
DOIs
Publication statusPublished - Apr 2022

Keywords

  • adoption of AI
  • challenges of AI
  • interorganizational collaboration
  • organizational routines
  • public sector

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