Artificial Intelligence for the Public Sector: Opportunities and challenges of cross-sector collaboration

TL;DR

This paper explores how AI can be integrated into public sector services through cross-sector collaboration, highlighting opportunities, challenges, and strategies for effective management.

Contribution

It provides an analysis of the opportunities and challenges of AI in the public sector and proposes strategies for managing cross-sector collaborations effectively.

Findings

Cross-sector collaboration is essential for AI integration in public services.

Management challenges hinder the success of collaborative AI initiatives.

Strategies are proposed to improve collaboration effectiveness.

Abstract

Public sector organisations are increasingly interested in using data science and artificial intelligence capabilities to deliver policy and generate efficiencies in high uncertainty environments. The long-term success of data science and AI in the public sector relies on effectively embedding it into delivery solutions for policy implementation. However, governments cannot do this integration of AI into public service delivery on their own. The UK Government Industrial Strategy is clear that delivering on the AI grand challenge requires collaboration between universities and public and private sectors. This cross-sectoral collaborative approach is the norm in applied AI centres of excellence around the world. Despite their popularity, cross-sector collaborations entail serious management challenges that hinder their success. In this article we discuss the opportunities and challenges from AI for public sector. Finally, we propose a series of strategies to successfully manage these cross-sectoral collaborations.