Exploring the factors, affordances and constraints outlining the implementation of Artificial Intelligence in public sector organizations

Artificial Intelligence (AI) is viewed as having great potential for the public sector, to improve the management of internal activities and the delivery of public services. However, the fulfillment of its potential depends on the proper implementation of the technology, characterized by unique factors, that afford or constraints its use. What these factors are and how they affect AI implementation is still poorly understood, and scholars call for studies to expand our knowledge through empirical evidence. This study relies on a case study methodology and, by adopting an abductive approach, it applies a double theoretical perspective: the Technology-Organization-Environment (TOE) framework and Technology Affordance and Constraints Theory. The findings identify several factors that are unique to AI implementation and characterize each of these factors in terms of how they afford and constraint AI implementation. We also argue that factors, affordances, and constraints vary due to the type of AI technology, the characteristic of the service, and the organization. The list of factors and the discussion of the implications of the findings for research and practice are presented in the paper, shedding light on the complex path that public organizations are now taking to exploit the potential of AI systems.

GIULIA Maragno;  TANGI Luca;  GASTALDI Luca;  BENEDETTI Michele; 

2023-08-22

ELSEVIER SCI LTD

JRC134086

0268-4012 (online),   

https://www.sciencedirect.com/science/article/pii/S0268401223000671,    https://publications.jrc.ec.europa.eu/repository/handle/JRC134086,   

10.1016/j.ijinfomgt.2023.102686 (online),