Why Do Decision Makers (Not) Use AI? A Cross-Domain Analysis of Factors Impacting AI Adoption

TL;DR

This study explores why decision-makers in medicine, law, journalism, and the public sector choose to adopt or reject AI tools, highlighting key influencing factors and providing practical guidance for responsible AI deployment.

Contribution

It introduces a cross-domain analysis of decision-maker factors affecting AI adoption and develops an AI adoption sheet for better understanding and support of deployment decisions.

Findings

Decision-maker background influences AI adoption decisions.

Perceptions of AI impact stakeholder relationships.

Cross-domain factors explain differences in AI adoption rates.

Abstract

Growing excitement around deploying AI across various domains calls for a careful assessment of how human decision-makers interact with AI-powered systems. In particular, it is essential to understand when decision-makers voluntarily choose to consult AI tools, which we term decision-maker adoption. We interviewed experts across four domains -- medicine, law, journalism, and the public sector -- to explore current AI use cases and perceptions of adoption. From these interviews, we identify key factors that shape decision-maker adoption of AI tools: the decision-maker's background, perceptions of the AI, consequences for the decision-maker, and perceived implications for other stakeholders. We translate these factors into an AI adoption sheet to analyze how decision-makers approach adoption choices through comparative, cross-domain case studies, highlighting how our factors help explain inter-domain differences in adoption. Our findings offer practical guidance for supporting the responsible and context-aware deployment of AI by better accounting for the decision-maker's perspective.