Effective Adoption and Implementation of AI Principles

Abstract

The study examines employee perceptions on the adoption and implementation of artificial intelligence (AI) principles in organizations. 49 interviews were conducted with employees of 24 organizations, across 11 countries. Participants all worked directly with AI and represented a range of positions from junior data scientist to Chief Analytics Officer. The study found that there are eleven components that could impact the effective adoption and implementation of AI principles in organizations: communication, management support, training, ethics office(r), reporting mechanism, enforcement, measurement, accompanying technical processes, sufficient technical infrastructure, organizational structure, and an interdisciplinary approach. The components are discussed in the context of the research on business code effectiveness. The findings offer a first step in understanding the impact of adoption and implementation on the effectiveness of AI principles in organizations. They suggest that simply having AI principles will not be enough to prevent unethical AI outcomes but that several adoption and implementation components uncovered in the study could help address this.