From FAT to value: building competence through fairness, accountability and transparency for sustainable business

Abstract

Purpose The aim of this paper is to investigate how core characteristics of artificial intelligence (AI), including fairness, accountability and transparency (FAT), contribute to sustainable business value creation. Design/methodology/approach The data were collected through a survey of 572 respondents who reported AI awareness and workplace exposure to AI. A covariance-based structural equation modeling (CB-SEM) approach was used to test the hypothesized relationships. Findings The empirical results show that FAT principles significantly strengthen AI-enabled business models, which in turn build AI-driven competence. This competence positively influences both sustainable business value and digital well-being. Mediation tests confirm that AI-driven competence partly mediates the link between AI-enabled business models and these outcomes, while leadership support further amplifies competence's effect on both value creation and digital well-being. Originality/value AI is often seen as a driver of organizational sustainable competitive advantage, but its impact is not uniformly positive. When poorly governed or lacking transparency and fairness, AI can undermine both performance and social outcomes. This study addresses this paradox by arguing that sustainable benefits stem from building AI-driven competence, not merely increasing adoption or investment. It advances knowledge by (1) linking responsible AI principles of FAT with dynamic capabilities theory to clarify how AI creates organizational and societal value, (2) presenting the AI-enabled business model as the bridge that translates technical features into repeatable, scalable processes and (3) identifying leadership support as a key factor that ensures AI competence effectively delivers both performance gains and social responsibility.