Achieving the Double Bottom Line with Artificial Intelligence by Addressing Inequity: A Global Comparative Analysis of an Educational Technology Firm

Abstract

Can companies use artificial intelligence to attain the Double Bottom Line (simultaneous pursuit of financial performance and social impact) by enhancing equity? Drawing on equity theory, we develop a conceptual model whereby perceived AI quality positively affects firm performance that is mediated by equity in the educational technology sector. Using observational data collected from a global AI-powered learning app, we find support for educational equity as a full mediator between perceived AI quality and firm performance. Moreover, we also find support for conditional indirect effects. The mediating role of educational equity is moderated by political, economic, socio-cultural, and technological factors. Our research contributes to the growing popularity of transforming a business model from a bottom line to a double bottom line approach. We discuss how our study extends the IS literature on the integration between artificial intelligence and equity and the managerial implications for an inclusive information system.