Ethical AI Leadership
TL;DR
This mixed-methods study integrates survey data from 542 leaders across health care, finance, government, education, and nonprofits with twenty-two interviews to examine how digital literacy and ethical infrastructure shape trust in AI-mediated decision systems.
Abstract
Generative Artificial Intelligence (GenAI) is reconfiguring authority, accountability, and legitimacy in organizational leadership. This mixed-methods study integrates survey data from 542 leaders across health care, finance, government, education, and nonprofits with twenty-two interviews to examine how digital literacy and ethical infrastructure shape trust in AI-mediated decision systems. Findings show that 77% of respondents now incorporate GenAI into leadership decisions, reflecting a shift from hierarchical control to distributed, participatory orchestration. Ethics policies (β = .48, p < .001) and digital literacy (β = .42, p < .001) significantly predict trust in GenAI governance. Interview evidence demonstrates that confidence relies less on technical accuracy than on the institutionalization of ethics, transparent oversight, clear decision rights, bias audits, and mechanisms for contestation and redress. Sectoral contrasts illustrate how power shapes these safeguards, determining who is protected, who bears risk, and who can influence AI-enabled decisions. The study reframes leadership in the algorithmic age as the design of accountable, adaptive, and equitable decision architectures. Leaders who pair ethical governance with digital fluency are best positioned to sustain legitimacy and justice as GenAI becomes embedded in organizational life.