Responsible AI in Business: Business Ethics, Epistemic Risk, and Governance in the Generative AI Era

Responsible AI in Business reframes the ethics of generative AI as a problem of organizational design and governance engineering. Rather than treating "trustworthy AI" as a set of abstract principles, the book argues that responsibility is enacted through standards, controls, documentation, evaluation, procurement, and assurance—mechanisms that decide what counts as evidence, whose concerns are actionable, and which trade-offs organizations accept. It develops an ethical and epistemic framework for enterprise GenAI, including inductive bias as corporate architecture, truth and justification in AI-mediated decision-making, governance of data sources (privacy, copyright, retrieval), fairness and value trade-offs, and transparency and provenance for synthetic content. The book concludes with a practical operating model for institutionalizing Responsible GenAI, integrating emerging regulatory expectations and management-system approaches into audit-ready, capability-based governance.