Ethical AI and Governance: A Commerce-Centric Synthesis of Principles, Standards, and Corporate Stewardship

Abstract Artificial Intelligence (AI) is now a pervasive general‑purpose technology, reshaping customer experience, operations, supply chains, and finance. These gains are shadowed by ethical risks: opaque decision‑making, bias and discrimination, privacy violations, safety/security failures, and systemic concentration risks within the AI supply chain. Modern governance is responding with principles (OECD, UNESCO), regulations (EU AI Act), management‑system standards (ISO/IEC 42001), and risk frameworks (NIST AI RMF). This paper integrates those guardrails through a commerce lens: board accountability, assurance and auditability, documentation practices (e.g., model cards and datasheets), and market‑level implications (e.g., transparency in supply chains, Indian DPDP Act compliance). I propose a practical operating model—G‑A‑M‑E (Govern–Assure–Measure–Engage)—to institutionalize ethical AI in corporations, and outline research directions for empirical testing in finance, retail, and manufacturing.