Article
Artificial Intelligence in Corporate Governance and Ethical Decision-Making
Purpose
Artificial intelligence is increasingly influencing corporate decision-making, risk monitoring, compliance, auditing, human-resource management, and strategic planning. Although artificial intelligence can strengthen the speed, consistency, and analytical capacity of corporate governance, it can also introduce algorithmic bias, limited explainability, accountability gaps, privacy risks, and ethical ambiguity. This paper examines how artificial intelligence is reshaping corporate governance and ethical decision-making and identifies the organizational and institutional conditions under which its benefits and risks may arise.
Design/methodology/approach
The paper adopts a structured conceptual-review approach. It synthesizes interdisciplinary literature on artificial intelligence, corporate governance, business ethics, algorithmic accountability, leadership, data governance, and regulatory oversight. The analysis organizes the literature around five themes: governance efficiency, algorithmic risk, board-level oversight, business-intelligence-enabled monitoring, and regulatory and stakeholder governance.
Findings
Artificial intelligence does not automatically improve or weaken corporate governance. Its effects depend on the quality of data, transparency of algorithms, digital competence of board members, ethical commitment of organizational leaders, stakeholder participation, monitoring mechanisms, and regulatory clarity. The paper proposes an integrated framework in which governance mechanisms connect artificial-intelligence capabilities with ethical and organizational outcomes. Board digital literacy, leadership commitment, data quality, organizational culture, board diversity, and the regulatory environment operate as important enabling or constraining conditions.
Research limitations/implications
The paper is conceptual and does not provide statistical tests or causal evidence. Future studies should empirically test the proposed relationships through longitudinal, comparative, experimental, case-study, and mixed-method designs.
Practical implications
Boards should establish clear responsibility for artificial-intelligence oversight, develop directors’ digital competence, conduct algorithmic audits, maintain human review of high-impact decisions, and incorporate artificial-intelligence risks into existing governance and assurance systems.
Originality/value
The paper integrates technological, ethical, organizational, and institutional perspectives into a unified framework for examining artificial intelligence in corporate governance. It also develops research propositions and a future research agenda for responsible artificial-intelligence governance.