The Impact of Artificial Intelligence on Corporate Governance: Focusing on Three Critical Accountability Gaps and Strategies to Strengthen Board Oversight

Ghasemi, Maziar; Jafarpour Jalali, Mohammad

doi:10.22034/apj.2026.2090422.1066

The Impact of Artificial Intelligence on Corporate Governance: Focusing on Three Critical Accountability Gaps and Strategies to Strengthen Board Oversight

Document Type : Review Paper

Authors

Maziar Ghasemi ¹

Mohammad Jafarpour Jalali ²

¹ Department of Management, Adiban Garmsar Institute of Higher Education, Garmsar, Semnan, Iran

² Department of Electrical Engineering, Adiban Garmsar Institute of Higher Education, Garmsar, Semnan, Iran

10.22034/apj.2026.2090422.1066

Abstract

The integration of artificial intelligence into strategic decision-making processes enhances accuracy, speed, and efficiency; however, it simultaneously introduces unprecedented challenges to the traditional accountability framework within corporate governance. Employing a critical analytical approach and drawing upon findings from authoritative research in the fields of artificial intelligence and corporate governance, this article argues that existing legal and ethical systems are ill-prepared to address three structural gaps arising from algorithmic decision-making at the board level.
Accountability is defined as a tripartite relationship among an agent, the board of directors, and the general assembly of shareholders, wherein the agent is obligated to justify and explain their conduct, while the assembly holds the authority to question, judge, evaluate performance, decide on the continuation of cooperation, and take legal action if necessary. The first gap concerns the absence of a clear rule for determining responsibility when AI systems make errors, as responsibility is a "bundle" concept comprising multiple components, and merely attributing it cannot resolve ethical dilemmas. This gap manifests acutely in augmented intelligence and reinforcement learning contexts. The second gap involves the lack of a mechanism to monitor the board itself in its capacity as the overseer of AI systems—referred to herein as the "monitor of the monitor" dilemma. The third gap stems from the temporal misalignment between board decision-making cycles and AI system processing speeds, which undermines effective oversight and timely accountability.
This study proposes three policy-oriented solutions: the non-delegable rule of ultimate human responsibility; the establishment of a specialized AI committee within the board, endowed with continuous auditing authority; and the redefinition of fiduciary duty such that algorithmic literacy and oversight over the lifecycle of AI models become integral components of directors' legal responsibilities. These three solutions are analyzed within the framework of accountability's four objectives: compliance, reporting, monitoring, and enforcement.

Keywords

Artificial Intelligence

Corporate Governance

Board of Directors

Accountability Gap

Algorithmic Decision-Making

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