Artificial intelligence in corporate boards: a dual-dimensional framework for integration across autonomy and structural levels

Abstract

This study examines the integration of artificial intelligence (AI) into corporate governance, with a specific focus on board-level decision-making. It critically evaluates five progressive stages of AI adoption—assisted, augmented, amplified, autonomous, and autopoietic—against the criteria of technological feasibility, legal compatibility, and ethical viability. Augmented intelligence has emerged as the most operationally and normatively sound model, enhancing decision quality while preserving human oversight and accountability. However, existing research has narrowly focused on the technical evolution of AI, neglecting the structural levels at which it is embedded within boards. To address this gap, this study introduces a two-dimensional framework that maps AI adoption along two intersecting axes: the degree of AI autonomy and governance locus of integration, spanning individual directors, board committees, and the full board. This model provides a more granular and context-sensitive lens for understanding how AI can be responsibly adopted within board structures. The paper concludes with governance-level-specific recommendations to ensure the ethical and effective deployment of augmented intelligence, contributing to both academic theory and policy design. By aligning conceptual insights with real-world dynamics, this study advances a context-sensitive roadmap for the ethical and effective integration of AI in corporate governance.

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