The rapid diffusion of Artificial Intelligence (AI) within organisations is reshaping how knowledge is created, processed, shared, and governed within and across firms. As AI systems become embedded in strategic decision-making, corporate governance structures are increasingly called upon to perform a new function: acting as the “ecological” infrastructure that regulates the flows, risks, and externalities generated by algorithmic knowledge production. Against this background, this track explores corporate law – broadly understood as the body of rules and principles governing the organisation, accountability, and liability of a company – as a form of “ecological governance” of AI, capable of balancing innovation, risk, and stakeholders’ protection within a rapidly evolving knowledge ecosystem.

Building on the concept of knowledge ecology proposed by IFKAD 2027, the track investigates how corporate legal instruments (board oversight, internal control systems, compliance programs, algorithmic auditing, directors’ duties, disclosure obligations) function as feedback loops and regulatory mechanisms that preserve the “health” of organisational knowledge ecosystems exposed to AI-driven disruption. Additionally, the track examines how principles traditionally rooted in company law, – including directors’ duties, the business judgment rule, risk oversight, and corporate social responsibility, – may be reinterpreted to address the systemic risks posed by opaque, adaptive, and autonomous AI systems.

Particular attention is given to the allocation of liability where corporate decisions are informed, supported, or generated by AI systems. The track therefore considers how corporate law may address accountability gaps arising from delegation to algorithmic systems, the interaction between human oversight and automated decision-making, and the imposition of responsibility for AI-related risks and outcomes. It also explores the relationship between corporate governance mechanisms and broader regulatory frameworks, asking how internal corporate structures can translate external legal and ethical requirements into effective organisational practices.

From a scholarly perspective, the track aims to bridge law, management, and knowledge management studies, fostering interdisciplinary dialogue on how legal design can support (or hinder) the sustainable evolution of knowledge ecosystems in the AI era. From a managerial perspective, it addresses the practical challenges faced by boards, executives, and compliance officers in embedding AI governance within existing corporate structures, balancing innovation incentives with accountability, transparency, and long-term value creation.

This track welcomes theoretical, empirical, and case-based contributions regarding, but not exclusively limited to, corporate law, corporate governance, business ethics, knowledge management, and AI governance scholars. It explicitly resonates with the IFKAD 2027 theme by framing corporate law not merely as a compliance tool, but as a genuine ecological governance mechanism: one that shapes the conditions under which knowledge, data, and algorithmic intelligence can coexist, evolve, and generate sustainable value without compromising the resilience of the broader organisational and societal ecosystem