Corporate Liability for Ai-Driven Decisions: Legal Reforms and Comparative Perspectives

Abstract

Artificial intelligence increasingly influences corporate decisions concerning employment, credit, healthcare, insurance, and consumer services. Its benefits are accompanied by harms that can be difficult to explain, attribute, and remedy. Responsibility may be divided among developers, suppliers, deploying companies, and individual users, while affected persons lack access to the evidence needed to challenge a decision. This article examines corporate liability through doctrinal and comparative analysis, focusing on India alongside European, British, and American approaches. It considers contemporary problems involving generative AI, discriminatory automation, autonomous agents, and cross-border supply chains. The article argues that legal responsibility should reflect the applicable duty, operational control, and contribution to harm. It proposes proportionate record-keeping, meaningful human review, coordinated regulatory supervision, and carefully targeted evidentiary reforms. Effective accountability requires both preventive governance and practical remedies, without assuming that every adverse automated outcome establishes liability.