Artificial Intelligence and the Transformation of Contract Law: Legal Challenges and Pathways Toward a Regulatory Framework

Abstract

The rapid diffusion of artificial intelligence (AI) into commercial practice — from AI-assisted negotiation to self-executing smart contracts — is placing sustained pressure on the doctrinal foundations of contract law, particularly the requirements of offer, acceptance, intention to create legal relations, and consensus ad idem. This paper examines the extent to which AI-driven contracting challenges classical contract doctrine and evaluates the adequacy of existing legal frameworks to address issues of formation, interpretation, performance, liability, and accountability. Using a doctrinal and comparative legal research method, the study analyzes statutory instruments, case law, and scholarly literature from common law and civil law jurisdictions. The findings indicate that while courts and legislatures have begun to accommodate AI-mediated transactions through concepts such as electronic agents and functional equivalence, significant normative gaps remain regarding liability allocation when an autonomous system produces an unintended or erroneous outcome, and regarding the attribution of intent to non-human decision-making systems. The paper argues for a graduated regulatory model that combines risk-based liability rules, mandatory transparency obligations, and sector-specific codes of conduct, rather than a single uniform statute. The discussion concludes that contract law's traditional reliance on human intention must evolve toward a functional, outcome-oriented standard capable of accommodating autonomous and semi-autonomous contracting systems without abandoning the doctrine's core commitments to fairness, foreseeability, and party autonomy.