Artificial intelligence in corporate legal risk management: A governance and accountability framework

The acceleration of the regulatory requirement, globalization of operations and digital transformation has increased the corporate vulnerability to legal risk. The current legal risk management methods which are mostly reactive and manual fail to handle the scale and complexity of the modern legal and compliance issues. Corporations are in turn moving towards artificial intelligence (AI) more and more as a method of improving legal risk identification, evaluation, and reduction. The paper explores the ways of using AI to balance the control of corporate legal risk and governance, accountability, and ethical responsibility. Using a qualitative and conceptual research of the existing literature, the study examines the major types of corporate legal risk such as regulatory compliance, contractual risk, litigation exposure, governance failures, and data protection issues. The paper examines AI applications within the corporate legal functions, including natural language processing, machine learning, and predictive analytics, and puts into the limelight, how these applications can be used to facilitate proactive and predictive risk management. Meanwhile, the paper critically considers the issues related to the use of AI such as algorithmic bias, transparency, threats to privacy, and legal accountability ambiguity. To resolve the challenges a conceptual framework is suggested, which incorporates the AI capabilities in the corporate level of legal risk management in a regulation-focused and ethically sound framework. The article adds to the literature because it offers a comprehensive view of AI-sensitive law risk management and offers useful data that corporations should consider in terms of finding the balance between innovation and legal accountability.