HOW LEGAL FRAMEWORKS SHAPE AI DECISION-MAKING IN CORPORATE MANAGEMENT

The relationship between legal systems and artificial intelligence decision-making in managing business organizations is becoming increasingly crucial in light of fast-paced technological progress and growing legal complexities. The topic for this research is the role of binding legal norms, exemplified by the EU’s AI Act and data governance laws, in both directly and indirectly conditioning managerial decisions through artificial intelligence systems. The study will be conducted through qualitative comparative research on large global organizations operating in high-risk business environments and will isolate instances of patterns and trends in managing legal risks through artificial intelligence systems and processes. The research will draw on semi-structured, qualitative research on views obtained from compliance professionals, artificial intelligence software engineers, and CXO personnel, and on content and text analysis of corporate governance reports to evaluate the effectiveness of legal compliance in altering organizational behavior patterns. The research will show how legal systems are no longer external influences on business organizations, as they are increasingly being constitutive of organizational behavior through various internal mechanisms, including accountability algorithms, legal risk software, and cross-functional ethics committees, thereby increasingly subjecting artificial intelligence decision processes to a set of legally informed constraints and determinations. This will show how this synthesis of artificial intelligence decision systems and legal systems is leading to a paradigm shift in management decisions and inference, thereby leading to greater resilience and greater trust building in corporate organizations by increasingly positioning the law as a resource, and thereby leading to greater confidence and trust and trust-building in artificial corporate management systems.