Regulating Artificial Intelligence in Corporate Decision-Making: A Comparative Study of India and Global Frameworks

In today's world, Artificial Intelligence (AI) plays a pivotal role in the operations of business firms by making decision-making processes more efficient, reliable, and scalable. By enabling predictive analytics, automation, and big data processing capabilities, AI is becoming an integral part of various corporate functions, such as financial forecasting, human resources management, compliance, and customer profiling. This research paper aims at reviewing the present regulatory framework on AI in corporate decision-making processes, with an emphasis on the legal context in India, while also referring to international regulations, specifically those of the European Union and the United States. Using doctrinal research methodology, the author examines statutory provisions, such as the Information Technology Act, 2000, and the recently introduced Digital Personal Data Protection Act, 2023, together with various policy documents and judicial decisions to highlight how constitutional principles related to privacy, equality, and proportionality can be used in cases where there are no specific laws regulating AI. Despite some progress in creating an appropriate legal framework, it is found that India still has a number of significant regulatory gaps when it comes to the governance of AI. Most notably, it does not have any legislation specifically dedicated to artificial intelligence issues; moreover, there is no provision for its mandatory application or enforcement in practice. Compared to other international legal frameworks, such as the one created by the European Union, which relies on risk assessment and imposes clear compliance obligations, this may make AI governance in India less structured and more challenging. This research paper concludes that regulatory regimes for AI should ensure both innovation and accountability simultaneously. To achieve this balance in India's context, a combination of binding regulations and ethical principles should be used, along with an appropriate classification of AI systems and their risk assessment.