Artificial Intelligence (AI) is quickly transforming the managerial decision-making process in industries with a higher level of efficiency, faster and more precise. The use of AI tools in modern organisations is becoming common in major management processes like human resources, marketing, supply chain and strategic planning. These tools are useful in the analysis of data, prediction, recruitment and prediction of customer behaviour, hence making managers make better-informed decisions. Nevertheless, on the one hand, AI has great beneficial effects on the operation, and on the other hand, it poses essential ethical concerns. Algorithm bias, insufficient transparency in decision-making, data privacy and accountability gaps are some of the concerns that have triggered debates globally regarding responsible use of AI. The work attempts to address the two sides of AI-based decision-making, both in relation to the efficiency gains in the management field and the ethical concerns in Indian organisations. The study used both a mixed-method and primary data collection, which was based on the use of structured questionnaires and interviews with 100 managerial professionals working in different industries. Still, most of the results, a large portion of the companies have adopted AI to enhance performance, but most of them have not established clear ethical standards or guidelines to promote responsible use of AI. Biases in recruitment instruments, unprotected data policies and a general lack of human control were widely cited. The article highlights the necessity of a moderate solution to AI adoption, one that integrates technological innovations and ethical regulations. It also adds to the expanding discussion on responsible AI by providing a set of specific recommendations that can be implemented by managers, policymakers and leaders of corporate entities. These involve the creation of internal ethical principles, increasing the AI literacy and creating regulatory oversight systems to make sure that AI-driven decisions are efficient and ethical at the same time.