Ethical AI in Enterprise Automation: Balancing Security, Compliance, and Bias Mitigation

Abstract

This paper explores the ethical dimensions of Artificial Intelligence (AI) in enterprise automation, emphasizing the critical need to balance security, regulatory compliance, and bias mitigation. AI technologies are revolutionizing industries by optimizing operations, enhancing decision-making, and reducing costs. However, their adoption brings ethical challenges, particularly concerning data security, compliance with evolving regulations, and the risk of biased decision-making. The study analyzes existing literature, industry practices, and real-world case studies to provide insights into these ethical concerns. It emphasizes the importance of transparency, accountability, and continuous oversight in AI deployment, proposing an ethical framework that incorporates fairness, privacy, security, and accountability into AI system design. By addressing these concerns, businesses can ensure that AI technologies contribute to societal well-being while maintaining public trust.