Ethical and Governance Challenges of AI in Information Systems: Toward Responsible Adoption in Enterprise Systems

Artificial Intelligence (AI) is rapidly reshaping enterprise information systems (EIS), from decision-support tools to enterprise resource planning (ERP), customer relationship management (CRM), and human resource information systems (HRIS). While AI adoption promises efficiency, personalization, and predictive insights, it also introduces profound ethical and governance challenges. Issues such as algorithmic bias, data privacy breaches, lack of transparency, and weak accountability structures threaten both organizational integrity and societal trust. This article examines the ethical and governance dimensions of AI in enterprise systems, highlighting policy gaps, emerging frameworks, and the need for responsible AI adoption. Using case-based insights and policy analysis, it argues for a multi-stakeholder governance model that integrates corporate responsibility, regulatory compliance, and societal values. The findings underscore the importance of aligning enterprise AI practices with data ethics and governance to safeguard both organizational value and social well-being.