As organizations adopt artificial intelligence systems with increasing autonomy and scope, the implementation of ethical agents has brought about meaningful sociotechnical impacts for firms and their employees. Two distinct approaches to managing these ethical agents can be seen by contrasting the normative principles of Information Systems with the empirical push for autonomous moral agency in Machine Ethics. With the rising popularity of Large Language Models, we review implementation efforts and challenges of Machine Ethics as a more agentic yet descriptive approach to embedding ethical principles in systems. By formal analysis of these orthogonal approaches, we synthesize an integrated solution that combines the context- awareness of dialogue agents with theoretically informed techniques to increase their adherence to normative ethical theory. Bridging the gap between firms, ethical theory, and technical implementation ensures that values from management design frameworks are truly present in these agents and their downstream impacts.
