Regulatory Human-Agent Teams: Co-Creating Ethical Oversight

This article advances the discourse on artificial intelligence in regulatory contexts by proposing a conceptual framework for "human-agent teams" as collaborative partnerships rather than traditional automation solutions. Building on existing empirical research from the compliance and AI governance literature, this conceptual article examines how compliance professionals and AI systems can function as integrated teams with complementary capabilities, shared accountability, and co-created ethical frameworks. Drawing from interdisciplinary theoretical foundations including cognitive systems engineering and distributed cognition, the article synthesizes recent empirical findings that demonstrate the potential of collaborative human-AI models in regulatory settings. The article develops a layered accountability framework to address responsibility distribution between human and AI team members and proposes six design principles to guide implementation. By analyzing existing research on human-AI collaboration in compliance contexts, this article demonstrates how the human-agent team paradigm could enhance regulatory compliance while maintaining ethical standards, ensuring transparency, and adapting to evolving oversight requirements. The proposed framework suggests that human-agent teams may create more resilient and trustworthy compliance operations than either human-only or AI-only approaches, though empirical validation of this conceptual model remains a critical area for future research.