Artificial intelligence (AI) increasingly generates expert-level outputs across professional domains, fundamentally reshaping how expertise is created and shared in society. This transformation creates a pressing challenge: as AI democratizes access to sophisticated knowledge, the validation and contextualization of expertise require novel approaches to maintain trust and professional standards. Contemporary regulatory frameworks provide essential foundations for AI governance, presenting opportunities for additional mechanisms to address the evolving nature of expertise in AI-enabled environments. This Comment proposes Expertise Contextualization as a complementary regulatory pillar that embeds dynamic context markers within AI systems, enabling clear delineation of AI capabilities within professional knowledge frameworks. Through mechanisms such as knowledge boundary mapping and contextualized confidence metrics, this approach enhances existing governance structures. Implementation through regulatory pilots, cross-industry standards, and expertise repositories offers a practical path toward responsible AI integration in professional domains.
