Taxonomy-Driven Analysis of Open-Source AI Risk Mitigation Tools

As enterprises deploy LLMs at scale, governance and risk management become harder to handle manually, especially given a fragmented landscape of evaluation, security, and monitoring tools. This paper maps 21 open-source AI risk tools to 32 subcategories of the MIT AI Risk Mitigation Taxonomy using an LLM-assisted RAG pipeline analyzing code and documentation. This work is valuable for enterprise AI governance teams, compliance officers, and tool developers seeking to identify coverage gaps—particularly in governance, legal, and financial risk categories—and could inform how organizations combine automated tooling with human oversight and regulatory processes for responsible AI deployment. Paper: https://arxiv.org/abs/2608.07446