As the development and use of AI systems expands, policymakers increasingly recognize the need for targeted actions that promote beneficial outcomes while mitigating potential harms. Yet there is often a gap between these policy goals and the technical knowledge required for effective implementation, risking ineffective or actively harmful results (Reuel et al., 2024b). Technical AI governance—a nascent field focused on providing analyses and tools to guide policy decisions and enhance policy implementation—currently lacks sufficient venues for exchanging scholarly work. This workshop aims to provide such a venue, fostering interdisciplinary dialogue between machine learning researchers and policy experts by ensuring each submission is reviewed by both technical and policy specialists. Through this collaboration, we seek to accelerate the development of robust governance strategies that lead to safer, more equitable AI systems.