Breaking Down Barriers Assistant: Leveraging AI to Conduct Policy Analyses with Complex Data

Evidence-based policy design increasingly relies on integrated administrative data, yet access to and effective use of these data remain constrained by technical and institutional barriers. This paper introduces the Breaking Down Barriers Assistant, an AI-powered analytical platform designed to democratise access to complex, linked administrative datasets for policy analysis. The system enables users to query secure, pre-aggregated Australian administrative and survey data using natural language and supports the full policy research cycle through three integrated tools: variable discovery, visual analytics, and automated reporting. Methodologically, the BDB Assistant combines Retrieval-Augmented Generation with controlled code generation and execution, ensuring that all analytical outputs are grounded in verified metadata, auditable Python code, and human-in-the-loop validation. Using benchmark comparisons with established platforms such as YouthView and the BDB Community Profiles, we demonstrate that the Assistant can accurately reproduce complex spatial and longitudinal policy analyses that traditionally require advanced technical expertise. The findings show that the system substantially reduces time-to-insight while maintaining strict standards of accuracy, transparency, and privacy. The BDB Assistant illustrates how responsibly governed generative AI can expand analytical capacity within government and the social sector, supporting more timely, rigorous, and locally targeted evidence-based policymaking.