Research: Investigative Workflows and Opportunities for AI Augmentation

This research explores how investigative workflows—particularly in government and compliance environments—can be transformed through automation and AI. Drawing on firsthand experience as a federal investigator, the project quantifies the inefficiencies embedded in current processes, from manual data entry and repetitive interviews to report writing and supervisory coordination. By modeling labor hours, salary costs, and opportunity costs at the task level, the research demonstrates how even routine investigative activities can consume significant time and public resources. These insights are used to map “inefficiency curves” across the investigative lifecycle and identify where automation can meaningfully reduce burden while preserving evidentiary integrity and auditability.

Building on this foundation, the project evaluates the emerging market for investigative technology across RegTech, compliance management, and case management systems, identifying a gap for purpose-built tools that support investigators rather than replace them. It outlines a concept for an automated investigative platform that integrates structured data ingestion, AI-assisted analysis, and report generation to improve speed, consistency, and decision-making. In parallel, the research applies investigative tradecraft—such as OSINT-based due diligence and adversarial risk analysis—to assess how technologies can be misused and how safeguards can be embedded early. Together, this work positions investigative expertise as a critical lens for shaping the next generation of compliance and audit technologies across both public and private sectors.