Rulemaking Comment Analytics
Description
The rulemaking process generates large volumes of public comments that require timely and consistent analysis. Manual review is labor-intensive, slow, and prone to variability, creating delays in identifying sentiment, themes, and stakeholder concerns. We need a more efficient, scalable method to analyze these comments so regulators can make informed decisions within required timeframes.
Detailed example
The AI tool will produce structured summaries of public comments, including sentiment analysis, key themes, and recurring issues. It's output will provide regulators with a consolidated view of stakeholder feedback, enabling faster interpretation, prioritization of concerns, and more informed decision-making during the rulemaking process.
AI / analytics pattern
Generative AI: AI that generates new or synthetic content (e.g., images, videos, audio, text, code).
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
The Comment Analytics use case leverages Gen AI to rapidly analyze public comments submitted during rulemaking, including identifying sentiment, key themes, and areas of concern. This significantly speeds up the review process, reduces manual workload, and provides consistent, data-driven insights to support more informed regulatory decision-making.
Audit / financial statement impact
The AI-driven comment analytics tool does not make or directly influence binding policy or regulatory decisions; it only synthesizes and summarizes public input for human review. Because its outputs do not determine individuals’ rights, benefits, services, or access to government resources, it does not meet the definition of a High-Impact AI use case.
Controls / human review
ATO: Not reported; PIA: Not published