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Fire & Rescue showcases analytics and AI plans to quality-assure incident reports
Summary
The Fairfax County Fire & Rescue Department described analytics-driven workflow improvements and a planned AI/large-language-model project to help quality-assure about 130,000 annual incident narratives, aiming to reduce staff time on routine QA.
The Fairfax County Fire & Rescue Department presented its analytics work as a model for other county agencies and described a planned partnership with DIT to apply machine learning and large language models to quality-assure incident narratives.
John Morrison, data analytics strategy manager for Fire & Rescue, said three factors drive the department’s success: executive leadership support, skilled staff, and an enterprise IT foundation managed by DIT. Morrison showed how automation and low-code/no-code tools capture on-scene performance data and allow firefighters and officers to review incidents the next day.
Morrison said the department produces nearly 130,000 incident narratives annually and is piloting AI tools to improve quality assurance so staff can focus on higher-value tasks. He framed the effort as increasing operational efficiency while working within cybersecurity and policy guardrails provided by DIT.
The presentation was offered as a use-case for other agencies and drew board interest in replicating similar integration and automation across county services.
