AI-Enabled Asset Management and Decision Support for Federal Lands Highway

Forecast New Requirement Updated

Agency
Solicitation expected
Estimated value
$2,000,000 to $4,900,000
Set-aside
No set-aside

Forecast facts

Anticipated award
Not on record
NAICS code
541990 All Other Professional, Scientific, and Technical Services
Forecast number
52064
Points of contact

Forecast details come from the GSA Acquisition Gateway. Agencies' dates and values are estimates.

About this forecast

Written by GovTribe AI ·

The Department of Transportation, co-funded by the Intelligent Transportation Systems Joint Program Office and Federal Lands Highway, will issue a competitive delivery order solicitation by November 29, 2026, for an AI-enabled Asset Management and Decision Support program serving Federal Lands Highway and seven federal partner agencies. The initiative integrates artificial intelligence into existing engineering workflows to automate routine tasks, eliminate bottlenecks, and enhance asset data collection and analysis, transforming raw information into actionable insights to optimize multi-agency transportation investments and asset management decisions.

The estimated award value ranges from $2 million to $4.9 million. Performance and administrative oversight occur within the Department of Transportation and Federal Highway Administration. Direct inquiries should be directed to Lisa Randall, Senior Environmental Planner, at lisa.randall@dot.gov or 415-748-8399.

Forecast text

Co-funded by the ITS JPO and Federal Lands Highway (FLH), this project establishes an AI-enabled Asset Management program for FLH and its seven federal partners. Currently, FLH engineering workflows are highly manual, limiting data utilization. Rather than replacing existing systems, this initiative integrates practical AI to streamline routine tasks, eliminate bottlenecks, and optimize how asset data is collected and analyzed. This approach transforms raw information into actionable insights, improving multi-agency transportation investments and asset management decisions.

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