The Technology Modernization Fund (TMF) announced about $83.4 million in new investments across the State, Agriculture and Transportation departments on October 1, FedScoop reported. 

The investments cover four projects involving agentic AI, system consolidation and AI-enabled records processing, with the projects designed to integrate AI into agency systems and speed up government workflows.

The projects are designed to modernize existing technology by connecting fragmented systems, applying AI to large volumes of information and automating parts of administrative work. 

The investments also include human review of automated decisions in the projects using AI for decision-making.

Agentic AI Moves Into Federal Workflows

According to the report, the State Department will receive $17.3 million to deploy agentic AI for help-desk operations, research and scenario planning. The project will also allow employees to build their own automated agents, with a person reviewing every automated decision. TMF expects the project to save more than 100,000 staff hours annually once fully operational.

At the Department of Agriculture, a $10 million project will consolidate 10 review systems operated by different departmental agencies into a single platform. AI will then identify applications eligible for the fastest review path. The project is expected to save 1.8 million labor hours each year and process about 78% of fast-track applications in near real time.

The United States Department of Agriculture (USDA) will receive $52.3 million to replace a high-risk legacy payroll system at its National Finance Center with a cloud-based platform built around AI and automation. The new system will align with the Office of Personnel Management’s HR 2.0 plan for rebuilding federal human resources systems.

The Transportation Department will use another $3.8 million to add AI to its aviation consumer complaint system. The technology will categorize complaints, identify duplicates and extract public records faster, while employees review each automated decision.

Data Integration Becomes a Foundation for AI

For chief data officers (CDOs), the investments show how AI projects increasingly depend on the condition and structure of the underlying data and systems.

The USDA review project is an example of that. Bringing 10 separate systems into one platform creates a common environment for applying AI, while the Transportation project shows how structured information can support automated classification and analysis. These efforts also make data integration and consistency important considerations before AI is deployed.

That aligns with the broader role of data leaders in building reliable systems for AI-enabled work. Organizations need to understand where information resides, how systems connect and how automated decisions can be reviewed and traced.

It’s encouraging to see that federal agencies are addressing those foundations alongside AI deployment.