This article looks at how the General Services Administration is using artificial intelligence to automate internal work after a big workforce reduction. The push is led by the internal AI tool USAi and a strategic “million hours challenge.”
It also touches on what this could mean for other federal agencies, workforce development, and broader modernization efforts.
GSA’s AI strategy and the EOA playbook
The General Services Administration is rolling out a focused internal AI automation program after losing nearly 40% of its workforce since October 2024. The aim is to speed up routine processes and shift human effort toward higher-value work.
Central to this is the EOA playbook—eliminate, optimize, automate. GSA wants to try this approach internally first and maybe bring it to other agencies if it works.
The strategy starts with listing low-value tasks that can be cut or streamlined. Automation gets introduced step by step, only where it actually makes things run better.
The agency hopes that by clearing out the backlog of routine duties, it can keep service levels steady and give staff more room for complex work.
Eliminate, Optimize, Automate: the three-step playbook
With the Eliminate, Optimize, Automate framework, GSA is targeting tasks that eat up time but don’t add much value. The focus is on reducing repetitive work and making processes run faster and more consistently.
It’s really about rethinking how things get done, cutting out unnecessary steps, and putting automation where it makes the biggest difference. Leaders say automation should support the workforce, not replace it.
The plan is to move staff into higher-value roles and help the agency bounce back as it rebuilds capacity.
USAi and the million hours challenge
At the core of GSA’s effort is USAi, an internal AI tool that spots and automates routine tasks. The agency started a “million hours challenge” to measure the impact of automation and free up staff for more meaningful work.
So far, they’ve already found about 400,000 hours of work that can be automated—almost halfway to their goal.
Deputy Director Michael Lynch says that real success depends on using these tools internally and tracking what changes. The aim isn’t just to save time, but also to make daily operations more accurate and consistent.
Automation handles the repetitive stuff, so employees can focus on work that actually needs a human touch.
Internal governance and workforce roles
A small group of employees is helping leadership figure out the best places to use automation. About 300 staff wanted to join GSA Labs, and the first group of about 30 members is now in place.
This internal consulting team is tackling five top-priority problems from a list of 17 issues. The project is both a modernization push and a way to help staff grow their skills.
Participants do this automation work on top of their regular jobs, not as a paid second gig. The idea is to build capability, not just swap out people for tech.
Impact on operations: Public Buildings Service and workforce demand
GSA’s staffing cuts have hit operations hard, especially in the Public Buildings Service (PBS). PBS lost about 45% of its employees between September 2024 and November 2025.
This led to delays in property disposals, stalled sales, and trouble managing facilities. PBS plans to hire around 400 employees over six months and has already invited another 400 laid-off staff to come back.
These staffing changes show how cuts can slow down asset management and service delivery. Automation could help get things back on track and keep key services running.
The PBS experience hints that other parts of the agency—and maybe other agencies—might also need AI-powered tools soon.
Broader implications for the federal landscape
GSA’s AI push is part of a bigger trend in the federal government. Agencies are turning to automation to recover after losing staff.
Others, like the EPA and the IRS, are also trying AI-driven approaches to pick up the pace. The White House budget talks have even considered more IRS cuts, betting that technology can make up the difference.
Workforce development, governance, and risk considerations
As automation scales up, governance, training, and risk management step into the spotlight. Agencies have to think about data governance, change management, and keeping services running smoothly during transitions.
Automation brings efficiency, sure, but it’s important to give staff real chances to reskill. Performance metrics need to show both time savings and quality improvements—otherwise, what’s the point?
- Operational resilience: Automation spreads out routine tasks, so there aren’t as many single points of failure.
- Skill development: Programs like GSA Labs focus on upskilling and building internal consulting expertise. That’s got to be a good thing.
- Governance and transparency: Agencies need clear decision rights and regular audits as automation grows. No one wants a black box running the show.
- Cross-agency potential: If pilots work, maybe they’ll inspire broader adoption and some much-needed standardization across the federal landscape.
The GSA’s work with USAi and the million hours challenge gives us a peek at how AI might help keep public services steady—even when staff disruptions hit hard. It’s worth keeping an eye not just on productivity, but also on how people feel, how well training actually works, and what all this means for the mission in the long run.
Here is the source article for this story: GSA looks to automate a million work hours, after losing nearly 40% of its workforce