Congress moves to fix how the federal government recruits AI talent
Republicans and Democrats are backing a plan to overhaul how agencies hire and train people with artificial intelligence skills. The AI Talent Act aims to speed up hiring, improve assessments, and help agencies keep the experts they actually need.
The effort is led by Reps. Sara Jacobs (D-CA) and Jay Obernolte (R-CA), with Senate sponsors Sens. Andy Kim (D-NJ) and Jon Husted (R-OH). Supporters say the bill closes a long-standing gap: the private sector can hire faster and pay more, leaving critical roles unfilled across government.
As one backer put it, the bill would make it easier for agencies to identify, hire, and retain first-class AI talent. Jacobs framed the problem clearly: the United States needs in-house capabilities to innovate safely, protect the country, and deliver for the public.
What the bill does
- Establish Agency Tech & AI talent teams to improve recruiting, assessments, job announcements, and candidate evaluation.
- Authorize the federal personnel agency to create a central AI and tech talent team to lead pooled hiring, train agency hiring teams, and develop shared resources.
- Allow subject-matter experts to develop and run skills-based assessments so candidates must demonstrate real technical proficiency.
- Enable agencies to share qualified candidate pools ("shared certificates") to reduce duplicate hiring cycles and speed placement.
- Create a shared online platform to reuse and customize validated technical assessments across government.
- Phase out automated self-assessments over five years, with limited, publicly posted waivers.
- Let agencies stand up additional talent teams in other high-need areas like cybersecurity, data science, health care, and IT.
Why this matters for federal managers
If you lead programs or hiring, this directly affects your staffing playbook. Expect more pooled hiring, more emphasis on hands-on skills tests, and less reliance on inflated self-ratings in questionnaires.
"Shared certificates" could cut months off your timeline by letting you pull from pre-qualified candidates cleared by peer agencies. A centralized AI talent team would also give you training, templates, and technical assessments you don't have to build from scratch.
What you can do now
- Inventory your AI-related work: where models are used, where they're planned, and where risk or mission impact is highest.
- Draft skills-based position descriptions with clear, testable criteria. Prioritize must-have skills over degree requirements.
- Line up subject-matter experts who can help design and score practical assessments.
- Coordinate with your HR office to prepare for pooled hiring and shared certificates.
- Start building or collecting validated technical assessments you can reuse and adapt.
Timeline and implementation signals
The five-year phase-out of automated self-assessments is a big shift. Plan for pilots and interim waivers, but assume skills demonstrations will become the default for technical roles.
Watch for the central AI talent team's guidance, shared platforms, and training. These shared resources should reduce one-off processes and help smaller agencies compete for talent.
Where to find more
Track federal-wide AI initiatives and hiring updates at AI.gov. If you need structured upskilling paths for technical roles, see role-based course catalogs at Complete AI Training.
Bottom line
This bill gives agencies a practical way to hire faster, verify skills, and share hard-won talent pipelines. If you're in government, prepare your teams now so you can plug into the shared systems the moment they launch.
Your membership also unlocks:
