A bill to establish Federal agency technology and artificial intelligence talent teams to improve competitive service hiring practices, and for other purposes.
SB 3410 would create new federal hiring structures focused on technology and artificial intelligence positions. It authorizes agencies to establish “agency talent teams” made up of recruiters, assessment experts, subject matter experts, and related staff to improve hiring for tech and AI jobs in the competitive service. These teams would help write job announcements, improve examinations, share certificates of eligible candidates, and support pooled hiring across agencies.
The bill also gives the Office of Personnel Management (OPM) authority to establish a government-wide technology and AI talent team, expand existing hiring experience efforts, and create an online platform for agencies to share and customize technical assessments. It defines “technical assessments” broadly to include structured interviews, work exercises, industry assessments, coding tests, and similar tools, and it encourages use of existing platforms such as USA Hire when practicable. The bill further sets standards for examinations, including a preference for job-related assessments and limits on relying solely on automated self-assessments after five years, subject to waiver.
The bill would amend federal hiring practices under title 5 by creating new optional agency talent teams and expanding OPM’s role in coordinating, standardizing, and sharing assessment tools for competitive service hiring. It would affect federal agencies, OPM, chief human capital officers, human resources staff, and applicants for technology and AI-related positions, while also influencing how examinations are designed, shared, and documented. The bill does not create a new substantive program outside personnel management, but it would change how agencies recruit and evaluate candidates for high-need technical roles.
Based on the bill text and the absence of recorded committee debate or votes in the provided materials, the overall sentiment appears supportive and reform-oriented. The legislation is framed as a workforce modernization measure intended to improve federal hiring speed, quality, and consistency for technology and AI jobs. Its tone suggests an emphasis on practical hiring improvements rather than controversy, with a focus on better assessments, pooled hiring, and cross-agency coordination.
The main potential point of contention is the bill’s approach to hiring assessments and the balance between flexibility and oversight. Supporters may favor allowing subject matter experts and agencies to design customized technical assessments and share them across government, while critics could worry about uneven standards, reduced central validation, or administrative complexity. Another possible issue is the provision limiting sole reliance on automated self-assessments after five years, which could be viewed either as a safeguard against weak screening tools or as a constraint on agency hiring flexibility. No specific objections or amendments are reflected in the provided committee materials.