Artificial intelligence is beginning to reshape every stage of the government employee lifecycle, from recruiting and applicant screening to workforce development, employee engagement and retention. But realizing its potential requires public-sector organizations to balance innovation with transparency, governance and human oversight.
Recorded at the NASPE 2026 Annual Meeting, this episode of State Gov Today examines how state governments are approaching AI in human resources, addressing workforce shortages and modernizing the employee experience while keeping people accountable for consequential decisions.
Host George Jackson speaks with:
State governments continue to face hard-to-fill positions, changing employee expectations and pressure to deliver services more efficiently. The panel explains that AI can help, but states are entering the technology at different levels of maturity.
Juan Williams says Tennessee has moved further into experimentation and implementation. The state established an advisory committee that brings together government, academia, the private sector and other stakeholders to shape how AI is used. Employees are gaining access to protected tools such as ChatGPT and Copilot, giving them an opportunity to build familiarity with AI inside a controlled environment.
Recruiting is one area where Tennessee is seeing practical value. After changes to compensation and total rewards increased applicant volume, AI began helping recruiters review large groups of applications for minimum qualifications. Williams emphasizes that a person remains responsible for the final determination. The technology reduces repetitive work and gives recruiters and hiring managers more time for higher-value responsibilities.
Byron Decoteau explains that Louisiana is also examining how AI can reduce administrative burdens. The objective is not to remove people from recruiting or onboarding. It is to automate routine processes so HR professionals can spend more time with candidates and new employees.
Louisiana agencies have adopted AI policies aligned with statewide technology standards, and employees are beginning to test closed systems that offer greater security than publicly available consumer tools.
Decoteau encourages employees to treat AI like a new colleague whose work must be reviewed. The technology can provide a useful draft, improve job postings and help clarify position descriptions, but employees must verify the result and apply their own judgment before using it.
The conversation also highlights a growing expectations gap. Many people entering government have used digital assistants and generative AI throughout their education and personal lives. When they encounter legacy systems in the workplace, the difference can affect recruitment, productivity and retention.
Modernization therefore involves more than acquiring a new tool. It requires collaboration among HR leaders, technology teams, agency executives and employees.
The second segment focuses on the conditions that must be in place before AI can scale across the government workforce.
Transparency is central because applicants, employees, labor organizations and residents deserve to understand when AI is being used, what role it plays and where a person remains responsible.
Leslie says states increasingly recognize that government carries responsibilities that differ from those of private companies. Fairness and explainability are especially important when technology may influence hiring, performance management or another decision affecting an individual’s livelihood.
For Illinois, that discussion includes organized labor. Kerley explains that labor partners should be involved early so AI can be positioned as a tool for upskilling employees, creating more meaningful work and automating frustrating tasks.
She prefers the idea of an “expert in the middle.” Public employees bring experience and accountability to an automated process rather than functioning as a ceremonial final check.
That same transparency should extend to the public so residents can understand how AI is helping government respond more quickly while people remain accountable for the outcome.
Decoteau adds that government leaders must be able to explain a decision. If they cannot understand or communicate why an AI system produced a recommendation, they should not rely on that recommendation.
AI may support administrative work, analyze prior cases or identify patterns, but decisions involving employees, families or vulnerable residents require deeper professional judgment.
The panel also examines scale. Tennessee evaluates whether a successful use case can benefit multiple agencies or the broader enterprise. Louisiana’s experience shows that scale depends on mission and context.
A tool that performs well in a regulatory or administrative-law setting may not meet the needs of training professionals or employees doing more creative work. Government should therefore scale capabilities because they solve shared problems, not simply because a pilot was technically successful.
The most valuable applications give employees time back, improve the experience of applicants and workers, and help government deliver better services without surrendering accountability.