A BILL to amend the Code of Virginia by adding in Chapter 6 of Title 2.2 an article numbered 3, consisting of sections numbered 2.2-622 through 2.2-625, relating to Artificial Intelligence Workforce Impact Act established; report.
HB310 creates the Artificial Intelligence Workforce Impact Act within the Code of Virginia. The bill requires each state agency, beginning January 1, 2028, to file annual reports with the Department of Human Resource Management describing workforce changes tied to the adoption or use of artificial intelligence systems. Those reports must cover positions eliminated, vacancies left unfilled because AI took over duties, jobs materially changed by AI, retraining provided, new AI-related positions created, and a description of the AI system involved.
The bill also establishes a trigger for more detailed planning: if an agency reports 10 or more AI-related workforce impacts in a fiscal year, it must submit an Artificial Intelligence Workforce Transition Plan within 180 days. That plan must identify positions at risk, describe retraining and reskilling efforts, address partnerships with the Virginia Community College System or higher education institutions, outline reassignment strategies, maintain service continuity, and provide an implementation timeline. Affected employees would be eligible for retraining, layoff-related benefits, career transition services, and other support measures.
In addition to agency-level reporting, the Department of Human Resource Management must review the submissions and prepare an annual statewide report for the Governor, legislative leaders, and JLARC. That report must summarize total impacts, trends across agencies and occupations, projected workforce needs, mitigation strategies, and risks to continuity of government services, and it must be posted publicly on the General Assembly website. The bill therefore adds a new reporting and oversight framework focused on how AI affects state employment and service delivery.
The overall sentiment reflected in the bill’s structure is cautious and oversight-oriented rather than anti-AI. It does not ban or limit agency use of artificial intelligence; instead, it emphasizes transparency, workforce planning, and employee transition support. The absence of recorded votes or committee testimony suggests there is no documented floor-level debate in the available materials, but the bill’s referral and final status indicate it was not advanced out of Appropriations.
The main point of contention likely concerns administrative burden and the cost of compliance versus the value of monitoring AI-driven workforce changes. Supporters would likely view the bill as a proactive labor and governance measure to protect employees and preserve service continuity, while critics may see it as duplicative reporting or an obstacle to agency innovation. The 10-impact threshold, the required transition plans, and the coordination with multiple state entities could also raise questions about implementation complexity and resource needs.
HB310 would add new provisions to Title 2.2 governing state agency reporting on AI-related workforce impacts and would require the Department of Human Resource Management to collect, analyze, and report statewide data on AI-driven job changes. It would affect state agencies, state employees, DHRM, the Virginia Community College System, the Virginia Employment Commission, and legislative oversight bodies such as JLARC and relevant committees. The bill does not regulate private-sector AI use; its legal effect is limited to Commonwealth employment and workforce transition processes.
The bill’s tone is generally cautious and management-focused, reflecting concern about AI’s potential effects on state employment while still allowing agencies to use AI systems. Because the bill was left in the House Appropriations Committee and there are no recorded votes or committee transcripts in the provided materials, there is no direct evidence of formal support or opposition in the record. The bill’s design suggests an intent to prepare for AI-related disruption rather than to restrict technology adoption.
Likely areas of contention include whether the reporting requirements and transition-plan mandates are necessary or overly burdensome, how agencies would define and measure an AI-related job impact, and whether the 10-impact threshold is an appropriate trigger for additional planning. Supporters would likely emphasize employee protections, retraining, and continuity of government services, while opponents may focus on administrative costs, compliance complexity, and the possibility that the bill could slow AI adoption in state government. Questions may also arise about how much discretion agencies would have in determining when AI substantially caused a workforce change.