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Tracking AI -replaced jobs in Virginia: How will AI affect ODU’s workforce?

Guest Post, ODU-AAUP ally

How will AI affect academic labor, especially given its rapid integration into areas of research, teaching, and learning here at ODU?

Michael Feggans
97th District
D – City of Virginia Beach

Virginia Beach Delegate Michael Feggins has proposed a bill requiring state agencies, starting in 2028, to report how many jobs “are eliminated, left vacant, altered or newly created each year because of AI.” The Artificial Intelligence Workforce Impact Act – HB310 – would require “agencies who report 10 or more AI-related job impacts to submit a workforce transition plan within six months, identifying at-risk positions and a strategy for retaining or reassigning affected employees.”

Once AI technology is fully integrated at ODU, what changes can we expect for faculty and staff? This bill is an important first step towards tracking the operational effects of AI.

See a recent WHRO story about the proposed bill here

On a related note, in July, 2025, the AAUP released a new report, Artificial Intelligence and Academic Professions, sharing survey findings and calling for the establishment of policies in colleges and universities that prioritize economic security, faculty working conditions, and student learning conditions as advancements in artificial intelligence (AI) technologies accelerate. 

As ODU works to integrate AI as a key part of student learning and job preparedness, Stanford University researchers have found a 16% drop in available entry-level positions most likely affected by AI.

Some other takeaways (full study at the end of this story):

  • We find substantial employment declines for early-career workers in occupations most exposed to AI, such as software development and customer support.
  • While economy-wide employment continues to grow, employment growth for young workers has been stagnant.
  • Entry-level employment has declined in applications of AI that automate work, with muted effects for those that augment it.
  • Labor market adjustments are more visible in employment than in compensation.
  • These patterns hold across various alternative analyses.

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