CPAI Issue Brief · Work & Economy · Workforce & economy
AI Proficiency & the Workforce
AI use at work has outrun training, and the fluency that helps the least-experienced most is reaching them last.
What’s happening
AI adoption at work has spread faster than almost any prior technology, while training has barely moved — leaving a gap between using AI and using it well. Meanwhile, the evidence on jobs is more nuanced than the headlines: mostly task change, with the first narrow employment signals only now emerging.
What the evidence shows
Company-reported surveys find about two-thirds of leaders would not hire someone without AI skills, while only 39% of AI users had received any training. The strongest randomized evidence shows AI raising productivity most for the least-experienced workers — about 35% in a field experiment with 5,000+ support agents. Employer-survey projections (WEF) estimate roughly 120 million workers are unlikely to receive the retraining they will need — a projection, not a measurement.
leaders who wouldn't hire without AI skills vs. workers who got training
Microsoft/LinkedIn 2024 — company-reported
productivity gain for the least-experienced workers
Brynjolfsson, Li & Raymond, QJE 2025
workers projected unlikely to get needed retraining
WEF Future of Jobs 2025 — projection
Where it reaches constituents
Workers at every level, and the employers and educators who train them. The equity finding — AI fluency helps the least-experienced most — means the training gap falls hardest on the workers with the least, unless programs reach them on purpose.
The current legal & regulatory landscape
The federal America's AI Action Plan (July 2025) includes worker-skilling programs, and Workforce Pell (effective July 2026) extends aid to short credential programs; the Digital Equity Act's capacity grants were terminated in May 2025. North Carolina's roadmap commits to credentialing 50,000+ residents in AI skills by 2028 — and notes the state cannot yet attribute layoffs to AI, because its reporting data was not built to capture it.
In North Carolina
Census Business Trends and Outlook Survey data analyzed by NC Commerce (published July 2026) found 18.9% of North Carolina businesses currently use AI, against 17.9% nationally — while 23.2% report employees using AI for work tasks. Employee use runs ahead of firm adoption. Among NC businesses using AI, roughly 10% report it replaced an employee task against 16.8% reporting it replaced existing software. Separately, an industry analysis using Lightcast data estimates 286,290 North Carolina tech jobs — about 61% of the state's tech workforce — are exposed to large language model technology. The state's AI Strategic Roadmap targets credentialing more than 50,000 residents in employment-enabling AI skills, and the roadmap itself recommends updating the state's WARN data collection to capture AI-related job losses, with a March 2027 deadline — an acknowledgment that the state cannot currently attribute any layoff to AI.
Bill statuses described as of August 19, 2026. Descriptive only — CPAI takes no position on any pending measure.
Considerations policymakers are weighing
- ·How workforce programs reach the automation-exposed and least-credentialed workers who gain the most.
- ·Whether "AI skills" funding measures durable capability or just enrollment.
- ·The data infrastructure needed to know what is actually happening to jobs.
Listed as live debates, not recommendations. CPAI does not take a position on how these should be resolved.
This brief condenses a full, sourced public guide. The complete evidence and citations:
AI Proficiency and the Workforce →Key sources
A nonpartisan resource
The Center for Practical AI is a nonpartisan 501(c)(3) nonprofit. We provide education, research, and analysis, and we offer briefings and testimony on request. We do not endorse candidates or lobby for or against specific legislation. Everything here describes the evidence and the current landscape — the policy choices are yours.
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