Maryland’s comptroller has launched a public AI Economic Impact Tracker that brings together evidence of expanding demand for artificial intelligence (AI) skills and forecasts of substantial workforce disruption. Its purpose is to offer policymakers a window into an economic transition extending far beyond the state.
The portal combines government data, university research and private-sector analysis to track employment and business adoption. It also connects those changes to potential pressures on tax revenues and public budgets, giving fiscal officials a framework for assessing AI alongside employers and workforce planners.
“AI is reshaping our economy, and Maryland must meet this moment to support our workers and businesses,” Comptroller Brooke E. Lierman said, according to NottinghamMD.
The national hiring figures show considerable momentum. The tracker’s dashboard reports 273,000 U.S. AI job postings during the first nine months of 2026, up 79% from the total for all of 2025. AI positions represented 1.8% of all postings in the third quarter. California, New York, Washington, Texas and Illinois led in posting volumes.
Those figures draw on the University of Maryland–LinkUp AI Maps project, which analyzes employer postings. Its definition focuses on technical AI skills, including machine learning and model development. It excludes positions requiring only the use of chatbots and jobs building or maintaining data centers. Postings measure recruitment demand, rather than completed hires or net employment gains.
The displacement evidence presents a different picture. Employers cited AI in 120,136 announced U.S. job cuts through September, approximately 21% of the total, according to Challenger, Gray & Christmas. AI was the leading reason cited for cuts during that period. These are employer announcements, however, rather than an independently verified count of positions eliminated solely by automation.
Longer-term estimates are substantially larger. The American AI Jobs Risk Index, developed at Tufts University’s Fletcher School, identifies 9.3 million jobs vulnerable to displacement under its median adoption scenario. Slower and faster adoption assumptions produce a range of 2.7 million to 19.5 million vulnerable positions. The tracker places the projections within a two-to-five-year horizon, according to Digital Planet.
Tufts estimates annual wage income at risk of $200 billion to $1.5 trillion, with a midpoint near $757 billion. Those potential losses explain why AI’s employment effects matter to fiscal authorities: reduced earnings could weaken consumer spending and the revenues supporting government services.
Risk is concentrated in sectors central to the digital economy. Tufts estimates displacement vulnerability at 18% in information, 17% in finance and insurance, and 16% in professional, scientific and technical services. Coding support, documentation, claims processing and know-your-customer work are among the susceptible activities. These projections describe possible displacement, not inevitable layoffs, and occupations with strong productivity potential can also face substantial replacement risk.
Business adoption remains harder to measure consistently. The portal acknowledges limited evidence covering enterprise integration, operational spending and realized productivity across industries and business sizes.
Its initial business evidence comes from a Maryland survey of 276 senior decision makers, predominantly at AI-engaged organizations. That sample cannot establish a national adoption rate. Nevertheless, its distinction between basic tools and deeper integration illustrates an issue facing employers nationwide: 91% of respondents used AI, while only 32% reported advanced uses involving core systems, automated processes or agents.
The staffing responses suggest disruption may emerge through slower hiring as well as layoffs. Only 4% anticipated eliminating existing positions; 64% expected AI to expand current employees’ capacity, while 32% anticipated fewer replacement hires or slower recruitment. The findings point to the importance of monitoring vacancies and career entry opportunities alongside announced cuts.
For companies, these measures also offer a way to assess whether spending on AI translates into durable skills demand, higher output or a smaller pipeline of opportunities for new workers.
The tracker will receive quarterly updates, with periodic fiscal research briefs beginning in 2027. For policymakers and businesses, its value will depend on maintaining clear distinctions among technical capability, employer intentions, observed hiring and modeled losses. Tracking those measures together can help identify where retraining, worker support and closer scrutiny of AI deployment may become necessary.