Stanford launches AI Economic Indicators to track jobs, adoption, and productivity

The public platform includes dashboards on AI exposure in the labor market, macroeconomic signals, and generative AI use by workers and firms.

Stanford Digital Economy Lab has launched AI Economic Indicators, a public platform tracking how AI is affecting jobs, productivity, adoption, and the wider economy

The Stanford Digital Economy Lab has launched AI Economic Indicators, a public platform tracking how artificial intelligence is affecting work, productivity, adoption, and the wider economy.

The platform brings together regularly updated dashboards for policymakers, business leaders, researchers, and workers trying to understand how AI is changing labor market outcomes, firm behavior, and economic growth.

The Stanford Digital Economy Lab said the project combines data from government statistical agencies, researchers, and private companies. It is designed to address the lag between rapid AI adoption and slower-moving traditional economic data.

Three dashboards are available at launch: the Canaries Dashboard, developed with ADP Research; the Takeoff Tracker; and the Adoption Monitor.

Susan Young, Director of Strategic Initiatives at the Stanford Digital Economy Lab, said in a LinkedIn post: "One challenge with major technological change is that it can take years for traditional data sources to fully capture what is changing. Part of the motivation behind the Indicators is to shorten that gap."

Three dashboards at launch

The Canaries Dashboard tracks employment across occupations and worker groups with different levels of AI exposure.

The dashboard groups workers by AI exposure score and compares employment trends across those groups. Early results show modest differences between the five exposure groups, with employment growth lowest for the most exposed occupations.

A separate early-career employment view focuses on workers aged 22 to 25. Stanford Digital Economy Lab said the two most exposed occupation groups for early-career workers have seen noticeable declines since the introduction of ChatGPT, while the other three occupation groups have grown.

The lab said those patterns become less pronounced and eventually disappear for older workers. The early-career group accounts for 7.0 percent of employment in the Canaries sample at baseline.

The Takeoff Tracker monitors macroeconomic indicators associated with advances in AI capabilities and broader economic change. Stanford Digital Economy Lab said its current set of 12 indicators shows no decisive evidence of takeoff at present.

Tracking AI adoption by workers and firms

The Adoption Monitor tracks generative AI use by individuals and firms across available surveys and datasets.

Stanford Digital Economy Lab said self-reported generative AI use for work differs across recent surveys. Hartley et al. report a decrease in adoption, while Gallup and Bick, Blandin, and Deming report continued increases toward 50 percent adoption.

The platform also tracks current and expected firm-level AI adoption. Stanford Digital Economy Lab said US firms lead adoption of AI technologies but show little gap between current and expected use.

By contrast, firms in the UK, Germany, and Australia expect to increase adoption.

The indicators are organized around five questions: how AI affects employment and wages, whether broader measures such as productivity and GDP show AI effects, whether traditional metrics capture consumer benefits, how worker skill requirements are changing, and how AI is being used to complement or replace human labor.

The AI Economic Indicators project is supported by Schmidt Sciences, the Siegel Family Endowment, and other individual donors.

Young said the platform is a "living project" that will add new data sources, dashboards, and measurement efforts over time.