THE STATUS QUO NEEDS TO CHANGE
There are many challenges with the current national data model. Take three examples: data on jobs, skills and industries.
The story is similar for skills. Information on local skills is often not fit for purpose. Many new and emerging skills are reported with a three-year lag. The best skills registry, O*NET, is national rather than local. And while there is information from the private sector about aspirational skills employers seek, there is no systematic way of tying those skills to hires, jobs and earnings. So, job seekers don’t clearly know the most valuable skills to acquire, and employers are swamped with job seekers whose skills don’t match their open positions.
Industry data available today are similarly not fit for describing local sectors. The current system groups companies into industries based on a description of a service economy that was developed 50 years ago. To understand what is happening to sectoral trends in the new innovation economy, we should be rethinking how to group firms by the ideas they produce and the workforce they hire.
Our limited and outdated data infrastructure puts us at a disadvantage. The current system cannot answer important questions about the effects of new technologies like AI on jobs and skills, leading to “vast uncertainty.” State and local training providers are unsure about what curricula to develop. Job seekers don’t know what skills to acquire. And for employers, it increases the likelihood of hiring the wrong person, which can be very costly.
The good news is that there are better approaches emerging from the states.
LOOK TO THE STATES
Many state agencies are not waiting for the federal workforce information system to change. They recognize that their new systems must not just reflect the new economy in their states but also provide headlights into needs around emerging skills. They are using new technologies and data to define new measures of skills, and tying them to new measures of jobs and earnings. They are redesigning their systems, not just to better prepare for AI but to prepare for future waves of technological change tied to regional economies and local industries. Philanthropic foundations and federal agencies have supported the infrastructure that is needed to scale, including Credential Engine, the U.S. Chamber of Commerce Foundation’s Jobs and Employment Data Exchange (JEDx), the Digital Credentials Consortium, and the recently announced goals of Genesis Mission. There are many examples of what has already been done in the key challenge areas; a few are listed below.
Identify New and Emerging Technologies
AI is the current poster child, but many new technologies are emerging, like synthetic biology, advanced manufacturing, quantum computing and semiconductors. States like Ohio, New Jersey and Arkansas are working with the Industries of Ideas project that is tracing new ideas coming out of their research universities to their local firms based on who they’re hiring from the universities. In Ohio, employer-level information on the link between federal research investments in AI, employer hiring and job creation provide forward-looking and actionable information about what employers are likely to do in the future.
Modernize Measures of Jobs
Understanding the tangible impacts of technological change on employers, jobs and the workforce requires more sophisticated local, timely, forward-looking and actionable indicators. Five states, led by Kentucky, have led the way to securely combining education and workforce data across state lines (in a FedRAMP secure environment) using new technologies to produce new local jobs and earnings measures in their Multi-State Postsecondary Report. This effort is now being scaled to other states.
Modernize Skills Measures
The new economy depends crucially on employers being able to find workers with the skills they need. Today, our measures of skills are based on 10-year projections that cannot keep up with changing technologies.
Arkansas’ Launch is working with the Industries of Ideas project to develop near-real-time skills-based information tools that match employers and workers quicker. These tools focus on skills, not just assumptions based on degrees. They use employer data from job postings to build domain-specific natural language processing tools that identify and extract in-demand AI skills according to known and new emerging labels. These tools recognize varying terms that employers use and develop a common language bridging job postings and curriculum. This enables the collection and reporting of actionable, local data — on both an individual and aggregate basis — about the successful in-state hiring of job seekers with different sets of skills and their resulting earnings and job duration.
A NEW ALLIANCE
The data sources foretelling the future of work are in the states. They alone have the components of data that, if well integrated, could provide accurate headlights into what technologies are being adopted by their local employers in their local industries. Just as the agricultural extension program transformed local American agriculture after the Civil War, state-led workforce information systems could transform local American innovation now.
For more information about the Industries of Ideas project, visit the website or attend the inaugural convening of economic leaders, academia, employers, skills development experts and public-sector leaders in Washington, D.C., on April 30, 2026.
Julia Lane is a professor emerita at New York University's Graduate School of Public Service. She is the author of Democratizing Our Data: A Manifesto and has founded many national public data infrastructures.
Suzette Kent is a technology transformation leader who previously served as the federal chief information officer. She has been a partner at Accenture, EY and managing director at JP Morgan. She currently leads an advisory business working with technology companies, businesses, academic institutions and workforce development companies across industries in the public and private sectors.
