Artificial intelligence is changing more than individual jobs. It is also challenging how employers define talent, evaluate candidates and build career pathways.
That is the focus of a new policy playbook from Opportunity@Work, a nonprofit focused on skills-first hiring. Building an AI-Ready Workforce: A Policy Playbook for a Skills-Based Labor Market provides public-sector leaders with model policy language, implementation guidance and examples for reducing reliance on four-year degrees when they are not essential to a role.
The development arrives as AI changes the tasks employees perform and, potentially, the routes through which workers acquire experience. For HR technology teams, that creates a practical challenge: recruitment systems and workforce platforms need to identify what people can do, rather than relying too heavily on traditional credentials.
The Skills-First Workforce Is Becoming a Technology Issue
Opportunity@Work estimates that more than 75 million U.S. workers are Skilled Through Alternative Routes, or STARs. The organization defines STARs as workers with a high school diploma or equivalent who do not hold a bachelor’s degree but have developed skills through routes such as military service, community college, apprenticeships, certificates, bootcamps and on-the-job experience.
That distinction matters because conventional applicant-tracking and recruiting processes can use educational credentials as an initial filter. A skills-based model instead attempts to understand the capabilities associated with a job and match candidates against those requirements.
The shift is already reflected in the HR technology market. Skills intelligence, talent marketplaces, AI-powered candidate matching and competency management systems are increasingly being used to create more granular views of workforce capability.
Gartner has also identified skills-based hiring as a growing priority, noting that employers are removing degree requirements for some positions to broaden the available talent pool.
AI Could Disrupt the Pathways Workers Use to Build Skills
Opportunity@Work’s latest research analyzes more than 190 million job transitions over the past decade and finds that similarity between skills is an important factor in how workers move between jobs. The organization argues that intentional job design will become increasingly important as AI changes the tasks that make up individual roles.
That creates an underappreciated HR problem.
Workers often build capabilities by performing increasingly complex tasks on the job. If AI automates those early tasks, employees may lose some of the opportunities traditionally used to develop experience and move into higher-paying roles.
Gartner is seeing a related pattern. Its 2026 research found that 22% of CHROs reported that at least one business leader had stopped hiring for entry-level roles because of AI automation. Gartner also reported that 95% of organizations had implemented AI in some capacity during the previous year, while only one in five had achieved significant or transformational value.
The implication for HR leaders is not simply to add AI skills to job descriptions. Organizations may need to rethink how junior employees acquire expertise when AI takes over portions of traditional entry-level work.
Skills Intelligence Could Become More Important
The Opportunity@Work playbook puts policy implementation at the center, but the underlying workforce challenge has direct implications for enterprise HR technology.
Recruiting platforms increasingly need to translate job requirements into skills, identify transferable capabilities and surface candidates whose experience does not follow conventional career paths. Learning platforms can then help employees close specific capability gaps rather than requiring broad retraining.
This is particularly relevant as AI makes skills change faster. Gartner says organizations should focus on capabilities that can evolve as AI augments, reengineers or creates new forms of work, rather than continuously adding new lists of technical AI skills.
For HR technology vendors, that favors systems capable of maintaining dynamic skills profiles and connecting them to recruitment, learning, performance and internal mobility.
Employers Are Already Testing the Model
The shift is not limited to public-sector policy. Opportunity@Work reports that 77% of employers are now more likely to hire STARs than they were three to five years ago. It also says STARs currently occupy 783,000 more well-paid roles than its 2020 trajectory would have predicted.
Those figures come from Opportunity@Work’s own research and should be viewed in that context. They nevertheless illustrate how changes in hiring requirements can affect the accessibility of higher-paying roles.
The technology layer could determine how scalable those changes become. Applicant tracking systems, talent marketplaces and skills intelligence platforms can either reinforce traditional credential filters or provide employers with more detailed ways to evaluate demonstrated capabilities.
As AI reshapes the labor market, the distinction between talent acquisition technology and workforce development technology is becoming less clear. The next generation of HR platforms may need to connect the two: identifying what a candidate can do today, what skills they could develop next and how AI is changing the work itself.
Market Landscape
Skills-based hiring is becoming an important component of the broader HR technology shift toward skills intelligence and continuous workforce planning. AI is increasing the need for organizations to understand transferable skills while potentially disrupting traditional career ladders.
For employers, the practical challenge is building systems that connect job architecture, recruiting, learning, internal mobility and workforce analytics. For HR technology providers, this creates an opportunity to move beyond credential-based candidate filtering toward more dynamic skills models.
Opportunity@Work’s playbook adds a public-policy dimension to that transformation, while the organization’s STAR research highlights the workforce implications. Together, they point toward a labor market where demonstrated skills and adaptability may become increasingly important signals alongside—rather than automatically behind—formal education.
Top Insights
- Opportunity@Work’s new playbook gives public-sector leaders practical tools for implementing skills-based hiring as AI changes jobs and workforce requirements.
- More than 75 million U.S. workers are classified as STARs, highlighting a substantial talent pool outside traditional four-year degree pathways.
- AI could disrupt career progression if automation removes the entry-level tasks through which workers traditionally develop skills and experience.
- HR technology providers can support the shift through skills intelligence, candidate matching, internal mobility and learning systems connected to workforce data.
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