A new University of Phoenix study finds that HR leaders are considerably more confident about knowing which skills employees need than knowing whether workers actually possess them, exposing a workforce skills visibility gap as AI changes job requirements.
Organizations are gaining confidence in identifying the skills their employees need, but far fewer are confident those workers actually have them. That disconnect is emerging as a significant challenge for HR teams as artificial intelligence, automation and other technologies reshape jobs and workflows.
A new Future of Skills Development report from University of Phoenix, based on a Harris Poll survey of 755 U.S. HR leaders, found that 64% of respondents are very confident they know the specific skills employees need to perform their jobs. Only 43% are equally confident that employees actually possess those skills.
The 21-percentage-point difference highlights a problem that is becoming more important as organizations attempt to build AI-ready workforces: knowing what capabilities are required is not the same as having reliable visibility into the capabilities already available internally.
That distinction could affect everything from workforce planning and internal mobility to recruitment and employee development.
The research also shows that HR leaders are struggling to predict how requirements will change. Twenty-seven percent identify keeping pace with technological advances, including AI, as their biggest source of uncertainty when planning future workforce skills. Just 46% are very confident they can predict the skills employees will need two to three years from now.
For HR technology providers, that creates an opportunity to move skills intelligence beyond static competency frameworks. Organizations increasingly need systems capable of mapping existing employee capabilities against changing job requirements and identifying where development investments are likely to have the greatest impact.
The University of Phoenix findings suggest that the challenge is not simply an AI skills shortage. HR leaders are also balancing technical capabilities with skills that are harder to quantify.
Nearly 59% of respondents say soft or durable skills—including communication, collaboration and problem-solving—are their organization’s primary talent-development focus, compared with 37% prioritizing technical skills.
That combination is becoming more relevant as AI takes over individual tasks rather than entire occupations. Employees may need to understand new AI tools while simultaneously exercising judgment, communicating effectively and adapting workflows around them.
Recent IDC research makes a similar argument, suggesting that human capabilities such as judgment, critical thinking and collaboration remain important as enterprises move from AI experimentation toward broader deployment.
The problem extends into hiring. University of Phoenix found that HR leaders most often rely on managers’ direct knowledge and performance reviews—both cited by 51%—to assess the skills employees currently have or need. Only 49% say managers are very prepared to identify, assess and discuss skill gaps with employees.
That reliance on managerial judgment can make skills data difficult to standardize. Two managers may assess the same capability differently, while performance reviews often provide only periodic snapshots of employee development.
Formal assessments are becoming one way organizations address that problem. Thirty-eight percent of respondents said they feel confident that an applicant’s skills and ability to perform a role have been properly verified only after a skills evaluation, assessment or technical test. More than 71% said their organizations use some form of digital credential—including microcredentials, digital badges or digital wallets—to verify skills for at least some applicants.
The findings point toward a broader shift in HR technology from learning management to skills intelligence. Rather than simply recommending courses, emerging platforms are attempting to connect skills data with job requirements, assessments, learning pathways and internal mobility.
Gartner is also emphasizing the need for stronger HR skills data as AI adoption expands. Its 2026 HR guidance says only 7–8% of HR leaders report having reliable skills data or managers equipped to use AI effectively, underscoring the infrastructure challenge behind workforce transformation.
The University of Phoenix research further shows that many organizations have not yet formalized the process. Only 44% of HR leaders say their organizations regularly conduct formal skills-gap analyses, while 51% say their organizations communicate very clearly which skills employees need to develop for future roles.
The situation also varies by industry. Manufacturing respondents were more likely to prioritize technical skills, with 56% putting greater emphasis on them, while 64% of financial-services respondents prioritized durable skills. Healthcare respondents reported comparatively stronger confidence in both identifying required skills and knowing whether employees possess them.
For HR leaders, the implication is straightforward but difficult to execute: workforce readiness requires visibility into both sides of the equation. Companies need to know what skills changing jobs will demand and have credible evidence of what their employees can actually do.
As AI accelerates the rate of change, that visibility could become a core layer of the HR technology stack. Learning platforms, talent marketplaces, performance systems and workforce-planning tools will increasingly need to share skills data rather than treating development as a separate HR process.
The organizations best positioned for the AI-driven workplace may therefore not be those that simply train employees fastest, but those that can continuously identify emerging requirements, measure existing capabilities and connect the two with evidence.
Market Landscape
The HR technology market is moving toward skills-based workforce management, combining skills intelligence, assessments, learning, internal mobility and workforce planning. AI is accelerating the need for this shift because job requirements can change faster than traditional competency frameworks and annual development cycles.
The competitive landscape includes HCM vendors such as Workday, SAP and Oracle, learning platforms, talent marketplaces and specialist skills-intelligence providers. The emerging differentiator is increasingly the quality and currency of an organization’s skills data.
For University of Phoenix, the findings also reinforce an opportunity for workforce solutions that connect employer demand with learning and credentialing. The broader market challenge is turning skills data into reliable evidence that can inform hiring, development and redeployment decisions.
Top Insights
- HR leaders are much more confident identifying required skills than verifying whether employees actually possess them, revealing a persistent workforce visibility problem.
- AI is increasing uncertainty around future job requirements, making static competency frameworks less useful for long-term workforce planning and development.
- Durable skills remain a major priority, suggesting AI transformation requires technical literacy alongside communication, collaboration, judgment and problem-solving capabilities.
- Digital credentials and skills assessments are gaining importance as employers seek stronger evidence of candidate and employee capabilities.
- Skills-gap analysis remains inconsistent, leaving HR teams with limited visibility into where workforce capabilities align—or fail to align—with future demand.
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