Human resources teams face difficulty pinpointing which skills employees currently possess during a period of accelerated AI integration, a problem experts describe as a “skills visibility gap.” Although HR leaders understand the competencies required to work alongside automation, only 43% express confidence that their workforce actually holds those abilities, according to research by The Harris Poll for the University of Phoenix, published last week.
The discrepancy reveals a deeper issue: HR departments frequently depend on managers’ evaluations or performance reviews to confirm skills, but less than half of survey respondents said managers were prepared to recognize or correct skill deficiencies. This problem intensifies as HR transitions from conventional hiring practices to assessing how work is executed—whether by human workers or machines.
Beyond technical abilities, AI adoption is eroding employees’ capacity to exercise critical reasoning and judgment, two key traits for effective collaboration with automated systems, IBM’s latest research shows. Over time, workplace AI may also diminish workers’ specialized expertise in certain job functions as systems take over repetitive tasks. These trends force HR teams to rethink their priorities, shifting focus toward “durable skills”, qualities like communication, teamwork, and problem-solving, that retain relevance even as automation redefines roles. However, Nathan Jones, vice president of product management at the University of Phoenix’s workforce solutions division, argues that this approach must broaden. “The workforce conversation needs to move beyond technical skills versus durable skills,” he said. “Increasingly, people need both.”
This dual emphasis reflects broader industry movements. A recent Graduate Management Admission Council survey found that recruiters now prioritize AI-related skills and strategic thinking as the two most critical categories for future hiring decisions. The data suggests employees will need to combine technical expertise with human-centered competencies to deliver meaningful contributions in AI-powered workplaces. Yet compensation structures have not adapted accordingly. Payscale’s latest findings indicate that salary frameworks still lag behind the growing demand for AI-related skills, while job seekers increasingly demand higher pay for proficiency in these areas. The mismatch risks alienating workers who feel their ability to adapt to new technologies is not properly rewarded.
To address this, some companies are investing in upskilling programs that blend technical training with soft-skill development. These efforts aim to close the visibility gap by supporting environments where workers can demonstrate and refine both their existing strengths and emerging capabilities. Still, the effectiveness of such programs hinges on HR’s ability to measure progress beyond traditional metrics, such as certifications or performance ratings, and instead track real-world application of skills in AI-assisted workflows.
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