All too often, jobseekers and employers seem to exist in non-compatible realities. While jobseekers flood the job market with descriptions of their generalized skills in communication, leadership, and problem-solving to fill various roles in different sectors, employers are looking for the more specific skills that will get the job done, say the authors of a report from the Wharton School and Accenture. And they propose that AI is accelerating this shift from a role-based economy to a skills-based economy. The researchers have created a tool, the Wharton–Accenture Skills Index (WAsX), to measure which skills fall into the over-supplied and under-supplied categories at a given point in time. They have also teased out from role-based job descriptions how specific skills, over time, independent of the job role, affect wages. They refer to WAsX as a “recurring, empirical benchmark.”
The authors focus on findings from the life sciences sector, where the disconnect between jobseekers’ descriptions of their skills is highly mismatched with what employers are looking for. They show, by mapping skills surpluses and deficits over time, that the organization of the labor market has shifted. Jobseekers in this sector “overwhelmingly emphasize broad traits such as communication, accountability and high-level leadership,” while employers “struggle to find the specialized capabilities that advance scientific work.” The consequence of this shortage, say the authors, is a decrease in research productivity and scale-up operations.
When it comes to wages, WAsX clearly shows that technical scientific depth and strategic or management-oriented skills offer a wage premium. Specifically, “(m)anagerial skills such as strategic analysis and healthcare management, and technical scientific skills such as biometric technologies, electrophoresis and advanced lab procedures correspond with higher predicted salaries, reflecting their scarcity and impact.”
The authors propose that the disconnect between how workers market themselves and what employers need is becoming more critical as AI changes the way work gets done. AI is not merely automating tasks; it is changing how specific tasks are accomplished. WAsX has shown that demand is falling in skills tied to routine content creation and structured, repeatable cognitive work, while demand is rising for jobs that require judgement, coordination, compliance, and domain-specific execution. This means that the economic value of skills is changing. Those that can be automated are becoming less valuable, while those that require judgement, contextual understanding, and hands-on execution are becoming more valuable.
WAsX measures these changes as they occur, offering insights for employers, workers, and educators. The authors advise employers to break roles into their underlying tasks and capabilities. This decomposition clarifies which tasks agents or robots can assume, and which require human judgment, coordination or domain expertise. When leaders examine work at this level, they gain the flexibility to redesign jobs, allocate tasks more efficiently and plan their workforce around how work truly gets done—rather than around static job titles.
The advice for workers is to focus on higher-value skills. They also advise workers to use advanced AI to build higher-level capabilities, such as for “generating practice scenarios, explaining technical concepts, simulating tasks and accelerating mastery of tools or methods.”
The report advises educators to shift more curriculum toward “specialized, job-ready capabilities and by expanding labs, project-based learning and experiential formats that build depth rather than relying predominantly on generalist preparation.”
Read the Wharton School and Accenture report, The Skills Mismatch Economy: Insights from the Wharton-Accenture Skills Index, here.