Goodbye, empty job titles. Along with transforming the workforce, AI is now rewriting the résumé. A new recurring report, the Wharton-Accenture Skills Index, reveals a mismatch between how workers present themselves and how employers hire and compensate. The proposed solution for the modern job hunt? Less attachment to titles and more emphasis on skills.
The index, abbreviated WAsX, is a collaboration between the Wharton AI & Analytics Initiative and Accenture, a global professional services company spanning industries from life sciences to industrial. The index was released in January and co-authored by Wharton’s vice dean of AI and analytics and K.P. Chao Professor Eric Bradlow, along with Accenture’s James Crowley W96 and Kenneth Munie WG04, who each have more than 20 years of experience with the firm, and Selen Karaca-Griffin, who leads the research program for Accenture’s partnership with Wharton. The authors suggest that skills are the new currency of the labor market, and they have built WAsX to measure them. The index will work as a sort of skills thermometer, continuing to track which ones are hottest in demand and coldest in decline.
Bradlow’s research has been published in the Journal of the American Statistical Association and the Journal of Marketing Research, among others, but as he told Dan Loney on Knowledge at Wharton’s This Week in Business podcast, some of the impetus for creating the index was anecdotal. “I talk to alumni, travel the world, talk to our current students,” Bradlow said. “The minute I’m done talking, the number one question asked of me is, ‘What should my high-schooler be studying? What jobs are going to be left over?’ I think it’s the most significant question from our side — from the academic side. What should we be training students to do?”
The Skill Cluster Methodology
Combining Accenture’s expertise in consulting for the world’s leading businesses with Wharton’s academic research, WAsX takes a scientific approach to examining which skills matter most in the age of AI. The report’s datasets scraped approximately 220,000 websites to gather more than 100 million unique U.S. job postings and upwards of 150 million people profiles. As expected, the online postings skewed toward white-collar positions, so WAsX also pulled in employment totals from the U.S. Bureau of Labor Statistics to serve as an “anchor,” better reflecting the job market as a whole.
The next step in evaluating which skills were AI-proof was to create about 2,000 “skill clusters.” Researchers grouped 33,000 unique skills and 442 skill subcategories; for example, the cluster “MS Office 365 Suite” would include the more granular skills of Microsoft Word, Microsoft Excel, and Microsoft PowerPoint. Accenture also tapped into the powers of artificial intelligence itself when building the report, using it to explore job-posting data dating back to 2022 (when OpenAI released ChatGPT) and analyze demand in skill clusters.
The Mismatch Problem
When examining the data, researchers noticed that the way workers were presenting themselves wasn’t matching up with employers’ wish lists. The skills most often cited in worker profiles but least often in job postings were leadership and accountability, communication, problem-solving, project management, and computer science. In contrast, the skills employers cited most often but workers cited least often included public speaking, digital marketing, public relations, web development, and teaching methodologies.
Even a traditionally straightforward career path like life sciences isn’t immune to this problem. An example from that sector illustrated the mismatch well: It was an industry where the gap between what workers listed on their résumés and what employers said they wanted was particularly vast. Employers were looking for skills that would advance scientific work, including lab techniques, analytical chemistry, and data-rich experimentation, along with environmental and hazardous materials management. Instead, all they found were broad traits such as communication, accountability, and high-level leadership. This could have grave consequences for the world, forming bottlenecks that would slow life-saving research.
The mismatch problem reveals that advice workers might have received to generalize their profiles may now be outdated. Across industries, researchers found that job seekers were highlighting “safe” and general skills such as teamwork and problem-solving. Generalist traits such as these make it hard for employers to differentiate one profile from another — and thus harder for job seekers to land positions that are right for them.
The skills that employers did value were specialized and execution-oriented — the kind that determine whether work moves from concept to completion. Employers also placed a premium on technical depth, scientific fluency, digital and analytical precision, operational expertise, and role-level leadership. They looked for workers who could shape decisions in real time, which they rarely found on job-seeker profiles.
“Go back 30 years,” Bradlow said on This Week in Business. “‘What job should I go into?’ That’s not the right question anymore. It’s ‘What skills do I need to have?’”
The Price of a Skill
In analyzing the datasets, the researchers came upon an interesting phenomenon: They could actually put a price on a skill based on its demand. Context matters in this area. For example, a sales representative could boost salary by $8,000 by including the skill “strategic analysis” on a résumé, while a validation engineer could decrease salary by $10,000 for noting the same skill. AI was already shattering the idea that some skills are always “high value,” but WAsX confirmed it, painting a picture of an ever-shifting labor market.
The implication that the skills gap carries real economic consequences continued throughout the report. Researchers again relied on their fluency with AI tools, using machine learning to map out a few of the skill clusters and examine which skills had a positive impact on salaries when they appeared in job postings. Salaries were increased the most when the skills treatment planning, configuration management, and health-care management were present.
It came as no surprise that task-based or routine operational skills — those that are widely available or susceptible to automation — led to lower salaries. From these patterns, researchers concluded that employers reward skills that are scarce, consequential, or central to decision-making, while they discount skills that are abundant or easily substituted.
“The impact that generative AI will have on all jobs is in some sense immeasurable,” Bradlow said in a Knowledge at Wharton summary of the report. “We all have a responsibility to figure out how to leverage generative AI to do our jobs better, more efficiently, and with more impact. It is this set of skills — human plus AI — that we are educating our students on at Wharton.”
AI Is Redistributing Value
A positive outlook was a theme throughout the Skills Index: Instead of viewing AI as their replacement, the report suggested, workers should focus on the skills they bring to the table and use them in concert with AI. But the researchers found the impact of AI on jobs can be more nuanced than the simple automation of routine tasks.
WAsX tracked shifts in the talent landscape by measuring changes in demand for different skill clusters for three years. The report identified the top 10 skill clusters that have high exposure to AI automation or augmentation and examined their shifts in demand. The steepest climb in demand was for regulatory compliance skills, while research and analysis skills took a nosedive. Marketing strategy and project management remained relatively stable.
The authors used these clusters to identify patterns in how AI is redistributing economic value across skills. For example, although generative AI has decreased employer demand for writing and routine analysis, it is increasing demand for skills that require judgment, coordination, and regulatory/compliance expertise. Operations management, which requires real-time coordination and contextual decision-making, also remained in solid demand.
WAsX aims to measure these changes in job functions as they unfold, helping the public make evidence-based career decisions and anticipate where demand — and scarcity — is likely to grow and making recommendations on how workers might navigate these shifts.
Action Steps for All
WAsX suggested actionable steps that employees, employers, and educators alike can take to thrive in this new job market. For those looking for work, the report recommends that they reframe their résumés as portfolios of high-value skills. The goal is to stand out among other applicants, so describing role-specific capabilities with great precision and detail is a must. The co-authors also suggest that job seekers prioritize upskilling and utilize AI to strengthen their technical skills.
“I go directly to the bottom of people’s résumés, which is where they list their skills,” Bradlow said on This Week in Business. “That’s what everyone’s hiring against today.” He added that job seekers can use AI to prepare for the skills assessments they’ll face when searching for their next roles.
For employers, the study proposes that they take stock of the skills they already have reflected on their teams, identifying surpluses and deficits. That way, they can better target their hiring and direct reskilling investments to where they matter most. “Leaders need more than intuition — they need evidence,” Crowley, the global products industry practices chair at Accenture, told Knowledge at Wharton. “The Wharton-Accenture Skills Index gives organizations a way to precisely measure where skills are falling behind, where they are accelerating, and what that means in real economic terms.”
WAsX also has implications for the next generation of workers. The authors advise educators to rebalance curricula toward job-ready, economically scarce capabilities. They also advocate using AI in the classroom through simulations, practice environments, and feedback tools. Educators (especially business schools) should teach students how to highlight their skills effectively, with clarity and relevance — emphasizing specific techniques and applied experiences rather than broad traits. And there is no age limit on being a student.
“Be a lifelong learner,” Bradlow told the Philadelphia Inquirer in an interview about WAsX. “Skills will always be valued. Jobs in a particular workflow can go away. People with skills will be hired.”
Published as “AI’s Talent Reset” in the Spring/Summer 2026 issue of Wharton Magazine
