IBM Study Finds AI Widens Gap Between Employee and Executive Skill Views

A new global study from the IBM Newsroom highlights a widening gap between what leaders expect and what employees feel they can deliver in an AI-driven workplace. The research, conducted by the IBM Institute for Business Value, surveyed 1,500 Chief Human Resource Officers and 8,800 employees worldwide. The core finding is a disconnect in priorities: while 71% of CHROs identify the ability to supervise and validate AI outputs as the most essential skill, only 29% of employees rank human judgment as important.

This mismatch occurs against a backdrop of growing anxiety among the workforce. Sixty percent of employees express concern about skills erosion, with critical thinking cited as the most frequently declining capability. The stakes are tangible for organizations, as those that clearly define whether workflows are human-led or AI-executed report an 18% reduction in risk and a 20% improvement in quality. However, nearly half of organizations do not involve the CHRO in defining AI strategy, leaving a significant leadership void in this transition.

Accountability gaps increase employee risk

One of the most pressing trade-offs identified is the lack of clear accountability structures. Forty-three percent of employees report that when AI systems fail, the blame falls directly on them. This creates a hostile environment for challenging machine outputs, with 41% of CHROs acknowledging that employees may not feel safe overriding AI decisions. The data suggests that when HR shares responsibility for defining which decisions remain human-led, employee confidence to question AI recommendations rises to 76%, compared to just 43% where HR is merely advisory.

Furthermore, AI adoption is creating what executives describe as "invisible" work. Eighty percent of CHROs believe that employees are spending significant time validating AI recommendations, fixing mistakes, and managing exceptions. For 42% of employees, this additional labor either increases their workload or goes unrecognized. This hidden burden complicates efforts to measure true productivity, as the gains from automation are often offset by the manual effort required to ensure accuracy.

HR functions lag in AI adoption

Ironically, the department tasked with leading AI transformation is often the slowest to adopt the technology. Seventy-two percent of organizations make limited or no use of AI within their own HR functions. CHROs themselves rate their teams' capabilities low in AI literacy, with only 13% reporting high proficiency. This internal lag creates a credibility gap, as HR is expected to guide organizational change while struggling with basic implementation and measurement of AI tools.

The study indicates that organizations with mature HR AI capabilities, including strong governance and measurement frameworks, are nearly twice as likely to report positive business KPIs. The catch is that building this maturity requires a coordinated approach across the C-suite, which 73% of CHROs say they struggle to achieve. Without this coordination, the potential benefits of AI remain locked behind operational inefficiencies and unclear roles.

Redesigning work for human value

To bridge the gap between executive intent and employee reality, the study suggests a fundamental redesign of work processes. Rather than viewing AI as a simple tool to be added to existing jobs, organizations must define where human judgment is indispensable. This involves explicitly marking tasks as human-led, AI-assisted, or AI-executed. By doing so, companies can protect the unique human capabilities that drive value, such as problem framing and ethical judgment, while allowing AI to handle routine processes.

The ultimate stake is the preservation of critical thinking in the workplace. When judgment is built into how work is done, 62% of CHROs report growing employee confidence in AI-enabled decisions. Conversely, where this structure is absent, confidence declines. The path forward requires HR to move beyond an advisory role and take active ownership of the human side of AI deployment, ensuring that technology serves the workforce rather than eroding its skills and security.