Research Highlights a Growing Disconnect Between AI Adoption and Workforce Strategy

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As organizations accelerate AI adoption, a growing number of executives are finding themselves responsible for leading a transformation they do not yet fully understand.

New research from LinkedIn suggests that this leadership gap is becoming one of the most significant barriers to enterprise AI adoption. According to a survey of 1,252 C-suite leaders across the U.S., U.K., and India, 50% acknowledge they lack clear visibility into the skills and roles their organizations will need as AI matures, while 78% say they are implementing AI faster than they can effectively measure its impact.

The findings point to a broader challenge facing senior leadership teams: AI is not simply introducing new tools into organizations; it is forcing leaders to rethink how work is structured, managed, and measured.

“We’re at this place where the C-suite is navigating this moment without a real playbook they can rely on,” said Mark Lobosco, Chief Business Officer at LinkedIn, in an interview with Fortune.

The absence of a clear roadmap has exposed what LinkedIn describes as a workforce “blind spot.” But the issue appears to extend beyond uncertainty about future skills. It reflects a deeper tension within organizations, where leaders are being asked to champion transformation while simultaneously questioning the management practices and assumptions that helped define their careers.

For many organizations, the initial response has been a top-down push for AI adoption. Lobosco argues that approach is unlikely to succeed on its own. Effective transformation requires employees to view AI as a tool for career growth rather than job displacement, a shift that depends as much on organizational trust as technological capability.

At the same time, executives cannot delegate responsibility for AI transformation. Leaders who lack firsthand experience with AI tools may struggle to build credibility with employees expected to incorporate those tools into daily work.

“You can’t ask your team to do something that you don’t know how to do yourself,” Lobosco said.

The challenge is becoming more urgent as organizations create entirely new categories of work. According to the survey, 82% of C-suite leaders report the emergence of new AI-related roles since 2022, including AI engineers, responsible AI architects, and forward-deployed engineers. Yet many of the same organizations remain uncertain about what their workforce structures will look like in the next two years.

The disconnect highlights a growing execution challenge. Companies are investing in AI talent and experimentation while still lacking a clear vision for how technology will reshape workflows, decision-making, and organizational design.

Leadership advisers increasingly argue that traditional management approaches may be poorly suited to this environment. Carolyn Dewar, founder of McKinsey’s CEO practice, recently argued that the execution discipline that drove success over the past decade is becoming less effective in an era defined by uncertainty and rapid technological change. Instead, leaders must rely more heavily on judgment, strategic imagination, and adaptability.

Operational leaders are encountering similar realities. At Fortune’s COO Summit, Okta President and COO Eric Kelleher noted that managers have historically been trained to optimize human headcount, not coordinate work between human and digital workers. As AI becomes embedded into business processes, organizations may need to rethink budgeting, workforce planning, and performance management from the ground up.

The challenge, then, is not merely adopting AI but redesigning organizations around it. Much like factories initially used electricity to power existing machinery before eventually reconfiguring entire production systems, many companies today are layering AI onto existing workflows rather than fundamentally rethinking how work gets done.

The question for leadership teams is whether they can evolve quickly enough to lead that redesign. LinkedIn’s findings suggest that while companies are moving aggressively on AI, many executives are still determining what the destination should look like—and how to bring their organizations there.