AI’s Real Impact: Shifting Roles, Not Just Displacement, According to Jason Averbook

In a recent LinkedIn post, Jason Averbook explores the nuanced impact of Artificial Intelligence on the U.S. job market, moving beyond the headline figures of potential displacement to highlight a more significant trend of role transformation.

Averbook begins by referencing a widely cited statistic from Tufts University Digital Planet indicating that 9.3 million U.S. jobs face AI displacement risk in the next two to five years. However, he directs attention to accompanying data from Harvard Business School that offers a more detailed picture.

“Job postings for automatable, checklist-style roles: down 17%. Job postings for roles requiring human judgment and AI collaboration: up 22%.”

This contrast, Averbook argues, reframes the narrative around AI. Instead of a blanket threat, the data suggests a bifurcation of the job market. As Jason Averbook notes, “The work that can be described as a process is exposed. The work that requires you, your judgment, your relationships, your ability to read a room and make a call with incomplete information, is gaining value.” This indicates a growing demand for skills that complement AI rather than those that can be easily automated.

The Disconnect Between Perception and Reality

Despite the potential for AI to augment human capabilities, Averbook points to a significant disconnect in how employees perceive its impact. He cites ADP Research indicating that a mere 22% of global workers believe their job is safe. This sentiment is particularly concerning, as Averbook highlights:

“Nearly four out of five people are going to work every day inside organizations where AI is supposed to be making things easier, and reporting that it isn’t.”

This widespread feeling of AI not delivering on its promise of ease suggests a deeper organizational challenge beyond the technology itself. Averbook posits that the lack of realized productivity gains stems from a fundamental misunderstanding by many leaders.

Adoption vs. Embodiment: The Crucial Distinction

Averbook emphasizes a critical distinction that many organizations are missing: the difference between merely adopting AI and truly embodying it. He explains that adopting AI often involves a simple procurement decision, while embodying AI signifies a deeper transformation.

CFO Survey Data Reveals Divergent Outcomes

Further data from a National Bureau of Economic Research and Duke University CFO survey underscores this point. Averbook shares that AI-driven job cuts are projected to be nine times higher this year compared to the previous year. Paradoxically, workers who are actively using AI tools report significant increases in time spent on certain tasks.

“…workers using AI tools report time on certain tasks has increased by up to 346%.”

This seemingly counterintuitive finding, according to Averbook, illustrates the gap between superficial implementation and genuine integration. He concludes that many companies have engaged in the former – AI adoption as a procurement exercise – while mistakenly believing they have achieved the latter – a transformative embodiment of AI. Averbook’s analysis stresses the need for leaders to move beyond simple acquisition and focus on the strategic integration and cultural shifts required to truly leverage AI’s potential, thereby enhancing rather than merely displacing human roles.