In a recent LinkedIn post, Ben Eubanks explores the significant impact of generative artificial intelligence (AI) on the job market, particularly concerning early-career professionals. Eubanks highlights new research that contrasts with earlier downplaying of AI’s disruptive potential, emphasizing that the evidence now suggests substantial shifts in employment patterns.
The post draws on large-scale data examining U.S. workers across numerous firms. Eubanks points out the stark differences in employment trends between early-career workers and their more experienced counterparts in roles highly exposed to AI.
“Workers ages 22–25 in the most AI-exposed jobs have seen about a 16 percent relative decline in employment since late 2022, even after controlling for firm-level shocks.”
AI’s Disproportionate Effect on Young Professionals
Eubanks details how AI adoption is affecting different age groups unevenly. According to the data he presents, young software developers, specifically those aged 22-25, have experienced a notable decline in employment opportunities since late 2022, a trend not mirrored by older developers.
This disparity is further underscored by the fact that employment in low-exposure roles has continued to grow across all age groups. The contrast is particularly sharp within high-exposure roles, where younger workers face declines while those aged 35-49 see employment growth.
As Ben Eubanks notes, the crucial nuance is that wages have remained broadly flat. This suggests that organizations are opting to adjust their workforce through headcount reductions rather than altering pay scales.
Automating Tasks, Complementing Experience
The analysis presented by Eubanks indicates a clear pattern in how AI is reshaping job functions. He argues that AI is primarily automating tasks that are codified and easily checkable, often associated with entry-level positions.
Conversely, AI appears to be complementing experienced workers who possess judgment, relational skills, and tacit knowledge. This dynamic is weakening the traditional career ladder, making it harder for new entrants to gain experience.
“AI is: Automating codified, checkable, entry-level tasks. Complementing experienced workers who bring judgment, relationships, and tacit knowledge. Weakening the traditional career ladder into many white-collar fields.”
Rethinking Entry-Level Roles and Career Progression
Eubanks raises critical questions for business leaders and HR professionals regarding the future of work. If AI is automating foundational tasks, then the traditional pathways for gaining experience are being disrupted.
He poses several thought-provoking questions:
- What will replace classic entry-level learning roles?
- How can individuals build experience if the first rung of the career ladder disappears?
- Are businesses prioritizing automation over augmentation where it might be detrimental?
Eubanks suggests the need for innovative approaches to career development, drawing parallels to apprenticeships in trades or residencies in medicine. He emphasizes the historical lesson that proactive planning is essential to avoid reactive, suboptimal outcomes.
“History shows that if we don’t plan proactively then we end up reacting in the moment, which usually doesn’t lead to optimal results.”
The insights shared by Ben Eubanks on LinkedIn serve as a crucial call to action for leaders to anticipate and adapt to the evolving landscape of work shaped by AI, particularly concerning the development and integration of early-career talent.
📝 About This Content
This article is based on insights shared by Ben Eubanks on LinkedIn.
📅 Originally posted on January 6, 2026 | View original post on LinkedIn →