Fortune, relaying comments Chesky made in an ABC News interview, reported that Chesky said, "AI can do a lot of lower-level, more entry-level position jobs. But if no young people can get jobs, then you have no one in the future to do the highly strategic leadership positions," and added, "So we need to make room for people early in their careers, even if AI can do the interns' work."
In that ABC interview, Chesky described AI as a set of tools that still require human oversight and argued that people will continue to value relationships and leadership even as automated systems grow more capable.
His comments come as data from researchers, consulting firms and labor agencies indicate that AI adoption is rising across white-collar work while entry-level job postings, internships and traditional early-career pathways are under pressure.
Key Points
- Brian Chesky warns that cutting early-career roles while adopting AI could weaken companies' future leadership bench.
- Fortune reports that large firms including Amazon, Meta and Salesforce have reduced headcount while increasing their focus on AI.
- Randstad finds global postings for roles requiring 0–2 years of experience declined by 29 percentage points since January 2024.
- Randstad also reports Gen Z averages 1.1 years per job in the first five career years, compared with 1.8 years for Millennials.
- Brookings estimates more than 30 percent of workers could see at least half of their tasks disrupted by generative AI, while McKinsey finds employees use AI more than leaders estimate.
- BLS, the U.S. Labor Department and NACE highlight mixed signals: stable youth participation, expanded apprenticeship funding and a projected 3.1 percent decline in intern hiring.
The AI Paradox in Corporate Hiring
Chesky has repeatedly framed AI as an important capability that should complement, not replace, human roles. He told Fortune, "I think AI is mostly going to be a tool. I don't think it's magic," and told ABC News, "AI is not magic. It needs rules. People need clear instructions."
At the same time, he has linked this view to a specific concern about the structure of corporate workforces. If AI systems absorb a large share of basic analytical, operational or administrative tasks that early-career staff once handled, his argument is that employees will have fewer chances to practice judgment, communication and coordination in lower-risk settings before moving into senior roles.
That concern is shaped by research on how generative AI overlaps with existing white-collar work. A 2024 analysis from the Brookings Institution found that more than 30 percent of workers could see at least 50 percent of their occupation's tasks disrupted by generative AI, with much of that impact concentrated in cognitive and nonroutine activities rather than manual work, according to Brookings.
Fortune notes that large employers, including Amazon, Meta and Salesforce, have cut jobs in recent years while expanding their AI investments, reflecting a pattern in which automation and cost control initiatives advance in parallel.
Separately, TechCrunch reports that more than 22,000 workers at technology companies have been laid off in 2025, drawing on data from Layoffs.fyi to track reductions across the sector.
A 2025 report from McKinsey, based on U.S. surveys of employees and C-suite leaders, adds another dimension to this paradox. McKinsey finds that C-suite leaders estimate only 4 percent of employees use generative AI for at least 30 percent of their daily work, while 13 percent of employees say they already do so, indicating that staff are three times more likely to be using these tools at that intensity than leaders believe.
The same McKinsey research reports that 47 percent of employees expect to use generative AI for more than 30 percent of their work within a year, compared with 20 percent of leaders who expect employees to reach that level of usage in that timeframe.
Together, this evidence shows that generative AI is already embedded in many kinds of white-collar work and that adoption may be driven as much from the bottom up as from executive directives, even as senior leaders face pressure to show near-term cost savings.
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Quantifying the Entry-Level Decline
While Chesky's warning focuses on long-term leadership, several datasets point to short-term shifts in entry-level hiring that could affect how many people ever reach mid-level management.
A 2025 report from Randstad analyzes more than 126 million job postings worldwide and finds that roles requiring zero to two years of experience declined by an average of 29 percentage points between January 2024 and mid-2025.
Randstad reports that junior technology roles fell by 35 percent over that period, while entry-level roles in logistics fell by 25 percent and in finance by 24 percent, indicating that the contraction is broad-based rather than limited to a single sector.
CNBC, citing data from Revelio Labs, reports that entry-level postings dropped by roughly 35 percent from January 2023 through mid-2025, reinforcing the view that opportunities for recent graduates and early-career workers have become scarcer.
Broader cuts add to that picture. Outplacement firm Challenger, Gray & Christmas reports that U.S.-based employers announced 806,383 job cuts between January and July 2025, a 75 percent increase compared with the same period in the previous year.
Within that total, Challenger identifies the technology industry as the leading private-sector contributor to job cuts through July 2025, with 89,251 layoffs, and notes that automation and AI-related changes are among the factors cited for reductions.
Labor force data from the U.S. Bureau of Labor Statistics show that 23.7 million people aged 16 to 24 were working or actively seeking work in July 2025, and that the youth labor force participation rate was 59.5 percent, little changed from a year earlier, according to BLS.
That combination of relatively stable youth participation and reduced entry-level job postings suggests that competition for corporate starting roles has intensified even if the overall number of young people in the labor market has not grown rapidly.
Geography further shapes who can access new AI-related work. A 2023 analysis from Brookings finds that more than 60 percent of generative AI job postings in the year ending July 2023 were concentrated in just 10 U.S. metro areas, with nearly one quarter in the San Francisco Bay Area.
If employers consolidate both AI-intensive roles and early-career openings in a small group of regions, this can limit pathways into corporate leadership for young workers who live elsewhere or cannot easily relocate.
Taken together, these figures indicate that the contraction of entry-level opportunities is broad, measurable and influenced by both technological change and general cost-cutting, rather than being a minor fluctuation tied to a single business cycle.
Generational Workforce Patterns
The same Randstad research highlights how younger workers are responding to these conditions. Based on a global survey of 11,250 workers and the job posting analysis, Randstad reports that Gen Z employees average 1.1 years with an employer during their first five years in the workforce, compared with 1.8 years for Millennials, 2.8 years for Gen X and 2.9 years for Baby Boomers.
The report also notes that 22 percent of Gen Z respondents had left a job within a year and that 33 percent planned to change jobs within the next 12 months, with many citing limited progression and purpose in their current roles.
These shorter stints can give young professionals experience across multiple organizations and business models, but they also reduce the time available for structured development, long-term projects and internal mobility programs that have traditionally helped employers evaluate leadership potential.
Data from the Pew Research Center show that AI usage is already a routine part of many jobs. In a 2025 survey, 21 percent of U.S. workers said that at least some of their work is done with AI, up from 16 percent a year earlier, while 65 percent reported that they use AI rarely or not at all.
Pew finds that workers younger than 50 and workers with at least a bachelor's degree are among the most likely to use AI at work, and that the increase in workplace AI use over the previous year was driven largely by workers with higher education levels.
McKinsey's U.S. survey offers a related perspective on expectations. While 13 percent of employees report already using generative AI for more than 30 percent of their daily work, 47 percent believe they will reach that threshold within a year, compared with 20 percent of C-suite leaders who expect employees to do so, according to the firm's 2025 report.
For employers, this combination of shorter tenures, fewer entry-level postings and rising employee use of AI tools means that a significant share of skill acquisition and experimentation is happening in shorter windows and sometimes outside formal training structures.
If early-career cohorts cycle through roles quickly and in smaller numbers, fewer employees will accumulate the mix of technical familiarity with AI systems and organizational knowledge that senior leadership roles often require.
The Human Elements of Leadership
In his ABC News interview, Chesky drew a distinction between what AI can do and what he views as the enduring requirements of leadership. "People are still going to want relationships," he said. "Leadership is still going to matter."
He linked this view to a broader philosophy about technology, adding, "AI is not magic. It needs rules. People need clear instructions," and emphasizing that human judgment and accountability remain central even when AI tools support decision-making.
A 2025 commentary from Brookings on workforce transitions argues for investment in "workforce capacity development" as part of a national response to AI and other structural changes. The piece stresses the importance of mentoring, networking, credentialing, and placement support that help people move between occupations with dignity.
Executive search firm Spencer Stuart reports that the average age of newly appointed S&P 500 CEOs fell to about 53.8 years in 2022 after previously peaking at about 56, implying that many leaders have accumulated several decades of experience before taking the role.
That long preparation period means that decisions about hiring and developing people in entry-level and mid-level roles today will influence the pool of potential CEOs and other senior executives well into the 2030s and 2040s.
Chesky's argument links these timelines by suggesting that even if AI handles more tasks at the start of a career, companies still need employees who have progressed through teams, projects and managerial responsibilities so they can eventually oversee both people and complex technical systems.
Industry Response and Future Implications
Public policy and employer behavior show partial efforts to support early-career development, although they have not fully offset the decline in entry-level postings identified by private-sector data.
In 2023, the U.S. Department of Labor announced $65 million in grants to help states expand access to registered apprenticeships in high-growth, high-demand industries, according to a department release from the U.S. Department of Labor.
Registered apprenticeships combine paid work with structured learning, which can create alternative talent pipelines for occupations that do not rely solely on traditional entry-level office roles.
At the same time, the National Association of Colleges and Employers reports that overall intern hiring is expected to fall 3.1 percent for the 2024–25 academic year, even though more than 70 percent of surveyed organizations plan to maintain or increase their intern hiring levels, according to an April 2025 article from NACE.
NACE attributes much of this projected decline to larger employers trimming their internship programs, while some also broaden the pool of eligible students beyond rising seniors, which may change how early-career talent moves into full-time roles.
When set against Randstad's evidence of fewer entry-level postings and Challenger's record of higher job cuts, these apprenticeship and internship figures suggest that structured early-career programs are evolving but may not fully replace the volume of traditional junior roles that previously fed corporate leadership pipelines.
Chesky's warning aligns with this data environment rather than standing apart from it. Brookings research documents high exposure of white-collar tasks to generative AI, McKinsey finds that employees are adopting AI tools more extensively than leaders assume, and labor statistics show stable youth participation alongside tighter competition for the first rungs of many career paths.
The central question for companies is therefore not only how much work AI can perform, but how firms will organize hiring, training and progression so that enough people accumulate the experience needed to manage both human teams and advanced technologies over the coming decades.
The available evidence indicates that decisions made now about entry-level hiring, internships and apprenticeships will influence whether organizations face leadership shortages later, even if AI capabilities continue to improve.
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