Podcast Summary: "Where Did All the Entry-Level Jobs Go?"

Azeem Azhar’s Exponential View
Guest: Ben Zweig, CEO of Revelio Labs
Original Air Date: November 14, 2025

Episode Overview

This episode explores the recent downturn in entry-level job opportunities, particularly as it relates to the rise of artificial intelligence and changing labor market dynamics. Azeem Azhar invites Ben Zweig, CEO of Revelio Labs, to discuss what’s actually happening in the workforce, how AI is truly impacting entry-level positions, the complexities of labor signals, and what both organizations and early-career job seekers can do to adapt.

Key Discussion Points & Insights

1. The Current State of the Labor Market

• Headline Trends: Hiring and attrition are both at a low point, affecting young and entry-level workers especially ([02:02]).
• AI’s Role: While AI is credibly affecting some entry-level roles (especially in AI-exposed occupations), it’s not causing mass technological unemployment ([02:02], [03:00]).
• Managerial Risk Aversion: Employers are becoming more risk-averse and avoiding the risks associated with hiring and training entry-level workers, opting for experience over potential ([03:30], [04:45]).

Quote:

“We are seeing decreases in demand for entry-level workers and that is particularly concentrated among AI-exposed roles.”
— Ben Zweig ([03:13])

2. How Revelio Labs Gathers and Interprets Data

• Private Sector Data: With government agencies like the BLS behind on labor reporting, Revelio uses micro-level data from sources like LinkedIn/resumes to track employment flows, job changes, and hiring trends ([06:24]-[07:15]).
• Comparative Analysis: Revelio’s global approach allows for deeper, more timely insights than country-by-country statistics ([07:15]-[08:35]).

3. Evidence and Complexity of the AI Impact

• Academic Papers & Confirmation: Revelio’s analysis supports findings such as in Brynjolfsson’s “Canaries in the Coal Mine”—AI-exposed entry-level positions see sharper declines in hiring than senior-level ones ([11:14]-[11:30]).
• Definition of Exposure: AI exposure isn’t about full jobs; it’s about the specific tasks within jobs that can be automated ([12:12]).
• Caution on Causality: It’s likely a combination of expected AI impact and general business uncertainty causing hiring slowdowns—not just actual AI substitution ([13:20]).

Quote:

“What we’re actually seeing is less of a commentary on what AI is doing and it’s more about what the expectation of AI is doing.”
— Ben Zweig ([13:40])

4. The Power of Managerial Expectations & Exuberance

• Hiring Delays: The belief in rapid, transformative AI has made managers cautious about long-term hiring, causing them to delay entry-level hires ([14:07]-[15:50]).
• Potential for Mismatch: If these expectations outpace reality, it could have harmful effects not only for grads but also for businesses ([14:55]).

Quote:

“A young grad hire is for three years, not just for three weeks…even if AI can’t do what people say…managers believe it might be able to do that…and are putting off long-term hiring.”
— Azeem Azhar ([14:07])

5. Task Automation, Adaptation, and Job Evolution

• Adaptive Organizations: Organizations that can fluidly reconfigure work in response to changing demands (including AI automation) are more resilient ([17:44]-[19:24]).
• Jobs as Bundles of Tasks: The new theory (and emerging practice) is to view jobs as evolving bundles of tasks rather than static roles ([19:24]-[22:29]).

Quote:

“An organization that can be fluid... where people do what the business needs. And business needs change all the time.”
— Ben Zweig ([19:24])

6. Real-World Application and Organizational Challenges

• Conversion to Practice: Transitioning the ‘jobs-as-tasks’ theory into practical reality is challenging, especially for large, hierarchical organizations ([22:50]-[27:52]).
• Limitations of Internal Mobility: Internal reallocation and reskilling ideas often fail because managers are reluctant to lose valued staff, and tacit knowledge isn't easily moved between teams ([27:52]-[30:45]).

Quote:

“One thing that I think is an overrated idea bordering on bad idea is re-skilling and reallocating people to where the needs are highest.”
— Ben Zweig ([27:52])

7. Flexibility vs. Stability, and Worker Wellbeing

• Tradeoffs: Adaptive, flexible organizations risk creating instability and eroding psychological safety and job dignity ([30:45]-[31:49]).
• Job Crafting: Allowing employees to have some self-determination over their evolving roles (‘job crafting’) can help maintain integrity and engagement ([32:26]-[33:33]).

Quote:

“The people in the organization... should be given a lot of discretion about how to reconfigure their work. And I think that, that ultimately respects their intelligence.”
— Ben Zweig ([33:13])

8. The Technical Evolution and Future of Skills

• Three Vectors of AI Change: AI is getting:
  1. More generalizable
  2. Capable of handling more complex multi-step tasks
  3. Supported by better ‘agentic’ (orchestrating) frameworks
     ([33:33]-[36:26])
• Orchestration as a Core Skill: The most valuable human skill may become the ability to orchestrate and coordinate between systems, tasks, and people ([36:26]-[38:19]).

9. Advice for Entry-Level Workers and Graduates

• Develop Orchestration Skills: “Managing projects end-to-end” and showing ability to coordinate and complete initiatives is increasingly important ([39:26]-[46:37]).
• Strong Signaling: Costly and concrete signals (like undertaking substantial, challenging projects, or advanced degrees) are more credible than easily obtained credentials ([44:52]-[46:02]).
• Network and Immerse: Build industry connections and learn the domain-specific language, as networking is as important as ever ([46:37]-[47:28]).

Notable Quotes:

“Taking on an ambitious project and just grinding it out…I think that is something that…will pay dividends.”
— Ben Zweig ([46:37])

“It’s about networking…get to know people, get to know how they talk, how they think…listen to podcasts on certain domains.”
— Ben Zweig ([47:09])

Memorable Moments & Quotes with Timestamps

• Wit about Kombucha Millennials:

  “Taking on board a millennial who might need their kombucha and early break on a Friday afternoon to take go for a meditative stroll is higher risk than whipping the corporate wage slave in their 50s for another, you know, few hours in the week.”
  — Azeem Azhar ([04:45])

• Enduring Value of Adaptive Organizations:

  “I think it’s a very common pattern for someone to enter a job thinking they’re going to do one set of things. And then as the job evolves, they find themselves doing totally different things.”
  — Ben Zweig ([18:09])

• Pushback on Internal Talent Marketplaces:

  “If you say, you know, hey, here’s a part of the business where we don’t need as many people … so we recommend you take this person and move them to that team. Because of all this tacit knowledge … the manager is probably going to say, ‘No way in hell are you taking my best person.’”
  — Ben Zweig ([28:32])

• Signals Must Be Costly:

  “Signals really have to be costly. A big tuition bill is one way to … show that … you can bear that cost or something … that imposes a cost on you and has real trade offs.”
  — Ben Zweig ([45:00])

Actionable Advice Summary

• For Job Seekers:

  • Cultivate experience in managing projects end-to-end
  • Demonstrate the ability to coordinate, execute, and finalize multi-faceted work
  • Seek out challenging, tangible ‘signals’ of commitment (e.g., significant projects, advanced degrees)
  • Build and leverage professional networks; understand and speak the language of your chosen field

• For Organizations:

  • Recognize the value of adaptive, task-based work arrangements
  • Facilitate employee-driven role evolution (job crafting)
  • Be mindful of the psychological and cultural impacts of flexibility and job design

Notable Timestamps for Key Segments

• [02:02] — Labor market conditions: Less hiring, low attrition, and AI-exposed job risk
• [11:14] — Revelio confirms entry-level decline in AI-exposed jobs
• [12:12] — What “AI exposure” means
• [14:07] — Managerial expectations shaping entry-level job market
• [17:44] — Adaptive organizations and the evolution of jobs
• [27:52] — Limits of internal reskilling and reallocation
• [32:26] — Job crafting as a way to maintain autonomy and integrity
• [36:26] — How growing AI capability is captured in workforce data
• [39:26] — Practical advice for graduates: Project management, orchestration, and credible signaling
• [46:37] — Ben’s one big piece of advice for students and parents

Tone and Style

The conversation balances pragmatic analysis with occasional humor and candid realism. Both speakers blend data-driven insight with accessible examples and skepticism about easy solutions, creating a thoughtful and measured discussion about the challenges ahead in the era of AI and exponential technology.