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AI-native startups hire fewer juniors, Harvard finds
A Harvard Business School and INSEAD working paper finds AI-native startups are 25% smaller, employ 13% more engineers, and carry roughly 15% lower shares of entry-level workers and managers than non-AI peers. Their hires skew senior, elite-educated, Silicon Valley-based, and male, suggesting AI is concentrating rather than democratising opportunity. Startups built around AI hire fewer entry-level workers than their peers, according to a working paper from Harvard Business School and INSEAD, first reported by Business Insider. The firms are leaner, flatter, and heavily weighted towards senior technical talent. Researchers Rembrand Koning and Hyunjin Kim examined Y Combinator startups from 2020 to 2024 alongside a broader set of US venture-backed firms. They define AI-native startups by two shifts: using AI internally to make employees more productive, and embedding it in products so customers can automate work that once required human teams. The numbers are stark, with AI-native startups 25% smaller, employing 13% more engineers, and carrying roughly 15% lower shares of both entry-level workers and managers. The share of senior workers runs 20% higher, and valuations are comparable to non-AI peers, implying more value created per employee. The workers these firms do hire skew a particular way. "These workers are especially likely to be graduates from elite institutions, concentrated in Silicon Valley, and male," the authors wrote. That cuts against the hopeful reading of the AI boom, in which juniors use AI to punch above their grade and vibe coding lowers the technical bar. The paper suggests opportunity is instead concentrating among the already credentialed. The authors' deeper worry is compounding inequality, warning that if AI accelerates learning for those who use it, "differential adoption rates may translate into widening performance gaps". That applies to workers within firms and to the entrepreneurs who found them. The bottom rung is cracking The findings echo what is already visible in the labour market, where AI is killing the summer internship and graduate unemployment is climbing. Recent graduates now make up just 7% of new hires at major tech companies. Big Tech is busy converting payroll into compute, with Meta and Microsoft cutting 23,000 roles as AI spending hits records. Demand at the top is so hot, meanwhile, that AWS is putting $1bn into forward-deployed AI engineers. Even hiring itself has become an AI-on-AI arms race. For new graduates, the machines now sit on both sides of the table. The study's implication is uncomfortable for anyone selling AI as a democratising force. The technology may flatten hierarchies inside companies while steepening the climb to get into them.
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AI Startups Hire a Specific Type of Employee. Do You Fit the Mold?
The findings show that young, entry-level workers are at a disadvantage in the AI era. Tech companies have a predictable playbook when it comes to recruiting talent: Snatch up new hires in summer internships and place them into six-figure positions right out of college. Now, however, the game is changing. Researchers at Harvard Business School and nonprofit business school INSEAD found in a recent study that AI startups are forming smaller teams with fewer hierarchical layers. They are also hiring fewer entry-level workers than non-AI startups. Companies that build AI products and services hire 15% fewer entry-level employees than other startups without an AI focus. There's additionally a typical mold of a person who is likely to work for AI startups. "They are geographically concentrated in Silicon Valley, and employ workforces that are more male, more likely to hold advanced degrees, and drawn from more prestigious employers and institutions," according to the study. The findings show that young, entry-level workers are at a disadvantage in the AI era. There are fewer opportunities at the bottom of the corporate ladder. For example, the study showed that AI startups employed 20% more senior employees than non-AI startups. These AI-native companies also have 15% fewer managers and fewer management layers because they place senior employees in technical positions that require in-depth expertise rather than supervisory roles. Also, AI startups employed 13% more engineers than other startups. The study found that AI companies raise 20% more capital per employee compared to non-AI firms and tend to have higher valuations per employee. If these AI startups continue to raise funds from investors, entry-level employees could find it harder than ever to secure employment, per the study. Tech companies are hiring fewer Gen Z workers According to a 2025 study by compensation management software company Pave, the percentage of Gen Z employees ages 21 to 25 in technology companies halved between 2023 and mid-2025. These Gen Z employees comprised 15% of the workforce at large public tech companies in January 2023. By August 2025, that percentage dropped to a mere 6.8%. At private companies, young workers are also on the decline. The study found that during the same period, from January 2023 to August 2025, the percentage of Gen Z employees at big private tech companies dropped from 9.3% to 6.8%. Just like the Harvard Business School study, the Pave report discovered that workers at tech companies are now older and more experienced than ever. Pave researchers revealed that the average age of employees at large public tech companies rose from 34.3 years in 2023 to 39.4 years in 2025. The private sector had a more incremental rise, increasing from 35.1 to 36.6 years old across the same time period. "If you're 35 or 40 years old, you're pretty established in your career; you have skills that you know cannot yet be disrupted by AI," Matt Schulman, founder and CEO of Pave, told Fortune last year. "There's still a lot of human judgment when you're operating at the more senior level."
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AI-Native Startups Hire Fewer Junior Workers and More Senior Talent, Harvard Study Finds - Microsoft (NAS
Researchers from Harvard Business School and INSEAD said in a working paper published in June that AI-native startups are building smaller, flatter organizations while hiring fewer entry-level workers and more experienced technical talent than traditional startups. The study, titled "AI-Native Firms," analyzed Y Combinator startups from 2020 through 2024 and a broader group of U.S. venture-backed companies founded during the same period. The researchers defined AI-native firms as companies that use artificial intelligence both to improve employees' productivity and to embed AI directly into the products they sell. The researchers found AI-native startups are about 25% smaller than comparable non-AI startups while employing roughly 13% more engineers. They also have about 15% fewer entry-level employees and managers, while the share of senior workers is about 20% higher. Despite operating with smaller teams, the companies achieve valuations similar to non-AI peers, suggesting they generate more value with fewer employees. Changing Hiring Patterns According to the study, AI is reshaping hiring by reducing the need for large junior workforces while increasing demand for experienced technical employees. The authors found AI-native companies are more likely to hire graduates from elite universities, are concentrated in Silicon Valley and employ a workforce that skews male. The researchers said AI is improving productivity in two ways. Companies are using AI internally to help employees complete tasks such as coding, sales and design more efficiently, while also building AI directly into products so customers can perform work that previously required human teams. The authors warned that if AI adoption continues to accelerate unevenly, it could widen performance gaps among workers and entrepreneurs rather than expanding access to opportunities. International Monetary Fund Managing Director Kristalina Georgieva has also urged policymakers to ensure AI's economic benefits are broadly shared as the technology transforms labor markets. Disclaimer: This content was partially produced with the help of AI tools and was reviewed and published by Benzinga editors. Photo courtesy: Shutterstock Market News and Data brought to you by Benzinga APIs To add Benzinga News as your preferred source on Google, click here.
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A Harvard Business School and INSEAD study reveals AI-native startups are building leaner teams with 25% fewer employees overall, hiring 15% fewer entry-level workers while employing 20% more senior talent. The shift toward experienced, elite-educated engineers concentrated in Silicon Valley suggests AI is concentrating opportunity rather than democratizing it, raising concerns about widening inequality in the tech job market.
AI startups are fundamentally changing how tech companies build their teams, according to a Harvard study that examined Y Combinator startups from 2020 to 2024 alongside a broader set of U.S. venture-backed firms
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. Researchers Rembrand Koning and Hyunjin Kim from Harvard Business School and INSEAD found that AI-native startups are approximately 25% smaller than their non-AI peers while achieving comparable valuations, implying significantly more value created per employee1
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Source: Benzinga
The Harvard Business School and INSEAD study defines AI-native startups by two critical shifts: using AI internally to boost employee productivity in tasks like coding, sales, and design, and embedding AI directly into products so customers can automate work that previously required human teams
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. This dual approach to internal productivity and product development is reshaping workforce composition across the startup ecosystem.The numbers paint a stark picture of changing hiring trends in the AI job market. AI-native startups employ roughly 15% fewer entry-level employees and 15% fewer managers compared to traditional startups
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. Meanwhile, the share of more senior talent runs approximately 20% higher at these companies2
. These firms also employ 13% more engineers than non-AI startups, reflecting the technical expertise required to build and deploy AI systems1
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.AI startups have created flatter organizational structures with fewer management layers, placing senior employees in technical positions that require deep expertise rather than supervisory roles
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. The study also found that AI companies raise 20% more capital per employee compared to non-AI firms and tend to have higher valuations per employee2
.The workers AI-native startups do hire skew heavily toward a particular profile. "These workers are especially likely to be graduates from elite institutions, concentrated in Silicon Valley, and male," the authors wrote
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. This pattern cuts against the optimistic narrative that AI would democratize opportunity by allowing junior talent to compete with more experienced workers through AI-assisted productivity tools.The broader tech sector mirrors these trends. Gen Z workers ages 21 to 25 comprised 15% of the workforce at large public tech companies in January 2023, but by August 2025, that percentage dropped to just 6.8%
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. At private companies, young workers declined from 9.3% to 6.8% during the same period2
. The average age of employees at large public tech companies rose from 34.3 years in 2023 to 39.4 years in 20252
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The researchers warn that if AI accelerates learning for those who already use it effectively, "differential adoption rates may translate into widening performance gaps"
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. This concern applies both to workers within firms and to the entrepreneurs who found them. As Matt Schulman, founder and CEO of Pave, explained to Fortune: "If you're 35 or 40 years old, you're pretty established in your career; you have skills that you know cannot yet be disrupted by AI. There's still a lot of human judgment when you're operating at the more senior level"2
.The findings echo what's already visible across the tech sector, where major companies like Meta and Microsoft have cut 23,000 roles as AI spending hits records
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. Meanwhile, demand for senior AI expertise remains intense, with AWS investing $1 billion into forward-deployed AI engineers1
. Recent graduates now make up just 7% of new hires at major tech companies1
.If AI-native startups continue attracting investment at current rates, the authors suggest that opportunity concentration could accelerate rather than reverse. The technology may flatten hierarchies inside companies while simultaneously steepening the climb to get into them, creating a paradox where AI improves productivity for those already inside elite organizations while raising barriers for those trying to enter the field.
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