{"id":355957,"date":"2026-07-09T02:11:17","date_gmt":"2026-07-09T02:11:17","guid":{"rendered":"https:\/\/peraltafinancing.com\/uncategorized\/ai-is-killing-entry-level-jobs-but-paying-experienced-workers-more\/"},"modified":"2026-07-09T02:11:17","modified_gmt":"2026-07-09T02:11:17","slug":"ai-is-killing-entry-level-jobs-but-paying-experienced-workers-more","status":"publish","type":"post","link":"https:\/\/fivemor.com\/?p=355957","title":{"rendered":"AI Is Killing Entry-Level Jobs \u2014 But Paying Experienced Workers More"},"content":{"rendered":"


\n<\/p>\n

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For decades, the path into a professional career followed a familiar route: land an entry-level role, work hard, accumulate experience, and climb the ladder. Artificial intelligence is dismantling that pathway \u2014 and a new Federal Reserve study confirms that the disruption is not hitting everyone equally. While fresh graduates and young workers are finding fewer doors open to them, experienced professionals are watching their salaries surge in ways that would not have seemed possible just three years ago.<\/p>\n

The research, published by the Federal Reserve Bank of Dallas, cuts through the noise around AI and jobs to reveal something more nuanced than the usual doomsday headlines. AI is not simply replacing workers \u2014 it is reshaping who gets rewarded, and who gets left behind.<\/p>\n

Two Types of Knowledge \u2014 and Why It Changes Everything<\/h2>\n

To understand why AI is producing such unequal outcomes, the Dallas Fed study draws a critical distinction between two types of workplace knowledge. The first is codified knowledge \u2014 the kind you find in textbooks, training manuals, and online courses. It is learnable, transferable, and can be documented in steps. The second is tacit knowledge \u2014 the accumulated judgement, instinct, and situational awareness that only come from years of real-world experience on the job.<\/p>\n

AI is exceptionally good at codified knowledge. It can process vast libraries of information, apply rules, generate reports, draft communications, and handle structured analytical tasks with impressive accuracy. What it cannot do \u2014 at least not yet \u2014 is replicate the gut feeling of a senior lawyer who knows when a deal is about to fall apart, or the instinct of an experienced engineer who senses a system is about to fail before the data confirms it.<\/p>\n

This is the core of the divide. Entry-level workers, fresh from university, primarily bring codified knowledge \u2014 the textbook learning that AI can now replicate instantly and cheaply. Experienced workers bring tacit knowledge that AI cannot easily replace \u2014 and that distinction is now showing up directly in wages and hiring data.<\/p>\n

The Numbers Behind the Divide<\/h2>\n

The wage data tells a compelling story. Since ChatGPT launched in late 2022 and triggered the current wave of AI adoption, nominal average weekly wages across the United States have grown by around 7.5 percent. In the computer systems design sector \u2014 one of the most AI-exposed industries \u2014 wages have risen by 16.7 percent over the same period. Among the top ten percent of the most AI-exposed industries, wage growth has averaged 8.5 percent, comfortably above the national rate.<\/p>\n

For young workers, the picture is sharply different. Workers aged 22 to 25 in AI-exposed roles have seen employment fall by 16 percent since late 2022, even as their older colleagues remain relatively stable. In software development specifically, junior developers aged 22 to 25 experienced a staggering 20 percent decline in employment compared to their peak in late 2022. U.S. companies adopting AI have reduced junior hiring by around 13 percent according to Cornell University research.<\/p>\n

Perhaps the most telling statistic: entry-level job postings requiring zero to two years of experience have dropped by 29 percentage points. In the software and IT sectors, more than 60 percent of so-called entry-level roles now require three or more years of experience \u2014 a contradiction that leaves fresh graduates stranded at the very first step of the career ladder.<\/p>\n

The Career Ladder Is Breaking<\/h2>\n

The consequences extend well beyond individual paycheques. For generations, the entry-level job was not just a way to earn money \u2014 it was the first rung on a ladder that, with enough time and dedication, could lead anywhere. The stories are famous: Doug McMillon started at Walmart unloading trucks and became its CEO. Mary Barra joined General Motors at 18 on the assembly line and eventually ran the company. Antonio Neri went from a call centre agent at Hewlett Packard to chief executive.<\/p>\n

Those stories are becoming harder to imagine in an AI-shaped economy. SignalFire, a venture capital firm, tracked hiring data across the largest technology companies and found a 50 percent decline in new role starts for people with less than one year of post-graduate experience between 2019 and 2024. The decline was consistent across sales, marketing, engineering, operations, finance, and legal \u2014 suggesting this is not a sector-specific trend but a broad structural shift.<\/p>\n

\u201cThe loss of clear entry points does not just shrink opportunities for new graduates \u2014 it reshapes how organisations grow talent from within,\u201d said Heather Doshay, a partner at SignalFire.<\/em><\/p>\n

Which Experienced Workers Are Winning the Most?<\/h2>\n

Not all experienced workers are benefiting equally. The Dallas Fed study found that occupations with the highest experience premiums \u2014 the gap between entry and senior wages \u2014 are also the most exposed to AI and seeing the fastest wage growth. These include:<\/p>\n

    \n
  • Lawyers and legal professionals \u2014 experience premium exceeds 100%, with AI augmenting research and drafting tasks while senior judgment remains irreplaceable<\/li>\n
  • Insurance underwriters and credit analysts \u2014 complex risk assessment built on years of pattern recognition commands growing premiums<\/li>\n
  • Marketing specialists \u2014 strategic brand thinking and client relationships carry enormous tacit value that AI tools amplify rather than replace<\/li>\n
  • Senior software engineers \u2014 those who understand system architecture and business context are seeing wages soar even as junior coding roles shrink<\/li>\n
  • Healthcare professionals \u2014 clinical experience and patient judgment remain deeply human, with entry-level healthcare postings actually rising by 13 percentage points<\/li>\n<\/ul>\n

    \u00a0<\/p>\n

    At the other end of the scale, roles where both entry-level and experienced workers perform similar codifiable tasks \u2014 fast-food preparation, ticket processing, dry cleaning \u2014 are experiencing negative wage growth as AI can substitute for workers at every level of seniority.<\/p>\n

    The Warning From the Top<\/h2>\n

    The most dramatic warning has come from the highest levels of the AI industry itself. Dario Amodei, chief executive of Anthropic \u2014 one of the world\u2019s leading AI companies \u2014 predicted in 2025 that AI could eliminate roughly 50 percent of all entry-level white-collar jobs within five years, potentially pushing U.S. unemployment rates to levels not seen since the Great Depression. He described the potential outcome as a \u201cwhite-collar bloodbath\u201d and urged lawmakers to act urgently.<\/p>\n

    Boris Cherny, the Anthropic engineer behind Claude Code, went further still, suggesting that the title \u201csoftware engineer\u201d \u2014 once the most reliable entry-level position in technology \u2014 could be effectively extinct by the end of 2026. Cherny noted he had not written code himself since November 2025, having handed all coding tasks over to AI entirely.<\/p>\n

    Already in the first two months of 2026 alone, roughly 32,000 job losses were recorded in technology firms. In 2025, nearly 55,000 job cuts were directly attributed to AI by company announcements \u2014 out of a total 1.17 million layoffs across the U.S. economy, the highest figure since the pandemic year of 2020.<\/p>\n

    Is There a Long-Term Silver Lining?<\/h2>\n

    Not every expert shares the most alarming forecasts. Anders Humlum, a labour economist, points out that two and a half years of widespread AI adoption have not yet produced the kind of mass unemployment that some predicted. He notes that historically, even the most transformative technologies \u2014 steam power, electricity, computing \u2014 took decades to generate large-scale employment effects. \u201cEven if AI eventually matches the technical capabilities of entry-level white-collar workers,\u201d he said, \u201cthe time required for workflow adjustments and human adaptation is routinely underestimated.\u201d<\/p>\n

    Goldman Sachs Research broadly agrees, projecting that AI\u2019s impact on overall employment will be relatively mild and short-lived. Their modelling suggests unemployment may rise by around 0.5 percent during the transition, reflecting short-term friction rather than permanent structural collapse. Over the longer term, analysts point out that over 85 percent of employment growth since 1940 came from technology-driven job creation \u2014 a pattern they expect to continue.<\/p>\n

    A new model is also beginning to emerge at the entry level. Some analysts are tracking the rise of what they call \u201cAI Apprenticeships\u201d \u2014 where junior workers use AI tools to perform at a mid-level capacity far earlier in their careers than would previously have been possible. Universities are striking deals with AI companies including Anthropic and OpenAI to train students to harness these tools from day one.<\/p>\n

    What New Graduates and Young Workers Should Do Now<\/h2>\n

    The short-term picture is genuinely difficult for young people entering the workforce right now. Career experts are clear that waiting for the job market to return to normal is not a viable strategy. Here is what they recommend:<\/p>\n

      \n
    • Master AI tools immediately \u2014 employers increasingly expect new hires to arrive proficient with tools like ChatGPT, Copilot, and Claude. Treat AI fluency the way previous generations treated Excel \u2014 as a basic workplace skill.<\/li>\n
    • Build experience aggressively \u2014 even unpaid internships, freelance projects, or volunteer work counts. In a market that no longer hires on potential alone, any real-world experience sets you apart.<\/li>\n
    • Target sectors that are still hiring at entry level \u2014 healthcare, skilled trades, government, and physical services are actively recruiting and largely resistant to automation.<\/li>\n
    • Go narrow, not broad \u2014 specialist knowledge in a niche area (AI ethics, cybersecurity, green energy) is far harder for AI to replicate than general business skills.<\/li>\n
    • Think about the experience premium \u2014 before choosing a career path, ask whether the experienced version of that role commands significantly more than the entry-level version. High experience premiums signal long-term security.<\/li>\n<\/ul>\n

      \u00a0<\/p>\n

      The Bottom Line<\/h2>\n

      The era of AI is not treating all workers the same. It is accelerating a divide that was already quietly forming \u2014 between those whose value lies in what they know from books, and those whose value lies in what they have lived through on the job. For experienced workers with genuine tacit knowledge, AI is a powerful amplifier that is pushing wages to new highs. For entry-level workers whose primary asset is textbook learning, AI has become a formidable competitor.<\/p>\n

      The Dallas Fed study puts it plainly: returns on job experience are increasing in AI-exposed occupations. In other words, the premium on having actually done something \u2014 rather than just having studied it \u2014 has never been higher.<\/p>\n

      The career ladder is not gone. But it has been moved \u2014 and for millions of young workers, the first rung is now much harder to reach.<\/em><\/strong><\/p>\n

      Sources: Dallas Federal Reserve Bank \u2014 AI & Labour Market Study (2026) | SignalFire Venture Capital Entry-Level Hiring Report | DesignRush AI Job Displacement Statistics 2026 | Cornell University AI Hiring Impact Study | Goldman Sachs Future of Work Research | Anthropic CEO Dario Amodei Congressional Testimony 2025 | NACE Class of 2026 Graduate Employment Report | Challenger, Gray & Christmas Layoff Tracker 2025<\/em><\/p>\n

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