Death of Entry Level Jobs

Are we building a world without beginners?

Welcome to this week’s edition!

Unless you’ve been living under an (AI) rock, you will have heard the echos of Dario Amodei (Anthropic’s CEO) nefastous prediction “50% of entry-level white-collar jobs disappearing in 1-5 years”. Is the ground already shifting beneath the feet of new graduates, or is the panic premature? And more importantly, what practical moves can both companies and aspiring professionals make to navigate this turbulent new era?

So, this week, we're cutting through the noise to explore:

• What’s the current trend actually looking like for new graduates? We'll dig into the latest data and on-the-ground reports.

• What solutions can both companies and graduates turn to? We’re talking actionable strategies, not just theories, to adapt and thrive in a world where AI is rewriting the rulebook for entry-level work.

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What’s going on for Entry-Level Roles?

So, Amodei’s prediction hangs heavy in the air. But before we jump to a future where AI is the gatekeeper of all entry-level roles, let's take a hard look at the now. What’s the current job market actually like for new graduates? Is the ground already trembling, or is this just a distant rumble?

The Data Doesn't Lie: It's Tough Out There

Frankly, the picture isn't pretty. Recent analysis paints a stark reality: that once-golden ticket of a college diploma is losing some serious shine.

• Rising Graduate Unemployment: The New York Fed flagged that the unemployment rate for US workers aged 22 to 27 with a bachelor's degree or higher climbed above 5.3% in September (the latest comprehensive data point available as of early 2025 reporting), its highest since August 2021. Oxford Economics even notes that for the first time since they began tracking it in 1980, the unemployment rate for recent graduates is consistently higher than the overall national unemployment rate. So whilst it isn’t anywhere close than the 50% that Amodei talks about, it’s not trending in the right direction.

• The Shrinking Degree Advantage: Even more telling? The gap between graduates and their peers without degrees is razor thin. While grads sat at 5.3%, those without college degrees (same age group) had an unemployment rate of 6.7%. This is the second smallest spread in decades. Cast your mind back to June 2010: graduate unemployment was 7.1%, but for young workers without a degree, it was a staggering 16.2% – a chasm nearly seven times wider than today.

• Worse for Some: For the 20-24 age bracket, unemployment is nearly double the national average at 8.2%. And it's particularly bleak for young men in this group, facing a 9.6% unemployment rate, a significant jump from 6.7% a year prior.

Why the Squeeze on New Grads?

This isn't a single-cause problem; it's a cocktail of factors creating a perfect storm for the Class of 2025 and recent alumni:

1. A "No-Hire, No-Fire" Market: While the overall US job market has shown resilience (with a national unemployment rate around 4.2% and a long streak of job additions), there are, as one article put it, "cautionary signs beneath the hood." Businesses, rattled by chaotic trade wars and high interest rates, are playing it safe. This translates to a slowdown in new hiring, especially at the entry level. LinkedIn data shows entry-level hiring is down a whopping 23% compared to March 2020, exceeding the 18% decline in overall hiring.

2. Skills Over Sheepskins: Employers are increasingly prioritizing demonstrable skills over formal credentials. Julia Pollak from ZipRecruiter puts it bluntly: "a college degree isn't the signal it used to be." With a massive 80% increase in Americans holding degrees from 2001 to 2021 (while the labor force grew less than 13%), the competition is fierce. This has led to a drop in job postings explicitly requiring a college degree – down to 17.8% this year from an average of 20.4% over the past five years, according to Indeed. That small percentage shift represents hundreds of thousands of jobs now open to non-degree holders who might have the requisite skills.

3. Sector Divergence: The pain isn't evenly distributed. While trades, healthcare support, and logistics (often not requiring degrees) see robust demand, the traditional graduate hunting grounds like technology and finance are showing clear signs of strain. Indeed's job postings in software development, for instance, are down 32% from pre-pandemic levels, while construction jobs are up 23%. An anecdote from an ING economist paints a vivid picture: a manufacturing CEO gets 90 applicants for a $50k finance team role but struggles to find even one for a $100k production supervisor position.

4. Post-Pandemic Reckoning: Some of this is an echo of the "Great Hire" of 2021-2022. As Luke Pardue from the Aspen Institute notes, many firms overhired in professional services post-pandemic and are now dealing with larger-than-needed workforces, leading to fewer openings for newcomers.

5. The AI Shadow Looms: And then there’s AI. While economists like Kory Kantenga from LinkedIn urge caution against blaming AI entirely (citing historical adaptations like ATMs not wiping out bank tellers), the signs are troubling. Amodei's warning of AI potentially wiping out half of entry-level white-collar jobs within 1-5 years resonates when Oxford Economics points out that employment in computer science and mathematics for those aged 22-27 has declined by 8% since 2022, while remaining stable for older workers in those fields. Matthew Martin from Oxford Economics believes AI is "definitely displacing some of these lower-level jobs."

The result? A generation facing a "hopeless" job search, as one graduate described it, applying for hundreds of positions with little to no response. Worker confidence among Gen Z has, according to LinkedIn, tumbled to record lows. It’s a market where it’s taking considerably longer for anyone hunting for work to find a job, and new graduates are feeling that acutely, often while saddled with significant student debt.

What should companies do?

The allure of immediate cost savings and the efficiency of seasoned "AI orchestrators" (as Anthropic's Mike Krieger might describe his ideal hires) is undeniable.

But let's be brutally honest: simply cutting off the lower rungs of the ladder, or assuming AI can indefinitely fill the void, isn't a strategy – it's a slow march towards a critical talent shortage down the line. If entry-level roles are where foundational skills, professional judgment, and even the understanding of what to orchestrate are built, where will your next generation of senior leaders and innovators come from? This is the "Orchestrator Paradox" in action, and it’s a problem companies need to solve proactively, not stumble into.

So, what can forward-thinking companies actually do, beyond just wringing their hands or hoping for the best? It’s about shifting from short-term contraction to long-term talent cultivation in an AI-augmented world:

1. Reimagine, Don't Just Eliminate, Entry-Level Roles: The knee-jerk reaction might be to slash roles AI can "do." Instead, redesign them. Focus entry-level positions on tasks that require uniquely human skills: complex problem-solving, critical thinking applied to AI outputs, ethical oversight, nuanced client communication, and true out-of-the-box creativity. Think of these new roles as "Junior AI Augmenters" or "Human-AI Interface Specialists," where learning to leverage AI tools effectively and critically is a core competency from day one.

2. Invest in "New Collar" Talent Development: Forget waiting for the "perfect" candidate. Build them. Launch modern apprenticeship programs or "AI Academies" within your organization. These could focus on practical AI application, data literacy, ethical AI use, and the "soft skills" needed to collaborate in hybrid human-AI teams. Consider "synthetic apprenticeships" using AI-driven simulations to rapidly build experience in complex decision-making scenarios. This isn't just about graduates; it's about identifying aptitude from diverse backgrounds.

3. Build Your Own AI Orchestrator Pipeline: Don't just hunt for expensive, experienced orchestrators. Cultivate them. Create clear pathways for junior talent to grow into these roles. This means structured mentorship from senior AI leads, rotational programs exposing them to AI integration across different business units, and project-based work where they learn to manage AI tools to achieve strategic outcomes.

4. Get Serious About Skills-Based Hiring (For Real This Time): The talk about "skills over degrees" has been around for years, but the current market demands genuine commitment. Move beyond CV keyword scanning. Implement practical assessments, challenges that involve using AI tools to solve a real-world problem, and interviews that probe for adaptability and critical thinking. The ability to learn and leverage new technologies (including AI) effectively is now a baseline skill.

5. Embrace "Human Capital Reinvestment": If AI is driving productivity gains, reinvest a portion of that value into your human workforce. This could mean dedicated budgets for upskilling and reskilling initiatives, funding for the "New Collar" programs mentioned above, or even contributing to broader societal initiatives that help build a resilient, AI-literate talent pool. Ethical AI deployment isn't just about data privacy; it’s also about a just transition for your people.

6. Foster a Culture of Human-AI Teaming: Shift the narrative from "humans vs. AI" to "humans amplified by AI." This requires training not just for junior staff but for managers too, teaching them how to lead, motivate, and evaluate teams where AI is a core member. Encourage experimentation and knowledge sharing around effective AI use.

7. Widen the Talent Aperture: The next brilliant AI orchestrator or creative problem-solver might not come with a traditional CS degree from a top-tier university. Look at candidates from vocational programs, intensive bootcamps, or those with non-linear career paths who can demonstrate high aptitude, AI literacy, and the critical thinking skills you need.

The "why bother?" is simple: companies that actively cultivate talent in this new era will not only sidestep the future "Orchestrator" skill cliff but also foster greater innovation, loyalty, and a more diverse, resilient workforce. Ignoring the entry-level crunch, or seeing AI as a simple replacement, is a recipe for being outmaneuvered by those who choose to build the future of their workforce, not just manage its decline.

What should graduates do?

The old playbook – good grades, decent university, straightforward job application – is gone. AI seems to be holding the pen for many of the new, sometimes daunting, chapters. The data shows it's a tougher market, and the "degree advantage" isn't what it once was.

1. Proof of Work: Your Portfolio is your new Diploma: With employers prioritizing skills over just credentials (as the Indeed data clearly shows), "showing" is more powerful than "telling." More on this in ‘The Proof of Work Paradox’ which I recently wrote)

   1. Build Tangible Proof of Work: Undertake personal projects, contribute to open-source initiatives, participate in hackathons, or seek out "micro-internships" or freelance gigs. Crucially, document process, role, the tools used (especially AI), and the measurable outcomes.

   2. Think Projects, Not Just Positions: Even if you haven't had a formal "job," a portfolio of well-executed projects can speak volumes about capabilities.

2. Network - The "hidden job market" is more important than ever. As AI takes over also in the job-matching process, having a human connection will matter more, allowing to understand where there could be roles or ‘project work’ done even before the positions are opened.

   1. Modern Mentorship: One way is to seek out individuals working in roles that blend human expertise with AI – these are your future "AI orchestrators." Learn from their career paths and set-up your personal ‘board of directors’.

3. Build - Proactively building tangible projects or ventures will offer a significant edge. The use of "vibe coding" and AI tools can accelerate the creation of prototypes, the launch of micro-businesses, or the development of community-focused digital products. The primary aim might be entrepreneurial success. However, regardless of the venture's commercial outcome, the process itself can provide an undeniable proof-of-concept of applied skills, create powerful networking opportunities, and allow for a “lateral” approach to the job market. This will help position graduates as demonstrated innovators and problem-solvers, something that will be in higher demand.

4. Cultivate "Meta-Learning": Your most valuable skill will be the ability to learn new things quickly and effectively, unlearn old habits, and adapt to new tools and paradigms as they emerge.

   

5. Run 100 careers: Forget the old single-track career map; the 21st century, as Andy puts it, is your invitation to 'Develop 100 Different Lives.' This isn't just about job hopping; it's about embracing your work journey as a series of diverse roles, continuous learning cycles, and adapting with agility to whatever comes next.

What should governments do?

All of this calls for urgent, comprehensive societal conversations that extend beyond individual adaptation, exploring a portfolio of solutions. Some ideas could be:

• Robust Safety Nets & Economic Redesign: Discussions around Universal Basic Income (UBI) or a "Citizen's Dividend" are gaining traction. Beyond that, we could explore tax shifts – potentially higher taxes on automated processes or capital gains from AI, with reduced taxes on human labor – to rebalance incentives. Ideas like "data unions" or digital cooperatives could empower individuals to collectively bargain for the value their data contributes to AI training.

• New Developmental Pathways: We might need publicly funded or incentivized "AI Transition Fellowships" for recent graduates, or "micro-internship" platforms offering short, project-based experiences. Revitalized national service corps, focused on digital literacy, community AI projects, or environmental regeneration, could provide both experience and societal benefit.

• Reimagining Career Structures & Value: If traditional jobs shrink, concepts like a shorter work week or formalized job-sharing become more pertinent. We may need to actively foster and professionalize roles in the "Care Economy" (elder care, mental health, childcare) and the "Green Economy" (renewable energy, sustainable agriculture), which often require significant human presence and nuanced interaction. "Purpose stipends" or "social impact grants" could fund individuals working on community-benefiting projects outside traditional employment structures.

• Public Investment in AI Accessibility: Investing in "Public Option AI" – open-source tools and platforms – could democratize access, foster innovation beyond big tech, and potentially create new categories of public-sector technology roles focused on ethical deployment and maintenance.

Final Thoughts

This moment demands a fundamental redesign – a total rethink of how we approach talent development, what opportunity even looks like in an AI-augmented world, and what value a new professional truly brings. The future of work, and frankly, the vitality of our communities, will depend on whether we're brave enough to move beyond just mitigating damage.

Beyond the individual efforts of some forward-thinking companies and the sheer hustle of proactive graduates, where are the broader coalitions forming to tackle the systemic nature of this beast? I think we need more modern 'unions,' digital worker guilds, whatever you want to call them – structures adapted for the AI age, fiercely focused on ensuring lifelong learning, equitable access to opportunity, and a real voice for individuals in how these powerful new tools reshape our working lives.

Ciao,
Matteo