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Sofia was ready for the grunt work.
Graduation from UCLA’s Anderson School of Management felt like a lifetime ago. Today, she was stepping off a red‑eye, clutching her blue‑chip consulting new‑hire packet and primed for the classic rite of passage: endless spreadsheets, late‑night pizza, a senior associate showing her how to sweat the details and bonding with other fresh grads over the rote work of consulting.
Minutes after badge pickup, an internal AI tool coughed up a market analysis that once took rookies three days to complete and sent it to her inbox.
“Tighten the narrative on this and then get it ready to brief the client,” her manager said.
No spreadsheet reps. No context-building. No getting into the weeds with the data.
Sofia isn’t real, but thousands of grads are discovering the same void as they step into roles after graduation. The entry‑level floor where everyone gets their start has been quietly paved over. It was a messy, repetitive but essential step that vanished almost overnight in some industries.
Organizations have largely shrugged at the development. But their reckoning is coming soon enough.
AI Is Replacing the Entry Level
First you learn how to proof contracts. You get into the details, you learn to pick out common failings and gaps. After you have that foundation, only then are you ready to negotiate them.
That was the deal.
Now, machine readers tear through NDAs in seconds. Bookkeeping bots reconcile ledgers before interns log on. Generative tools crank out decks junior analysts once spent entire quarters building.
None of this is hypothetical. Forty percent of employers have budgeted for AI-driven staff reductions. Tech companies hired half as many grads in 2024 as they did in 2019.
If you’re a grad like Sofia, employed at a prestigious firm straight out of college, you might feel lucky. In many ways, you are. The AI rug pull on early-career jobs is real.
While organizations are currently banking on the advantages of AI in spite of rising failures, the long-term future of those organizations is less sure.
When you remove the first rung of that career ladder, that first step becomes more difficult. What is the future of a company if it can’t figure out how to close the experience gap?
Some Employers Aren’t Training Staff
Today’s white collar, entry-level job titles whisper “associate.” The expectations look more like “director.”
New employees are expected to understand and audit opaque AI outputs. They calm clients unnerved by algorithmic logic and uncanny speed. They flag ethical concerns before legal catches up. Harvard’s Project Zero calls this the rise of "judgment work" and it’s one of the last advantages humans hold over machines.
If entry-level employees never have to get into the weeds and never have to struggle to find a candidate for a role or flag suspicious numbers in an audit, how can they build judgment without experience?
Employers aren’t hiring to train, though. They’re hiring to plug immediate gaps. And they want AI fluency, domain expertise and emotional intelligence in a single hire without asserting effort.
The runway is gone but the altitude keeps rising. It’s an unrealistic future for employees and companies alike.
First Repairs: Corporate Triage
Some companies are scrambling to patch the gap. Others are hoping no one notices.
Upskilling and reskilling are popular and relatively easy steps. Amazon’s Upskilling 2025 prepays tuition and channels warehouse workers into AI and cloud roles. IBM’s AI-powered "Your Learning" platform delivers micro-lessons tied to performance data.
DHL built an internal marketplace that uses AI to recommend career paths and learning modules. Delta’s iGrow platform links growing employee competencies to performance outcomes. PepsiCo, Henkel and Salesforce are investing in frameworks that prioritize upward mobility and AI augmentation.
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Companies are also developing role-specific learning programs, said Michelle Westfort, chief product officer for workforce education provider InStride. These programs “build both leadership and job-specific skills in areas like frontline management, manufacturing operations and AI fluency,” she said. They’re already increasing outcomes such as promotions in as little as three months.
These are real signals. While they don’t go far enough on their own, they are an important start. Unfortunately, though, they’re still too rare.
Too many organizations still have their heads buried in the sand, hoping people remain engaged after AI-driven layoffs (and AI failures that inevitably get redirected to humans to fix). Others treat AI as a bolt-on, running one-off training sessions while quietly eliminating the jobs they once used to build careers.
Mostly, they hope they don’t have to hire entry-level talent because they don’t have a plan for getting them trained to a level beyond what AI can deliver in minutes.
Synthetic Apprenticeships for White Collar Employees
When a junior analyst automates PowerPoint slide-building in their first week on the job, the manager is impressed, and no one asks how the work gets done.
That self-starter culture is booming. Prompt-engineering boot camps offered by traditional education providers and commercial outfits alike are full. Online forums pass around optimization tricks like Spotify playlists.
But none of this is evenly distributed.
Grads without mentors, networks or savings can’t afford to chase certificates or fumble through a dozen paid tools. The digital escalator is running, but hundreds of thousands of grads banking on a decent job can’t get to it.
Experience still matters, but it doesn’t show up on the job description. That’s why we can’t leave this all to grads to figure out.
One solution is a synthetic apprenticeship. Instead of making people jump right into a mid-level career role, put them into a simulated environment. Instead of learning how to do data analysis and what to look for when things go wrong through repetition, learn to spot errors and what conclusions can be drawn from the data.
Simulations like this aren’t new. They are used in manufacturing to teach people how to use machines and learn safety without the consequences of injury or expensive mistakes when things go wrong. In healthcare, they train nurses and doctors on medical procedures or to learn patient care.
Synthetic apprenticeships can work in a white-collar environment by teaching employees how to use judgment in a foundational way. Like a recruiter learns the ropes on attracting talent early as a recruiting coordinator, or an IT professional learns how to diagnose errors as an associate, it’s an intentional step to give them time and build experience necessary to know when AI has gone off the rails.
In short, we create learning and development paths with AI that don’t just assume automated tools have the right answers, but also how to interpret and judge the outputs like a mid- or senior-level person.
It’s the only sustainable way forward for organizations, unless they envision a future where no one runs the bots anymore. The future of our organizations depends on investing early in training people's capabilities and judgment.
A Future Organization Worth Fighting For
Every quarter that goes by without a reimagined entry-level talent strategy is one where the future of your company wanes and your culture forgets what it means to be a person in the workplace.
If you're waiting to act, you're already behind.
This is not a time to observe and prepare. This is a time to build. It might be messy and imperfect, but the future of companies hangs in the balance.
The organizations planting seeds now by funding apprenticeships, rewiring how judgment gets developed and expanding who gets access will be the only ones with leaders ready to run the business in ten years.
Everyone else will be caught looking for talent that never got a shot. Invest in that strategy now while veterans still remember how and rookies are still asking to learn.
Editor's Note: Read more about how AI is changing the dynamics of our workplaces:
- Finding Your Place in the AI-Driven Post-Skills Era — Why cultivating judgment, critique and contextual intelligence matters more than skills in an era defined by AI-driven automation.
- Poor AI Planning, Not Technology, Is Costing Jobs — As AI adoption accelerates, poor strategy, not the technology itself, is driving job losses, skill gaps and cultural breakdown.
- Workforce Planners Say AI Isn't Ready for Prime Time — The volatility of the current business environment is making workforce planning tough. AI can help, but not in the way you might think.
