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Time charter

* [Entry-level workers](/partner-content/-partner-name-/tag/entry-level-workers/)  
## Entry-level workers  


# What AI is Doing to on-the-Job Learning—and How to Protect It

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#### Is TIME a reliable news source?

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by 

[Brian Elliott](https://time.com/author/brian-elliott/)

Executive-in-residence, Charter

Brian Elliott is Charter's executive-in-residence and CEO of Work Forward.

Sep 1, 2026 10:30 AM UTC

![](https://static.time.com/v3/assets/bltea6093859af6183b/blt3d68f28e00719c62/6a960c8ef51dc7920ffc9093/charter-job-learning.jpg?branch=production&width=1200&quality=75&auto=webp&crop=3:2)

by 

[Brian Elliott](https://time.com/author/brian-elliott/)

Executive-in-residence, Charter

Brian Elliott is Charter's executive-in-residence and CEO of Work Forward.

Sep 1, 2026 10:30 AM UTC

On a panel last week, I was asked what my top concern is about AI and work. I said the impact on younger workers, but my biggest worry isn't what AI is doing to entry-level hiring. It's what AI is doing to how early-career people _learn,_ and the skills and experiences that they—and their employers—will need in just a few years.

The fears around entry-level job losses are easy to understand, and all too real. [Erik Brynjolfsson](https://www.linkedin.com/in/erikbrynjolfsson/)'s [team at Stanford](https://digitaleconomy.stanford.edu/news/canariesaug26/) found that workers aged 22 to 25 in the most AI-exposed jobs are now employed about 19% below where they'd be if they had kept pace with older peers. In July,[ unemployment for recent grads](https://www.newyorkfed.org/research/college-labor-market) hit 5.7%, above the[ 4.1% rate](https://www.bls.gov/news.release/empsit.nr0.htm) for everyone else. None other than Bill Gates, meanwhile, is[ warning us](https://www.gatesnotes.com/work/make-ai-work-for-everyone) that "the jobs at most risk are entry- and mid-level" and that "there is no plan."


No wonder [55% of adults under 30](https://www.pewresearch.org/short-reads/2026/08/18/young-adults-in-the-us-are-increasingly-wary-of-ai-concerned-it-will-take-jobs/) now say they're more worried than excited about AI, up from 31% five years ago.

Sign up for Charter's newsletter to get the handbook for the future of work delivered to your inbox.

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You can unsubscribe at any time. By signing up you are agreeing to our [Terms of Service](https://www.charterworks.com/terms-of-service/) and [Privacy Policy](https://www.charterworks.com/privacy-policy/).

But even if layoffs and slower entry-level hiring deserve the attention they’re getting, here's why learning worries me more. Layoffs and hiring freezes are loud, and we have multiple economists and experts looking at entry-level jobs. What AI does to learning is quiet, starting by hurting critical thinking in our education systems and continuing into organizations, where learning and development investments are too often reflexively cut when budgets get tight. An Atlassian survey, for instance, found that executives are [84% more likely](https://www.atlassian.com/blog/state-of-teams-2026) to invest in technology than in developing teams’ AI skills. 

There are two problems here, and they compound each other: AI is changing how people learn, and it’s quietly dismantling the on-the-job coaching and development that could make up for it.

## **What AI does to learning**


AI’s impact on hiring is visible, but it’s also a challenge CEOs can easily reverse. About[ a third of companies](https://www.washingtontimes.com/news/2026/mar/10/ai-layoff-reversal-companies-rehire-customer-roles-eliminated/) that cut jobs for AI have since rehired some of them, and I’ve talked to executives who’ve reversed their take on entry-level hires. Changing the trajectory of learning and development is harder: its ownership inside organizations is diffuse, and it's not easily measured by the kinds of metrics most organizations value.

The cleanest evidence of AI’s negative impact on learning is an [experiment](https://www.pnas.org/doi/10.1073/pnas.2422633122) by a team of researchers at Wharton. About a thousand students worked through a high school math unit, and the group with a GPT-4 tool did 48% better while using it. But once the AI tool was taken away, the same group scored 17% worse on a test about the unit: the tool had dulled their learning. A version that gave hints instead of answers, meanwhile, erased the harm, turning the tool into a tutor that made students do the work.


Such learning gaps are already showing up in the workplace. One head of talent I spoke with in a recent [Charter Forum](https://www.charterworks.com/forum/) session watched new grads fail a test they would have passed two years earlier, likely because they leaned on AI during school and never built the skills. To help address those gaps, [Andrew Wang](https://www.linkedin.com/in/wangandrewd/), CEO at AI startup Valon, requires that new employees learn to do their jobs [before being allowed to use AI](https://www.businessinsider.com/valon-ceo-bans-ai-most-new-hires-job-skills-2026-8) at work. His reaction to people who’ve pushed back on the approach: "If you have a much better idea here of how to make sure people learn, please tell me."

The challenges aren’t limited to office work. [Matt Beane](https://www.linkedin.com/in/mattbeane/)'s [fieldwork](https://engineering.ucsb.edu/news/code-building-skills-our-modern-workplace) at UC Santa Barbara looked at how surgeons train. In robotic surgery, the lead surgeon runs the machine. The trainee, who used to be an active assistant, watches but does not get to do hands-on training. The resulting drop in “reps” after adding robotics can stunt skill development, and Beane says the most driven young surgeons end up teaching themselves on the side. 


Meanwhile, research increasingly points to multiple [cognitive taxes](https://www.charterworks.com/the-cognitive-tax-of-working-with-ai/) people experience from working with AI. There’s "[cognitive debt](https://margaretstorey.com/blog/2026/02/09/cognitive-debt/)," the gap between what you produce and what you understand: an[ MIT study](https://arxiv.org/abs/2506.08872) put people in EEG caps and found that ChatGPT users showed lower brain activity and often couldn't quote an essay they had just written using AI. Then there’s "[cognitive surrender](https://papers.ssrn.com/sol3/papers.cfm?abstract%5Fid=6097646)," when you hand your judgment to the machine, going along with the AI’s answer without checking its logic. 

## **The pressure to deploy AI is cutting coaching and feedback**

Adding guardrails to AI might help it act more like a tutor than an answer machine. Feedback can help address the AI slop that results when people give in to cognitive surrender. But that will happen only if we give frontline managers the time and space to actually develop their teams. I’m hearing concerns directly from managers, workers, and some researchers that if we keep adding to the load of frontline managers, we’re pushing them to the point where they don’t have time to coach their teams. 


I recently interviewed a researcher who has worked with a professional-services firm, as well as with a manager in the firm. (Both requested anonymity to speak freely about the challenges they face.) The researcher described the loss of friction in day-to-day work—wrestling with the data, reworking models and presentations to hit quality standards, puzzling over the findings to shape insights—that results in learning. Today, too many workers just ask AI, because it's faster. 

The manager, meanwhile, shared how AI had increased expectations from clients and senior leadership for more output in less time. She’s still managing a team of junior staff members, as well as AI agents that she uses directly. The tools themselves help with analysis and drafting, but lack judgment rooted in the client’s context, or trained experience. Under increased pressure, she picks from the same bad options every day: slow down to teach and fall behind, or fix it herself and skip the coaching.


## **Building for the future**

The good news is that all of these issues are within leadership’s control. They just take some intentional thought about the opportunities for long-term growth. A few recommendations:

**Separate "automation-worthy" from "development-critical" tasks.** [Rebecca Hinds](https://www.linkedin.com/in/rebecca-hinds/), head of the Glean Work AI Institute, recommends that leaders ask what a newcomer learns by doing a task before automating it. “Protect the work that builds judgment, even when AI can do it faster.” She also says that when AI automates management tasks like status updates and meeting summaries, the time managers free up needs to go to feedback and coaching. That only happens if managers are rewarded for team development.

**Use AI to augment manager feedback.** [Hilary Gridley](https://www.linkedin.com/in/hilarygridley/) couldn’t give feedback on everything her direct reports produced when she was head of core product and AI at WHOOP. So she built a custom GPT that [graded more routine communications work](https://www.charterworks.com/hilary-gridley-power-user/) against the criteria she cares about. Her reports, she said, get feedback that's “probably 80% as good as what I would do, but they can get it over and over and over and they can get it on demand.” That also frees up manager time to coach on larger-scale challenges, while increasing feedback frequency on day-to-day tasks.


**Put guardrails on AI.** The AI prompts given to students in Bastani's studies did no harm: they just forced more interaction and learning. We can adapt our AI tools at work to help. One AI company built a “discernment” skill—a set of instructions for AI agents—so that for any answer an employee might act on, the tool returns three hard questions that test its own logic, teaching the user to question AI’s context and reasoning.

**WHAT ELSE TO READ:**

* **How PwC is** [**changing learning**](https://www.charterworks.com/how-pwc-is-changing-learning-for-the-ai-) **for the AI era**, a conversation with PwC US’s chief people and inclusion officer Yolanda Seals-Coffield
* **Getting ahead of the** [**leadership gap**](https://www.charterworks.com/download-getting-ahead-of-the-leadership-gap/), our playbook about closing the leadership pipeline
* **Inside how Anthropic teaches effective AI use**, Charter’s [conversation](https://www.charterworks.com/inside-how-anthropic-teaches-effective-ai-use/) with Anthropic education and research programs lead Kristen Swanson

---

## Read more from Charter

[READ MORE](https://time.com/partner-content/charter/)

[Open article: How to Maintain the ‘Heartbeat of Work’ in the Age of Ai](https://time.com/partner-content/charter/how-to-maintain-the-heartbeat-of-work-in-the-age-of-ai/)

![charter-kaneps.jpg](https://static.time.com/v3/assets/bltea6093859af6183b/blta122a4a35c4df3e7/6ac02a2ac7c47f291891ce00/charter-kaneps.jpg?branch=production&width=1200&quality=75&auto=webp&crop=3:2)

### How to Maintain the ‘Heartbeat of Work’ in the Age of Ai

[READ MORE](https://time.com/partner-content/charter/how-to-maintain-the-heartbeat-of-work-in-the-age-of-ai/)

[Open article: AI Did Not Kill the Entry-Level Job. Leaders Did.](https://time.com/partner-content/charter/ai-did-not-kill-the-entry-level-job-leaders-did-/)

![charter-on-the-job-learning.jpg](https://static.time.com/v3/assets/bltea6093859af6183b/bltb4bd5a83d2e40ae4/6a9a1146643c9ef723a5beb5/charter-on-the-job-learning.jpg?branch=production&width=1200&quality=75&auto=webp&crop=3:2)

### AI Did Not Kill the Entry-Level Job. Leaders Did.

[READ MORE](https://time.com/partner-content/charter/ai-did-not-kill-the-entry-level-job-leaders-did-/)

[Open article: Why the Office Isn’t a Cure for Loneliness](https://time.com/partner-content/charter/why-the-office-isn-t-a-cure-for-loneliness/)

![charter-announcement-1.jpg](https://static.time.com/v3/assets/bltea6093859af6183b/blt15c29d033b5277ae/6a906813f92b6b0a3da1794a/charter-announcement-1.jpg?branch=production&width=1200&quality=75&auto=webp&crop=3:2)

### Why the Office Isn’t a Cure for Loneliness

[READ MORE](https://time.com/partner-content/charter/why-the-office-isn-t-a-cure-for-loneliness/)

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