Isaac, 33, has been a mid-level software development engineer at a Big Tech company for four years and noticed a drop in vacancies at his workplace in early 2025. However, the work did not disappear with them. Tasks once performed by junior engineers – such as writing and testing code, fixing bugs and contributing to development projects – were absorbed by senior employees, often under the assumption that AI would make up the difference.
And while AI has accelerated the speed of shipping code and functions, there are fewer people performing tasks like design, testing, and collaborating with stakeholders, which AI has no control over. The cracks were hard to ignore. “Seniors get burned out, and when they leave, there’s no rush to replace them because ‘the AI will do it’!” says Isaac. Afraid that he will become the next uptight senior, he looks for his exit, ideally at a smaller tech company. (Isaac spoke to Fast Company under a pseudonym to avoid possible retaliation.)
The shift is striking considering lately that corporate America has been courting Gen Z with fanatical zeal. Organizations tried to prove that they understood younger workers. They flooded LinkedIn with thought leadership in the field multigenerational workplace of the future, and adapted benefit programs to include this welfare allowances And mental health days. Reverse mentorship programs, where younger employees share knowledge and perspectives with older colleagues – promoted by companies such as Target, Accenture and PwC– promised to give junior employees a voice in shaping culture and strategy. Some companies even brought Generation Z votes in the boardroom.
But now, in the case of companies like Isaac’s, entry-level employees, once heralded as essential to innovation and growth, are struggling to get a toe — let alone a foot — in the door. Internships, entry-level and junior positions, the essential stepping stones to white-collar careers, have been disappearing for several years due to cost pressures and post-pandemic belt-tightening. As of 2023, there are entry-level job openings in the US sunk 35%according to labor research firm Revelio Labs.
The advent of AI is accelerating the entry-level apocalypse. Two-fifths of the world’s leaders revealed that entry-level roles have already been reduced or eliminated due to the efficiency of AI performing investigative, administrative and briefing tasks, with 43% expecting this to happen in the coming year.
“While there has been steady hiring or even growth in the skilled trades, we are seeing significant declines in entry-level positions in technical, customer service and sales positions,” said Mona Mourshed, founder of the workplace development nonprofit Generation. “As we are in the business of training and placing people in entry-level positions, we find this very concerning.” Graduates are clearly not doing well, but so are the companies that decided they could do without them.
AI at work: the driverless supercar
The logic was seductive in its simplicity. Reduce costs, move faster, reduce training budgets and let AI and a leaner workforce do the rest. In reality, it produces something very different: flat teams with little agency, endless cycles of rework, and exhausted senior staff juggling all levels of tasks at once.
One Redditor who posted about how their company stopped hiring entry-level engineers, received hundreds of other responses while others came up with similar stories. One commenter noted, “I’m not sure what the plan will be after the knowledge transfer is over.”
Isaac has seen this dynamic unfold firsthand. His company’s leaders see AI as a force multiplier and are quick to fixate on shipping functions. Isaac understands their point: “[AI] can directly write better, faster, and more readable code than most developers,” he admits. However, he points out that “any seasoned engineer knows that the hardest part isn’t writing the code, it’s designing and testing it.” Yet there are far fewer people to delegate this work to, so senior developers have to do it alone.
The problem is compounded by the fact that AI does not understand the problem it is intended to solve. If left unchecked it can go rogue. Isaac recalls several examples of chatbots deleting production stacks – without being asked – because they couldn’t figure out how to solve a problem. “Without an expert who knows how to drive and guide this, AI is just a supercar without a driver,” he says. The team has seen their workload steadily increase in line with automation, so the time savings this brings has had little impact. Many seniors have checked out and several burned-out engineers have signed up for medical leave.
Research from project management platform Asana underlines this growing ‘efficiency illusion’. While 77% of employees are already using AI agents Nearly two-thirds say the tools are unreliable and more than half say agents confidently produce false or misleading information. The result is that time is wasted: an American study shows that employees spend a lot of money additional 4.5 hours per week Fix AI workplace.
“AI can make work look faster on the surface, but it can also involve a lot of cleanup work: double-checking output, correcting errors, and redoing steps that were based on incorrect information,” Mark Hoffman, Asana’s Work Innovation Lead, tells Fast Company. When something goes wrong, accountability is unclear, he adds, and the onus often falls back on the employee to catch errors, explain the outcomes and manage the risks. It causes record levels of burnout; 77% of knowledge workers say their workload is unmanageable and 84% are digitally exhausted.
When mistakes slip through the cracks, the consequences are costly and embarrassing. Three-quarters of Americans report at least one negative consequence of poor AI outcomes, including work rejected by stakeholders (28%), security incidents (27%), and customer complaints (25%). In October, Deloitte was forced to do so reimburse the Australian Department of Employment and Industrial Relations after a report found it contained AI hallucinations and workflows. In the past, novice consultants would have performed these types of tasks. It is striking, however, that Deloitte has reduced its cohort of graduates 18% and eliminated hundreds of early-career positions earlier that summer.
The demographic time bomb
Not only are workloads increasing, by hollowing out their lower ranks, companies are putting themselves squarely in the path of a slow-burning demographic time bomb as seniors retire. record numbers.
From 2024 to 2032, 18.4 million experienced employees The 55 to 64 age group is expected to retire with post-secondary education, but only 13.8 million younger workers (currently 16 to 24 years old) are entering the workforce with equivalent qualifications. Even in an AI-powered economy, where some jobs will be automated, companies still need people with judgment, context, institutional and sector-specific insight.
Yet many are taking steps – at least for today – to wipe out the training ground that turns beginners into experts.
“There won’t be an endless supply of experienced employees to fall back on, so everyone will be fighting for the limited, increasingly expensive talent with domain expertise,” said Cali Williams Yost, futurist and founder of flexible work consultancy Flex+Strategy Group. “Companies may have five years to train younger employees to adopt and acquire the niche knowledge, so AI has some potential to increase.”
Moe Hutt, an entry-level recruitment marketing expert and consulting director at recruitment marketing firm HireClix, has seen clients scale back or abandon hiring, citing AI-enabled workflows and economic uncertainty. Hutt points to the less visible consequences within organizations, beyond damaging the talent pipeline. “It’s human nature to want to help,” she says. “If there is no release valve when training juniors, there will be friction everywhere.”
For middle and upper management, delegating, teaching and seeing someone grow is a reward for the experience. Research consistently shows that knowledge sharing and mentoring improves motivation, increases psychological well-being, And reduces burnout among experienced employees. With no one to train or teach, disengagement spreads, hollowing out a workforce where most people have already checked out.
Being AI-savvy and prepared for the demographic cliff are not mutually exclusive. Organizations can build pro-worker environments that empower workers with AI without eroding their future talent pipelines. PwC – admittedly, another company that has been that way too open about the cuts in recruiting startersat least in Britain, is experimenting with what that balance might look like training junior accountants to become managers of AI. Entry-level employees are exposed to leadership and responsibility early on, as the company builds a cache of managers fluent in both human judgment and machine output. It’s proof that efficiency and succession planning can coexist.
This matters because the disappearance of entry-level jobs will not only be a problem for the corporate workforce – it will also be a social crisis. A well-functioning society depends on the younger generations gradually taking over the tasks of the older generations.
AI could write the code, but without humans trained to guide it, question it, and ultimately replace their elders, there will be no one left to keep the lights on.
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