Why young workers are struggling to land entry-level jobs

Young workers are being shut out by a low-hire, low-fire economy

The main constraint for young workers is not mass layoffs. It is a shortage of hiring. Companies are keeping existing employees while reducing the number of new people they bring in. Economists Rodgers and Kassens describe this as a “low-hire, low-fire” economy.

That distinction matters. An experienced worker benefits when a company decides not to cut staff. A recent graduate does not. Young people need employers to create openings, make offers, and accept the cost of training people with limited experience. When hiring slows, the entry point into the labor market gets narrower even if headline employment remains relatively stable.

Rodgers and Kassens examined the Current Population Survey, produced jointly by the U.S. Census Bureau and the U.S. Bureau of Labor Statistics (BLS). They also used the BLS Job Openings and Labor Turnover Survey, or JOLTS, to assess broader labor demand. Their analysis points to weak hiring as a central part of the problem facing younger workers.

The business risk extends beyond the current hiring cycle. Entry-level jobs develop the people who later become experienced engineers, managers, sales leaders, and specialists. If companies repeatedly reduce junior hiring, the immediate benefit is lower recruitment and training cost. The longer-term consequence can be a smaller pool of workers with the experience needed for more senior positions.

Executives therefore need to distinguish between reducing headcount and changing how junior talent is developed. Companies can keep hiring selective while making entry-level development more efficient. Structured onboarding, apprenticeships, targeted training, and clear skill requirements can reduce the cost and uncertainty of hiring inexperienced workers.

The key management question is whether current hiring levels can support the skills the business will need several years from now. A low-hire environment can improve near-term cost control. If maintained too long, it can also weaken the future talent pipeline.

AI skill demand is raising the entry barrier for young workers

About one-third of the increase in unemployment among workers aged 18 to 24 is attributable to rising demand for skills required in AI jobs, according to the analysis by economists Rodgers and Kassens. Their conclusion is important because it separates AI’s effect from the broader slowdown in hiring. AI matters, but it does not explain the entire decline in opportunities for young workers.

The researchers describe AI’s impact as “narrow, early and age-specific.” Employers increasingly want skills related to generative AI, machine learning, and neural networks. At the same time, companies are advertising fewer openings and making fewer offers. Young applicants therefore face two constraints at once: fewer opportunities to enter the labor market and higher technical requirements for some of the jobs that remain.

Rodgers and Kassens reached this conclusion by analyzing detailed job postings. They classified positions as AI jobs when employers required skills from a defined group of AI-related capabilities. This method provides evidence about how demand for skills and tasks is changing. It does not establish that companies are using AI to automate jobs, eliminate junior positions, or screen applicants. The researchers explicitly make that distinction.

A decline in entry-level hiring should not automatically be attributed to AI replacing workers. The broader low-hire environment remains a major factor. The evidence instead indicates that AI is changing what some employers expect candidates to know before they are hired. That shift can place inexperienced candidates at a disadvantage because they have had less time to acquire applied technical skills.

Companies also face a practical choice. They can require new hires to arrive with AI capabilities, or they can develop those capabilities internally. Requiring experience can reduce training needs today, but widespread use of that approach can narrow the available junior talent pool. Structured AI training, clearer entry-level skill requirements, and roles designed around learnable capabilities can give employers another option.

For C-suite leaders, the priority should be to identify which AI skills actually create value in each role. Not every employee needs expertise in machine learning or neural networks. Some roles require the ability to use generative AI tools effectively; others need deeper engineering knowledge. Precise requirements can prevent businesses from adding unnecessary qualifications that exclude capable candidates without improving performance.

AI is already raising the employment threshold for some young workers, but it is one part of a wider hiring problem. Companies that define AI requirements carefully and invest selectively in junior development can gain needed capabilities without unnecessarily restricting their future talent supply.

Early-career employment is falling fastest in AI-exposed work

Since late 2022, early-career employment has declined significantly in occupations with high exposure to AI, according to a 2025 Stanford University study. Software engineering and customer service are among the affected fields. The timing overlaps with the rapid spread of generative AI after OpenAI launched ChatGPT in late 2022.

The important signal is the difference by career stage. AI can perform or assist with tasks that have traditionally been assigned to junior employees, particularly routine coding, information retrieval, drafting, and customer interactions. This gives employers more options for completing some work without expanding entry-level teams. The Stanford findings indicate that younger workers in highly exposed occupations have experienced the clearest employment pressure.

But the evidence does not prove that AI directly caused every lost job. The period since 2022 also includes a broader slowdown in hiring. Technology companies in particular adjusted employment after aggressive expansion during the pandemic. The findings therefore support a relationship between AI exposure and weaker early-career employment.

This distinction matters for business decisions. Executives should not frame workforce planning as a simple choice between AI and junior employees. The more useful question is how AI changes the mix of tasks within each role. If software can handle more routine work, companies need to determine which remaining tasks justify an entry-level position and how junior employees will acquire the experience needed to perform higher-value work.

There is also a longer-term talent issue. Senior employees do not enter the workforce with senior-level experience. Organizations traditionally develop expertise through progressively more complex responsibilities. If AI reduces the volume of basic work available to junior employees, companies may need to redesign training rather than simply reduce recruitment. Otherwise, lower entry-level hiring today can translate into fewer experienced candidates for specialist and leadership positions later.

For C-suite leaders, this calls for workforce design based on tasks and skills. Identify which activities AI can perform reliably, which require human judgment, and which junior workers need to practice to develop expertise. Then redesign entry-level roles around valuable work that combines AI use with structured learning and increasing responsibility.

The business opportunity is to use AI to improve the productivity of new employees rather than treat junior headcount as an automatic target for reduction. The 2025 Stanford evidence shows that early-career employment in AI-exposed fields is already under pressure. Companies that preserve effective paths from junior to experienced work will be better positioned to maintain critical skills as AI adoption expands.

Remote work is making junior talent harder to develop

Young workers’ unemployment rose by 1 percentage point in jobs that can be performed remotely, according to research from the Federal Reserve Bank of New York. Older workers moved in the opposite direction: their unemployment rate in remote-capable occupations declined slightly. Younger workers also performed better in occupations that could not be done remotely.

The core constraint is training. Experienced employees can often work independently because they already understand professional processes, organizational expectations, and the technical requirements of their roles. New graduates need more instruction, observation, feedback, and repeated interaction with experienced colleagues. Distance can make those activities more costly and less frequent unless the company deliberately designs for them.

Hiring patterns at one Fortune 500 company reinforce this explanation. The researchers concluded that the firm appeared willing to train junior employees when workers could interact in person, but became more reluctant to employ inexperienced people when distance created barriers to development. This finding does not establish that remote work causes higher youth unemployment across the economy. Evidence from a single company should not be generalized to every employer, industry, or occupation.

The broader New York Fed findings are still relevant for workforce strategy. Remote work does not necessarily create the same value for every employee. An experienced specialist who already has strong internal networks may need little direct supervision. A new employee learning both a profession and a company’s operating methods can have very different requirements. Applying one remote-work policy to both groups can therefore produce different outcomes.

For executives, the answer is not necessarily a broad return-to-office mandate. The more precise response is to determine which activities require proximity and which can be performed effectively at a distance. Early-career roles may benefit from structured periods of in-person onboarding, regular access to experienced colleagues, defined mentoring responsibilities, and clear performance feedback. Remote training also needs explicit processes rather than depending on informal communication.

Managers are central to this model. Hiring junior employees without giving senior staff the time or incentives to teach them will weaken development regardless of location. Companies should therefore treat mentoring capacity as part of workforce planning. If managers and experienced employees are expected to develop new talent, that work needs defined ownership, adequate time, and measurable outcomes.

The strategic issue extends beyond where employees work. Companies need a reliable process for turning inexperienced hires into productive, independent employees. The Federal Reserve Bank of New York research suggests that physical proximity can make that process easier for some junior workers. Businesses that want to preserve remote flexibility should ensure their training systems can deliver the same development deliberately.

Key executive takeaways

• Low hiring is restricting the talent pipeline: Companies are retaining existing staff but creating fewer entry-level opportunities. Leaders should test whether today’s hiring restraint could leave them short of experienced talent in the coming years.
• AI skills are raising entry requirements: Rising demand for AI capabilities accounts for roughly one-third of the increase in unemployment among workers aged 18 to 24 in the cited analysis. Define which AI skills each role actually needs and train promising junior hires where practical.
• AI-exposed roles face greater early-career pressure: A 2025 Stanford study found significant declines in early-career employment in highly AI-exposed fields. Redesign junior roles around AI-assisted work, human judgment, and structured skill development rather than treating automation as a reason to eliminate entry-level hiring.
• Remote work can complicate junior development: New York Fed research found youth unemployment rose by 1 percentage point in remote-capable jobs while declining slightly for older workers. Build structured mentoring, feedback, and targeted in-person training into flexible-work models.