Just yesterday the market was confidently repeating a mantra: “AI will eat juniors first.” The logic seemed airtight—if an algorithm writes code, answers tickets, and sorts data faster and cheaper, why keep beginners on the payroll? Especially in an era of optimization, layoffs, and margin-driven KPIs.

And then—a reversal. IBM, a corporation with a market capitalization in the hundreds of billions of dollars, announces that in 2026 it will triple entry-level hiring in the United States. Developers included. Against the backdrop of talk about the “end of the junior era,” this sounds almost like a challenge to the market.

And yet, this is neither sentimentality nor a social mission. It is cold calculation. While some companies are trying to “save on the base,” IBM is rewriting the very structure of entry roles. Not to eliminate beginners—but to change their function in a system where routine has already been taken over by AI.

The question is not whether artificial intelligence will replace junior specialists. The real question is this: what will happen to companies in three to five years if they stop cultivating their own talent pipeline today.

A Market in a Rush to Lay Off Its Future

For the past two years, the market has been living in a state of technological panic. Generative AI has learned to write code, compile reports, respond to customers, and analyze data—all the tasks traditionally assigned to newcomers as their “entry ticket” into the profession. Hence the tempting managerial formula: if AI handles basic tasks, why hire basic employees?

We are already seeing many companies freeze junior positions, cut internship programs, and rethink their hiring funnels. The market is shifting toward “ready-made” specialists. Middle and senior—yes. Entry-level—questionable.

At first glance, it seems rational. In practice, it is risky.

Why? Because entry level is not just cheap labor. It is the foundation of the organizational pyramid. It is the part of the team from which leads, architects, and product managers grow within a few years. Remove the bottom layer, and the structure does not become lighter. It becomes fragile.

And against this backdrop, IBM takes a step in the opposite direction. It does not shrink the base—it expands it. But under new rules.

What Exactly IBM Announced

IBM did not issue loud slogans about “saving juniors.” The wording was pragmatic: the company plans to triple entry-level hiring in the United States in 2026. And this is not limited to administrative or support roles—software development is in focus as well.

What matters more is something else. Overall headcount in the U.S. is expected to remain roughly at the same level. In other words, this is not a story about large-scale workforce expansion—it is a redistribution within the structure. IBM is not “adding people.” It is changing the proportion.

After a wave of layoffs and optimization, the company is redesigning its organizational architecture: widening the base rather than narrowing it. This is particularly telling at a time when the broader market is moving in the opposite direction—compressing entry-level hiring and betting on ready-made specialists.

But the key point is not the numbers. The key point is the content of the roles. IBM is not returning to the old model of junior positions. These roles have been rewritten for a reality in which AI is already embedded in workflows. And that is the strategic difference.

Why IBM Is Betting on Newcomers in the AI Era

At first glance, the decision seems paradoxical. If AI can handle routine tasks faster and cheaper, it would be logical to cut the bottom layer of the organizational pyramid. But IBM is operating from a different calculation—not short-term savings, but long-term resilience.

AI does take over “grunt work”—repetitive operations, boilerplate code, basic data processing. Yet at the same time, it creates a new layer of tasks: interpreting results, quality control, adapting outputs to specific clients, and taking responsibility for outcomes.

And this is where the need arises not for fewer people, but for people with a different profile.

If a company stops hiring newcomers today, in three to five years it faces a talent gap. There is no one to grow into middle and senior roles. No one to take on architecture, management, and strategy. The organization ends up competing for ready-made specialists in an overheated market instead of developing its own.

IBM, in essence, is choosing the model of “AI plus human,” not “AI instead of human.” And that distinction matters.

In this structure, newcomers are not executors of routine tasks, but participants in the ecosystem around AI—those who learn to work with the tools, supervise them, and amplify business results. It is an investment not in immediate productivity, but in the company’s future competence.

And that is why the bet is not on shrinking the base, but on redesigning it.

How Roles Are Being Rewritten at IBM

The key point is not simply an increase in the number of vacancies. It is the rewriting of entry-level roles themselves.

Traditionally, a junior position in IT revolved around simple, repetitive tasks: maintaining existing code, fixing bugs, preparing documentation, performing basic analytics. It was a kind of “production school”—a zone where a specialist gained experience through volume. Now that volume is partially taken over by AI.

As a result, the role changes. Instead of executing routine operations—working with AI-generated outputs. Instead of writing dozens of lines of boilerplate code—formulating tasks for AI tools, reviewing results, optimizing them, and adapting them to real business contexts.

A junior is no longer just a “junior executor.” He or she becomes:

• an operator and curator of AI tools;
• a link between business and technology;
• a participant in client interaction;
• a quality controller of automated solutions.

This represents a fundamentally different development trajectory.

In effect, IBM acknowledges that if AI handles the base level, newcomers must be trained one step higher from the start—in the domain of responsibility and thinking, rather than mechanical execution.

And this changes the very model of entry into the profession. Not “first routine, then complexity,” but “first working with the tool, then managing the system.”

What This Means for the IT Market

The IBM story is not a private HR experiment. It is a signal to the market. While some companies are cutting juniors in an attempt to lock in short-term savings, others are beginning to redesign their hiring structures for a new technological reality. And the issue here is not the number of people, but the architecture of the team.

If the model of “not hiring entry-level” becomes widespread, in a few years the market will face a shortage of middle and senior specialists. Not because people will disappear. But because they simply will not go through the growth path inside companies. AI accelerates work. But it does not cultivate expertise.

The second effect is a shift in expectations for newcomers. A junior in 2026 is no longer someone who is “learning to write code.” It is someone who can:

• work with AI tools,
• formulate tasks,
• validate results,
• understand business context.

The third shift is in competition itself. Companies will compete not for the number of developers, but for a team’s ability to integrate AI into processes. And in this race, the winner will not be the one who cut the most people, but the one who adapted its structure the fastest.

For outsourcing and product companies, this is especially sensitive. If entry-level roles are not redesigned now, in a few years businesses will either have to overpay in the talent market or sacrifice speed.

IBM is effectively testing a new norm: not “how many people can AI replace,” but “how should an organization be rebuilt so that AI strengthens people.” And if the experiment proves successful, it may become a benchmark for the entire technology sector.

Not Humanism, but Strategy

The IBM story can easily be interpreted as an optimistic case—“AI is not killing jobs.” But in reality, this is not about optimism. It is about strategic thinking.

AI is already reshaping the structure of work. It does displace certain tasks. It reduces execution time. It lowers the need for routine operations. Ignoring this would be pointless.

But cutting entry-level roles is a managerial illusion of savings. Payroll expenses are reduced today—a deficit of expertise is created tomorrow.

IBM is not betting on protecting jobs. It is betting on controlling its future talent cycle. The company understands a simple truth: a senior does not appear out of thin air. A senior grows out of a junior. Remove the first layer, and in a few years the pyramid begins to sag.

AI is a tool for acceleration. But it does not ensure organizational continuity.

And the key question for the market today is not: “Will AI replace newcomers?”

It is this: “Which companies, five years from now, will be capable of operating complex systems—those that invested in developing people, or those that decided algorithms were enough?”

The answer to that question will determine not just the fate of juniors. It will determine the structure of the entire technology market.

IBM Headcount Dynamics Over the Past 10 Years

The data is based on IBM’s publicly available annual reports (Form 10-K) and aggregated historical SEC filings.

What the trend shows:

• From 2016 to 2020—a gradual workforce reduction.
• 2021—a sharp drop (Kyndryl spin-off and structural reorganization).
• After 2022—relative stabilization with moderate decline.

The overall ten-year dynamic reflects an approximate 29% reduction compared to 2016 levels.

For our analysis, this context matters: the decision to triple entry-level hiring is not happening during a period of expansion, but against the backdrop of a decade-long workforce optimization. That makes the move look strategic rather than cyclical.