Amid growing investor concerns about the disruptive impact of artificial intelligence (AI) across global industries, the veteran U.S. technology giant IBM, often referred to as "Big Blue," has announced plans to triple its U.S. entry-level hiring by 2026. This decision comes even as AI appears to be suppressing demand for early-career workers more broadly across the global tech sector. While IBM declined to specify exact hiring numbers, it stated the expansion would be "across the board," affecting a wide range of roles in multiple departments.

This announcement contrasts sharply with signals from another tech leader, Microsoft. Around the same time on Thursday Eastern Time, Microsoft's AI chief, Mustafa Suleyman, suggested in a media interview that AI could fully automate "most tasks" for white-collar professionals such as lawyers, accountants, project managers, and marketers within the next 12 to 18 months. This timeline is significantly earlier than general expectations from the business community and Federal Reserve policymakers, sounding an alarm for the global labor market.

Recent market turbulence, dubbed "Software-mageddon," has been fueled by new AI tools and agentic AI collaboration platforms from Anthropic, a major rival to OpenAI. This has triggered widespread selling in SaaS and broader software sectors globally. Reflecting these severe concerns, the S&P 500 Software and Services Index has fallen approximately 13% since late January, erasing nearly $1 trillion in market value in the week leading up to last Thursday. Domino-effect fears of AI disruption have hit various industry sectors consecutively over the past one to two weeks, from software and SaaS to private equity, insurance, and even labor-intensive sectors like real estate, property management, and logistics, accelerating investor sell-offs of potential "losers."

Addressing the question of whether AI is taking over entry-level jobs, IBM is choosing to swim against the current. "Yes, and specifically for those roles we're told AI can do," stated Nickle LaMoreaux, IBM's Chief Human Resources Officer, at a conference in New York this week. LaMoreaux emphasized that she has completely redesigned the job descriptions for entry-level positions, such as software developers, to build the case for this hiring initiative internally. She noted at the Charter-led Leading With AI summit, "The entry-level jobs you had two or three years ago, AI can do the vast majority of those now. So, if you're going to convince a business leader you need to make this investment, you have to be able to demonstrate the real value these individuals bring today. And that has to be through completely different work."

As a result, LaMoreaux stressed, the portfolio of responsibilities for IBM's early-career employees has significantly changed. With AI tools handling most routine coding tasks, the company's junior software developers now spend less time on that and more time on in-depth communication and collaboration with clients. In the human resources department, entry-level staff now intervene when HR chatbots underperform, correcting outputs and proactively communicating with managers as needed, rather than personally handling every query as in the past.

IBM's latest decision, from a company at the forefront of AI and quantum computing, comes as questions mount about whether AI will erase opportunities for new graduates. Last year, Dario Amodei, CEO of Anthropic, warned that half of all entry-level office jobs could disappear by 2030. Rapid recent advancements in AI models have intensified anxiety among university students, who fear being entirely displaced in an already challenging job market.

LaMoreaux argued that cutting early-career hiring might save money short-term but poses a significant future risk of creating a scarcity of middle managers. This could force companies to continually "poach" talent from competitors, which is often more expensive than internal promotion. She added that such external hires typically take longer to adapt to company culture and systems compared to talent cultivated internally, who integrate more easily into daily operations.

Some tech industry executives and economists believe that hiring young employees represents a better investment for companies during global technological upheaval. Melanie Rosenwasser, Chief People Officer at file-sharing platform Dropbox Inc., remarked that regarding the use of AI technology, "They are like riding in the Tour de France, and the rest of us are with training wheels. Seriously, they are laps ahead of us in their proficiency with AI tools and agentic AI." To leverage young employees' AI skill proficiency, Dropbox is now expanding its internship and new graduate programs by 25%.

IBM is actively transforming junior engineers into frontline forces for the AI era while simultaneously cooling the "AI panic narrative." On one hand, IBM explicitly acknowledges that "much of the entry-level work from the past 2-3 years can now be done by AI," leading to a reshaping of junior role responsibilities and redirecting newcomers toward work with "frontline strategic value," such as client collaboration and AI output correction. On the other hand, the decision to triple U.S. entry-level hiring by 2026 objectively helps temper the "AI disrupts everything" panic narrative that suggests AI will directly eliminate entry-level positions—provided the roles are fundamentally redesigned.

From IBM's perspective, AI does not linearly erase jobs but shifts the value focus of a role from "producing content/writing code/making spreadsheets" to "taming AI into a controllable production line." Undoubtedly, AI first consumes repetitive labor at the "task-level" granularity, while companies will re-slice "role-level" definitions. Microsoft's Suleyman speaks to the automation of "most tasks" within many professional roles, potentially at a pace faster than the market anticipates. IBM's action, while acknowledging this premise, involves rewriting entry-level job descriptions to continue investing in talent supply and migrating human effort to higher-value areas, such as client collaboration, AI exception handling, quality control, and implementation delivery.

From the underlying technical logic of agentic AI workflows, this "role reshaping + hiring expansion" is highly pragmatic. Agents excel at breaking down processes into sub-tasks and executing them automatically (writing code, generating documents, initial screening, creating reports, running experimental scripts, etc.). However, once deployed in production environments, the real bottlenecks often shift to permissions and data connectivity (identity/RBAC, system interfaces, data lineage), tool invocation reliability, evaluation and regression, governance and auditing, and inevitable long-tail exceptions. This implies that enterprises need more entry-level talent skilled at "making AI-run processes operational": their value creation shifts from "manual output" to orchestrating, validating, monitoring, correcting, and co-creating with business stakeholders to transform AI capabilities into efficiently delivered, batch-ready outcomes.

IBM has recently clearly prioritized the implementation of "large-scale, enterprise-grade AI projects"—not just selling AI models or tools, but focusing on selling comprehensive capabilities for "integrating AI into existing systems and efficiently governing and utilizing it in multi-cloud/hybrid cloud environments." IBM's recently released Enterprise Advantage service, an asset-based consulting service for scaling agentic AI in enterprises, emphasizes helping clients rapidly build, govern, and operate internal AI platforms, connect AI to existing systems, and scale agent applications without changing clouds, models, or core infrastructure. To scale this methodology, "people" themselves become part of the delivery capacity; expanding entry-level hiring is likely preparation for the delivery and management梯队 needed over the next 2-5 years.