ACM CareerNews for Tuesday, January 20, 2026

ACM CareerNews is intended as an objective career news digest for busy IT professionals. Views expressed are not necessarily those of ACM. To send comments, please write to [email protected]

Volume 22, Issue 2, January 20, 2026

AI and infrastructure roles dominate the IT-related positions in a new LinkedIn jobs report that ranks the fastest-growing roles in the U.S. over the past three years. The 2026 list shows sustained demand for technical talent supporting AI development, deployment, and operations, alongside data center and quantitative roles tied to infrastructure and analytics. AI engineers rank as the fastest-growing role overall. These professionals design and implement AI models used for tasks such as prediction and decision-making.

AI consultants and strategists are also seeing a spike in hiring demand from organizations. This role primarily focuses on helping organizations plan and implement AI initiatives. The work centers on aligning AI technologies with business goals. Common skills for this role include large language models (LLMs) and machine learning operations (MLOps). These roles are concentrated in the technology and consulting sectors, with hiring strongest in San Francisco, New York City, and Boston. MLOps skills such as model versioning, monitoring, cost optimization, and governance are now seen as minimum requirements rather than differentiators in the case of AI-related jobs. For an AI consultant, it is a combination of these requirements and the skill to scope out problems and determine what level of AI should be utilized for a particular problem and effectively communicate trade-offs.

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Recruiters Are Increasing Their AI Usage as Pressure to Hire Intensifies
HR Dive, January 8

Recruiters are increasingly using artificial intelligence to find suitable candidates for the limited number of available roles. As a result of heightened hiring pressures, 93% of recruiters said they planned to grow their AI use in 2026 in order to meet hiring goals, evaluate candidates and source talent. Meanwhile, 42% said that they are being asked to fill roles more quickly, and 39% said they are being asked to find hidden gem candidates with skills they never would have found before. 

As recruiters work to meet the demands of an increasingly competitive marketplace, AI adoption has accelerated. An August study found that by 2026, one-third of companies expect AI to be running their entire hiring process. To date, nearly two-thirds of recruiters (65%) said they are already using AI tools. The new LinkedIn report found that 59% of recruiters are currently using AI to surface hidden gem candidates. Nonetheless, 66% of recruiters told LinkedIn that finding quality talent had gotten harder, and 73% said they felt unprepared to manage the pressures of their job this year, including navigating increased expectations from their organization. Job seekers also told LinkedIn they were concerned, with 80% saying they felt unprepared to find a job in 2026.

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3 Low-Cost Ways to Level Up Your Career Growth in 2026
Quartz, January 2

The fastest way to get a raise is by investing in yourself. The data speaks for itself. U.S. workers who completed training programs saw an average 8.6% boost to their incomes, according to a new study. In addition to earning more, investing in training can help you land a new job or earn a promotion. With that in mind, the article provides three low-cost strategies to take control of your own professional development.

The easiest way to level up your career growth is to tap into free and low-cost online learning. Online learning is everywhere, and some courses are even free. Two popular options are LinkedIn Learning and Coursera. These are virtual training platforms offering access to free content without a paid subscription. These programs offer industry-recognized certifications, and you can complete some of them during free trial periods. Additionally, some top universities and colleges offer free or low-cost continuing education for professionals. Some employers do offer learning stipends, so check with your company first before paying out of pocket for training.

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AI Is Rendering Some IT Skill Sets Obsolete
CIO Dive, January 13

The lifespan of IT skills is growing shorter as organizations scramble to modernize the toolsets of their workers amidst rapid AI deployment efforts. By 2027, more than 40% of IT skills will be rendered partially obsolete. The shift can be attributed to the rapid adoption of AI within IT departments, as well as the increasing consolidation of roles and skill sets. While tech jobs are not disappearing outright, the way work gets done is certainly changing. AI is compressing skill cycles, reshaping roles and shifting where productivity comes from faster than most organizations expect.

Tech executives spent much of last year fine-tuning their approach to talent acquisition and development. Changes in job categories amid AI adoption gave urgency to this task as companies responded to change. The job market, too, reflected this shuffle. Demand for broader categories of tech talent remained flat while postings for AI-specific roles skyrocketed. As companies infuse processes with newer tools, with software development serving as an early example, human-only tasks are shrinking, while AI-led and human–machine collaboration spreads across engineering. The change is not expected to shrink headcount growth. Instead, AI adoption will help drive a net expansion of 78 million jobs by the end of the decade.

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AI Is Augmenting Jobs, Not Displacing Workers
WebProNews, January 15

According to the new Economic Index report from Anthropic, AI is fast becoming a technology that augments rather than eliminates human roles. The report is based on real-world interactions, where users from various sectors turn to AI for tasks ranging from coding to creative brainstorming. The report introduces five foundational metrics that gauge the role of AI in the workplace. These include user and AI skills, task complexity, autonomy levels, success rates, and the purpose of use, whether personal, educational, or professional. By querying Claude on real-world interactions, Anthropic has uncovered patterns that suggest AI is more of a collaborator than a competitor.

In regions with high AI adoption, tasks are becoming more complex, indicating that workers are offloading routine work to focus on higher-level problem-solving. This perspective aligns with broader trends observed in labor markets. While headlines often focus on the threats of automation, the data shows a nuanced reality. AI is reshaping job functions, not erasing them wholesale. Engineers at tech firms, for example, report using AI to handle 90% of code writing, allowing them to tackle the most challenging coding tasks that demands human ingenuity. Anthropic has noted that this shift in workflows does not lead to layoffs. Instead, it boosts overall output.

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One Chief Economist Says the Job Market Is Tighter Than You Think
Inc.com, January 16

According to the latest ADP employment data from December, hiring slowed while layoffs stayed at historically low levels. While those results point to a softening market, pay growth held strong. The reason for that is clear: employees who switch jobs can command a premium from their new employers. While pay growth for job-stayers stayed at 4.4 percent from November to December, increases jumped from 6.3 percent to 6.6 percent for job-changers.

The salary data reveals that employers still have to compete for talent, even though overall hiring has slowed. Although the pay premium for switching jobs has dropped since peaking at 14.3 percent in 2021, job-changers still saw stronger raises than job-stayers: 6.6 percent versus 4.4 percent in December 2025. The difference in pay highlights the current lack of available skilled workers, and the resulting need to pay higher salaries to attract top workers.

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How AI Is Reshaping IT Careers
BuiltIn.com, January 14

The last two years have proven that the impact of AI on the workforce is no longer hypothetical. Large-scale layoffs driven by automation began in the second half of 2025 and will continue through 2026 as organizations optimize workflows and streamline repetitive tasks. Yet the picture is far more nuanced within IT. Contrary to early predictions of sweeping displacement, IT careers are stabilizing. According to a new survey, fewer than 25 percent of IT organizations expect to downsize in the coming year, while fully half plan to add staff.

AI is changing the fundamentals of how digital organizations operate. Infrastructure, data platforms, cloud services, cybersecurity, and automation are becoming increasingly interconnected through AI-enabled workflows. As a result, the composition of IT teams is being recalibrated with new priorities. When surveyed, IT leaders identified a clear top need for the year ahead. Most (62 percent) require professionals who understand AI data management, up from 43 percent in 2023. This signals a profound shift in what it means to build and operate modern data environments.

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Entry-Level IT Jobs: Why They Are Increasingly Harder to Get
Spiceworks.com, January 12

For entry-level IT workers, a job search can be difficult. Especially for remote positions, openings are routinely flooded with hundreds or even thousands of applicants. After all, when you are up against candidates in other cities or even countries, competition can be intense for coveted roles. Adding to the challenge of landing an IT job, universities are turning out more tech graduates than in previous years, which translates to more people chasing after entry-level IT jobs. The number of students earning an undergraduate degree in computer and information sciences has more than doubled over the last decade.

By tracking historical employment rates and job openings for computer support specialists, it is possible to see the immediate impact on entry-level jobs. That is because computer support specialist is a role that has often served as the entry point for a career in IT. There are far fewer open IT support positions available today than in the recent past. In 2008, there were 234,600 open U.S.-based computer support positions, compared to just 50,500 in 2024. And while the total number of computer support specialist roles has grown over time, from 565,700 in 2008 to 882,300 in 2024, hiring has slowed considerably. Growth began to stall in the mid-2010s, when the number of open computer support positions began to drop significantly.

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Artificial Intelligence: Managing the Unmanageable
Blog@CACM, January 14

Recent advances in artificial intelligence have started to challenge the long-held assumption that tasks performed by computers are predictable, controllable, and safe. In the past, computer scientists programmed machines to complete tasks; now, they are programming them to reach goals and letting them find their own way to get there. It is like the difference between giving someone instructions to assemble something and asking them to build a specific item from scratch. The technical term for this is non-deterministic computing, which means we no longer fully know what our software will do next. This uncertainty changes everything about how we need to think.

Traditional software offers remarkable predictability. It does exactly what you tell it to do. In contrast, an AI agent acts more like a super-fast and very eager new team member with no understanding of existing guardrails. You tell it to optimize network performance, and it studies traffic patterns, identifies inefficiencies you missed, and starts making changes. When this works, it is genuinely impressive. These systems find solutions that rigid automation cannot. However, what happens when that eager AI agent accidentally disrupts your revenue-generating platform in its quest for optimization? Or what if it makes complicated changes that no one on your team can unravel? The worrisome part is not that AI agents fail. After all, traditional software fails, too. The difference is that an agent can execute its plan perfectly and it can still lead to disastrous results. And since these systems operate at machine speed, they can inflict significant damage before anyone realizes something is wrong.

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Techno-Optimism, Techno-Pessimism, and Techno-Realism
Communications of the ACM, December 18

When it comes to the adoption of new technology, computer science professionals can be divided into three distinct categories: techno-optimists, techno-pessimists, and techno-realists. Techno-optimists argue that technology is the glory of human ambition and achievement and often call for unrestricted technological progress. On the other hand, techno-pessimists lay out scenarios for how AI models could become all-powerful and eventually pose an existential risk to humanity. Techno-realists attempt a more nuanced take on the impact of AI.

The awkward discourse about AI currently taking place between techno-optimists and techno-pessimists needs to end. Instead, there needs to be new thinking on how to shape AI for the common good. This is especially the case when it comes to reward functions for AI. Sometimes, AI might attempt to attain the wrong outcome if the initial reward functions are faulty. The worrisome part is that these reward functions might appear to be perfectly OK at the outset. It is only when a potentially disastrous outcome emerges that the initial reward function is shown to be faulty. This suggests that there might be a fundamental safety problem for AI that has been ignored.

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