ACM CareerNews for Tuesday, August 4, 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 15, August 4, 2026
Demand Outweighs Supply For AI-Skilled Workers
CIO Dive, July 29
Nearly 60 percent of employers are seeking workers who can utilize AI to deliver output, but the supply of these types of employees is lean, according to a new report from Indeed. The job site commissioned a study of more than 1,000 job seekers and 300 employers. Only 14 percent of employees defined themselves as AI natives, underscoring the scarcity of workers who have sufficient know-how to use AI technology to perform tasks and workflows.
AI companies have invested billions in data center and infrastructure to build out the compute needed to support use, but enterprise customers are struggling with finding the IT talent to scale this investment. The data center and infrastructure segments are pushing up global IT spending, which is set to surpass $6.3 trillion this year. Meanwhile, spending on AI tools and compute often lags behind the skills needed to turn AI investments into AI adoption. Casting a wider net when hiring workers will not fix the gap since the external supply of employees skilled in AI is insufficient to meet the demand. The more useful move for tech leaders is to build these skills inside the organization they already have, rather than treat it purely as a recruiting problem. In the absence of widespread formal AI training, most employees are putting in the work on their own to increase their familiarity with the technology.
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IT Hiring Sees a Boost as Software Development Jobs Slowly Bounce Back
CIO.com, July 13
Tech job postings rose for the sixth straight month in June, as employers are increasingly on the hunt for qualified talent to support major technological initiatives. The June employment data suggests that employers are ramping up their technology investments and hiring the talent needed to support them. Even as some tech companies announce layoffs, employers in other industries are accelerating digital transformation initiatives and moving from AI experimentation to implementation.
Data shows that AI and machine learning (ML) job title postings are up 173% year-over-year from Q1 2025 to Q1 2026. These are roles that typically offer median salaries 22% higher than the overall IT market. Hiring for jobs in data analysis (10%), cybersecurity (4%), and IT support (1%) have also seen increases. Tech postings in the finance and banking industry are up 47%, with manufacturing IT jobs up by 27% and IT roles in the insurance, aerospace, and defense sectors up by 23%, pointing to growth for IT across a range of sectors.
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The New Junior Developer: Harder to Land, Harder to Replace
Dice Insights, July 29
This year has seen a dramatic increase in software development job postings, and certain core skills are still very much in high demand. This challenges the popular narrative that AI is threatening career opportunities for entry-level software developers. As a result, experts say that young jobseekers should not worry about AI taking junior jobs away. AI has impacted but not replaced important roles such as cyber engineer and cybersecurity analyst. Regardless of level, tech professionals that engage deeply with AI to solve business problems will remain relevant in the field.
Junior developer roles still exist amidst the explosion of new AI initiatives, but they are under pressure. The engineers thriving early-career are the ones using AI to go deeper, not just faster. Board members and CEOs are also facing pressure to get more done with less resources. That pressure cascades down to developers and knowledge workers to use AI tools. However, use of AI-generated code is causing technical debt to accumulate, as the AI leads to errors that need fixing later. For example, organizations are shipping content product code without understanding the context of the code. Therefore, junior developers still need to understand, read and write code, because people need to check the work of the AI coding assistant.
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Entry-Level AI Workers Now Need Senior-Level Skills
Computerworld.com, June 24
Even entry-level workers with AI capabilities now need senior-level skills to land a job. In fact, AI-exposed entry-level roles are seven times more likely to require traditionally senior-level skills such as judgement and leadership. That is because AI is changing the traditional career ladder. Companies are increasingly looking for candidates that use the cutting-edge tools and services to amplify their performance and grow faster. Organizations must rethink how they mentor and train junior staff, helping them step up much earlier in their careers.
Entry-level job seekers are already dealing with stagnant wages, layoffs, and stalled hiring. Early-career AI job postings have flatlined in highly AI-exposed sectors, and listings for junior roles with mid-career or senior-level skills have grown 35% since 2019. By the end of May, AI-driven job cuts had reached 87,174 for 2026, already outpacing the total of around 54,836 in 2025. The AI-driven layoffs have not reached dangerous levels quite yet, and workers are more productive with it than without it. But companies are rethinking hiring and long-term operational strategies as AI becomes a routine component in daily workflows and processes. Businesses are restructuring aggressively as they reposition for an AI-driven economy.
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Is AI Really a Job Killer? Some Employers Say They Are Actually Hiring More
Fast Company, July 29
The fear that AI is killing jobs has been fueled by ongoing layoffs across corporate America. However, as researchers have repeatedly pointed out, these layoffs still do not point to widespread job displacement. In fact, a new report suggests that some companies may actually be adding jobs due to AI. More than one-third of hiring organizations (35%) said AI will increase head count at their company in the near future. Almost one-quarter of them said hiring due to AI had already increased accordingly; over one-third said AI had already enabled them to accelerate their recruiting process.
The number of people who said they were actively hiring at a lower rate due to AI was far smaller, at 16%, and only 14.4% said they had plans to decrease head count in the coming years. What does seem to be changing, however, is job expectations. Nearly three-quarters of people surveyed said AI skills were now either a major advantage or requirement for certain roles. Over half of employers also expect that their workers will now be more productive. Economists and researchers have warned for some time now that the narrative around AI-related job displacement is misleading and overestimates the impact of AI thus far. Even AI leaders are now backing away from their assertions that the technology would eliminate jobs en masse.
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AI Is Creating New Roles in Cybersecurity: Here Are the Jobs in Hot Demand
ITPro, July 21
Nearly three-quarters (74%) of companies have overhauled security team structures due to the influx of AI tools, and that is sparking high demand for cybersecurity pros with AI-relevant skills. Overall, the rise of dedicated, AI-focused roles in cybersecurity is driving up salaries across the industry. High-end salaries for AI security roles now top $260,000, with positions such as Post-Quantum Cryptography Migration Specialists and AI Governance Leads in high demand.
AI is not taking over cybersecurity jobs. However, it is changing which skills are necessary for the work. Routine analytical work is increasingly automated, while demand is accelerating for professionals who can secure AI systems, govern AI risk, conduct AI red teaming, and orchestrate AI-powered security operations. Dedicated AI roles spanning a range of security-related areas are popping up across the industry. AI security engineers, for example, are in hot demand, now commanding salaries of around $185,000 on average. Roles focused on specific areas and threats are also emerging. Ads for AI Identity Deepfake Defense Specialists have been identified. Other new AI-related roles include: AI Governance, Risk & Compliance Lead, AI Red Team Specialist, and AI Supply Chain Security Engineer.
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Nvidia CEO: How AI Could Actually Create Jobs
Axios, July 24
Nvidia CEO Jensen Huang thinks the artificial intelligence revolution is a wellspring of new jobs. This optimism puts Huang at odds with the dire warnings of massive tech layoffs still to come. According to Huang, it is complete nonsense that AI technology could destroy one-half of American jobs. In fact, AI will do the opposite of eliminating jobs. While AI is automating all of these different tasks, it is actually increasing the amount of jobs that the world needs.
Huang also suggested that the explosion of new data centers could become a catalyst for manufacturing jobs. While the construction and data center spending surge has boosted demand for some manufacturing sectors, overall manufacturing employment levels are still down from their post-pandemic peak. And many of those construction jobs are temporary. While data centers can boost local hiring, the centers themselves keep far fewer permanent workers. Recent studies have shown that AI is bound to change the way people work, but so far, it is not replacing them en masse. That is not to say it hasn't caused some employment pain. AI has been increasingly cited in layoff announcements, though some analysts say that is likely more about redirecting resources than automating gigs.
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Nearly Half of Workers Say They Would Let AI Negotiate Their Pay
HR Dive, July 30
Approximately one-half of U.S. adults (47%) would let artificial intelligence handle pay negotiations for them. However, more than three-quarters of adults said they did not know that AI can give biased career and salary advice. For example, AI can sometimes recommend lower salaries for workers from certain demographic backgrounds. People are handing the most consequential money conversation of their lives to a tool most have never questioned.
Of the more than 2,000 adults surveyed, 1 in 3 have already asked AI about their salary, a raise, a bonus, or how to negotiate. Millennials are the most likely to do so, with more than half saying they have. Workers are not only turning to AI to negotiate pay. Nearly half (49%) said they would also use it to negotiate benefits. Among those who have asked AI for career or pay advice, 43% said they think that their race, gender, ethnicity or sexual orientation influenced the advice given to them. And when told AI can recommend lower salaries for women and people of color, half said they were disappointed, one-third said they were angry, and 16% did not mind.
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Eight Myths on Software Engineering and Generative AI
ACM Queue, May 26
Generative AI is reshaping software engineering, but industry experts are mixed about what the actual impact has been. Marketing claims, anecdotal wins, and misinterpreted studies have given rise to a set of persistent myths that are quietly driving poor decisions about AI adoption, tooling, and how to measure success. Overall, there are eight misconceptions about software engineering and generative AI. For example, we already know developers do not actually spend most of their time writing code. That means AI code generation, even when it works well, touches a surprisingly small slice of the actual job.
AI works better for some tasks, some developers, and some contexts than others. Productivity gains do not flow automatically from handing engineers a license. They require rethinking workflows at the organizational level. Adoption stalls when developers do not trust the tools, lack time to learn them, or worry about de-skilling. The narrative about rapid growth at startups embracing AI ignores the compliance, legacy systems, and reliability constraints that define enterprise software. This means practitioners, team leads, and engineering leaders need a clearer, research-backed picture so the decisions organizations make about AI are grounded in evidence, not just enthusiasm.
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The Evolution of Employee Monitoring in Productivity Management
Blog@CACM, July 27
Most workers would work differently if they knew every keystroke was being saved, every website logged, and every idle minute tallied. That is precisely how employee monitoring started. The first tools had nothing to do with improving work. The goal was to catch people not working when they were not being observed. That approach has evolved over the past twenty years. Today, AI-powered platforms build behavioral profiles, surface patterns across weeks, and flag anomalies before any human analyst would catch them.
Remote work required better tools for tracking productivity. So did honest conversations about what companies can collect, and what workers are owed in return. Before modern tooling existed, organizations turned to keystroke loggers. What these tools could tell you was limited. It could only tell if a person was using a computer right now. The context gap was enormous. A developer quiet for a while might be solving a hard problem on paper, while a support agent typing nonstop might be writing a personal message. No logging software could tell the difference. Large data volumes, very little usable information. This tension between data volume and actionable insight has been a recurring theme across computing and technology discussions for decades.
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