ACM CareerNews for Tuesday, November 18, 2025
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 21, Issue 22, November 18, 2025
Tech Job Demand Rose in October
CIO Dive, November 13
Job postings for technology roles increased 5.3% month over month in October. Nearly half a million open job postings were active last month. Employers added 217,238 net new postings in October, a 3.8% jump from September. Given the prevailing economic unease, the better-than-expected volume of tech job listings is a welcome bit of good news. It speaks to the many moving parts of the vast tech workforce and the not always apparent offsetting effects of job gains, job losses and job transitions.
The U.S. Bureau of Labor Statistics delayed the release of its monthly jobs report amid the government shutdown, leading to a lack of good official data on the jobs market. The lack of government data has put private sector data in the spotlight, including from payroll services company ADP, which determined private sector employers added 42,000 jobs to the economy last month. Despite some positive signals, the technology sector is still absorbing the impact of significant layoff waves at major tech providers. Layoffs are a sign of shifting strategies. This is important to keep in mind since there are still thousands of open job postings at companies that have announced cuts.
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Want a Tech Job? These Skills Will Matter Most in 2026
ZDNet.com, November 14
IT professionals play a crucial role in supporting the technological advancements of organizations, as frontier technologies continue to evolve and transform the landscape of many industries. As a result, their roles are growing in demand, even with the rise of AI. A new report, which surveys over 800 IT professionals, provides insights into the latest trends in the IT space. Overall, there is a positive outlook for IT, but professionals do need to evolve their skills in response to AI.
The emergence of increasingly intelligent AI has raised widespread concern about its potential to replace human jobs. That fear is heightened in the tech industry due to the high competency of AI tools in performing coding-related tasks. That being said, analysts still project 9% growth in computer and IT occupations from 2024 to 2034, compared to a 3% growth for all occupations. Furthermore, the same data show that the 2024 median salary for computer and IT occupations is twice that of the median salary for all other occupations. Yet most respondents said they find it difficult to hire skilled IT talent.
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3 in 10 Firms Plan to Replace Workers With AI Next Year
HR Dive, November 13
Three in 10 companies plan to replace employees with artificial intelligence next year as the technology drives increased automation in the workplace. This will impact nearly all sectors of the economy, especially those that are IT-related. Among business leaders anticipating AI-related layoffs, a clear majority (59%) said the technology will replace 10% or more of their current workforce. One in ten respondents said they expect AI to replace 50% or more of their workforce.
U.S. employers announced 153,074 job cuts in October, up 175% compared with the year-earlier period, in part due to AI-driven automation. Among private sector employers, cost-cutting was the top reason cited for job reductions, leading to 50,437 announced layoffs. AI was the second-most cited factor in the private sector, triggering 48,414 job cuts. Despite the rapid rise of AI across industries, most chief financial officers (CFOs) are still in the early phases of using the technology in their own functions. CFOs are clear-eyed about the promise of AI, but they are equally aware that getting there will take time. Finance leaders are taking thoughtful, phased approaches when it comes to adopting the technology. They are focusing on building literacy and capability among their teams so AI can augment human expertise rather than replace it.
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AI Skills Increasingly Crucial For Cyber Pros Looking For Jobs and Advancement
Dice Insights, November 6
Cybersecurity hiring has slowed over the past six months, as businesses reassess their budgets amid a slowing U.S. economy. Still, the CyberSeek job board currently lists more than 514,000 open cyber positions. A look at the open position numbers shows that the cybersecurity profession has reached a major milestone. CyberSeek found that 10 percent of all these available security positions specifically state that the job requires candidates to have some type of artificial intelligence (AI) skill to be considered. For other segments of employers, it may be an implied skill requirement not explicitly mentioned in the job listing.
While there is concern that AI could eliminate entry- and junior-level positions, research firm Gartner found that organizations that want to deploy AI for security still need skilled cyber professionals. These employees, however, must also be trained in AI and related areas so they understand the intricacies of how these virtual chatbots and other platforms work.
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How to Hire in the Age of the AI Workplace
Inc.com, November 7
Even as more powerful AI systems are hitting the market and companies are rushing to embrace them, there is a growing awareness that training and skill levels among workers are not matching the same pace. A new study looks at the kinds of tools that people are using to help them get hired in the first place, and also the differing skill levels that candidates need to have to be attractive to employers nowadays. Though AI is still relatively new, the data shows there is already some changing expectations about what good AI use means.
Over half the 550 U.S. organizations surveyed said AI is involved in daily decision making. This is a very high percentage, given that market leading AI ChatGPT was only released to the public three years ago. Meanwhile, the data also shows that only 38 percent of the leaders of these companies feel their employees are fully prepared to use the tech. This gap between expectation, deployment, and practical AI use is reshaping the job market. It is replacing workers in some cases, as well as revealing who is ready to work alongside it. The research shows that while many companies are already relying on AI internally in ways that are likely shaping their business growth, just 27 percent of recruiters are comfortable with job candidates using AI tools to help them shape their resumes or in negotiating salaries.
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Hybrid and Remote: The Future of In-Demand IT Jobs
Spiceworks, November 11
The continued skills and jobs gap in the tech sector has forced many changes in how organizations recruit and retain IT workers. This includes wide-scale acceptance of remote and hybrid work models. IT roles that were traditionally only done on-site are now often done remotely, and job candidates can sometimes negotiate that perk when considering a job offer. This change is driven by necessity, with data showing that 76% of U.S. IT employers report difficulty finding skilled talent. Remote flexibility has become a strategic imperative to attract and retain these professionals.
Remote work opportunities are now common, especially with many contract IT positions, such as those involving hard-to-acquire skills and experience. Individual IT contractors have always been able to manage their workload without the dependencies of others or direct management. They often work on a ticketed or task based project management system. In the IT sector, these roles are typically software engineers, programmers, help desk and support technicians. Just over half of active IT openings are remote, with most concentrated in contract roles supporting Workday, SAP, Epic, ServiceNow, and cloud or data development.
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How Companies Use AI to Choose Who Gets Hired and Fired
TED Radio Hour (NPR), October 3
The job application process is going through a dramatic transformation. It started about 25 years ago, with the launch of new internet-based job platforms like LinkedIn, Monster, and ZipRecruiter. Once you go online, an algorithm will show you all the jobs that you are probably qualified for, and you can apply with one click. But as the years went by, they became too much of a good thing. It got so easy to apply for a job that everyone started applying to everything. That is especially true today, with the growing popularity of AI.
The job search market has now reached a point where a lot of companies close the application process after 24 hours because they have already received hundreds or even thousands of resumes. Google says they get over 3 million applications a year. IBM gets over 5 million applications. No wonder hiring managers are overwhelmed, and they want a solution. To get through all those applications, companies turned to software that weeded out the least-qualified people immediately. But even that had limitations. So, about 10 or so years ago, big companies started using AI. The hope was to screen applicants for more than just their qualifications. Amazon, for example, built an algorithm to rate applicants, kind of like how shoppers rate products. They had built a machine learning algorithm to find out who are going to be the people that are going to be successful in a specific branch of Amazon. To do this, Amazon fed all the resumes from qualified applicants from over the previous decade and asked the machine to find patterns.
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The Surprising Truth About Why Some People Have Better Jobs Than Others
Fast Company, November 3
Jobs that pay well, offer stability, and provide opportunities for career growth are almost universally considered better. A tenured professorship, a senior engineering role at a reputable company, or a stable IT position all combine financial security with long-term prospects and prestige. Jobs that grant people a degree of control over how and when they work tend to score higher on satisfaction than those defined by micromanagement or rigid supervision. Occupations that contribute to something meaningful are viewed as more fulfilling than those that feel transactional or pointless.
A good way to acknowledge these nuances, and yet still predict whether a person is likely to access better jobs, is to examine why some individuals have more choices than others. That is, in any job or labor market, available job or career opportunities may have different degrees of appeal or attractiveness; but from the perspective of job seekers, the more employable you are, the more likely to are to find and maintain a desirable job. With this in mind, there are some critical learnings about the science of employability that explain why certain people are better able to access in-demand jobs. For example, research has consistently shown that employability is largely a function of personality. Traits such as conscientiousness, emotional stability, curiosity, and sociability predict not only who gets hired, but also who thrives once employed. Personality shapes reputation and reputation determines whether we are trusted, promoted, and retained. For instance, people who are reliable, calm under pressure, and open to learning tend to be more employable than those who are erratic, avoid feedback, or difficult to work with. Moreover, personality also predicts job satisfaction: even in objectively good jobs, neurotic or disagreeable people are less likely to feel content, whereas optimistic and adaptable individuals find meaning in a wider range of roles, and are resilient if not satisfied even with jobs that make most people miserable. In short, who you are determines both the jobs you can get and how you feel about them once you do.
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The AI Deskilling Paradox
Communications of the ACM, November 7
Throughout history, new technologies have reshaped the way people work. Each advance delivered progress for society, but often at the cost of job loss and deskilling. Artificial intelligence (AI) is triggering a similar disruption. It alters the way people think and how they work. While AI augments and improves many processes, the deskilling that occurs as a result of AI can contribute to a loss of basic knowledge, a deterioration in social interaction skills, and a diminished ability to analyze, understand, and diagnose critical problems. As a result, researchers are exploring ways to develop new critical thinking frameworks tailored to AI.
Concerns about deskilling appeared in the late 19th century, when machinery and factory automation began to replace human labor on a grand scale. Specific knowledge and roles disappeared. There were fewer job opportunities and usually lower pay for people who had jobs centered on these tasks. Today, AI saves time and sometimes outperforms humans at tasks. The problem is that people who no longer maintain these skills may see their abilities erode, particularly when it matters most. Worse, people with little knowledge or training can perform the same work with AI, thus driving down wages. Without appropriate oversight and controls, both groups may perform worse.
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The Art and Discipline of Prompt Engineering
Blog@CACM, November 7
With the rise of generative AI, prompt engineering has quickly emerged as a potential new career opportunity. Yet some job seekers are still puzzled about what makes a good AI prompt, and how these prompts can be used within specific job roles or to accomplish certain tasks within the work place. Successful prompt engineers realize that clarity and context are required to unlock precision. Vague requests yield vague results, while thoughtfully structured prompts can produce sharp outcomes.
A prompt is the set of instructions you give an AI model. It dictates what the system does and how it responds. Unlike humans, AI cannot infer intent from tone or guess unspecified needs today. Without specificity, the results generated are generic. The difference between vague and specific prompts is dramatic. Prompts are your interface between human intent and machine output. Mastering them is about conveying what you want from AI. Using a framework to structure your prompt could make it more effective. One framework takes into account the following factors: Task, Role, Format, Context, Constraints. Each element of this framework serves a specific purpose in translating your intent into instructions. Task defines your objective with precision. Role establishes the AI’s expertise. Format dictates usability. Context provides the background without overwhelming detail. Include relevant examples that improve the direction of the response. Make sure to leave out extraneous information as it could dilute the response. Constraints set boundaries on tone and content.
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