ACM CareerNews for Tuesday, July 7, 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 13, July 7, 2026
Want an AI-Proof Job? New Research Says You May Be Safer at Companies Embracing the Technology
Yahoo Finance, July 4
While AI is often cited as one of the reasons for mass layoffs in the tech sector, it also appears to be creating new jobs at many companies. According to a new research report, firms are starting to look for more entry-level hires, especially young workers who are AI-native. The report tracked AI spending and the workforce records of nearly 22,000 U.S. companies between January 2021 and February 2026. It found that firms that spent more on AI ended up increasing their workforce headcount by an average of 10% over the two years after rolling out the technology.
Companies that made the largest AI investment expanded entry-level job hiring by 12%. Thus, when choosing between two different firms that are otherwise similar, jobseekers should focus on the one that is using AI. The early and intense AI adopters spent more than $100 per month per employee on AI and had their employees using advanced AI, such as coding subscriptions, as opposed to simple ChatGPT subscriptions. The low-intensity, casual AI adopters did not see any hiring gains and reduced headcount. The study showed a positive effect on employment from AI because it focused on firms adopting AI, many of them fast-growing, venture-backed companies hiring AI-native junior employees. It reached a different conclusion than a 2025 Stanford University study, which examined payroll data across the entire labor market and found that employment among young software developers had declined by nearly 20% from its late-2022 peak.
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Demand For AI-Ready Coders Skyrockets in 5 Years
CIO Dive, June 23
According to a new study, roles for developers with AI skills have skyrocketed in the last five years, far outpacing demand for non-AI roles. Based on an analysis of 35 million global job postings since 2021, the study found that AI-augmented roles for software development jumped nearly 600%. By comparison, traditional developer roles increased just 28% in the same period. AI trainers, who work to guarantee model reliability and trustworthy outputs, was the fastest-growing position globally, increasing nearly 300% in five years.
While AI-attributed layoffs continue to generate headlines, AI adoption is actually leading to increased hiring in specific categories. Nearly one-quarter of roles for software developers in the U.S. and the U.K. now require expertise in AI as organizations grapple with lengthy hiring cycles. In fact, more than a half million tech job postings are open in the U.S., according to the latest data. As a result, leaders aiming to support widespread adoption in their organizations should look more closely at their talent strategies. People transformation, not technological transformation, is almost always the area that is lagging, the one that takes the most effort and the most time.
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Show Your Work: How to Prove Your Way to a Job Offer
Dice Insights, June 26
Tech employers are increasingly requiring tangible evidence of the capabilities of a job candidate through completed projects, case studies, open-source contributions and code repositories before making hiring decisions. The rise of proof-of-work screening is a major shift that transitions the focus of the hiring process from proof of what you know to proof of what you can actually do. In short, hiring organizations are looking for hard evidence that you have done similar work in the past and proof that you can do it again.
First and foremost, candidates should use evidence and proof to address the needs and concerns of hiring managers. They should select work samples that directly connect their past experience and results with the specific problems the hiring manager is trying to solve. The ultimate goal is to reduce the fear of making a bad hire. To avoid mistakes, managers look for answers to several key questions when they review samples. For example: Can this person actually do the work? The best way to answer this question is through the execution layer. Do not describe what you built, show it. Screen-share and walk the reviewer through data dashboards, campaign analytics, website UX flows, or software demos.
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Will AI Create New Entry-Level Jobs?
HR Dive, June 26
HR leaders believe that artificial intelligence will allow them to create new entry-level roles for junior employees, with 94% saying they expect that will happen within the next five years. In addition, 96% of HR leaders said entry-level roles will evolve into positions where employees supervise or manage AI within five years as these early career positions pivot away from carrying out basic tasks and toward collaborating with AI systems. Meanwhile, more than 90% of the HR professionals surveyed said that reshaping entry-level positions was up to middle managers, who are instrumental in redefining job roles.
Companies need more AI-ready workers, and they also need the proper developmental resources to keep pace with demand. Although 91% of respondents said workers have upped their requests for AI training over the past year, 46% of companies do not provide that training. Another 60% of HR professionals said their learning and development programs were too slow to keep up with the speed at which AI was moving. AI is reshaping the talent landscape and exposing the limits of traditional talent and learning models. With the fundamental shift in entry-level tasks and skill requirements changing rapidly, organizations must rethink how they hire and develop talent at pace. Employees and candidates with broad, interdisciplinary backgrounds are better suited to new AI-focused entry level roles than people with specific degrees or narrow skill sets, according to 69% of respondents. Another two-thirds (67%) said they find liberal arts degrees more valuable than they used to, and 97% said soft skills were especially important because they demonstrated adaptability, problem-solving, and human judgment.
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Computer Science Grads Have a New Dream Job
Entrepreneur.com, June 23
For years, the primary job goal for computer science majors in college was a high-paying role at a tech giant in Silicon Valley. Now, a growing number of graduates are reorienting their ambitions. Instead of working for well-established tech companies after college, they are taking a risk and starting their own companies. Several forces are converging to make company founder the new dream job on campus. The traditional pipeline from a computer science degree to a big-tech job has weakened. Hiring has slowed down, and automated tools have reduced the need for large junior engineering teams.
For many graduates, starting a new tech venture feels is the new top choice when confronted with months of unanswered applications or rescinded job offers. Additionally, AI tools have lowered the cost of shipping a minimum viable product, allowing small teams to create products that once required entire departments. In this environment, the founder path looks less like an outlier and more like a competitive option for ambitious computer science graduates who want to take control of their careers.
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Job Candidates Need These 2 AI-Proof Traits to Get Hired
CNBC, June 16
As they scale up their use of AI, companies are looking for new traits in the candidates they hire. One of these is curiosity. In a world that is moving as fast as today, with so much changing, workers have to be curious. This includes curiosity about new technologies, as well as curiosity about why certain decisions are being made. Workers also have to be willing to go the extra step. They need to prove that they have taken the extra initiative to get things done within their organizations, as well as to remain competitive in their current roles.
Job candidates should have curiosity about what is coming with technologies like AI, as well as curiosity about why decisions were made by key business leaders. This means understanding the overall business context, the philosophies that mattered, the debates that occurred, and why certain approaches might enable an organization to build stronger. To gauge the curiosity of a candidate, an interviewer might ask a question in a job interview like: What have you learned outside of your core discipline that you then put into practice for impact? For example, maybe a candidate experimented with vibe coding and then used it in a creative way to move a project forward at work.
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Report: AI Boom Hasn’t Altered Labor Force or Wages
Tech.co, June 23
The AI boom has had only a minimal impact on the U.S. workforce and wages, according to a new study from the European Central Bank (ECB). Despite heavy investment in AI technology, fears that artificial intelligence will lead to mass unemployment are so far largely unfounded. According to the research, the U.S, economy began to adjust to the emergence of AI several years ago, with jobs from the most vulnerable sectors being reallocated to other segments. This has gradually reshaped the labor market, but the study notes no major income effects.
The European Central Bank found that the AI boom of the last few years has not yet substantially altered the US workforce, despite fears to the contrary. There has also been no noticeable impact on wages, the report notes. Some workers may be displaced, with junior staff in highly exposed sectors thought to be most at risk. However, the report observes, the overall aggregate impact on the workforce and wages has so far been minimal. The U.S. economy begun its adjustment to the AI explosion several years ago. In the interim, jobs from the most vulnerable sectors have been reallocated to other segments, which has slowly reshaped the labor force.
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Technology Usually Creates Jobs For Young, Skilled Workers. Will AI Do the Same?
MIT News, May 21
While technology has the potential to replace traditional jobs, it also has the potential to create new lines of work. A new study of U.S. employment show that, historically, new forms of work have tended to benefit college graduates under 30 more than anyone else. This raises the promise that new AI technology might have the same impact. A lot of innovation-based new work is driven by demand. If you create a large-scale activity, there is always going to be an opportunity for new specialized knowledge that is relevant for it.
Right now, it is too soon to tell just how AI will affect the workplace. People are worried that AI-based automation is going to erode specific tasks more rapidly. However, eroding tasks is not the same thing as eroding jobs, since many jobs involve a lot of tasks. Right now, economists do not know what the new work will be, what it will look like, and who will be able to do it. New work, though, is always tied to new forms of expertise. At first, this expertise is scarce. Over time, it may become more common. In any case, expertise is often linked to new forms of technology. The four co-authors also collaborated on a previous major study of new work, published in 2024, which found that about six out of 10 jobs in the U.S. from 1940 to 2018 were in new specialties that had only developed broadly since 1940.
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Real-World Lessons of AI's Impact on Developers
ACM Queue, June 6
As AI tools become increasingly embedded in software development workflows, there is a growing need to understand their true impact on developer productivity and experience. A new study examines the influence of AI across the dimensions of the SPACE framework: Satisfaction, Performance, Activity, Collaboration, and Efficiency. Drawing on survey responses from more than 500 developers, the study suggests that AI is widely seen as enhancing productivity, particularly for routine tasks. The benefits vary, however, depending on task complexity, individual usage patterns, and team-level adoption.
Organizational support and peer learning play key roles in maximizing the value of AI. Current findings suggest that AI is augmenting developers rather than replacing them and that effective integration depends as much on team culture and support structures as on the tools themselves. On one side of the coin, it seems clear that developers themselves are not worried about the potential of AI to replace them in the foreseeable future. Only 10 percent of software engineers express concern that AI might take their jobs. For those working with these tools every day, the reality is clear: AI tools are not replacing developers; they are augmenting them, helping them work faster, smarter, and with less toil. On the flip side, some organizations remain hesitant about whether AI is worth the investment. The truth, assuredly, lies somewhere in the middle.
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Toward an AI-Corps
Communications of the ACM, June 25
The U.S. has outlined a national imperative to build an AI-ready workforce capable of innovating responsibly and competitively. However, despite major investments in AI research, workforce preparation continues to lag behind, and the shortage of AI professionals across industry and government continues to widen, with particularly low participation from rural and underrepresented communities. While several efforts have been undertaken to boost workforce participation rates, what might be needed is a program along the lines of CyberCorps, which has already demonstrated the success of a structured education and service model for cybersecurity workforce development.
While recent national discussions emphasize federally funded scholarship-for-service pathways into government agencies, the AI-Corps framework is intentionally broader, enabling institutions to cultivate AI talent through education, research, service, and internships without requiring mandatory post-graduation federal service. In contrast to the traditional emphasis on workforce shortages primarily at the federal level, there is a critical role to be played by regional, rural, and industry-adjacent ecosystems in scaling AI workforce development. Thus, the time is right for a comparable AI-Corps initiative. This would be a federally supported, scalable framework that integrates AI education, research, and civic service to build a diverse, ethical, and technically capable AI workforce.
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