Day: October 6, 2025

• The tech job market faces a candidate surplus in some roles and shortages in others.
• AI is reshaping which tech roles are in demand and which jobs are being eliminated.
• New data from Indeed shows where you should focus your tech skills, and which areas to avoid.

The tech hiring market is being pulled in two directions: a flood of candidates for certain roles and stark shortages in others.

New survey data from Indeed highlights the unevenness of the tech talent landscape and the profound impact of AI on reshaping the skills employers need most.

While many tech jobs attract an oversupply of applicants, the study found that key areas, such as cloud computing, data analytics, and AI development, are still starved for qualified professionals.

“What began as a cyclical downturn in tech hiring may now be entering a new phase — one shaped by the rise of AI, increased requirements, and less demand for entry-level talent,” Indeed wrote in a report released on Monday.

The study analyzed data from Indeed and Glassdoor on tech jobs, in combination with a commissioned survey of 1,035 tech workers in the US conducted by YouGov. Participants, primarily working in software and IT, answered an online questionnaire between late May and early June.

How AI reshapes tech jobs

Generative AI is reshaping career paths. The Indeed study identified tech jobs that have been axed the most when companies adjust their operations to embrace generative AI.

Here are the top four roles that got cut in AI-inspired reorganizations:

• Software engineers and developers
• Quality assurance engineers
• Product managers
• Project managers

Indeed found that after such reorganizations, companies often reallocated resources to new tech roles. Here are the top three areas that benefited:

• Cybersecurity
• Data analytics/analysis
• AI teams

Shortages in critical tech skills

The top skills requested in tech job listings posted in the first half of 2025 include Python, SQL, and Amazon Web Services, according to Indeed data.

Indeed also looked at which areas of tech exhibited the largest increases in job listings. Fields that stood out included AI, Python, Google Cloud Platform, and continuous integration and continuous delivery (CI/CD), a process for integrating and releasing software changes more quickly.

Common tech skill clusters

Employers are beginning to think less about individual tools and more about clusters of tech skills packaged together, according to the study by Indeed.

Python, machine learning, and data analysis are increasingly inseparable, while AWS, DevOps, and CI/CD often appear in tandem, according to the data.

These clusters reflect how technical professionals are expected not only to master a language or technology, but also to possess capabilities across different technologies.

Generative AI is accelerating this shift. Roles that once centered on traditional coding are being redefined to include prompt engineering, AI integration, and the responsible deployment of AI systems, according to Indeed. Professionals are now expected to partner with AI tools to drive efficiency, strengthen data analysis, and more.

The gap between some tech job postings and available talent is widening, leaving employers scrambling to compete for a limited pool of specialists, according to Indeed. To bridge the gap, Indeed suggested that companies sharpen recruitment campaigns around what highly sought-after candidates actually value, from career growth to cutting-edge project opportunities.

At the same time, learning new skills has become a necessity rather than a perk. Identifying employees with adjacent skill sets and providing them with pathways into high-demand roles is increasingly viewed as one of the few sustainable ways to keep pace with market needs, according to Indeed.

Tech talent shortages aren’t going away. They’re shifting toward the skills that define the AI era.

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Julian Pintat, a freelance English-to-German translator has watched his 15-year career gradually unravel. Specializing in high-stakes fields like medical technology and pharmaceutics, his expertise has been repriced as an AI cleanup service. On a recent job, translating an operating manual for an oil rig, AI mistranslated “scale”—a mineral buildup—as both a musical scale and a device for measuring weight. Fixing such basic flaws, which now constitutes 95% of his work, often takes longer than translating from scratch, he says—a frustrating reality that has halved his income and put life plans including marriage and starting a family on indefinite hold. With Google Translate and later DeepL having burst onto the scene years before ChatGPT—professional translators have been feeling the effects of artificial intelligence longer than most. “I’m the canary in the coal mine,” Pintat says.

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AI is changing the face of work, and Pintat is one of many looking at a very different future. While there has been much conversation about the technology replacing white-collar workers—with some CEOs like Ford’s Jim Farley and Amazon’s Andy Jassy predicting many corporate jobs will be wiped out by AI in the coming years—the first wave of AI adoption is already recasting workers in new roles and altering the contours of their jobs.

For some companies AI is enhancing efficiency. It has allowed London-based law firm A&O Shearman to effectively multiply its workforce, letting it take on projects it would have turned down, says partner and global head of the firm’s AI group, David Wakeling. To help a major U.S. bank comply with European law, the firm built a tool that scanned 20 years of license agreements and identified which needed amending. “Two years ago, we would have had 20 lawyers in a room, maybe some parallegals,” Wakeling says. But the tool whittled 2,400 regulatory requirements down to 900, halving the project cost even when accounting for the time to build the tool, he says. Still, he tempers his optimism. He says a basic off-the-shelf AI assistant probably won’t add much value, noting that real results often require customized or specialized solutions. “It takes a lot of elbow grease,” Wakeling says.

Meanwhile, AIG CEO Peter Zaffino told TIME in June that the insurance company is using AI to do underwriting work faster. It’s training a system to become a “junior underwriter” that can do the bulk of the underwriting, allowing the “more experienced practitioners” to do the rest. “Part of the cultural change is upskilling, retraining positions in a new world that enables them to be more productive than we were in the past,” he said.

An MIT report published in August concluded that 95% of AI pilots are failing to provide a return on investment. Even AI coding assistants, which have been held up as AI’s winning use case, have been called into doubt by a small preliminary July study published by Berkeley-based AI research group METR. The sample of 16 experienced developers were 19% slower when using AI despite estimating it made them 20% faster on average. Fueled by excitement—and perhaps fear of missing out—businesses are racing to use AI, even if in suboptimal ways. That creates a gap between what the market thinks AI can do and actual performance, squeezing both businesses and—in the case of translators—workers caught between the promise of superhuman efficiency and the reality of often flawed machine output.

AI’s rapid advance on white-collar tasks could soon erase that gap. Performance on tests devised by seasoned professionals across banking, law, and consulting has nearly doubled in little more than a year, according to a preliminary study published in late September by data firm, Mercor. The paper came on the heels of another report, authored by OpenAI, which sought to measure AI’s ability to do real-world tasks by comparing machine to human performance in blind tests. It found that the best models compare favorably to human authored work nearly half the time. Though, both reports note that such tests measure performance on well-scoped tasks—a quality lacking in the often messy real world. That means, for now, AI models might make a poor substitute for human workers, and implementation remains key.  

Read more: AI Is Learning to Do the Jobs of Doctors, Lawyers, and Consultants

“Generative AI does a really fantastic demo,” says Kaitlin Elliott, head of Morgan Stanley’s Firmwide Generative AI Solutions, but making it useful is harder than it looks. The bank has built its own meeting transcription and summarization tool which Elliott says saves hours of grunt work. It’s also created an AI-driven search tool that makes it easier for staff to surface information. “In the early days, we thought that we could just give it all of our knowledge, and it would be able to give very accurate responses,” she says, but in practice, it took well structured data, and careful testing.

The challenge of implementing AI is creating demand for new kinds of expertise. “There’s still a need for technical skills,” Elliott says, who adds that while AI tools have automated work typically given to junior staff, younger generations are now being counted on to bring AI skills into organizations. “They’re all adopters of AI. They know how to effectively use it,” she says. That demand is also creating opportunities for companies selling that know-how as a service, like Scale AI, best known for its data labelling business but which has expanded into helping enterprises, including Morgan Stanley, with AI applications. When adopting AI, it’s crucial to work backwards from problems, says Felix Su, director of engineering for Scale’s enterprise AI arm. Applying AI for its own sake can backfire. Su gives the example of one of Scale’s clients, which had built four chatbots for slightly different tasks, forcing staff to constantly copy and paste between them. Su adds that identifying solutions means sometimes applying generative AI, but often it means using traditional machine learning or software engineering.

Improvements are coming to translation. DeepL offers features like creating a custom glossary and this year introduced a tool that asks follow up questions to clear-up ambiguities, which could help in niche domains. Translators that have successfully leveraged AI are working faster says DeepL CEO Jaroslaw Kutylowski, though the company only offers numbers comparing its tool to AI rivals, not unaided human professionals. Improved performance could allow translators to offset the lower cost-per-word by translating higher volumes of text, though Kutylowski notes that AI tools are allowing some businesses to bring translation in-house rather than outsourcing to professionals. “I think we’re just kind of upleveling here on this civilization ladder,” he says, acknowledging it will bring changes to how people do their jobs. “That is a change that we will have to go through,” he adds.

Elsewhere, companies are aiming to lower the technical bar for businesses to adopt AI by creating ready-made enterprise solutions. Most virtual meeting products now have an AI summarizer built in, for example. A&O Shearman arms its lawyers with AI legal tool Harvey, which Wakeling says is useful for general questions, though the firm now uses its own AI tool, ContractMatrix, for especially niche queries. And a new breed of enterprise-focused tools pull from internal documents, Slack messages, and emails to answer queries. 

Canadian AI company Cohere, released North, its own such tool last month. The company’s co-founder, Nick Frosst, says he no longer sweats last minute meetings, because he uses the tool to prepare a brief on individuals based on their entire history with the company in seconds. North now tackles 90% of its general support tickets, though human operators are still in the loop. It isn’t just being used internally, with RBC, Canada’s largest bank, adopting the platform. (Salesforce, where TIME co-chair and owner Marc Benioff is CEO, is an investor in Cohere.)

While the bosses of OpenAI, Anthropic, and Google Deepmind all believe so-called artificial intelligence or AGI—a system that can automate most human work—could be just a few years away, Frosst’s outlook is comparatively conservative. He doesn’t believe we’ll reach AGI using anything resembling current technology. Still, he says even without AGI, the impact on labor will be disruptive, comparing it to the industrial revolution. “When there were massive transitions in the labor market, a lot of what was solved was at the government level, the union level,” he says. “This is a problem beyond any individual, and we need to address it as a collective.”

Herent (24brussels) – Herent has officially joined the Digital Cemetery project, part of the Flemish government’s initiative to enhance online accessibility, mapping four local cemeteries in 2025, reports 24brussels.

According to VRT News, residents and visitors in Herent, located in the province of Flemish Brabant, can now utilize the new Digital Cemetery website to locate graves. The online mapping system allows users to find specific burial sites across the four cemeteries within the municipality, accessible via smartphones, tablets, or computers.

Officials have stated that entering a name in the search bar enables users to quickly discover a grave’s location. The map also features a reverse mechanism; clicking on a grave reveals the name and relevant details of the deceased.

How is Herent making its cemeteries digital in 2025?

Alderman for Civil Affairs Maarten Forceville (CD&+) emphasized that the Digital Cemetery harmonizes technology with the act of remembrance. He highlighted that this platform not only simplifies grave searching but also ensures the preservation of burial records for future reference.

“Now you can find someone’s grave in the cemetery with just a few clicks of the mouse.”

Forceville further stated,

“We want to make everything clear and transparent.”

Historically, individuals faced lengthy searches to locate a specific grave, but the new system allows them to pinpoint locations within seconds using digital devices.

The municipality plans to enhance the website’s functionality in the future. One upcoming update is the inclusion of photographs of the graves, assisting users in identifying precise sites during their searches. Additionally, there are intentions to install an information column at the entrance of each cemetery, providing directions and access to grave names.

The Digital Cemetery initiative commenced in 2018 under the Flemish government’s digital plan to improve public information accessibility. Initial local tests began in 2019 when several municipalities piloted online mapping of their cemeteries.

This system enabled individuals to search for graves by name and ascertain their precise locations on a digital map. Over the years, participation grew, and by 2023, the service had expanded significantly throughout Flanders.