Tech
Will AI wipe out entry-level jobs? | Computer Weekly

Microsoft co-founder Bill Gates has become the latest to add his voice to a cacophony of warnings that artificial intelligence (AI) is eliminating entry-level jobs.
A recent report by job search engine Adzuna indicated that vacancies for graduate jobs, apprenticeships, internships and junior jobs with no degree requirement had dropped 32% since the launch of ChatGPT in November 2022. Employment website Indeed also stated that the number of recent graduate jobs advertised had fallen by 33% in mid-June compared with a year ago.
This situation appears to be reflected in the Big Four accountancy firms’ decision to cut early career hiring by up to 29% over the past two years. To make matters worse, Anthropic’s chief executive Dario Amodei recently made clear he expected AI to eliminate half of all entry-level jobs in five years.
The tech sector is far from immune either. Research by venture capital firm SignalFire revealed that since 2023, the number of new graduates being hired by Big Tech has dropped by 25%, and 11% in the case of tech startups. These numbers jumped to 50% and 30% respectively if comparisons were made with 2019 pre-pandemic levels, but, the study says, this situation cannot be attributed to AI alone.
Factors behind entry-level job decline
“The industry’s obsession with hiring bright-eyed grads right out of college is colliding with new realities: smaller funding rounds, shrinking teams, fewer new grad programmes, and the rise of AI,” it says. “Everyone took a hit in 2023, but while hiring bounced back in 2024 for mid- and senior-level roles, the cut keeps getting deeper for new grads.”
When combined with falling investment in training, this scenario is “creating fierce competition for the few entry-level jobs that remain”, the report points out. One unfortunate upshot here is that “companies are posting junior roles but filling them with senior individual contributors – a phenomenon known as the experience paradox”.
In other words, the research says, although AI is undoubtedly replacing some routine tasks, the “real story is more nuanced”.
“The bigger driver may be the end of the ‘free money madness’ driven by low interest rates that we saw in 2020-2022, along with the over-hiring and inflation it led to,” it adds. “Now, with tighter budgets and shorter runways, companies are hiring leaner and later.”
On the other hand, the study indicates, there is also a fundamental “hiring reset” taking place: “As AI tools take over more routine, entry-level tasks, companies are prioritising roles that deliver high-leverage technical output. Big Tech is doubling down on machine learning and data engineering, while non-technical functions like recruiting, product and sales keep shrinking, making it especially tough for Gen Z and early career talent to break in.”
The result of a market correction
Andy Heyes, managing director of IT recruitment consultancy Harvey Nash for the UK, Ireland and Central Europe, is seeing similar shifts, but he does not believe it is any single factor causing the squeeze either.
“Government policy on things like increasing National Insurance hasn’t helped the jobs environment and has hit business quite hard,” he says. “There’s also still the overhang from Covid-19 where businesses scaled up in 2022 and 2023 thinking there’d be much more remote working, which wasn’t the case, and we’re still seeing the long, slow downturn.”
Imran Akhtar is head of academy at mthree, a workforce solutions and graduate training programme provider. How he is seeing this scenario play out is in a reduction in the size of cohorts that recruitment managers are willing to hire.
“It’s not an eradication, but more of a correction,” Akhtar says. “People over-hired after Covid, but if you took out the Covid year, it would be a pretty steady stream.”
On top of such over-hiring, other factors having an impact here include an ongoing employer focus on staff retention, and general business uncertainty due to the wider geopolitical environment.
As to which entry-level positions are being cut the most, these are customer-facing roles, such as tech support and helpdesk, Heyes says – although he too is not seeing any roles being “taken out in their entirety”.
The changing nature of entry-level roles
Aliaksandr Kazhamiakin is chief executive and co-founder of IT hiring platform Yotewo. He has also noticed junior developer and designer jobs being affected.
“Posts are still available, but the benchmarks are changing a lot,” he says. “In the past, to get a developer’s role, you needed a degree and a good knowledge and understanding of coding and technology, but now it’s not enough.”
Instead, employers also want jobseekers to demonstrate soft skills, such as creativity and problem-solving. Candidates likewise need to show they have experience of using AI in their daily routine.
Moving forward, Kazhamiakin expects there to be a growing requirement for candidates to develop niche expertise in specific technologies or sectors, such as healthcare or financial services.
Such experience could potentially be gained through freelancing or “doing projects on the side”. However jobseekers do it though, the idea is that they will need to “bring more to the table”, he says.
Entry-level roles of the future
Professor David Barber is a distinguished scientist at workplace automation platform provider UiPath and Fellow of the data science and AI-focused Alan Turing Institute. He agrees that the nature of entry-level roles is changing.
In his view, as “technical capabilities are to some extent offloaded to AI”, the focus will increasingly move towards the provision of “high-quality experiences and services”. So, for example, a stage tester will no longer simply be expected to verify that software functions effectively and meets requirements.
“They’ll need to test the system in line with the company’s values and what they think the customer is looking for,” Barber says. “That will mean having an understanding of what the system can do so they can help improve the customer experience.”
He also expects to see the creation of an entire ecosystem around AI deployment, which will include entry-level positions.
“Organisations will be using technologies provided by a small number of tech providers, but the nuts and bolts of getting it all to work, which includes hooking systems up to databases and building usable interfaces for users, will require a lot of engineering,” Barber says. “So, as AI becomes more widely adopted, we’ll see an uptick in systems integration jobs to make systems reliable and responsive.”
The SignalFire report likewise points to a range of emerging roles. “Expect to see titles like AI governance lead, AI ethics and privacy specialists, agentic AI engineers, and non-human security ops specialists become commonplace,” it says. “It’ll take time to scale, but these are some of the roles new grads should be paying attention to.”
Blip or long-term dip?
Certainly, Heyes believes that the current reduction in entry-level roles is a blip rather than a long-term dip – although he would be concerned if the situation continued for any length of time.
“My view is that it’s too early to say whether AI will disrupt entry-level hiring in future,” he points out. “But I’ve not heard any companies saying so far they have any strategy to replace graduates with AI.”
Kazhamiakin takes a similar stance. “The short-term will be stressful for younger generations and there’ll be a gap between supply and demand for entry-level jobs, which will have a negative impact,” he says. “But longer-term, I don’t think it’ll be something to worry about – the market will bounce back, the main reason being that AI will create new jobs that become entry level at some point.”
But Rakesh Patel, managing director of workforce consultancy SThree, is concerned about the risk of creating a “pipeline gap”, which he believes will be most marked at the junior quality assurance testing, first-line support and coder level.
As a result, he says: “Rather than cut entry-level jobs, it makes more sense to reshape them to include more creative and collaborative AI-focused tasks. That would give people a chance to grow into more experienced roles.”
Otherwise, he believes: “There’s a real risk of creating a ‘lost generation’, not just in terms of unemployment but also underdevelopment as people may not get the chance to build the range of skills they need to be relevant to the market.”
What can employers do?
Christina Inge is an instructor for the AI in Marketing Graduate Certificate at Harvard University, and founder and chief executive of tech consultancy Thoughtlight. She agrees it is vital for employers to redesign rather than simply eradicate entry-level positions wholesale.
“We’re at risk of losing the ‘practice field’ where young professionals built both technical and emotional fluency,” she says. “Without entry-level work, people lack on-the-job learning, networks and informal mentorship.”
This situation not only damages individual career prospects. It also means that employers could end up “sleepwalking into a leadership vacuum”, with a dearth of middle managers within as little as five years, Inge warns.
As a result, she recommends “creating AI-augmented roles, where juniors interpret or validate AI outputs”. Expanding apprenticeship-style programmes that “combine structured learning with real responsibility” would also help.
But ultimately Inge says leaders must “resist the temptation to see junior workers as obsolete”, which will require setting an intentional strategy to the contrary.
“Success depends on pairing digital transformation with human development, and incentivising teams to mentor and upskill young staff. It also depends on tracking long-term return on investment, such as cost per hire, future promotability, loyalty and innovation,” she concludes.
Tech
OpenAI has slipped shopping into ChatGPT users’ chats—here’s why that matters

Your phone buzzes at 6 a.m. It’s ChatGPT: “I see you’re traveling to New York this week. Based on your preferences, I’ve found three restaurants near your hotel. Would you like me to make a reservation?”
You didn’t ask for this. The AI simply knew your plans from scanning your calendar and email and decided to help. Later, you mention to the chatbot needing flowers for your wife’s birthday. Within seconds, beautiful arrangements appear in the chat. You tap one: “Buy now.” Done. The flowers are ordered.
This isn’t science fiction. On Sept. 29, 2025, OpenAI and payment processor Stripe launched the Agentic Commerce Protocol. This technology lets you buy things instantly from Etsy within ChatGPT conversations. ChatGPT users are scheduled to gain access to over 1 million other Shopify merchants, from major household brand names to small shops as well.
As marketing researchers who study how AI affects consumer behavior, we believe we’re seeing the beginning of the biggest shift in how people shop since smartphones arrived. Most people have no idea it’s happening.
From searching to being served
For three decades, the internet has worked the same way: You want something, you Google it, you compare options, you decide, you buy. You’re in control.
That era is ending.
AI shopping assistants are evolving through three phases. First came “on-demand AI.” You ask ChatGPT a question, it answers. That’s where most people are today.
Now we’re entering “ambient AI,” where AI suggests things before you ask. ChatGPT monitors your calendar, reads your emails and offers recommendations without being asked.
Soon comes “autopilot AI,” where AI makes purchases for you with minimal input from you. “Order flowers for my anniversary next week.” ChatGPT checks your calendar, remembers preferences, processes payment and confirms delivery.
Each phase adds convenience but gives you less control.
The manipulation problem
AI’s responses create what researchers call an “advice illusion.” When ChatGPT suggests three hotels, you don’t see them as ads. They feel like recommendations from a knowledgeable friend. But you don’t know whether those hotels paid for placement or whether better options exist that ChatGPT didn’t show you.
Traditional advertising is something most people have learned to recognize and dismiss. But AI recommendations feel objective even when they’re not. With one-tap purchasing, the entire process happens so smoothly that you might not pause to compare options.
OpenAI isn’t alone in this race. In the same month, Google announced its competing protocol, AP2. Microsoft, Amazon and Meta are building similar systems. Whoever wins will be in position to control how billions of people buy things, potentially capturing a percentage of trillions of dollars in annual transactions.
What we’re giving up
This convenience comes with costs most people haven’t thought about.
Privacy: For AI to suggest restaurants, it needs to read your calendar and emails. For it to buy flowers, it needs your purchase history. People will be trading total surveillance for convenience.
Choice: Right now, you see multiple options when you search. With AI as the middleman, you might see only three options ChatGPT chooses. Entire businesses could become invisible if AI chooses to ignore them.
Power of comparing: When ChatGPT suggests products with one-tap checkout, the friction that made you pause and compare disappears.
It’s happening faster than you think
ChatGPT reached 800 million weekly users by September 2025, growing four times faster than social media platforms did. Major retailers began using OpenAI’s Agentic Commerce Protocol within days of its launch.
History shows people consistently underestimate how quickly they adapt to convenient technologies. Not long ago most people wouldn’t think of getting in a stranger’s car. Uber now has 150 million users.
Convenience always wins. The question isn’t whether AI shopping will become mainstream. It’s whether people will keep any real control over what they buy and why.
What you can do
The open internet gave people a world of information and choice at their fingertips. The AI revolution could take that away. Not by forcing people, but by making it so easy to let the algorithm decide that they forget what it’s like to truly choose for themselves. Buying things is becoming as thoughtless as sending a text.
In addition, a single company could become the gatekeeper for all digital shopping, with the potential for monopolization beyond even Amazon’s current dominance in e-commerce. We believe that it’s important to at least have a vigorous public conversation about whether this is the future people actually want.
Here are some steps you can take to resist the lure of convenience:
Question AI suggestions. When ChatGPT suggests products, recognize you’re seeing hand-picked choices, not all your options. Before one-tap purchases, pause and ask: Would I buy this if I had to visit five websites and compare prices?
Review your privacy settings carefully. Understand what you’re trading for convenience.
Talk about this with friends and family. The shift to AI shopping is happening without public awareness. The time to have conversations about acceptable limits is now, before one-tap purchasing becomes so normal that questioning it seems strange.
The invisible price tag
AI will learn what you want, maybe even before you want it. Every time you tap “Buy now,” you’re training it—teaching it your patterns, your weaknesses, what time of day you impulse buy.
Our warning isn’t about rejecting technology. It’s about recognizing the trade-offs. Every convenience has a cost. Every tap is data. The companies building these systems are betting you won’t notice, and in most cases they’re probably right.
This article is republished from The Conversation under a Creative Commons license. Read the original article.
Citation:
OpenAI has slipped shopping into ChatGPT users’ chats—here’s why that matters (2025, October 20)
retrieved 20 October 2025
from https://techxplore.com/news/2025-10-openai-chatgpt-users-chats.html
This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no
part may be reproduced without the written permission. The content is provided for information purposes only.
Tech
Spark plasma sintering and diffusion technology yield high-performance permanent magnets for green industries

A research team has developed an innovative manufacturing process for permanent magnets that overcomes the limitations of conventional techniques. The team’s breakthrough significantly advances the diffusion technology, which is essential for improving magnetic performance, and creates new possibilities for applying high-efficiency magnets in eco-friendly industries such as electric vehicles, wind turbines, and robotics.
The findings are published in the Journal of Alloys and Compounds.
The joint research team from the Nano Technology Research Division at DGIST was led by Dr. Donghwan Kim and Dr. Jungmin Kim.
With the rapid growth of the electric vehicle and wind power sectors, the demand for powerful permanent magnets capable of stable operation at high temperatures has soared. A major example is the neodymium (Nd-Fe-B) permanent magnet, widely used in electric vehicle motors. However, these magnets experience a decline in magnetic performance under extreme heat, requiring the addition of heavy rare-earth elements such as terbium (Tb) and dysprosium (Dy) to maintain their strength. The challenge is that these elements are both rare and expensive.
To address this issue, the grain boundary diffusion process has been widely adopted. This technique enhances magnetic performance by infiltrating a small amount of heavy rare-earth material into the magnet’s surface. However, diffusion in this process is limited to the surface layer and does not penetrate into the magnet’s interior, making it difficult to apply to thick magnets.
To overcome this limitation, the research team combined spark plasma sintering, an advanced manufacturing technique, with the grain boundary diffusion process. By pre-mixing the diffusion material during the powder-based magnet fabrication stage, uniform diffusion was achieved throughout the magnet. Consequently, the diffusion depth increased markedly compared with that achieved by existing methods, allowing for the creation of a core–shell structure in which the magnet exhibits uniform and enhanced magnetic performance.
Remarkably, even with the same amount of rare-earth material, the new process achieved higher diffusion efficiency and significantly improved overall performance. This advancement makes it possible to produce magnets that are smaller and lighter while maintaining strong magnetic strength. It is expected to contribute to the miniaturization, weight reduction, and improved energy efficiency of electric vehicle motors. Additionally, the process shows great potential for application to large-scale magnets.
Principal Researcher Dr. Donghwan Kim stated, “This study presents a method that overcomes the limitations of the conventional grain boundary diffusion technology, enabling uniform performance throughout the magnet. It will make a significant contribution to the development of high-performance permanent magnets required in eco-friendly energy industries such as electric vehicles and wind power generation.”
More information:
Seong Chan Kim et al, Homogeneous core-shell structure formation in Nd-Fe-B sintered magnets through advanced spark plasma sintering and internal grain boundary diffusion, Journal of Alloys and Compounds (2025). DOI: 10.1016/j.jallcom.2025.183635
Citation:
Spark plasma sintering and diffusion technology yield high-performance permanent magnets for green industries (2025, October 20)
retrieved 20 October 2025
from https://techxplore.com/news/2025-10-plasma-sintering-diffusion-technology-yield.html
This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no
part may be reproduced without the written permission. The content is provided for information purposes only.
Tech
Mystery Object From ‘Space’ Strikes United Airlines Flight Over Utah

The National Transportation Safety Board confirmed Sunday that it is investigating an airliner that was struck by an object in its windscreen, mid-flight, over Utah.
“NTSB gathering radar, weather, flight recorder data,” the federal agency said on the social media site X. “Windscreen being sent to NTSB laboratories for examination.”
The strike occurred Thursday, during a United Airlines flight from Denver to Los Angeles. Images shared on social media showed that one of the two large windows at the front of a 737 MAX aircraft was significantly cracked. Related images also reveal a pilot’s arm that has been cut multiple times by what appear to be small shards of glass.
Object’s Origin Not Confirmed
The captain of the flight reportedly described the object that hit the plane as “space debris.” This has not been confirmed, however.
After the impact, the aircraft safely landed at Salt Lake City International Airport after being diverted.
Images of the strike showed that an object made a forceful impact near the upper-right part of the window, showing damage to the metal frame. Because aircraft windows are multiple layers thick, with laminate in between, the window pane did not shatter completely. The aircraft was flying above 30,000 feet—likely around 36,000 feet—and the cockpit apparently maintained its cabin pressure.
So was it space debris? It is impossible to know without more data. A very few species of birds can fly above 30,000 feet. However, the world’s highest flying bird, Rüppell’s vulture, is found mainly in Africa. An unregulated weather balloon is also a possibility, although it’s not clear whether the velocity would have been high enough to cause the kind of damage observed. Hail is also a potential culprit.
Assuming this was not a Shohei Ohtani home run ball, the only other potential cause of the damage is an object from space.
That was the initial conclusion of the pilot, but a meteor is more likely than space debris. Estimates vary, but a recent study in the journal Geology found that about 17,000 meteorites strike Earth in a given year. That is at least an order of magnitude greater than the amount of human-made space debris that survives reentry through Earth’s atmosphere.
A careful analysis of the glass and metal impacted by the object should be able to reveal its origin.
This story originally appeared on Ars Technica.
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