Technology

Behind your ChatGPT and Gemini queries, there's a land grab happening to keep up the fevered pace of gen AI's growth. The consequences are significant.

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• Anthropic is offering Claude to all branches of US Government for next to nothing
• Move comes after OpenAI offered a very similar deal for ChatGPT
• AI companies are rushing to get their models adopted across the board

Anthropic has offered its Claude AI model to US government agencies for just $1 for the next year.

The offer extends to all three branches of the government, targeting the legislative and judicial branches alongside the executive.

The move comes almost immediately after OpenAI offered its ChatGPT enterprise for all US federal government workers for $1 per year per agency, as the firms look to undercut each other - and presumably create a reliance within the public sector, which is likely to use AI tools to help streamline their work and save money on admin costs.

Government contracts

“As AI adoption leads to transformation across industries, we want to ensure that federal workers can fully harness these capabilities to better serve the American people. By removing cost barriers, we're enabling the government to access the same advanced AI that's already proving its value in the private sector,” Anthropic said in a statement.

LLM companies are racing to obtain government contracts, with Anthropic, OpenAI, and xAI awarded a $200 million AI development deal with the US Department of Defence - all to develop models for US government customers for national security.

Claude has already been added to the General Services Administration’s (GSA) schedule to help streamline procurement, with Claude for Enterprise and Claude for Government offering support with handling sensitive unclassified work.

The firm will also give assistance to rapidly implement AI across agencies - with technical support for successful adoption into their ‘productivity and mission workflows’.

“This OneGov deal with Anthropic is proof that the United States is setting the standard for how governments adopt AI — boldly, responsibly, and at scale,” said GSA Acting Administrator Michael Rigas.

“This agreement puts the most advanced American AI models directly into the hands of those serving the American people.”

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• Paid ChatGPT users are getting access to a bunch of older models
• Altman teases an upgrade to ChatGPT-5’s personality is coming
• The new “warmer” upgrade is to counter the backlash to GPT-5

In his latest tweet on the social media platform X, Sam Altman, CEO of OpenAI, has confirmed that all paid ChatGPT subscribers will be getting access to not only the old GPT-4o model, but also older LLMs like o3, 4.1.

The popular ChatGPT-4.5 will also be coming back, but it will only be available to Pro subscribers. Altman says this is because “it costs a lot of GPUs”, a reference to the amount of compute power that it requires.

In the wake of the backlash against the removal of the popular 4o model with absolutely no warning when GPT-5 was released, Altman seems to have learned a lesson and has promised, “If we ever do deprecate it, we will give plenty of notice.”

All paid users of ChatGPT should now find a 'Show additional models' toggle in the ChatGPT web settings, which will give you access to all the older LLM models. You’ll also be able to add a new GPT-5 Thinking mini model.

Updates to ChatGPT:You can now choose between “Auto”, “Fast”, and “Thinking” for GPT-5. Most users will want Auto, but the additional control will be useful for some people.Rate limits are now 3,000 messages/week with GPT-5 Thinking, and then extra capacity on GPT-5 Thinking…August 13, 2025

Altman also makes reference to the highly criticized ‘colder’ tone of the new ChatGPT-5, which has alienated many users in the tweet: “We are working on an update to GPT-5’s personality which should feel warmer than the current personality, but not as annoying (to most users) as GPT-4o”.

His reference to ChatGPT-4o being annoying refers to the sycophantic phase that GPT-4o seemed to enter after an upgrade back in April.

Altman continues, ”However, one learning for us from the past few days is we really just need to get to a world with more per-user customization of model personality.”

Multiple personalities

Altman’s reference to “per-user customization” reflects OpenAI's recognition that what its users want is an easier way to select how formal, humorous, empathetic, or direct the assistant is.

Altman endured a recent AMA chat on Reddit where he got to listen to users' complaints firsthand. It seems to be GPT-5's lack of a personality that has most angered ChatGPT users, who had gotten used to building quite a rapport with GPT-4o.

If I were given free rein to imagine how I'd like ChatGPT to work, I’d like to get to the stage where ChatGPT's personality traits could be represented via sliders, like ‘professional vs. casual’ or ‘concise vs. detailed’. That would make it far easier to get the results you are looking for.

While CustomGPTs already exist, I’d love it if it were possible to easily switch between personality types, like ‘Work Assistant’ or ‘Creative Writing Coach’. However, I get the feeling it will be a long time yet before we get such an easily customizable AI chatbot to talk to.

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• GPT-5 now has multiple thinking modes to choose from
• Sam Altman has also confirmed an increase in rate limits for ChatGPT Plus subscribers
• GPT-5 launched less than a week ago to widespread criticism

GPT-5 just got its first major change, and now users can select between different modes when using the new model in ChatGPT.

Confirmed by OpenAI CEO, Sam Altman, on X earlier today, ChatGPT users can now choose between Auto, Fast, Thinking, and Thinking-mini when using GPT-5.

Each new mode offers a different way for GPT-5 to, you guessed it, think. "Auto" lets GPT-5 decide for itself how long to think, Fast" gives you instant answers, "Thinking-mini" thinks quickly, and "Thinking" will take longer to think for better answers.

The change comes following mass backlash related to GPT-5's performance, and will now give users multiple tiers of performance to choose from. We've yet to test all of the new thinking modes; however, when OpenAI decided to limit choice and remove legacy models, the lack of variety was met with widespread criticism.

OpenAI has since reverted back on those decisions, making 4o available again for paid subscribers, and adding the choice of multiple thinking abilities in GPT-5 only further cements the U-turn.

Updates to ChatGPT:You can now choose between “Auto”, “Fast”, and “Thinking” for GPT-5. Most users will want Auto, but the additional control will be useful for some people.Rate limits are now 3,000 messages/week with GPT-5 Thinking, and then extra capacity on GPT-5 Thinking…August 13, 2025

3000 messages a week? Yes please

New thinking modes aren't the only changes coming to GPT-5. Altman also announced the increase in rate limits for the brand new AI model following discontent from ChatGPT Plus users who pay $20/£20 a month to access the premium tier.

At launch, GPT-5's Thinking model was limited to 200 messages per week for Plus subscribers, now Altman says the rate limits have been increased to 3,000 a week. He also notes, "Context limit for GPT-5 Thinking is 196k tokens. We may have to update rate limits over time depending on usage."

Earlier this week, Altman said ChatGPT-5 Pro might be coming to Plus subscribers too, although he now appears to have backtracked, claiming, "we do not have the compute to do it right now."

GPT-5 hasn't even been out a week yet, but OpenAI has started to right the wrongs of the initial launch. With new rate limits and more choices in how long the AI model takes to respond with less or more thinking process, the company is trying to recapture its user base's trust.

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• However it means millions won't be able to use connectors
• GPT-5 sees some tweaks, and legacy models make a return

OpenAI has rolled out some handy new updates to Pro subscribers that will see ChatGPT link in more closely with top productivity tools such as Gmail, Google Calendar, Google Contacts and GitHub to reference content without the services inside conversations.

Plus members also get a few connectors, too, including collaboration tools such as Microsoft Teams and SharePoint, along with the likes of Box, Canva, Dropbox, HubSpot and Notion.

As has often proven to be the case with ChatGPT, other paying tiers including Plus, Team, Enterprise and Edu will also get the Pro features in the coming weeks via a staged rollout.

ChatGPT connects to even more workplace apps

We've already seen connectors link to some third-party services for easier, faster access to information, including Google Drive, but the latest update marks a considerable improvement with links to even more platforms.

However, there's one key twist that means millions of users will not be able to use them – OpenAI explained, "connectors for Plus/Pro plans are not available in EEA, Switzerland, and the UK." TechRadar Pro has sought confirmation as to why this is the case.

The news comes as OpenAI releases its GPT-5 and GPT-5 Thinking models to the world, with the company announcing the availability for business plans now.

Users can now select between 'Auto', 'Fast' and 'Thinking' variants of GPT-5 based on how much control they may require, with Plus users being granted 3,000 messages per week with GPT-5 Thinking before OpenAI directs them to the lighter GPT-5 Thinking mini model.

4o has also returned into the model picker following uproar that all previous models got removed upon the launch of GPT-5.

"Paid users also now have a 'Show additional models' toggle in ChatGPT web settings which will add models like o3, o4-mini, 4.1, and GPT-5 Thinking mini," OpenAI explained in a support page. "4.5 is only available to Pro users due to GPUs."

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• Millions play games on LinkedIn regularly, apparently
• Sudoku is the sixth game to be added to LinkedIn's gaming platform
• LinkedIn believes Sudoku games can be an ice-breaker

LinkedIn has added another game to its portfolio in the hope that it can keep more of its 1.2 billion users engaged with the job site platform for longer.

The launch of Sudoku marks LinkedIn's sixth game, which is designed to be played more quickly (within two to three minutes) with a 6x6 layout compared with traditional 9x9 versions of the game.

As with previous games added to the platform, LinkedIn believes Sudoku could serve as an ice-breaker to spark friendly competition among colleagues.

LinkedIn continues to add games to the platform

Although the platform is primarily designed for professional social networking, millions are said to play games on the platform daily, with peak time at 7am ET.

"More than a year after launching LinkedIn Games, engagement remains strong," the company wrote in a post.

It's estimated 86% of today's players will return tomorrow, and 82% will return next week, with Gen Z most likely to participate in online gaming.

Although Meta's platforms count more users than LinkedIn (3.5 billion daily users) and better fiscal growth, LinkedIn is less challenged in the space, focusing on professional networks rather than personal engagement - last quarter, the Microsoft-owned platform saw a 9% growth in revenue to $4.6 billion.

Recent months have seen countless incremental upgrades to the platform, including the addition of new games and useful injections of AI tools to help both job seekers and recruiters be more efficient.

This particular game comes with plenty of credentials, being built in collaboration with Nikoli (the Japanese publisher than popularized Sudoku) and Thomas Snyder, three-time World Sudoku Champion and puzzle designer.

"We don’t want to have a puzzle on LinkedIn that takes 20 minutes to solve, right?” LinkedIn Senior Director of Product Lakshman Somasundaram said in an interview with CNBC, speaking about the game's more condensed design.

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The UK and EU face a defining challenge—and opportunity—as they chart their digital economic futures. How can we unlock the full value of transformative technologies like AI, quantum computing, and cloud infrastructure while managing the growing tide of cyber threats?

The answer lies not in choosing between innovation and regulation, but in reimagining cybersecurity policy as a strategic lever for economic growth.

Today, trust in digital systems is a prerequisite for digital transformation. From small businesses to multinational firms, no organization can scale without confidence in the security of its infrastructure.

However, trust doesn’t emerge on its own—it’s built through smart, risk-informed policy. That’s why cybersecurity must be at the center of economic strategy, not an afterthought to it.

Growing recognition

Across the UK and Europe, there’s growing recognition of this link. For example, the UK’s Cyber Security and Resilience Bill positions cyber readiness as a core part of economic resilience. The EU’s cybersecurity policies also explicitly supports digital skills, market development, and cross-border data flows.

But to truly crystalize this moment, a clearer statement of how these policies are being designed to meet the moment is needed from government officials.

I recently attended the RSA Conference in the US and then travelled across both the UK and EU. Speaking with a variety of policymakers in different regions reminded me of the need we have to focus on partnerships, procurement and pivot in our cyber policy frameworks. I call these the “three Ps.”

Partnerships – Getting governments and the private sector on the same side of the table

High profile attacks such as those on the NHS, retailers and TfL over the past year have really brought into focus the impact cyberattacks can have on the wider population, and how fragile our digital systems are.

Cyber threats and how cyber policy can protect AI, cloud systems, and critical infrastructure were among the top concerns in every conversation I had with government stakeholders across the UK and EU.

To deliver cyber policy, however, governments and industry must sit on the same side of the table, working together to reduce systemic risk; cybersecurity cannot be delivered top-down. This means moving beyond passive compliance checklists toward dynamic, data-driven collaboration.

Private sector businesses often possess advanced technological capabilities and gather vast amounts of data through their daily operations, offering invaluable insights into emerging cyber threats.

Government agencies, on the other hand, bring a broader geopolitical and strategic understanding that helps interpret private sector data within the context of national and international security threats.

Bringing the government’s geopolitical context and regulatory levers together with the private sector’s technical capabilities and real-time intelligence, creates far more effective policies and faster threat responses.

Governments need to go beyond self-attested best practices and design partnerships that actively analyze the data gathered to identify which behaviors and deterrents actually work within a nation’s unique risk environment.

For small and medium-sized businesses in particular, clear, practical guidance shaped in collaboration is often the difference between resilience and risk exposure.

Some governments are doing better than others in recognizing the ability to translate complex policy goals into actionable, plain-speak directives, but this needs more intentional thought and design.

Procurement – Building success for the future

Economic growth will continue to increasingly depend upon digital infrastructure. For example, the UK government announced this year the AI Opportunities Action Plan and a £121 million investment boost for quantum technology. At the core of both announcements was how AI and quantum support the government’s economic mission.

Cybersecurity also plays a foundational role in the creation of resilient economic strategies. However, similar to intelligence sharing between the public and private sectors, the two parties often develop capabilities in silos that don’t work together. This leads to gaps in terms of the capabilities governments need and the solutions available to them on the market.

Cyber policy should guide how governments buy, fund, and signal the technologies they want to see in the market. This essentially means thinking about how the systems you build today will support success tomorrow.

We’re seeing governments improve in this area. For example, the NCSC’s guidance on post-quantum cryptography is a great example of future-focused leadership. While we don’t yet know when the "quantum year" will arrive, it’s encouraging to see progress and growing awareness that organizations need to be ready.

However, this alone is not enough. More incentives are needed to signal this as a priority for the private sector. Remember, procurement isn’t just a back-office function—it’s an economic strategy.

Research and Development (R&D) projects are an effective way to encourage collaboration and build momentum, and this is particularly needed in AI.

Britain, for instance, has some of the best universities and R&D centers in the world but loses talent to better-funded AI hubs. Governments have to create a long-term AI skills and R&D strategy that not only develops expertise but retains it.

Pivot! Pivot! Pivot!

In many of my conversations, stakeholders repeatedly used the word “pivot.” I was intrigued as to why this word came up so often. When pressed, I learned that what they really meant was “review.”

This is because not all regulations age well. You just have to look at the growing calls to review the Computer Misuse Act, for example. There’s a growing recognition among the UK and EU that some aspects of tech policy and investment need reviewing.

Some cybersecurity rules, though well-intentioned, may add a compliance burden—which in itself is a risk—without reducing actual cyber or business risk. Software misconfigurations, third-party supply chain risks, and emerging threats are not always addressed by the ever-growing complexity of overlapping regulations and rules designed to manage cyber risk.

This isn’t particularly new—we’ve long debated the balance between regulation and building trusted partnerships. While we want to open new frontiers for investment and innovation, it shouldn’t come at the expense of public trust.

However, this age-old argument is starting to shift. There’s greater recognition that the best way to maintain public trust isn’t necessarily through universal regulations, but through considered trade-offs.

Policymakers must be willing to pivot—reviewing what’s working, sunsetting what isn’t, and designing regulation that is adaptive, risk-based, and innovation-friendly.

The key is balance. Governments have to keep in mind the overall goal of policy: understanding the security of systems, minimizing the impact on resilience, and ensuring long-term economic growth.

Cyber is at the forefront of policy

Although I’ve had many different conversations with decision-makers, what struck me most was that security is no longer an afterthought, it’s now a central focus for governments.

From a private sector standpoint, cybersecurity is no longer a cost of doing business—it’s a condition for doing business. And it’s a competitive advantage waiting to be seized.

If the UK and EU want to continue enabling the next era of digital growth, they must address cybersecurity policies as a suite of policies that enable economic growth, focusing on partnerships and procurement, and having the courage to pivot when necessary.

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This article was produced as part of TechRadarPro's Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro

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• The Huawei Mate XT 2 could land on September 10
• That's the same week we're expecting the iPhone
• The first Huawei tri-fold was launched last year

The pioneering, triple-folding Huawei Mate XT that launched in 2024 is due to get a successor later this year – and the latest rumor suggests the premium device is going to be unveiled around the same time as the Apple iPhone 17 series.

This information comes from well-known tipster Fixed Focus Digital on Chinese social media platform Weibo (via Android Headlines), who says we can expect to see the Huawei Mate XT 2 announced on Wednesday, September 10.

If you've been keeping pace with the flurry of iPhone 17 rumors in recent weeks, then you'll know those are pointing to Tuesday, September 9 as the big day for the grand unveiling of Apple's next flagship phones.

The usual iPhone upgrades are in the pipeline – a faster processor, better cameras, and so on – but there's no doubt that it's Huawei that will be unveiling the most innovative and exciting handset that week, if these rumors prove to be accurate.

When are we getting a foldable iPhone?

Apple has always taken a rather slow and steady approach to smartphone innovation, which helps explain why Huawei is now on its second tri-fold phone and Samsung is on its seventh round of foldables, while Apple has yet to even hint that a foldable iPhone is coming.

The most recent information we have suggests that Apple will finally launch a folding iPhone in September 2026, alongside the iPhone 18 line. After that, we might get treated to a new model every 12 months, as Apple gets more familiar with the manufacturing process.

Rumors indicate that Apple has been working hard to minimize the crease on its foldable iPhone, and we're expecting it to cost a fair bit too. Other leaks suggest it won't claim the title of the thinnest foldable phone when it appears.

A folding iPhone has been a long time coming, and we're looking forward to seeing it, but Apple has a lot of catching up to do at this point, with Samsung expected to launch its own tri-fold phone at some point in October.

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• The iPhone 17 Air might have an A19 Pro chipset
• But it could have one less GPU core than the iPhone 17 Pro
• It might also have a worse screen and battery

The rumored iPhone 17 Air is an intriguing handset, as it could be a big hit for Apple – or a colossal failure, depending on how well Apple balances its build with its specs, and on how much people take to a super-slim iPhone. The latest leak though suggests Apple might not have got the balance right for me.

According to Fixed Focus Digital – a leaker with a reasonable track record – posting on Weibo (via GSMArena), the iPhone 17 Air will have an A19 Pro chipset, just like the iPhone 17 Pro and the iPhone 17 Pro Max. Except, it won’t quite be the same here, as this source claims that the Air’s version will have five GPU cores, while the version used by the Pro phones will have six.

It remains to be seen how much difference that will make, but it would mean the iPhone 17 Air is less powerful than the iPhone 17 Pro and Pro Max – though still probably more powerful than the base iPhone 17, which will reportedly have a non-Pro version of the A19.

Battery, screen, and camera compromises

The iPhone 16 Pro (Image credit: Future / Lance Ulanoff)

But this isn’t the Air’s only rumored compromise, as the same source also says that it will have a worse screen and battery than the iPhone 17 Pro.

They don’t get specific here as to the ways in which they’re worse, but presumably this means a lower battery capacity. As for the screen, that’s probably a reference to a previous claim they made that the base iPhone 17 and iPhone 17 Air wouldn’t have a variable refresh rate, and in turn therefore probably wouldn’t have an always-on display – though they will at least apparently have 120Hz screens.

So that’s quite a lot of compromises, and – coupled with the iPhone 17 Air probably just having one rear camera – this would almost certainly be too much of a compromise for me. Really, it seems only those who value aesthetics over everything else would choose to purchase the Air.

Yet there might be a lot of buyers like that, with Fixed Focus Digital predicting that the iPhone 17 Air will be a hit. So it will be interesting to see how well it actually does. We should find out in September, as that’s when the entire iPhone 17 series is expected to launch.

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• Alien: Earth's cast have teased what's next for their characters' complicated relationship
• The individuals they portray are reunited in the sci-fi horror show's second episode
• It's an encounter that comes as a major shock to one of them

Alien: Earth's cast have teased what fans can expect from their characters' complex relationship following their reunion in episode 2.

Speaking to TechRadar before Alien: Earth's two-episode premiere, Sydney Chandley and Alex Lawther suggested there'll be many moments of "tension" and "vulnerability" between their characters throughout the sci-fi horror show's next six entries.

Major spoilers immediately follow for Alien: Earth episodes 1 and 2. Turn back now if you haven't watched them yet.

Sydney Chandley plays Wendy, a synthetic with the consciousness of a child (Image credit: FX Networks/Hulu/Disney+)

As I briefly touched on in my Alien: Earth review, Chandler plays a Hybrid called Wendy. Created by Prodigy Corp., one of Earth's five multinationals, Hybrids are technological prototypes that see the consciousness of a child transferred into the body of an adult-sized synthetic. The reason children are used for such experiments is that their minds are more malleable than adults, so they won't reject the transformation process.

Episodes 1 and 2 of the Alien franchise's first-ever TV show reveal there's more to Wendy's creation than meets the eye, though. For one, her real name isn't Wendy, but rather the name this Hybrid picks for her transcendence. As we learn, her actual name is Marcy and she was chosen to be the first Hybrid because she had a terminal illness.

That's not all. Marcy was the biological sister of Joe 'CJ' Hermit, a medic employed by Prodigy who's portrayed by Lawther. Instead of telling Joe the truth about what happened to his younger sibling, Prodigy claimed Marcy had died. Oh, and the nefarious megacorporation also lied to Marcy about why Joe couldn't visit her at their secret Neverland headquarters – Prodigy telling Marcy he was always too busy to pay her a visit.

Joe is involved in the search and rescue operation in Prodigy City (Image credit: FX Networks)

However, when Wendy learns that Joe is part of the search and rescue operation after a Weyland-Yutani deep space research vessel crash lands on Prodigy City – a spaceship filled with terrifying creatures, no less – she convinces Prodigy CEO Boy Kavalier to send her, Kirsh, and her fellow Hybrids to aid the rescue effort. Long story short: Wendy/Marcy tracks down her brother, but it's not exactly the perfect reunion she was hoping for.

Considering he'd made peace with his sister's passing, it's easy to see why Joe can't grasp the fact that Marcy is somehow back from the dead. And, while Wendy/Marcy manages to convince Joe it's really her via a trip down memory lane in the Alien series' second chapter, it's clear that things can't go back to the way they were when the pair were kids.

"It's really fun to play with the vulnerability and innocence she carries, and marry that with the fact she's basically a weapon," Chandler said. "What does that do to the mind of a child? And what does that do to your sense of fear and your sense of identity?

"For Wendy, I think if she doesn't have her brother and that tie to her real life, her understanding of her identity could start to wobble," Chandler added. "It's very important for other reasons as well, but he's the only other person on earth who knows her as her full self. Everyone else is telling her she's something different, so she needs Joe to keep reminding herself of who she is."

A post shared by Alien: Earth (@alienearthfx)

A photo posted by on

"Nobody sees Marcy the way that Joe does," Lawther added. "It becomes that thing of longing for this person [Marcy] to be the person that they say they are, rather than what they seem to be [Wendy].

"And that causes tension between them," Lawther continued. "Joe's hanging onto this idea of his sibling who she can no longer be. He can't quite grasp this concept of this Hybrid being his sister, but being something else, too. He has a hard time recognizing the person that he lost and we'll see how that all unfolds as time goes on."

Alien: Earth episodes 1 and 2 are out now on Hulu (US) and Disney+(internationally). New episodes air weekly.

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• Workday study finds not many workers are happy being managed by AI, or seeing AI operate independently
• Nine in 10 believe AI agents could help boost their productivity at work
• Nearly half are worried about AI's effect on their critical thinking

The majority of workers say they are comfortable working with AI agents, however far fewer (30%) are comfortable being managed by them, new research has found.

The findings from Workday comes as four in five (82%) organizations expand their use of AI agents, with workers now demanding clearer boundaries and reassurance about their roles.

On the whole, the study found workers are generally happier when they're in control of artificial intelligence, with 75% fine with AI tools recommending skills or working alongside them compared with 24% who are comfortable with it operating in the background, without human knowledge.

Workers prefer to know when AI is being used

How much a worker trusts AI comes down to how much they use it – 95% of experienced users trust the tech, with only 36% of AI 'explorers' trusting responsible use.

"Building trust means being intentional in how AI is used and keeping people at the center of every decision," Workday AI VP Kathy Pham explained.

However, despite apprehension around advanced agentic AI taking control in the background, workers still acknowledge how it could help them.

Nine in 10 employees believe AI agents will help them get more done. To that degree, nearly half (48%) worry that the added productivity could come with increased pressure at work, potentially by increased workloads, as well as a decline in critical thinking (48%).

Rather than seeing AI as a human replacement and full colleague, most of the study's participants prefer to see AI as a teammate that can boost their own productivity. Sensitive areas like hiring, finance and legal matters are where it's perceived less favorably, underscoring the need for human oversight.

"We’re entering a new era of work where AI can be an incredible partner, and a complement to human judgement, leadership, and empathy," Pham added,

Still, despite early concerns, workers are less likely to worry about AI taking their jobs (12%), with most believing AI could actually help address ongoing talent shortages (76%).

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• Four new 3LCD projectors for up to 300-inch images
• Two Home Cinema models and two Pro
• One of each comes with AirPlay on board

Epson has launched four new projectors, and two of them will be of particular interest to Apple users. That's because for the first time, Epson is delivering AirPlay compatibility for retail home cinema projector purchasers – something that's been available in the likes of LG's Cinebeam range for some time.

The four projectors are all 3-chip 3LCD models and they're divided into two products: Home Cinema projectors, and Pro projectors. The AirPlay models also support Miracast.

The Home Cinema projectors are the Home Cinema 1100, which has AirPlay, and the Home Cinema 980, which hasn't.

The Pro models are the Pro EX9270 wireless projector, which is the AirPlay model, and the EX3290, which isn't.

The Pro EX9270 delivers 1080p at up to 300 inches and has AirPlay on board. (Image credit: Epson)Epson's new projectors: key features and pricing

The $899 (so around £660 or AU$1,370) Home Cinema 1100 with AirPlay is rated for 3,400 lumens of color and white brightness, and the $799 Home Cinema 980 is rated for 4,000 lumens.

Both deliver 1080p Full HD resolution at sizes up to 300 inches, both have picture skew sensors, and both have two HDMI ports. They feature Epson's 3-chip 3LCD technology that delivers "outstanding" images in a wide range of lighting conditions.

The $999 Pro EX9270 with AirPlay is rated for 4,100 lumens and the $649 Pro EX3290 is rated for 4,000. Like the Home Cinema projectors they too feature the 3LCD system and can throw images up to 300 inches; the EX9270 is full HD and the EX3290 is WXGA. There are twin HDMI ports, an image skew sensor and built-in speakers, and the Pro EX9270 also has 1.6x optical zoom.

All four projectors are available now directly from Epson and from authorized retailers.

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Brooklyn residents can choose from top internet providers, from local options to nationwide networks. CNET experts found the fastest, most reliable ISPs.

Could AI be the answer to the UK’s productivity problem? More than half (58%) of organizations think so, with many experiencing a diverse range of AI-related benefits including increased innovation, improved products or services and enhanced customer relationships.

You don’t need me to tell you this – chances are you’re one of the 7 million UK workers already using AI in the workplace. Whether you’re saving a few minutes on emails, summarizing a document, pulling insights from research, or creating workflow automations.

Yet while AI is a real source of opportunities for companies and their employees, pressure for organizations to adopt it quickly can inadvertently give rise to increased cybersecurity risks. Meet shadow AI.

What is shadow AI?

Feeling the heat to do more with less, employees are looking to GenAI to save time and make their lives easier – with 57% of office workers globally resorting to third-party AI apps in the public domain. But when employees start bringing their own tech to work without IT approval, shadow AI rears its head.

Today this is a very real problem, with as many as 55% of global workers using unapproved AI tools while working, and 40% using those that are outright banned by their organization.

Further, internet searches for the term “shadow AI” are on the rise – leaping by 90% year-on-year. This shows the extent to which employees are “experimenting” with GenAI – and just how precariously an organization's security and reputation hangs in the balance.

Primary risks associated with shadow AI

If UK organizations are going to stop this rapidly evolving threat in its tracks, they need to wake up to the threat of shadow AI – and fast. This is because the use of LLMs within organizations is gaining speed, with over 562 companies around the world engaging with them last year.

Despite this rapid rise in use cases, 65% of organizations still aren’t comprehending the implications of GenAI. But each unsanctioned tool leads to significant vulnerabilities that include (but are not limited to):

1. Data leakage

When used without proper security protocols, shadow AI tools raise serious concerns about the vulnerability of sensitive content, e.g. data leakage through the learning of information in LLMs.

2. Regulatory and compliance risk

Transparency around AI usage is central to ensuring not just the integrity of business content, but users’ personal data and safety. However, many organizations lack expertise or knowledge around the risks associated with AI and/or are deterred by cost constraints.

3. Poor tool management

A serious challenge for cybersecurity teams is maintaining a tech stack when they don’t know who is using what – especially in a complex IT ecosystem. Instead, comprehensive oversight is needed and security teams must have visibility and control over all AI tools.

4. Bias perpetuation

AI is only as effective as the data it learns from and flawed data can lead to AI perpetuating harmful biases in its responses. When employees use shadow AI companies are at risk of this – as they have no oversight of the data such tools draw upon.

The fight against shadow AI begins with awareness. Organizations must acknowledge that these risks are very real before they can pave the way for better ways of working and higher performance – in a secure and sanctioned way.

Embracing the practices of tomorrow, not yesterday

To realize the potential of AI, decision makers must create a controlled, balanced environment that puts them in a secure position – one where they can begin to trial new processes with AI organically and safely. Crucially though, this approach should exist within a zero-trust architecture – one which prioritizes essential security factors.

AI shouldn’t be treated as a bolt-on. Securely leveraging it requires a collaborative environment that prioritizes safety. This ensures AI solutions enhance – not hinder – content production. Adaptive automation helps organizations adjust to changing conditions, inputs, and policies, simplifying deployment and integration.

Any security experience must also be a seamless one, and individuals across the business should be free to apply and maintain consistent policies without interruption to their day-to-day. A modern security operations center looks like automated threat detection and response that not only spot threats but handles them directly, making for a consistent, efficient process.

Robust access controls are also key to a zero-trust framework, preventing unauthorized queries and protecting sensitive information. While these governance policies have to be precise, they must also be flexible to keep pace with AI adoption, regulatory demands, and evolving best practices.

Finding the right balance with AI

AI could very well be the answer to the UK’s productivity problem. But for this to happen, organizations need to ensure there isn't a gap in their AI strategy where employees feel limited by the AI tools available to them. This inadvertently leads to shadow AI risks.

Powering productivity needs to be secure, and organizations need two things to ensure this happens – a strong and comprehensive AI strategy and a single content management platform.

With secure and compliant AI tools, employees are able to deploy the latest innovations in their content workflows without putting their organization at risk. This means that innovation doesn’t come at the expense of security – a balance that, in a new era of heightened risk and expectation, is key.

We list the best IT management tools.

This article was produced as part of TechRadarPro's Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro

• 10Web announced a new WordPress plugin
• It allows users to create fully white-labeled websites in minutes
• Users can expect increased ARPU and reduced churn, 10Web says

You can now create a WordPress website in minutes, with the help of Generative AI (GenAI), without needing a third-party website builder or AI tool. Everything can be done in WordPress directly, through a chat interface, and without the website builder’s branding showing anywhere on the site.

This is all courtesy of the website builder platform 10Web, which just announced the launch of its fully white-labeled AI website builder solution. It comes in the form of a WordPress plugin, and allows users to create a website inside their hosting stack without relying on a separate builder platform.

In a press release shared with TechRadar Pro earlier this week, 10Web says the new offering should further increase ARPU, reduce churn, and differentiate through same-day AI website delivery.

“Hosting companies have been stuck selling blank WordPress installs,” said Arto Minasyan, Founder and CEO of 10Web. “With this solution, they can launch fully functional websites under their own brand in seconds. It’s the simplest way to deliver real customer value, without changing how they host or deploy WordPress.”

WooCommerce included

Usually, when a customer buys a hosting service, they get either a blank WordPress dashboard, or one bundled with themes and plugins. However, with the emergence of GenAI, expectations changed, and customers have gotten used to the “describe and build” experience, the company claims.

That being said, it claims “early tests” showed users being 30% more likely to publish their site compared to traditional WordPress onboarding flows. It didn’t say when the tests took place, who was tested, and against what, though.

In any case, 10Web says the plugin is built on its proprietary AI technology which leverages advanced models from OpenAI, Gemini, and Anthropic. The sites are mobile-friendly, fully structured, and based on a “simple business description”.

When users create a site, they will see a branded AI flow that generates the entire website, including WooCommerce integration, if needed. Finally, everything is white-labeled with the hosting provider’s name and logo, and includes a visual editor with AI Co-Pilot.

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In boardrooms and investor meetings, artificial intelligence is now table stakes. AI tools are everywhere. Analysts are forecasting trillions in potential value. McKinsey estimates that generative AI alone could boost the global economy by up to $4.4 trillion a year.

And yet, in the enterprise? Something’s not clicking.

Despite the hype, most AI projects are still stuck in the sandbox; demo-ready, not decision-ready. The issue isn’t model performance. It’s operationalization. Call it the Enterprise AI Paradox: the more advanced the model, the harder it is to deploy, trust, and govern inside real-world business systems.

The heart of the paradox

At the heart of this paradox, McKinsey argues, lies a misalignment between how AI has been adopted and how it generates value.

Horizontal use cases, notably tools like Microsoft’s Copilot or Google's Workspace AI, proliferate rapidly because they're easy to plug in and intuitive to use. They provide general assistance, they summarize emails, draft notes, simplify meetings, and so on.

Yet these horizontal applications scatter their value thinly, spreading incremental productivity improvements so broadly that the total impact fades into insignificance.

As the McKinsey report puts it, these applications deliver "diffuse, hard-to-measure gains.”

In sharp contrast, vertical applications (those baked into core business functions) carry the promise of significant value but struggle profoundly to scale. Less than 10 percent of these targeted deployments ever graduate beyond pilot phases, trapped behind technological complexity, organizational inertia, and a lack of mature solutions. LLMs are extraordinary. But they’re not enough.

It’s like trying to run a Formula 1 car on a farm track

The real enterprise challenge isn’t building a big, clever model. It’s orchestrating intelligence, across systems, teams, and decisions.

The world’s most innovative companies don’t want a single mega-model spitting out answers from a black box. They want a system that’s intelligent across the board: data flowing from hundreds of sources, automated agents taking action, results being validated, and everything feeding back into an improved loop.

That’s not one model. That’s many. Talking to each other. Acting with autonomy. And constantly learning from a dynamic environment.

This is the future of enterprise AI, and it’s what’s known as agentic.

What is agentic AI, and why does it matter?

Agentic AI systems are different from monolithic LLMs in one key way: they think and act like a team. Each agent is a specialist, trained on a narrow domain, given a clear role, and capable of working with other agents to complete complex tasks.

One might handle user intent. Another interfaces with an internal database. A third enforces compliance. They can run asynchronously, reason over real-time data, and retrain independently.

Think of it like microservices, but for cognition. Unlike traditional generative AI, which remains largely reactive (waiting passively for human prompting) agents introduce something entirely different. "AI agents mark a major evolution in enterprise AI - extending gen AI from reactive content generation to autonomous, goal-driven execution,” McKinsey researchers explain.

This isn’t some speculative vision from a Stanford whitepaper. It’s already happening, in advanced enterprise labs, in the open-source community, and in early production systems that treat AI not as a product, but as a process.

It’s AI moving from intelligence-as-an-output to intelligence-as-infrastructure.

Why most enterprises aren’t ready (yet)

If agentic systems are the answer, why aren’t more enterprises deploying them?

Because most AI infrastructure still assumes a batch world. Systems were designed for analytics, not autonomy. They rely on periodic data snapshots, siloed memory, and brittle pipelines. They weren’t built for real-time decision-making, let alone a swarm of AI agents operating simultaneously across business functions.

To make agentic AI work, enterprises need three things:

Live data access – Agents must act on the most current information available

Shared memory – So knowledge compounds, and agents learn from one another

Auditability and trust – Especially in regulated environments where AI decisions must be traced, explained, and governed

This isn’t just a technology problem, it’s actually an architectural one. And solving it will define the next wave of AI leaders.

From sandbox to system

Enterprise AI isn’t about making better predictions. It’s about delivering better outcomes.

To do that, companies must move beyond models and start thinking in systems. Not static models behind APIs, but living, dynamic intelligence networks: contextual, composable, and accountable.

The Agentic Mesh, as McKinsey calls it, is coming. And it won’t just power next-gen applications. It will reshape how decisions are made, who makes them, and what enterprise infrastructure looks like beneath the surface.

It isn’t simply a set of new tools bolted onto existing systems. Instead, it represents a shift in how organizations conceive, deploy, and manage their AI capabilities.

To really make this work, McKinsey says it’s time to wrap up all those scattered AI experiments and get serious about what matters most. That means clear priorities, solid guardrails, and picking high-impact "lighthouse" projects that show how it's done.

The agentic mesh isn't just a fancy architecture - it’s a call for leaders to rethink how the whole enterprise runs. Because real enterprise transformation won’t come from scaling a smarter model. It will come from orchestrating a smarter system.

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This article was produced as part of TechRadarPro's Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro