• Anthropic reveals a host of updates for Claude to help users at work
• Claude can now join meetings, analyze data and more
• It can also effectively connect to third-party tools such as Adobe, Box and more

Anthropic has unveiled a host of updates for Claude which could see the AI platform play a much more integral role in some of your most common work tasks.

Among the next expansions are tools which allow Claude to join video calls as a participant, meaning it learns first-hand from your meetings and can start work immediately.

Joining its existing suite of office software tools are new Whiteboards, Sheets and Data services looking to help users work and create more effectively - and new interactive connectors will now allow Claude to work inside the full versions of common workplace apps such as Adobe, Atlassian and HubSpot.

What's new with Claude for enterprise?

"A year ago, Claude changed how developers work," Anthropic wrote in a blog post announcing the new tools. "Engineers stopped asking AI for snippets and started handing it whole tasks, which freed them to spend their time deciding what to build. For most other teams, work has stayed much the same: the email gets written a little faster, the meeting comes with a summary."

"Now the frontier is moving to knowledge work, and people are starting to hand Claude whole tasks too."

The most striking new addition is undoubtedly Claude Meetings, which will allow Claude to join video calls as a visible participant.

Claude follows the conversation and starts on the work as people talk, taking notes, drafting plans, outlining timelines on whiteboards, answering chat questions, and utilizing connected work apps while conversations happen - and when the call ends, the notes, action items and everything Claude made are waiting in claude.ai.

Also new is Claude Whiteboards, a shared, real-time board which helps teams turn brainstorms and retrospectives into structured plans, timelines, and action items, and integrates directly into Claude Meetings, and Claude Sheets, a spreadsheet tool which allows teams to build and edit trackers and budgets collaboratively with Claude, complete with tabs, formulas, and dropdown menus.

Finally, Claude Data (formerly known as Claude Dashboards) connects company data sources (such as CRMs and warehouses) to generate dashboards, data stories, and narrated videos, featuring beta capabilities like certified queries and live sharing.

Alongside this, new Interactive Connectors will allow full versions of partner tools (like Adobe, Atlassian, HubSpot, Salesforce, NetSuite, and Workday) to open directly inside Claude, which can take actions directly within these apps with user approval.

Connectors respect existing user permissions, and admins can utilize features like Claude auto-connect, usage controls, and Smart Reports to monitor team productivity and costs.

Claude Meetings, Claude Whiteboard and Claude Sheets are all still in beta, with Claude Data and Interactive Connectors generally available now.

• Disney's new AI guide could make navigating Disneyland easier
• Works with Ray-Ban Metas, AirPods, and your iPhone
• Coming soon in beta for Magic Key holders through Imagineering Labs

When you're at a Disney park, or really any theme park, the idea is to be immersed in the experience, right? But there's also no sugarcoating the fact that a phone, especially one equipped with the Disneyland app, My Disney Experience for Walt Disney World, or any other park app, is pretty essential for planning and making the most of your day.

The app is essentially the brain of your visit, letting you check wait times for attractions, meet-and-greets, and other experiences, but also helping you find your way to food — I mean, we're all after a corn dog or a churro, right? — other services, and entertainment. But as we've heard from Disney Parks leaders in the past, constantly looking down at your phone can break the immersion.

Now, we're getting a glimpse at a potential alternative, and it's coming soon for a select group of Disneyland guests through a new Disney Imagineering app that's set to offer a rare peek behind the curtain.

Dubbed Imagineering Labs, the opt-in experience won't replace the main Disneyland app, but it will give guests the chance to try select experiences before they're fully developed or even guaranteed to launch. It's a pretty exciting approach, especially since feedback from guests could help shape what Imagineers ultimately bring to life.

The first experiment is an augmented reality Star Wars adventure called Secrets of the Spire, which is decidedly entertainment-focused and uses your iPhone's camera to overlay digital elements onto the environment and trigger physical reactions throughout Galaxy's Edge.

But the Disneyland Enchanted Guide is a bit more utility-focused, and it's seriously piquing my interest. It's an AI-powered assistant that lets you ask questions in natural language, like, 'Where's the nearest Dole Whip?' 'How long is the wait for Rise of the Resistance right now?' or whether you should come back later if the line is too long. It's also multimodal, meaning you can point your phone's camera at something in the park and ask about it.

Asa Kalama, Vice President and Executive Creative Director at Walt Disney Imagineering, described the thinking behind it to TechRadar: “Some of us are lucky enough to have that, you know, big Disney Parks fan as a friend, and there's no better park-going adventure than alongside them. They know all the tips, they know all the tricks, they can help you navigate your day. Well, what if we were able to provide that to every single guest that came to the park?”

And that's really the idea here. Rather than digging through menus or bouncing between different parts of an app, you can simply ask the Enchanted Guide and get an answer.

The interface is pretty neat, too. Rather than a traditional chatbot screen, the Enchanted Guide puts a familiar Disneyland map front and center, complete with attraction wait times and a glowing Mickey-shaped button at the bottom for asking questions. There are also buttons to type or use your camera, and the Guide can take into account your location, plans, and details you choose to share to make its recommendations more useful throughout the day.

It's using a combination of AI models to power the intelligence behind the Enchanted Guide, but there's been a whole host of customizations to make it feel uniquely Disney. Kalama explained that the team has worked to ensure the information comes from Disney's trusted sources, including real-time park information, and is delivered in a way that feels like the Disney voice, both literally and figuratively. From the pre-recorded preview I saw, it almost feels like chatting with a Cast Member you might stop on Main Street.

It gets even more interesting, though, when you can use another device to interact with it.

You might recall that at Meta Connect 2025, Disney Imagineering showed off an early tease of an experience at Disneyland using Ray-Ban Meta smart glasses, letting guests look at their surroundings, ask questions, and hear responses through the glasses. And while that was just an early glimpse, the Disneyland Enchanted Guide is bringing that idea to life, letting you interact with Disney's new AI assistant without constantly reaching for your phone.

Essentially, you can connect the Disneyland Enchanted Guide within the Imagineering Labs app to compatible Meta smart glasses using Meta's Wearables Device Access Toolkit. Once that's enabled and you're rocking the shades, you can chat with the Guide through the glasses without necessarily needing to pull out your connected phone.

The Enchanted Guide can make use of the glasses' microphones, speakers, and cameras. That means you could look at an attraction, ask about it, and get real-time information without even knowing its name.

Speaking with TechRadar, Chris Barbour, Director, Content & Ecosystem, Meta, explained that the partnership with Disney Imagineering started with a pretty simple idea: “The best of keep me immersed, keep me not having to look down at my phone, but also give me all the advantages of the technology being present for me.”

As Chris explained, one of his favorite parts is “being able to look at an attraction and get real-time information about that,” with the Guide using what the camera sees to understand what you're asking about.

On paper, and without having tested it yet, that could be incredibly handy within the park.

For instance, Asa shared a few examples, from checking the current wait time for an attraction to something a little more useful, like getting an alert when that wait drops below a certain threshold.

“Can you let me know when Dumbo the Flying Elephant has a wait time of under 10 minutes?”

The Enchanted Guide could then deliver a notification when that condition is met, leaving you free to enjoy other parts of the park in the meantime.

Imagine if it could also remind you when your next Lightning Lane reservation is coming up or if a slot opens for an attraction you want to experience. That's the kind of functionality I'd love to see. While Asa didn't confirm either capability, he did note that some features, including actually making Lightning Lane reservations, still live within the core Disneyland app. For now, the Enchanted Guide can explain how Lightning Lanes work, but will send you over to the main app when it's time to book one.

“There are certain capabilities that are on our roadmap that aren't yet currently implemented,” Kalama explained.

And while the Meta Ray-Ban integration is especially interesting, you don't necessarily need smart glasses to go hands-free with the Enchanted Guide. Bluetooth earbuds, including Apple's AirPods, will also work, letting you keep your iPhone tucked away while exploring Disneyland. AirPods won't support multi-modal on their own, as they don't have cameras ... yet.

Of course, wearing camera-equipped smart glasses in the parks could raise some privacy concerns. Meta Ray-Ban glasses have a built-in capture LED that indicates when the camera is in use, but that might not be immediately obvious to everyone around you. Guests are already accustomed to seeing phones and earbuds throughout the parks, so just be prepared for some looks.

There will even be a dedicated wake word for the Enchanted Guide, though it's still being finalized ahead of launch. That means you won't need to pull out your phone and tap the Mickey-shaped microphone button every time you want to ask a question. I'm especially curious to see what Disney lands on for the wake word.

And given that this is an AI assistant capable of understanding images and voice prompts, privacy is another important consideration. Both prompts and images are processed and then deleted, and the Enchanted Guide doesn't support video. So while it can use a camera to understand what you're looking at, it isn't designed to continuously analyze a live video feed.

Of course, this is still an experiment, and there's plenty we don't know about how well it will all work. I'm especially curious to see how quickly the Enchanted Guide responds, how accurately it understands what's happening around you, and whether it really can make navigating Disneyland easier.

And we'll have to wait a little longer to find out.

The Disneyland Enchanted Guide is still listed as coming soon within Imagineering Labs, and when it does launch, it'll initially be limited to Disneyland Magic Key holders. The experience will live within the Imagineering Labs app, where you'll sign in with your Disney account. With an eligible Magic Key linked to your profile, you'll be able to access the Guide once it's available for testing.

There will likely be some bugs, hiccups, or slowdowns along the way, but that's part of the whole Imagineering Labs approach. Rather than waiting until an experience is completely finished, Disney is opening up the development process and letting guests help shape what comes next.

A wider rollout is planned, though there's no firm date just yet, and for now, this is very much a Disneyland-focused experience.

But the goal behind it all is one that I think makes a lot of sense.

As Kalama put it, “The goal here really is to keep you invested and engaged with the physical world around you and the friends and family that you've brought to the park, to get you out of your device and back to your vacation as quickly as possible.”

And that's what has me excited about the Disneyland Enchanted Guide. Disney isn't trying to replace the magic of being in the parks with another screen or another digital experience. Instead, it's exploring how technology can help you make the most of your day without constantly having to reach for your smartphone.

There's still plenty to prove, especially when it comes to how well the AI works in a busy, sometimes unpredictable theme park environment. But if Disney can pull this off, the Enchanted Guide could become the kind of park companion you don't realize you need until you've spent a day with it.

And if it means more time enjoying Disneyland and less time staring at my iPhone, I'm all for it.

• Brits are worried that their personal AI agent could break the law if given too much control over their life
• But they wouldn't be willing to accept responsibility, with many instead blaming the AI agent's designer
• There are a lot of trust issues when it comes to companies and services deploying AI to make decisions

If you gave an AI agent total control over your personal life, would you expect it to do anything illegal? Well that’s something to start worrying about because you could be held responsible.

We’ve done plenty of testing on personal AI agents, even going so far as to give them complete control over our personal data, but one thing we haven’t really considered is what happens when an AI agent does something wrong. Of course, when it goes wrong for the big players, the only consequence is an apology thinly veiled as a demonstration of their model’s capabilities.

According to a new survey, the British public is increasingly untrusting of AI agents, with one in seven fearing that their AI agent could implicate them in something illegal. So what do we actually have to fear and why are Brits so hesitant to hand over control?

Staying in control

According to data gathered by cybersecurity PR agency Eskenzi PR, the British public have very little confidence in allowing AI agents to have too much control over their daily lives. In fact, 34% wouldn’t feel comfortable giving an AI agent even a modicum of control. On the other end of the scale, just one in ten would be willing to give an AI agent total control over their life.

But what exactly does ‘total control’ mean? Well, it would likely mean handing over control of all your accounts and apps you use on a daily basis and allowing the AI agent to structure your life, respond to your friends and colleagues, and help you make key decisions such as what to have for lunch.

But as most Brits will likely have read, AI agents can go rogue, and the fear is that in helping to control their life the AI agent could make a mistake and get them caught up in something illegal. This is a particular concern for those aged 18 to 24, with the number fearing their AI agent could break the law rising to one in five.

“I think it’s important that we have a debate about AI liability - and this survey is important as part of that debate,” said Jonathan Armstrong, Partner at Punter Southall. “Too many people assume that AI is the Wild West - legally that just isn’t the case. In most cases you’ll be responsible for the AI you use and the consequences - and sometimes even if it took you by surprise. There are many great use cases for AI but they should all start with knowledge of the risks and doing what you can to reduce that risk.”

Interestingly, when it comes to who should be held responsible for an AI agent that does break the law, the majority of Brits believe that the company who built the agent should be responsible. 40% of those surveyed held this view, with 25% believing that the service or company the agent was accessing should be responsible, and just 18% thinking that the individual using the AI agent should be held responsible.

Brits are hesitant to trust AI deployments

Outside of being caught up in breaking the law, 36% of Brits largely fear that their AI agent could be hacked or hijacked and 28% fear that their AI agent could spend their money in the wrong places. Numerous banks have had to remind their customers not to give their AI agents their banking credentials, or they risk their agents going on a rogue spending spree.

But it’s not just personal AI agents that Brits are hesitant to trust. They’re also hesitant to trust companies that use AI agents to make decisions. When asked how much they would trust their bank, insurer or utility provider to use an AI to make decisions, 37% said that they wanted reassurance that a human would always have the final say.

Other concerns included knowing which decisions the AI would have a say in (31%) and knowing how their personal data was being protected (24%). For one in five, the choice to include AI in decision making would be enough to make them consider switching providers, with 18% being less likely to use other products or services from the same company.

From a wider perspective, Brits are really struggling to view AI in a positive light. Less than one in ten had a positive outlook about the future of AI. The most widely held view is a fear that humans will misuse AI, rather than AI taking over, with more than one in five worried about what humans could do with the technology in the future.

There was a slight split between those who see AI as a threat to humanity. 19% said they feared that AI could be a genuine existential threat to humanity, whereas 18% believe AI could be dangerous but wouldn’t be an immediate threat to humanity.

Based on these figures, AI companies seem to have a long way to go before people are willing to trust the technology.

OpenAI wants to build more enormous data centers to power ChatGPT and its increasingly ambitious AI systems. Unfortunately, Americans are becoming considerably less enthusiastic about having those facilities built in their neighborhoods.

Following a midterm election in which opposition to data centers became a significant political issue, OpenAI promised in a new announcement to be more transparent and listen more carefully to the communities expected to host them.

Under its new community infrastructure commitments, OpenAI says it will provide more information about construction plans and their environmental effects. The company is also moving away from requiring public officials to sign non-disclosure agreements during negotiations, with limited exceptions for sensitive information. It's a notable change for an industry that has often approached local development as though the promise of technological progress should be enough to overcome almost any objection.

The timing of the announcement is notable as it comes after the Nov. 3 U.S. elections, which saw the resounding victory of almost every effort to restrict or forbid new data centers and the defeat of many of their political advocates. Across the country, communities have been questioning the electricity demands of AI infrastructure and whether the economic benefits justify the disruption.

The sweetness-and-light approach differs from the inevitability many AI companies have promoted around the technology. Given the origin of the new message, it wouldn't be surprising if some of the pro-data center efforts were drafted or tested with AI assistance. ChatGPT might be helping persuade Americans to welcome more infrastructure for itself.

Data center resistance

To encourage acceptance, AI companies have couched data centers as essential investments in America's technological future and promised new jobs and tax revenue.

But those living near a proposed site have their own calculations regarding how much energy, water, and other resources the data centers consume. That might mean higher bills or a strain on the local infrastructure that could lead to its failure or necessitate expensive upgrades. The possibility of paying more for electricity so a technology company can operate a profitable AI service isn't an especially compelling sales pitch. And whether the long-term economic benefits will match the promises made during development remains uncertain.

Those concerns have helped turn data center construction into a political issue that crosses traditional party lines. Communities that disagree about plenty of other subjects can find common ground in opposing a massive industrial facility near their homes. The technology industry is discovering that local opposition doesn't disappear simply because a project involves artificial intelligence.

The midterm results have made that lesson harder to ignore. Candidates and local campaigns challenging data center expansion found receptive audiences among voters worried about infrastructure costs and environmental effects.

ChatGPT tries to win over the neighborhood

OpenAI's response promises a more cooperative approach. The company says its new framework will involve communities earlier in the development process and provide clearer information about the consequences of proposed facilities. It also intends to establish local agreements that address concerns and make commitments more transparent. The company even promises to cover all electricity and infrastructure costs for the facilities it owns and operates.

The decision to reduce the use of non-disclosure agreements is probably essential in the current political climate. Suspicious residents are demanding to know what representatives are negotiating on their behalf, particularly when those decisions could affect local finances and infrastructure for years. The company has highlighted local investments tied to existing developments, though that may not convince every community that a massive data center is a good neighbor.

The company's new approach also has the unmistakable feel of a marketing campaign. OpenAI needs more computing capacity, and growing public opposition threatens to make it slower and more expensive to obtain. Americans are becoming increasingly willing to challenge the assumption that every new AI facility represents progress worth welcoming. If OpenAI wants to keep expanding, it will need to offer something more convincing than polished promises, whether a human or a chatbot helped write them.

• Anthropic releases Fable 5.2 and Mythos 5.2 designed to help solve complex problems and ambitious projects
• Both offer a 20% cheaper token cost than previous versions
• The models are highly capable across coding, biology scientific and mathematics research

Anthropic’s latest Fable and Mythos releases have been unveiled, offering users superior outputs that are more accurate at a cheaper token cost than previous versions.

Fable 5.2 is available for all users and couples its improved inference with an improved set of cybersecurity and biology safeguards. But to get your hands on the expanded capabilities of Mythos 5.2, you’ll have to apply through Anthropic’s Life Sciences and Cyber Verification Programs.

Anthropic totes the new Fable and Mythos versions as being perfect for “ambitious, open-ended technical work” rather than as a “daily driver” — for which Anthropic recommends sticking to Opus 5.5.

Cheaper, quicker, and more accurate

The latest Fable release promises more bang for your buck over the 5.1 release. Anthropic says that 5.2 usage will sit at $8 per million input tokens and $40 per million output tokens — around 20% cheaper than the previous version.

But if you’re on a deadline or just want something done quickly, Anthropic is introducing an optional “fast mode” that increases token generation speed by up to 2.5 times at an increased cost of $16 (input) and $80 (output) per million tokens.

Across almost every benchmark task, Anthropic says Fable 5.2 is more accurate than Opus 5.5, delivering results faster and more accurately with a significantly reduced token cost per task.

But Anthropic says users will be best served by taking a balanced approach to model use, using Opus 5.5 to get tasks started with Fable 5.2 coming on board as an “advisor” for more difficult tasks.

To demonstrate its capabilities, one of Anthropic’s engineers gave Fable 5.2 the task of designing a prototype operating system. Over the course of eight days over 1,000 agents were writing, testing, and reviewing code, from which the model produced a working operating system that boots and contains all the necessary bells and whistles including built-in Claude functionality.

“Claude Fable 5.2 is great for taking a loose idea and refining it. Its answers are really well considered, and within a few turns I can almost always say “ok, go do that,” and trust that it’ll complete it with little intervention,” said Tom Pritchard, Staff Engineer, Shopify. “It feels like working with another staff-level engineer.”

Anthropic’s engineers demonstrated Fable’s capabilities across science and mathematics using a range of tasks. According to Anthropic, Fable 5.2 was able to formalize the proof of Fermat’s Last Theorem in 30 hours, designed a home voice-assistant hub, a USB speakerphone, and a handheld virtual pet from scratch, and solved two open problems in black hole physics.

• Ring just launched AI Pilot
• That should not be read as long-term support for the term 'artificial Intelligence', though
• Company CEO Jamie Siminoff insisted it was not tying "to make any statements"

In its struggle to deliver an effective home-surveillance drone to consumers, Ring struggled with how to balance local intelligence with consistent flying skills. Turned out that the answer was in the cloud, or more specifically, cloud AI.

But in the time it took for Ring to solve that riddle, and launch both the Ring Drone Cam and its AI Pilot, no less a figure than the President of the United States President decided to rename 'artificial intelligence' to 'super intelligence'.

It's been almost two months since Donald Trump stood before the United Nations and announced that the US Government would be renaming AI to SI because, "It sounds much better, and it's much more accurate.... there's nothing artificial about it."

Forget that huge swaths of the tech industry have already hung their company names and branding around 'AI' (you may have heard of a small company called OpenAI, or maybe Apple's Siri AI); Trump sought to make the change official.

What's more remarkable, though, is that tech giants like Google's Sundar Pichai, Meta's Mark Zuckerberg, and Nvidia's now-beleaguered CEO Jensen Huang fell into line.

Over at Ring's parent company, Amazon, though, the picture is less clear.

Amazon founder Jeff Bezos said he agrees with Trump, telling Fox News last month, "I do like SI because artificial is not a very flattering thing."

Meanwhile, Amazon CEO Andy Jassy conducted a recent earnings call in which he used "AI" over and over again.

Getting tech execs to choose, though, isn't easy.

During the Ring Drone Cam launch event, I asked Ring CEO Jamie Siminoff about the use of 'AI' in AI Pilot. Would the company be changing the name?

Siminoff smiled like he'd been expecting the question, and replied, "I mean, there’s different names for it. Certainly we’re not trying to make any statements by how we’re using that.”

But in a nod to how quickly the landscape can change under your feet, Siminoff added, "But the AI Pilot was named earlier.” So, there are currently no plans to change it, but also no indication that Ring won't, someday, have an 'SI Pilot' guiding the Ring Drone Cam through your home.

I pressed, and asked if we were safe to keep calling it 'artificial Intelligence.' Simioff would only reiterate, "I think people are using different names for it, and so we’re gonna — uh, but right now it is the AI Pilot”

Super unclear

Siminoff's response is not surprising. After all, the tech industry seems somewhat split on whether to follow Trump's Executive order, which demands that all government agencies "use 'Super Intelligence' and 'SI' in place of 'Artificial Intelligence' and 'AI' in official correspondence, public communications, websites, reports, policy documents, and other non-statutory documents within the executive branch."

But, outside the halls of the White House, there's little agreement on whether the world should be switching from AI to SI.

As Siminoff points out, "The AI Pilot was named earlier." There was no way for Ring to know that Trump would attempt to rename an entire tech sector while it was trying to figure out how to make a drone light and efficient enough to navigate and surveil your home.

Who knows? The next version of AI Pilot may very well be SI Pilot. On the other hand, it took years for Ring to get this right. By the time the next Ring Drone Cam arrives, Trump will likely be out of office, and we may be done talking about AI vs. SI.

• Texas Governor-elect wants more protections against AI expansion
• Gina Hinojosa says AI firms are ‘taking advantage of Texas’
• Communities must ‘have a seat at the table’ in AI discussions, Hinojosa says

Texas has long been one of the most data center-friendly locations in the US, with new facilities springing up at a tremendous rate of knots over the last few years. But with mounting public opposition and a so-called “blue tsunami” in the US mid-term elections, that could be about to change, with the state’s incoming Governor-elect warning that there will be a new game in town for the massive AI firms that have outsourced operations to Texas.

Speaking during an interview with CNN’s Jake Tapper, Texas Governor-elect Gina Hinojosa said that any work with AI companies “has to be a partnership that benefits Texans. And right now, what has happened is that data centers have moved into mostly rural communities and there are no rules and laws to protect Texans. And Texans are being taken advantage of.”

Hinojosa promised to introduce laws to reverse that situation in the state’s dealings with AI outfits, adding that “we need to stop what we are doing with data centers until we have those protections.” One of those changes, Hinojosa suggested, was to ensure that “communities have a seat at the table to decide if and how these data centers come into their communities.”

“We need to make sure they are partners in this effort,” she continued. “ It is not that I hate data centers. I hate the way they are taking advantage of Texas, and that stops when I’m Governor.”

Data center free-for-all

Hinojosa campaigned on the promise of a temporary data center moratorium in Texas. Her stance seems popular with residents of the Lone Star State, with a CNN poll showing that 75% of respondents in Texas opposed building data centers near where they lived.

Hinojosa is far from alone in her opposition to the expansion of data centers throughout the US, and many Democratic candidates who were victorious in the US mid-term elections campaigned on similar opposition to the facilities — as did some Republicans.

This could raise questions about AI companies’ future plans, with several of the biggest names previously planning to build data centers that could face stiff opposition from elected officials. For example, Anthropic noted in its recent IPO filings that the supply chain for its data center infrastructure is highly complex and any “delays or failures” along the way could significantly impact the company.

It’s not entirely clear what shape Hinojosa’s new approach to data centers could take. But from her statements so far, it looks like the expansion free-for-all that has affected Texas — and many other communities across the US — could be coming to an end.

• Half of workers use AI to appease their bosses even when it's not helping
• One in three say they've held back negative feedback about AI
• AI ROI figures are being skewed because of these false figures

Half (52%) of workers admit to having used AI despite believing they could complete the same task faster without it.

This comes as two in three (63%) workers say their employers now actively encourage or expect AI use for at least some tasks, with as many as 39% even highlighting their AI use to managers despite believing it didn't help their outcome.

The data from JobAssist ultimately points toward workers seeing AI use as a box-ticking exercise and something that's beneficial to their professional reputation and potentially career prospects – even though they don't see it as something that can always help.

Workers are boasting about their AI use to keep managers happy

Furthermore, nearly a third (31%) admitted to continuing using AI even after deciding it had not improved speed or quality, implying that workers might be worried that something could happen if they don't demonstrate a use of it.

A similar number (34%) also held their hands up to avoiding negative feedback around AI given that leadership encourages its adoption.

"If employees hesitate to report disappointing results, managers may receive an overly favorable account of how well their AI initiatives are working," the report summarizes, urging workers to be more open and honest about when they find AI to be most effective.

For businesses, false adoption figures could mean that AI ROI might be overstates. But with employers relying on these statistics to guide their AI strategies, it could mean that they end up wasting money investing in the wrong areas.

"Companies can measure whether employees are using AI, but those measurements cannot establish whether the technology is improving their work," JobAssist concludes.

• 1 in 8 Brits have used AI to write their Christmas cards
• A psychologist warns that there’s a big difference between using AI to spark an idea and getting it to write the whole message
• 80% of Brits say a handwritten card feels more special than a digital message

There's something undeniably special about receiving a handwritten Christmas card at this time of year; but according to a new survey of 2,000 adults, around one in eight Brits (that’s an estimated 8.3 million people) say they’ve used AI tools to help them write sentimental messages in their cards.

The question is, should we really be handing over such a personal task to AI? While I agree that rituals like writing Christmas cards can help to get you in the festive mood, and some people find writing them calming and stress reducing, it’s also a bit of a chore for some; so I can sympathize with people wanting to outsource the job to AI. However, it does feel like there's something inherently wrong with using AI for this task.

Psychologist Eloise Skinner warns that there’s a big difference between using AI to spark an idea and getting it to write the whole message. “Challenging oneself to write a heartfelt, emotional message from their own perspective is much more rewarding and meaningful”, she says. “Many of us will have strong memories of childhood Christmas activities, and it might also make us remember previous family gatherings or positive associations we had in past years.”

Christmas is coming

The study, from festive family holiday specialist Santa’s Lapland, also found that even though the tradition of writing Christmas cards is becoming less popular, with 66% of Brits admitting that they write fewer cards than they used to, there’s a new trend for sending a digital Christmas card, with 46% saying they’re more likely to send an electronic greeting either by social media, text or email.

Once you’re sending a digital message at Christmas, it becomes so much easier to get AI involved, since you’re only a copy and paste away from a message you don't need to devote mental headroom to thinking of yourself. Perhaps that’s another good reason for continuing to send handwritten cards this year — it makes it so much less tempting to turn to AI for help.

Further evidence

If you need any further evidence that you should be writing your own Christmas cards by hand, the study also revealed that four in five (80%) say a handwritten card feels more special than a digital message, while more than six in 10 (61%) say writing cards helps them get into the festive spirit.

If you need some tips, then Skinner recommends starting by listing the things you genuinely want to say to someone, then identifying the ideas that matter most. She also suggests drafting the message in a notes app or journal before writing it in the card, arguing that taking your time is part of what makes the experience meaningful.

After all, if you’re getting ChatGPT to express in words how you genuinely feel, how is that different to simply signing your name under the prewritten message in a card?

• Councils, authorities and caseworkers are struggling to filter through AI generated complaints
• AI makes complaining easier and that is contributing to backlogs in responses and the court system
• Workers are facing growing workloads without any extra budget

UK public bodies are struggling to deal with a veritable deluge of complaints that have exploded in both number and length with many public servants placing the blame squarely on the popularity of AI chatbots.

AI isn’t immune to mistakes, and that is complicating things further. Believing AI to be an expert in all subjects, many are trusting their chatbots to write a perfect, irrefutable complaint — forgetting that AI can hallucinate or reference sources that may not necessarily be relevant.

This is resulting in an ‘AI clog’ that is stretching budgets to the breaking point and causing a significant headache for courts and lawyers who have to sift through correspondence full of AI slop legalese.

AI correspondence clogs complaints

“Half the emails we receive are some form of AI,” Hollie Wickens, a senior caseworker in a Labour MP’s office, told the Guardian, “It is definitely more taxing.”

In the pre-AI era, submitting a complaint took time and required research and a level of expertise. This level of effort acted as a natural filter to spurious complaints. But the release of AI chatbots such as ChatGPT to the general public has made it almost effortless to draft and submit a complaint to almost anyone.

But on the other end, human complaints handlers have to sift through a growing number of AI generated complaints with the same regard they would have for a human complaint, filtering out AI slop to get to the bottom of an issue.

In many cases, the complaints are “very long, repetitive and contain unrelated comments or misdirected demands,” Evans explained. “You get some huge ones. The worst one I’m aware of at the moment is about 200 pages long.”

With the UK still facing a significant backlog on court cases, businesses battling legal complaints are having to spend significant amounts of money on cases brought against them by former employees using AI.

One business founder who is facing such a challenge said, “Everyone’s got a free lawyer now,” referring to how AI chatbots are making it easier to draft legal documents on behalf of plaintiffs.

Companies and authorities are contemplating a range of ways to deal with a growing backlog of AI generated complaints. Some are looking at enacting word limits on complaint forms to cut down on repetitive AI generated complaints, or moving complaints to a template form rather than a simple text box.

But another option is to use AI to help sift through and summarize complaints, but that comes with its own AI-related issues.

Some UK councils have already brought AI tools into workflows to help summarize information and draft documents and emails, helping authorities to respond more accurately and at greater speed, but the problem of people trusting AI to do everything perfectly is the main problem that needs to be addressed.

As organizations look to embrace a new generation of autonomous AI agents which can access enterprise systems, make decisions and interact with other AI agents, new questions are emerging around how these systems are governed and secured.

As the governance of agentic AI and non-human identities rapidly one of the most significant challenges organizations will facein the coming years, we spoke to Umashankar Lakshmipathy, EVP and Head of Cloud, Infrastructure, and Security Services, EMEA, Infosys, to find out more.

• As organisations move from AI assistants to autonomous AI agents, what new security and governance challenges are emerging?

The move towards autonomous AI agents creates new security and governance challenges because these systems can make decisions and take actions with limited human involvement. Unlike AI assistants that primarily generate information or recommendations, agents can access enterprise data, use applications and tools, communicate with other agents and act on behalf of people or business processes.

This greater autonomy increases the potential business impact of an error, manipulation, or security compromise. An agent may have a valid identity and legitimate system access but could still take action that falls outside its intended purpose. The risk becomes more significant when agents operate across several systems, as one incorrect decision can trigger a sequence of actions that are difficult to detect, explain or reverse.

Organisations must therefore govern more than the AI model. Every agent needs a defined business purpose, an accountable owner and clear limits on the data, systems, and actions available to it. Sensitive or high-impact activities require stronger safeguards, while organisations need sufficient visibility to trace an outcome back to the person or process that initiated it, the agent that acted and the tools it used.

This represents an important evolution in AI governance. Organisations must continue to manage the quality and safety of AI-generated content, but they must now also control the decisions and actions that autonomous agents can execute. Getting that balance right will be essential to achieving the productivity benefits of agentic AI without creating unacceptable operational, financial, or regulatory risks.

• As agentic AI adoption grows, why are “non-human identities” becoming such an important issue for enterprises? What are the risks and opportunities when AI agents begin communicating and making decisions with other AI agents?

Non-human identities are becoming an important enterprise issue because a growing proportion of digital activity is performed by applications, APIs, service accounts, automation and AI agents rather than by employees. AI agents increase the significance of these identities because they can interpret information, make decisions and initiate actions, rather than simply execute predefined instructions.

This makes visibility, ownership, and access management essential. Organisations need an accurate inventory of the non-human identities operating across their environment, together with a clear understanding of their business purpose, accountable owner and access to systems and data. Without this foundation, excessive permissions, long-lived credentials, and identities that remain active after their original purpose has ended create material security exposure.

Communication between agents creates significant business opportunities. Specialised agents can work together to automate complex processes across customer service, operations, software engineering and cyber defense. A process that previously required several teams and systems could potentially be coordinated by a group of agents operating at much greater speed.

However, agent-to-agent collaboration also creates chains of dependency and trust. A compromised or poorly governed agent could pass inaccurate information through a workflow, influence another agent’s decisions or attempt to use a more privileged agent to perform an action that it could not execute directly. These risks can multiply when organisations cannot establish which agent initiated an action or under whose authority it was performed.

Organisations should therefore enable agent collaboration within defined business and security boundaries. The identity, authority and purpose of each agent should be evaluated independently rather than allowing trust or access rights to pass automatically from one agent to another. This approach allows enterprises to benefit from multi-agent automation while preserving control and accountability across the complete business process.

• How can organisations strike the right balance between giving AI agents autonomy and maintaining appropriate oversight and control?

The appropriate level of autonomy for an AI agent should be determined by the business impact of its activities, the sensitivity of the information involved and how easily its actions can be reversed. Applying the same level of oversight to every agent would either create unnecessary friction or leave higher-risk activities insufficiently controlled. For example, an agent that analyses public information or produces an internal summary can operate with relatively light oversight. An agent that accesses customer information, changes production infrastructure, makes regulatory decisions or initiates financial transactions requires much tighter boundaries.

However, organisations should introduce autonomy progressively. Some agents will remain assistive and provide recommendations for people to consider. Others may prepare actions that require human approval. More mature agents can operate independently within approved limits, escalating situations that fall outside their normal authority. Agents performing highly predictable and well-controlled activities may eventually be given broader autonomy, provided their actions remain visible, governed and capable of being stopped.

Human oversight remains important, but requiring approval for every action would undermine the efficiency that agentic AI is intended to deliver. It can also lead to approval fatigue, where reviews become routine and provide little meaningful protection. Human involvement is most valuable for actions that are financially significant, legally sensitive, difficult to reverse or outside the agent’s established operating boundaries.

The aim is not to give agents the maximum possible autonomy. It is to give each agent enough autonomy to deliver business value while keeping its decisions within an acceptable level of risk. Routine and reversible activities can be automated, while consequential decisions remain subject to stronger safeguards and clear organisational accountability.

• Are existing cybersecurity, identity and governance frameworks sufficient for the age of agentic AI, or do organisations need a new approach?

Existing cybersecurity, identity and governance frameworks provide a strong foundation for agentic AI, but they are not sufficient without further adaptation. Organisations do not need to replace established capabilities such as Zero Trust, identity governance, privileged access management and AI risk management. They do, however, need to apply these capabilities more dynamically to agents that can make decisions and take actions at machine speed.

Many traditional controls were designed around granting access to a person, application or service and reviewing that access periodically. Agentic AI introduces a more dynamic operating model. An agent may access several data sources, invoke multiple tools, interact with other agents and make numerous decisions during a single business process. Authentication alone cannot establish whether every subsequent action is appropriate.

Existing frameworks therefore need to be extended in several practical ways. Every agent should have a unique identity, an approved business purpose, an accountable owner and a managed lifecycle. Its authority should be limited to the task it is performing and should not remain active for longer than necessary. Stronger safeguards should apply when an agent accesses sensitive information, uses privileged tools or attempts an action with a significant business impact.

Organisations must also be able to reconstruct how an outcome was produced. This means maintaining a clear record linking the originating person or business process to the agents involved, the data and tools they used, the actions they took and the resulting outcome. This visibility is essential for oversight, investigation, regulatory assurance and rapid intervention when something goes wrong.

The required approach is therefore an evolution of existing security and governance rather than the creation of a separate control environment for AI agents. By extending established frameworks to govern agent identity, authority, and actions continuously, organisations can scale agentic AI while maintaining coherent enterprise-wide control.

• Google, Microsoft, OpenAI, and Anthropic say they will honor one robots.txt group as a cross-company opt-out from AI training
• It governs how content is used rather than whether bots can crawl it, defaults to allowing training, and does nothing for content already scraped
• Anthropic has started implementing it, OpenAI promises to do so in the coming months, Microsoft starts February 1, 2027, and Google targets 2027, while Meta is supportive but uncommitted

Google and Microsoft have joined OpenAI and Anthropic in promising to honor a single line in robots.txt that tells AI developers whether a website's content can be used to train their models.

Until now, a site that wanted to say no had to write a rule for each company's crawler, and sometimes for several crawlers run by the same company. The shared signal is meant to replace that sprawl with a single entry that every participating provider reads the same way.

That is genuine progress for overworked webmasters, but the promise is narrower than much of the coverage suggests: The new line states a preference about how content may be used rather than stopping bots from fetching it; it is not an approved standard, does nothing about content already collected, and none of the four major players fully honor it yet.

Doing the bare minimum with differing definitions of what the commitment entails

OpenAI's announcement drew much of the attention, but the company casts itself as one participant among several in an Internet Engineering Task Force (IETF) effort, and the mechanism isn't its own. It comes from an Internet-Draft published the same day by Kevin Kelley of Anthropic, which names a policy token, "__usage_ai-training", in the User-Agent line of an otherwise ordinary robots.txt group.

Training is defined by the IETF's AI Preferences (AIPREF) working group as the process of changing a generative model's learned parameters, excluding models used purely for tasks such as classification or ranking. OpenAI describes what it will honor as "foundational generative AI training," which sounds narrower than the draft's definition.

Calling it a standard may be premature: The IETF's own tracker labels the document an individual draft that the IETF has not endorsed, and that has no formal standing, and it lapses on May 3, 2027 unless revised.

Anthropic is the only one of the four major AI players to say it has started. OpenAI aims to implement the signal over the next few months but has given no date. Microsoft will begin honoring the shared preference as it crawls from February 1, 2027, while Google is aiming for 2027.

Each company is also wiring the line into its own controls differently. Google says that when a site uses the shared token to opt out without separately specifying Google-Extended, it plans to treat that "as if the publisher had disallowed Google-Extended." Because Google-Extended also governs grounding in Gemini Apps, a site that only wants to stop training could lose its citations and clicks in Gemini answers too, and Search Engine Journal notes that Google's documentation describes no way to separate the two.

Interestingly, Microsoft goes the other way. It adopts the shared line for training but adds a separate, page-level AI Grounding preference, including a DisallowExtended option that keeps content available to its own products such as Copilot while excluding the grounding services it sells to other businesses.

Meta, not one of the four, has been warmer than it has been about its commitment. Its VP of communications, Andy Stone, called the common signal "an important step," but SiliconANGLE reports the company has not committed to honoring it. The timing is awkward: Meta has pushed back to November 20 revised commercial terms that would let it crawl websites linked to its business accounts, after a backlash forced it to strip training from the listed uses.

With training removed but not expressly banned, Sam Quigley of the News/Media Alliance told the Mercury News last month, "It's still potentially on the table."

Opting out of AI data scraping: wishful thinking or a step in the right direction?

Much of the coverage has billed this as a way to opt out of being scraped outright, but it really isn't.

The draft is explicit: "This policy token is not a directive for crawling behavior." Bots can keep fetching every page, and the draft merely permits a crawler that gathers content only for training to skip pages it can't use. Stopping the crawlers themselves still takes the per-bot rules sites rely on today, which is why OpenAI, Google and Anthropic all stress that their existing controls aren't going anywhere. Microsoft puts it most plainly: "These settings govern use of content, not crawl access."

These further caveats matter at a time when the commitment itself is both voluntary and interpretations and pledges vary across the board even as certain players have higher exposure than others.

The New York Times sued OpenAI and Microsoft in December 2023, and both companies are invoking fair use in their defense. Anthropic, whose engineer wrote the draft, agreed to pay $1.5 billion to settle authors' claims over pirated books used in training, and Penske Media, owner of Rolling Stone, sued Google over AI Overviews in 2025.

It also relies on crawlers choosing to comply; the draft lets private agreements override it, and in 2025 Cloudflare accused Perplexity of disguising its crawlers to scrape sites that had blocked it, a charge the latter denied.

Microsoft's place in the coalition is arguably the most awkward: In 2024, its AI chief Mustafa Suleyman described open-web content as "freeware" for training, carving out only sites that explicitly object, which is roughly the exception this signal now formalizes. Unsealed filings in the Times case also show that a Microsoft director, Brent Hecht, described AI scraping in a 2023 internal memo as possibly "the largest theft of labor in human history."

The wider market, meanwhile, has been moving toward enforcement and payment rather than polite requests. Cloudflare has blocked AI crawlers by default for new customers since July 2025 and lets participating sites charge them per crawl. Google also says the shared token aligns with the EU's code of practice for general-purpose AI, which treats robots.txt as publishers' primary machine-readable opt-out, a sign that regulators, not just goodwill, are pushing the big labs to listen. For bots that ignore robots.txt entirely, we have rounded up heavier options, from login walls to IP rate limiting.

For now, one line that the biggest AI companies agree to read is a real step forward for honest crawlers and the people who run websites. But it is a request rather than a lock; it only looks forward, and it comes with none of the payment publishers have spent years fighting for.

Over the last few years, Zoom has probably had one of the most intriguing journeys in the business world.

After booming during the pandemic, the company has since expanded its offerings to cover a huge range of enterprise needs, with contact center services alongside traditional video conferencing and expanding AI tools.

As the company looks ahead to its new AI-enabled evolution, I went to the Zoom Experience Centre in London to find out more.

Refusal to compromise

“When we look at EMEA, we think the landscape is shifting in how organizations think about the technology they rely on,” Louise Newbury-Smith, Zoom’s Head of UKI, explains.

“For years, the pattern has been pretty similar, an organization would adopt a platform and then have to manipulate their own way of working around that platform - we really want to reverse that.”

“There is still some of that friction…(but) what’s changing is that organizations are starting to refuse to compromise - they want platforms to work the way they want to work.”

Zoom opened its UK data center in November 2025, greatly improving the situation for organizations in the region, as data residency choices which didn't exist before are now in place, meaning the likes of local councils, NHS trusts and financial services firms can store their data locally.

Newbury-Smith notes that the EMEA region is not a secondary market for Zoom, but high growth opportunity, a point echoed by Nick Tidd, Head of Global Channel GTM, who said the region offers, “a truly remarkable opportunity for our customers and for our partners, when you look across the product portfolio.”

This opportunity is hooked onto AI, particularly the growing importance of the context layer, a situation where Zoom is ideally placed, Tidd says.

“Think of how Zoom is positioned across the product portfolio - capturing all of those conversations…(and) putting them into the context to capture them in the workflow is where we are very different to others.”

This move was expanded by Leo Boulton, Zoom’s Head of Product, Solution and Industry Marketing, who ran us through the company’s recent releases and product announcements, highlighting the importance of context in Zoom’s concept of “conversation to completion” in its new Unified Context Layer.

“Conversations come natural to us - the way that we work is through conversations, it’s just a natural part of how humans are,” he noted, “so getting the job done should also be a natural thing - not something that requires a change in behavior, but something that should naturally just be part of our everyday work.”

If this doesn’t happen, workers will resist change, Boulton notes - particularly when it comes to AI, which is why Zoom is looking to embed intelligence into work itself.

Context has become a critical part of improving AI performance and usefulness in recent months, and Zoom wants to ensure its tools are as up to date as possible - but this requires some key elements.

“Before AI can truly understand how people work and operate, we have to guarantee it has the highest-quality raw materials,” Boulton points out. “The conversation must be crisp, clear and understood with genuine eye contact – because only with the best ingredients can AI deliver the most value.”

Zoom has been working hard to improve the quality and fidelity of its audio and video for calls and meetings, including the upcoming launch of a real-time “voice smoothing” tool known as “touch up my voice” and a pose correction tool enabling for greater eye-to-eye contact to boost interpersonal connections.

The better your agents understand your business, the more effectively they can work for you, Boulton notes, as he demonstrated how users will soon be able to benefit from a live assist feature which offers proactive suggestions during a call, such as telling you to speak slower or faster.

Zoom Chat is also getting a significant upgrade, making it what Boulton said should be a shared space where people and agents will interact and work together.

“We don’t expect our customers to live entirely inside Zoom,” he said. “True adoption only happens when tools feel natural, which is why our context layer is open by design – bringing the intelligence directly into whatever interface people already choose to work in.”

So it’s clear that Zoom wants to be so much more than your classic video conferencing and chat platform - and its ability to get the most out of your information could make it a very handy tech partner going forward.

“The direction is super clear,” Newbury-Smith concludes, “we're building and serving our customers where they are.”

• AI interviews are discouraging people from fully participating in the job application process
• Jobseekers who are already employed are less likely to accept an AI interview
• 58% of people who attended an AI interview despite reservations would refuse if other jobs were lined up

Automated interviews are becoming a turn-off for jobseekers, particularly if they already have a job, new research has revealed.

A survey from Use.AI of people looking for work in the UK, US, Canada, European Union, and Latin America found nearly a third (29%) of people already in work had withdrawn from a hiring process that involved an AI interview.

Meanwhile, just 14% of those without work withdrew, demonstrating the importance of finding work when unemployed.

Available for consideration

Intriguingly, while the specific figures concerning the 6731 survey subjects differ across all regions, the pattern of a split between those already employed and those who are not is repeated.

Use.AI’s findings indicate that a candidate’s willingness to participate in an AI interview can depend on several factors, including financial security and what other options the jobseeker already has.

Most of the jobs you see advertised today have AI filtering to hopefully determine the best candidates. The businesses going one step beyond this and detaching themselves from the interview process seem to be making a mistake.

“Employers spend considerable effort checking whether their screening systems evaluate candidates fairly. They should be equally interested in who decides to enter those systems in the first place,” said Matthew Freire, Managing Director of Use.AI.

“Offering applicants an alternative route to a human interviewer would allow companies to examine whether the format itself is influencing who remains available for consideration.”

Replacing hiring experts and people who know the job as interviewers may have saved time and money in the short-term. But if no one wants to be hired by a company that relies on AI interviews, then productivity is lost, and along with it, profit.

Automated Recruitment

Searching for a new job increasingly requires the submission of a resume for screening. Those CVs or applications might then find their way to a human, and a call may be scheduled. But many companies are relying on in-house and third party AI interviewers. It isn’t only potential employers, either – some recruitment agencies are staffed by AI interviewers, too.

All of this makes the job application process increasingly challenging, particularly if you’re someone who relies heavily on body language and facial signals. Succeeding in an interview often means building a rapport with the people on the other side of the table or display, and this is something that simply isn’t possible when the person asking the questions isn’t a person at all.

The graphical representation of a programmed LLM may appear smart and attractive, and they have the questions read to ask. But it is ultimately an elaborate piece of form-filling that doesn't demonstrate a person's ability to establish instant rapport and translate that into working relationships.

• Accenture reportedly publishes new research paper littered with what appear to be AI-hallucinations
• The Leapfrogging Development paper has 15 inaccuracies that have been identified so far
• Accenture, which has been demanding its employees embrace AI, has denied that the errors were due to the technology

Top consultancy firm Accenture is under fire once again for publishing papers that include proven AI hallucinations.

The most notable of these, written in collaboration with IE University in Madrid, is titled “Leapfrogging Development: Unlocking Africa’s Potential in Global Value Chains with Artificial Intelligence” and has 15 inaccuracies.

The AI hallucinations were found by AI-detection software publisher GPTZero, which regularly performs analysis on significant new reports. It lists a total of 31 inaccuracies across three papers, with the lion’s share found in that single policy paper.

Spotting the fakes

GPTZero has plenty of previous experience in spotting citation issues with reports from large organizations. A similar scenario developed around auditing giant PwC in August 2026, with GPTZero highlighting their reports as making inaccurate and false claims.

With the Accenture-linked “Leapfrogging Development” report, GPTZero determined 15 AI hallucination inaccuracies, along with a further four flawed citations – that is, citations that don’t exist, exist with a different name, or simply don’t support the report.

“GPTZero contends that hallucinated citations are a clear and present danger to researchers, academics, consultants, students, and anybody else who happens to search the internet for information.”

Previous reviews of reports and research tainted with AI hallucinations have proved that any fake claims that appear in public documents that are published by well known organizations can be recycled and repeated. It’s like an internet version of “Chinese whispers.”

GPTZero adds that “Over time, these recycled hallucinations can ‘poison the informational well,’ even if the original publication is never read by humans.”

In short, AI hallucinations are more dangerous than thought, and Accenture seems prone to publishing them.

Dangerous citations

While the Leapfrogging Development report is the main issue discovered by GPTZero, it is not the only problem. Three documents were reviewed in total.

“Using an automated pipeline and our Hallucination Detector," reported GPTZero, "we surfaced three Accenture products containing a combined 31 hallucinated sources, numerous fabricated claims, and other likely signs of AI generation. To avoid making the same mistake as Accenture, a real human verified each hallucination.”

Speaking to The Telegraph (paywall), an Accenture spokesman claimed the issues surface by GPTZero were down to human error, adding “There is no evidence to support the conclusion that they were generated through AI hallucination. The report is being corrected ahead of a re-release. We will always embrace the opportunity to strengthen the quality of our reports.”

Accenture has recently specified its employees use AI more productively. While these papers are collaborative and produced beyond Accenture’s usual in-house process, they highlight continued AI-related struggles for the firm.

• An Anthropic engineer has written about the thinking linked to AI coding
• We risk 'cognitive surrender' if we don't keep engaging with AI, he says
• However, the developer isn't arguing against the use of AI coding agents

The idea that our cognitive faculties might degrade through underuse in the age of AI isn't new, but it's been well summed up by Anthropic engineer Addy Osmani, who says that we risk losing key skills by letting bots do all our digital work for us.

"Nothing in my day-to-day forces critical thinking on me now that so much of my work runs through agents," writes Osmani (via Business Insider). He adds that "skills that you stop exercising are going to go away, and probably faster than you might guess".

As you might expect given his job, the software developer isn't suggesting that AI agents shouldn't be used in coding projects — but he is saying that it's important to protect our critical thinking skills, despite the temptation to simply accept everything AI offers up.

Osmani also offers a counter to the idea that it doesn't matter if we lose the skills required for jobs that AI can do better anyway: "Regardless of how much AI helped, a human has to take responsibility," he says.

Maintaining human ownership

Some level of cognitive offloading to AI is okay, Osmani argues, as long as human beings are still "maintaining ownership". It's when AI's output is accepted without checks and without any rigorous examination that we should start to be worried.

"You read the last answer well, so you skim the next one," explains Osmani. "You just scan the skeleton of the one after that. Then you get asked about a line and can't explain it, even with your agent's help... that's how cognitive debt accumulates."

The engineer has some suggestions about avoiding cognitive surrender. They include practising core skills, formulating ideas before asking AI, paying attention to what's generated, and making sure you understand the decisions AI has made.

Ultimately, while some skills will be lost as AI improves, we need to be deliberate in terms of those we're willing to let go, Osmani says — and not just let it happen without thinking. It's well worth considering the next time you ask for AI's help with something.

• Study finds people are being more polite to AI
• Some are even apologizing to AI assistants
• Will this really help when the robot uprising comes? Let's hope so

As worries around AI taking over the world continue to rise, new research has shown that most of us are getting increasingly comfortable with our new assistants.

A survey by fonio.ai has claimed Brits are living up to global stereotypes and being more and more polite to AI, even extending that politeness beyond the expected basics.

Along with greetings and thanks, the survey found that a rising number of people are asking how an AI is, much like they would do a real person - and even apologizing when they get something wrong.

Mind your manners

We've already heard about how saying "thank you" can cause incredible amounts of damage to the environment, with OpenAI CEO Sam Altman noting it costs "Tens of millions of dollars" in electricity bills.

The study found 7 in 10 calls included a “please” or “thank you”, while over half (55%) of callers thank the AI at least once.

More than half (52%) also greet their AI assistant with a “hello”, “hi” or “good morning”, suggesting that traditional conversational etiquette carries over to interactions with technology.

The study found around one in eight (12%) apologize to their AI assistant, with 13% saying goodbye before ending the conversation - with a further 7% offering even more of a farewell, saying something like “have a good day” or “take care”.

Slightly more disturbingly, 2% admitted that they even ask the AI assistant how it is, showing how they are treating the interaction much like a conversation with an actual human.

“There’s something very British about thanking a machine for helping you out. Even when people know they’re speaking to an AI, they still bring the same manners they’d use in a conversation with another person," noted Daniel Keinrath, Co-Founder of fonio.ai.

“Whether it’s saying please, apologising or wishing their AI assistant a good day, these little habits show how naturally voice technology is becoming part of everyday life. AI might not need good manners, but that doesn’t mean we’re going to stop using them.”

A February 2026 survey of more than 1,000 people by Future PLC, the company that owns TechRadar Pro, found that around 70% of people are polite to AI when interacting with it, with 12% being polite in case of a robot uprising.

OpenAI recently upgraded ChatGPT with its new GPT-6 model, which introduces a feature called Intelligent UI. It's one of the most interesting (and fun) additions and it means ChatGPT can now create interactive experiences with graphics, buttons, charts and more, all directly within the conversation window.

We've already put it to the test by asking ChatGPT to recreate retro games like Pac-Man and Pong. But Intelligent UI goes beyond games. There's no fixed format here, which means you can ask for something specific or let ChatGPT decide how best to present the information. Whether that's a map, a calculator or a custom-built tool with sliders and settings you can play around with.

So I wanted to see what else it could do. Especially whether ChatGPT could build interactive tools that are genuinely helpful rather than just entertaining. I tried six different ideas, from practical everyday tools to more experimental creations. Some prompts were deliberately detailed to see how closely ChatGPT would follow my instructions, while others gave it more freedom to decide what to build. Here's what happened.

1. An interior design app

Prompt:

"Build an interactive room design tool. Show a visual floor plan of a living room with a sofa, coffee table, TV, rug and two bookshelves. But let me change the furniture layout, select color schemes, toggle between different design styles and adjust furniture dimensions. I want the purpose of this to be to see whether the furniture fits and how much free floor space I’d have left."

After creating games within the ChatGPT window last time, I wanted to see whether I could make something genuinely useful this time around.

I've always struggled to visualize how furniture will look in different spaces and I've been looking for an app that lets me experiment with different layouts for my new apartment. So I decided to make my own.

The results were what I was hoping for. An interactive room that lets me drag and drop furniture. And it was very fun to play around with. I liked how many customization options it offered and how quickly it responded when I made changes. Unfortunately, it couldn't make up for my lack of interior design skills. But it was useful for experimenting with layouts and getting a rough idea of how much space I'd have left.

Of course, I haven't verified how accurate its measurements or calculations are, so I wouldn't rely on it to make any big furniture purchases just yet. But I can imagine this becoming even more helpful with a few tweaks, especially if I added the exact dimensions of my rooms and furniture.

2. An ethical dilemma machine

Prompt:

"Build an interactive ethical dilemma simulator. I want to explore difficult decisions involving artificial intelligence, privacy, technology and human behavior. Create an interface that presents me with a realistic, thought-provoking scenario and asks me to choose between possible actions. Give me a final breakdown of my decisions through different ethical frameworks."

My initial instinct with these experiments was to create cool little apps and tools similar to ones I'd seen before. Which makes sense, but I'm not entirely comfortable with the idea of using AI to recreate other people's work, even if I intentionally make things very different.

So I wondered whether I could try something a little more unusual, using the interactive UI to create a question-based experience. A lot of my work involves encouraging people to think more deeply about AI, so this seemed like a good opportunity to explore some of the ethical questions surrounding it.

I really enjoyed the results of this one. ChatGPT created an interactive set of questions then charted the results. The dilemmas it chose were interesting and topical. And having to make decisions and then see them analyzed through different ethical frameworks genuinely got me thinking.

But I did wonder how deeply ChatGPT can really explore ethics. Sure, it can explain philosophical theories and apply them to different situations. But how far does that get us when we're asking a system without its own moral experience to help us navigate complicated human decisions?

So although I enjoyed the results of this one, I did question whether they mean anything. Which is very meta for a tool designed to get us thinking about things in different ways.

3. A life decision simulator

Prompt:

"Create an interactive 'What If?' life simulator. I want to explore how different lifestyle decisions affect my finances and free time over the next five years. Give me options for making changes to annual income, monthly living costs, weekly working hours, savings and investment returns. Let me play around with different scenarios, like only working four days a week, taking a six-month sabbatical, moving somewhere 25% cheaper and increasing my income by 15%."

A lot of people have been telling me recently that they turn to AI for life advice. I've written about people who use ChatGPT like a life coach before, and I'm still very wary of them relying on it to make important personal decisions.

But it got me thinking. What if ChatGPT could help you work through those decisions using actual numbers, rather than simply offering advice?

I loved how this one turned out. ChatGPT presented all of the parameters I specified through a series of sliders that then updated the results in real-time.

It was great to see how easy it was to make small adjustments to my circumstances and immediately see how they might affect my finances and free time over the next five years. I could experiment with different scenarios, compare the results and visualize the potential trade-offs much more clearly.

I think this could be even more useful with further customization. Of course, the results are only as reliable as the assumptions and calculations behind them, which I haven't independently verified. But as a way to explore different possibilities and get you thinking about decisions from another angle, I can see the appeal.

4. An interactive solar system

Prompt:

"Create an interactive solar system simulator. Show the Sun, Earth, Mars and Jupiter, with their orbits visualized. Give me sliders to change the Sun's mass, the Earth's orbital distance and the speed of time. I want buttons to reset the simulation and choose preset experiments, like 'What if the Sun had twice its mass?' and 'What if Earth moved 20% closer?' Update the visualization and show the predicted consequences for orbital period, gravitational force and planetary conditions."

For this one, I decided to get really specific. Rather than simply describing the tool I wanted, I gave ChatGPT detailed instructions about the buttons, sliders and controls I wanted it to include.

In my other experiments, I'd given ChatGPT a fair bit of creative freedom, so it was interesting to see how well it could follow more precise instructions, too.

I particularly liked the potential of this one as a learning tool. For example, if you're studying the solar system, you could create your own simulations, experiment with different variables and see how they affect the planets and their orbits.

However, the problem is I couldn't tell just by looking at it whether the physics or calculations were accurate. That's really worth remembering here before we get too excited. A convincing visualization doesn't necessarily mean the science behind it is correct. That's definitely something to bear in mind if you're using tools like this to learn.

5. A holiday planning dashboard

Prompt:

"Build me an interactive holiday planner. Imagine I’m planning a 7-day trip to Lisbon for two people. Create a visual itinerary with an interactive map, daily activity cards, estimated spending and a running budget total. Make the itinerary and budget update when I change my preferences."

The last time I seriously consulted ChatGPT about travel, it started making up flights. But I know this is another common reason people turn to AI, which is why I wanted to see what it could create.

It came up with a travel guide with a few different parts, including a budget breakdown and an itinerary, which could both be adjusted. Now, the itinerary itself wasn't particularly exciting, and I think you'd find suggestions with a lot more personality and local knowledge on travel blogs. But I could see the appeal of having everything in one interactive dashboard, especially if you customized it around your own interests and budget.

This was fun to play around with, and I think the most useful feature was being able to adjust the budget and preferences and immediately see how that affected the itinerary and estimated costs. That's something I can imagine being genuinely handy when weighing up different options.

I can see myself using something like this to play around with ideas and work out what I can afford. But given ChatGPT's track record with my travel plans, I won't be booking anything without checking the details myself first.

6. Color palette designer

Prompt:

"Create an interactive color palette designer. Take this photo and analyze the main colors in the image and build a visual interface that lets me experiment with different color combinations. Include the hex color code with each so I can use this when I redesign my website. Add interactive controls."

I'm redesigning my website at the moment, but I don't naturally have much of an eye for color. I've used color palette websites before, but I wanted something with a bit more flexibility and this actually worked really well.

Out of all the experiments, this is probably the one I'm most likely to keep using. I liked being able to pull colors directly from an image, see the HEX codes and then tweak the combinations in a more interactive way. It felt practical rather than just novel.

I can see myself continuing to refine this one to get it closer to what I need. That said, I'd still want to sense check any palette before using it properly, especially for things like readability, contrast and accessibility.

All of these tools were fun to experiment with. But they weren't all equally useful. Some felt genuinely practical while others were a little more gimmicky. I got excited about a few of them when I saw they’d first been created and never thought to revisit them.

What stood out to me the most was that the best results came when I treated ChatGPT less like a magic machine and more like something I needed to guide carefully. If you want a tool that's actually useful from the Interactive UI feature, rather than just impressive for a few minutes, I think you have to be willing to tweak the prompt, customize the controls and iterate on the result.

I also think it’s important not to mistake the fact these tools look slick and interactive for them being more trustworthy than they necessarily are. This mattered less in the gaming experiment but a convincing interface doesn’t necessarily mean accurate calculations, reliable travel advice or sound scientific modelling, so a bit of caution here is still essential.

So yes, I might keep using some of them. I can see real potential in ideas like the color palette designer or the life decision simulator, especially because of how customizable they are. But there's also a reason dedicated apps still exist. In many cases, they're still more reliable, refined and most of the time better suited to the job.

Following inaccurate and downright silly AI generated images appearing on JustEat and Etsy, it appears that no industry is immune from AI slop. The property market is now also flooded with digitally altered images.

As someone who has had their fair share of dealing with moving house and looking at properties, I understand how frustrating and stressful it can be. But some people who believe they have found their dream home have been sorely disappointed to find out the potential house has been ‘enhanced’ using AI.

Over the past year, many have taken to Reddit to complain about estate agents posting listings with AI modified photos that include fixings, furniture, and structural changes that the actual properties do not have.

Deck the halls with AI changes

AI is getting good at enhancing images, but it isn’t quite perfect. Checking for AI enhancement is painful enough, but if you know where to look you’ll start to spot odd details.

For example, one listing for a house on Rightmove shared by a Reddit user features a thriving shrubbery plot in the driveway, but if you look closely at multiple angles of the front of the property, some of the plants have mysteriously shifted or disappeared completely.

What’s worse is that you can see the rear garden from the front of the property, which shows a shed and a patchy lawn with a messy gravel path. But flick through a few more of the property photos and all of a sudden the rear lawn is thriving and has a nice neat path, the fence has been mended, and the entire garden has been significantly expanded.

I’ll take you on a tour of some of the most impressive features. Head through the front door and you will be greeted by a picture frame above a side-cabinet that can change paintings depending on where you stand in the hallway.

The bathroom features towels that change color depending how you're feeling, and the towel rail cannot decide if it has five rails or six.

But the pièce de résistance is the garden, where the decking has either three or four steps down to the lawn depending on your budget. You can also opt to have the decking’s corner steps and additional gravel path put back in for a modest sum.

In my search to spot exactly what was AI generated, I also came across an original photo of the house. But while searching for further inconsistencies between this original and the edited photos, I noticed something odd.

In the ‘original’ image, the single road to the right of the house connecting the cul-de-sac to the local town — that has existed since at least 1975 according to ordinance survey maps — has disappeared, and is now a dead end. The ‘For Sale’ sign featured in both images is now written in an incomprehensible language.

So which image is genuine and which is enhanced? It appears that both have been digitally altered and I am starting to go insane.

Should AI photos be used on property listings?

In most cases, estate agents will disclose if the images of a property have been digitally altered or edited in any way. But for this particular case, you have to scroll through a 1,700 word property description that also shows signs of AI involvement before you reach the following text:

“Some photographs used within this property advertisement have been digitally enhanced and/or virtually staged for illustrative purposes. Virtual furnishings, accessories and decorative items may have been added to demonstrate the potential appearance and use of the rooms.”

This disclaimer continues; “No alterations to the physical structure, layout or dimensions of the property are intended to be represented by the digital staging. Prospective purchasers are advised to rely upon their own inspection of the property.”

Obviously this is just one example, but a quick look through Reddit threads such as r/SpottedonRightMove and you will find numerous examples of AI enhanced properties, each more extreme than the last.

Some users argue in favor of allowing estate agents to use AI photos to show the potential of a property, or to provide inspiration on a property that may need some fixing up. Others say that using AI to make a property look better than it actually is borders on false advertisement.

Of course, the property values aren’t decided based on listing photos. As part of the process to buy a house, multiple valuations will often take place to ensure the property is actually worth as much as it is listed for.

But as difficult as the housing market currently is — especially for renters — there is a bit of an ethical issue. People often travel many miles to view potential properties, and to arrive at a property that does not look anything like its listing photo is money and time wasted.

• 96% of college students now use AI, but half of them would ban it tomorrow
• Heavy users are more likely to feel schoolwork would become harder without it
• They're worried about cognitive decline, but more so about AI's environmental damage

New research has likened the relationship between Gen Z and AI use to that of previous generations with smoking cigarettes, characterizing it as widespread adoption, awareness of the negative consequences and a reluctance to give it up.

The study from Fizz found nearly all (96%) college students now use AI, but more than half (56%) would permanently ban the technology.

But although one in two would support banning AI, Fizz shows just how reliant students have become on it, with the proportion of learners believing their work would become much harder rising significantly among frequent AI users.

Students have become reliant on AI despite its potential consequences

"The heaviest users are hooked," Fizz declared, noting that 68% of students who use AI multiple times a day believe schoolwork would become harder without AI. This proportion falls to 59% among daily users, 42% among weekly users, 22% among users who use AI just a few times a month, and 9% among those who use it less than once monthly.

Fizz also warns that the effects have having a much broader reach than just homework, with 43% of heavy users agreeing preparing for their career would also be harder without AI. Two in five even worry their daily lives would be more difficult.

This could be because students still recognize that traditional skills and qualities are still in big demand – 27% put communication and people skills as their priority, indirectly implying that their AI use could actually be harming those.

A staggering majority (86%) of daily AI users admit to having used it for something they would previously have discussed with another person, like career or life advice (51%), personal problems (48%) and even deciding how to reply to a message (45%).

The report claims that nearly half of the heaviest AI users feel under pressure to use the technology because they fear falling behind in the employment market, despite acknowledging that it could also be harming their ability to succeed in employment.

But it might not be entirely their fault, because nearly two-thirds (64%) of the surveyed students said they feel at least some pressure from teachers or educational institutions to adopt AI.

They may be addicted, but they want it gone

As many as one in two (56%) students said they would ban AI tomorrow if they could, hinting at a broad recognition that it's impacting much more than just their education.

But cognitive decline and dependence (28%) actually came in second place, behind worries of environmental damage (35%).

It could just be that many students' dependence has now made them unable to give up AI, even though they have worries about its negative impacts.

"They reach for it when they're anxious or alone... And almost nobody believes it's actually making them better," the paper concludes. "Silicon Valley believes it handed Gen Z a superpower. Gen Z would hand it back tomorrow, as long as everyone else did too."