• 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."

• Famed game creator Hideo Kojima has voiced his opinions on AI
• He said human creativity is a vital part of the game-development process
• And he’s worried about a future where AI dominates the industry

Legendary games maker Hideo Kojima is known for the creativity of his output, from the Metal Gear Solid series to Death Stranding, so it’s unsurprising to hear that he has strong opinions on the use of AI in video games. And in a fresh interview, he told readers exactly where he feels AI falls flat compared to human-made artistic expression.

Speaking to Japanese site Game*Spark, Kojima said that while it’s good that AI has improved efficiency, “the fun isn’t in finishing the picture. It’s in the process … While it’s fine to tell a computer to create this or that, and then say, ‘That’s wrong, change it,’ I don’t find that very interesting in terms of craftsmanship.”

“I’m worried about what will happen to that aspect of the enjoyment of craftsmanship in the future,” he added.

Kojima said he feels that there’s a distinction between using AI for creative output and employing it to form a finished product: “If you’re just making a ‘product,’ that’s fine, but I think the fun for creators lies in the creative process itself. I think ‘creativity’ and ‘products’ are different things.”

In other words, AI doesn’t offer creators the kind of spark they get from crafting something themselves. And it’s that kind of magic that so often resonates with consumers of Kojima’s media.

His comments reflect those of Jason Graves, the composer of Call of Duty: Modern Warfare 4’s soundtrack, who spoke out against AI music generation, saying that “Music is not just a bunch of notes strung together.” Instead, the process is essential as it is based on “creative instincts forged by emotion and all the little decisions that give a piece of art its own unique personality.”

The effort itself is key

Kojima didn’t just muse on what AI means for video games and other creative outlets in the present — he also had thoughts on how it could impact the future.

For instance, the game director said: “It’s not about telling someone to make a song like this and then being satisfied with the result; it’s the trial and error in between that gets the adrenaline pumping, and it’s incredibly exciting. I don’t want a future where that’s lost.”

He then reflected that, “I think it will be fine for five or 10 years, but if AI continues unchecked, perhaps a future where AI plays a vital role in creative fields will come someday. Well, I won’t be around by then. It’s up to the younger generation to decide, so I want to pass the baton to them.”

If the goal is purely to improve efficiency, AI could help to build a “good future,” Kojima noted. But for someone like him, there’s evidently much more to crafting something than just making it quickly with minimal effort.

Indeed, the effort itself is a key part of creative development. As Kojima put it, “Even with plastic models, the shape is the same no matter who builds it, but the process of assembling it is what’s interesting, isn’t it?”

• Deloitte finds 28% of businesses report current revenue growth, up from 20% earlier this year
• Productivity and improved decision-making are still performing better
• Sovereignty has become an integral part of AI strategies

New Deloitte data has claimed that when it comes to business AI, we're finally at the stage of ROI, with more organizations than before now reaping the rewards of their costly deployments.

As many as 28% now report current revenue growth as a result of their AI strategies, up from 20% compared with earlier in 2026, the firm's report found.

Realizing higher revenue is largely seen as one of the most important returns from AI – with companies spending so much on services and infrastructure, they need to make that money back.

AI adopters are finally seeing increased productivity translate into higher revenue

While other areas like efficiency and productivity (up 74%), decision-making and data insight (up 60%), cost reductions (up 45%) and better client relationships (up 44%) are all moving in the right direction, Deloitte says increasing revenue is still one of the slowest to deliver tangible results.

Deloitte's research also indirectly implies that businesses could be getting carried away with these early signs, because the majority (86%) of businesses surveyed plan to increase AI investments over the next financial year.

Additionally, while early ROI markers are now heading in the right direction, Deloitte worries that many businesses still don't have the right visibility into AI's financial impacts. While three in four (71%) are tracking total spend across token consumption, many can only see the total bill and not the breakdown of which activities lead to which spend.

Jobs are changing because of AI

It's becoming an increasingly familiar concept that employers need to redefine roles as AI becomes more engrained – developers are already seeing a shift from writing code to managing AI agents, for example.

Deloitte says there's a long way to go on this front, because while three in five companies have already redesigned jobs 'moderate[ly]', only 15% of them have done so 'extensive[ly]' and 1% 'completely.'

"Many are still just scratching the surface," the report claims.

The future of AI investments looks different

Looking ahead, Deloitte expects sovereign AI to become even more of an important consideration. Nearly half of Americas (46%) and EMEA (47%) businesses are building in-house to regain control over their workloads, with three in four (74%) global respondents reporting at least 'moderate' importance of sovereign AI.

But the paper does acknowledge the benefits of using centralized hyperscalers, noting that going sovereign or building in-house comes with certain trade-offs – usually "capability, speed or cost."

At the same time, we're hearing more and more about enterprises like Revolut picking up the infrastructure bills themselves, choosing to self-host open-weight models for greater cost predictability, usually at the expense of model performance in scenarios where they can achieve their desired outcomes without leading frontier models.

The report sets out six key considerations for the next stages of AI: adopters must respond by redesigning work as a whole, not just the workflow; costs need to be traceable to the token degree, not just the full bill; AI strategies must align with actions that produce revenue; governance needs to keep up as systems become more autonomous; early adopters are now starting to look at physical AI like robots, and so should you; and sovereignty should be seen as an ongoing effort consideration over a one-time fix.

• OpenAI launches new program to protect residents and businesses near its data centers from power outages
• The Grid Protectors Program is designed to prevent OpenAI campuses from “hogging” all the power
• A new development in Effingham County, Georgia, will pioneer the program

OpenAI wants to protect local communities situated around its data centers from power outages, and has launched a new program intended to deliver both reliability and affordability to nearby residents and businesses.

The Grid Protectors Program is launching with the planned Effingham County, Georgia data center campus, which features an agreement with Georgia Power to make power available in a flexible demand scenario, which should cover demand for around 700,000 households.

OpenAI’s future facilities are designed to be more flexible in how they demand power from the grid, and the Grid Protectors Program viewed as a “starting point” for improved reliability for homes, businesses, and of course data campuses.

Grid Protectors pilot

The Grid Protector Program certainly seems a step in the right direction from OpenAI. It comes against a backdrop of growing concerns over the power requirements of AI data centers and protests over their approval, invariably in locations where residents are resistant.

OpenAI says the pilot site at Effingham County incorporates its agreement with Georgia Power to accommodate “up to 1,000 megawatts of flexible demand response.”

This is intended to ensure local residential and business properties have the power available “to help keep air conditioning running in hundreds of thousands of homes during extreme heat. For scale, that is equivalent to the average electricity demand of roughly 700,000 households.”

OpenAI says this is more than enough to cover the combined households of Washington, D.C., and Boston.

Financial assurances

By working to offer communities assurances of flexible energy at its new site, OpenAI clearly hopes that its upcoming data centers are recognized as more suited to locations that have recently come under fire.

Perhaps they want to be a part of those communities? The launch announcement adds that its new compute facilities are more flexible than older facilities, and OpenAI is committing itself under the Grid Protectors Program to collaborate with authorities.

“We will work with utilities, regulators and policymakers to develop practical arrangements for the campuses we build in the future,” it announces, “arrangements that reflect local grid needs, help campuses support the grid when it is under pressure, and pay the costs we create. Long-term contracts and financial assurances can protect other customers if a project is delayed, reduced or canceled.”

• Apple is reportedly cutting AI budgets per worker
• Developers will still likely have more than other workers
• Model choice and hosting provider could be enough to cut costs

Apple has reportedly started cutting the amount employees can spend on artificial intelligence, per Bloomberg reporting, making it one of the latest companies to be limiting AI tool expenditure as unpredictable costs skyrocket.

The Cupertino giant had already reportedly cut budgets from $300 per engineer per day to $200 in October 2026, but further reductions are said to be planned as this figure could be on track to drop to $100.

Non-engineers are likely to face even tougher restrictions, with the company considering a 75% cut from $100 to $25 per worker per day, the report claims.

Apple could be set to limit workers' AI budgets

Like other tech giants that have introduced similar cuts, budgets will likely be determined by team and project, and certain projects and individuals could be able to justify higher consumption if their work requires it. However Apple declined to comment on Bloomberg's story.

Workers could also be asked to reconsider the tools they use, with the company said to be permitting the use of ChatGPT, Claude and Gemini, rather than just one. Engineers may be asked to use lesser models, which are cheaper, or even transfer workloads to even cheaper models that run locally on the company's own hardware.

UK digital bank Revolut has already moved away from Claude in favor of open-weight models hosted on its own infrastructure.

While a budget cut from $300 to, possibly, $100 per day may sound like a 3x decrease, it might be more attainable for some workers than those figures suggest. Earlier AI efforts among tech giants saw developers so-called 'tokenmaxxing' – using AI more than they really needed to, just to appease company metrics. It's unclear whether this applies to Apple's developers.

Still, the company likely faces an expensive short-term future, with R&D expenditure up 32% in FY 2026 compared with FY 2025, and total operating expenses up 22%. Quarterly revenue rose just 12% year-over-year, in comparison.

• Etsy has updated its Seller Handbook to include new guidance on how AI can be used
• Products must include at least one unaltered listing image that shows the actual product
• AI can still be used for some purposes, but misleading images will hopefully start to disappear

In the wake of Just Eat’s AI generated food image fiasco, Etsy has decided to update its policies to prevent AI being used to generate or edit images, create guides, or use bots to generate listings.

The new guidelines, enacted in October, are part of an effort to crack down on images, recipes, and instructions that have been partially or fully AI generated that could mislead customers — and it could help cut down on the torrents of AI slop that have infiltrated the internet.

“You, our seller community, have told us you’re concerned about your work appearing alongside items that use AI in misleading ways, and that it’s becoming harder for buyers to recognize your role in creating your items,” the announcement states. “We're taking an important first step to address these challenges.”

Etsy changes AI usage rules

The steps Etsy is taking include changes to how products are physically presented in images, how AI can be used to edit images, and how functional guides are written.

For a start, Etsy now requires at least one of the listing images to be a real photo of the actual item being sold with on a real background without any edits or alterations made. But this image doesn’t have to be the first image potential customers will see when viewing your listing.

But if you’re wondering about non-physical purchases — such as artwork printed by a third-party — Etsy will allow unedited mock ups from manufacturers for print-on-demand services to be used as the ‘real’ product photo. As for audio and digital downloads, Etsy says the imagery cannot mislead customers.

Don’t worry, AI editing is still allowed in some circumstances such as to change lighting and exposure or to resize an image. Backgrounds can also be AI generated as long as the actual product isn’t changed in any way, but using AI to alter the actual product by changing colors, condition, or features of an item is now a hard no in Etsy’s books.

Finally, when it comes to other products commonly listed for crafters or cooks, Etsy is changing how they can be written. Written work for instructions, patterns and recipes have to be fully written by the seller with an image representing the real results. So for a knitting pattern or bread recipe, the image must show the finished product.

To enforce better detection of AI generated or misleading content, Etsy says it is “investing in tools to better identify authentic versus misleading images and detect and remove listings that use AI to create fraudulent inventory.”

The platform is also expanding categories to include misleading AI imagery when reporting listings, which will be used to “help us better understand how members perceive potential AI misuse.”

If you are currently using AI generated images for products on Etsy, you still have some time to update listings and won’t face immediate enforcement. The company says it will “provide tips to help you accurately represent your items and meet our photo expectations,” with guidance also provided to sellers with existing AI edited listings.

OpenAI has just released ChatGPT Images 2.6 across all subscription levels, including Free. It’s only a 0.1 upgrade to the previous Images 2.5, so it should come as no surprise that not that much has changed. In fact, there are only two new features, but they’re both worth your attention.

Firstly, you can now use ChatGPT to make animated GIF images, and second, you can now upload a persistent reference image, so you don’t need to keep uploading it when requesting a lot of different edits.

The first change is perhaps the most immediately interesting, but the second one could become more useful in the long run.

More cat GIFs, please

The Internet can never have enough cat GIFs, so naturally I decided to try the new feature on a photo of my cat, Chester. While Halloween has just been and gone, I thought I’d use that as inspiration for the sort of image I wanted to make of my cat. I used a fairly simple prompt: “Can you make a Halloween GIF of my cat to share with family?”

ChatGPT obliged without any objection, and transformed my cat into a feline wearing a Halloween-themed hat and cape and blinking slowly as a pumpkin flickered in the background. It’s especially fun for my family because there’s no way he’d ever let a human dress him up like this.

Once you’ve created your GIF it gives you a shareable link, so you don’t need to host it anywhere if you want to link people to it. Alternatively, you can download it or share it straight to X, LinkedIn and Reddit.

What ChatGPT produced was ok, but it was hardly going to set the Internet on fire, so I followed up with “That's cool, but it's not very active, can you make it more active please? Get creative.”

“Now we're talking!”, replied ChatGPT. “Your cat's gone full witch mode — casting a spell with a raised paw, conjuring a floating, glowing pumpkin, then giving a triumphant little meow before licking their lips. A proper bit of Halloween mischief!”

Indeed, the resulting GIF was much better, and Chester's movements looked realistic. I think this shows how important your prompt writing is — don’t be afraid to ask ChatGPT to get creative.

Time and time again

Of course, I might want to produce a GIF of this photo for a different occasion in the future so I asked ChatGPT: “Can you save the original photo as Chester so I can reference it again?”

After thinking for a second, it saved the photo as a reference image called Chester. It made a point that it was saving the original snap, not the Halloween versions, and said “In future chats, you can simply say something like: ‘Create a picture of @Chester dressed as a pirate.’ And I'll be able to use his original appearance without you needing to upload the photo again.”

I tested it with the prompt “Make a GIF of @Chester on the moon” and it provided one of Chester as an astronaut chasing a butterfly. How the butterfly was surviving on the moon, and how Chester was surviving when his ears poked through his space helmet, I don’t know, but I’ll go with it anyway.

Saving a reference image is a genuinely useful new feature. It might not be as flashy as the GIF creation, but I think it’s going to come in handy for the future. Overall I’m pretty happy with the Images 2.6 update. Nothing major has changed, but it’s nice to know I can now create a GIF from an image whenever I want, using ChatGPT’s natural language input method.

The best thing about Images 2.6 is how little effort it takes to get something fun out of it. I didn't need animation software, any technical knowledge or even a particularly clever prompt. All I needed was a picture of my cat and a willingness to let ChatGPT get creative. And now that Chester is saved as a reference image, I suspect this won't be his last starring role.