News

• Oracle thinks AI will change how we use software, but we'll still use software for years to come
• Agents will interact with structured software, humans will manage those agents
• Overall software revenue dropped 3% but cloud revenue rose 60%

Oracle co-CEO Mike Sicilia just declared on the company's first earnings call of fiscal 2027 that "AI is an accelerator, not a replacement for packaged applications," hitting back against the SaaSpocalypse argument that warns AI could replace traditional software as we know it today.

Central to his argument is that enterprise suites offer standardized, end-to-end processes and rules that AI can't replace. But that's not to say that AI won't have its role in software going forward.

Sicilia admitted that employee training and upskilling has long been a drawback for many software packages, and that's where companies like Oracle could actually lean on artificial intelligence to improve things.

With AI, employees no longer need to navigate so many complicated apps themselves, and AI agents can carry out tasks using the company's existing workflows and business rules. Humans will likely move over to supervisory roles, Oracle predicts.

"AI changes this dynamic," Sicilia said, noting that agentic AI could drastically reduce the time and cost involved with deploying enterprise applications.

"We are incredibly confident in the potential for this new paradigm to deliver much more rapid ROI for our customers," he added. The company is slated to add a new agentic AI accelerator to automate parts of SaaS implementation as soon as next month.

But the company isn't without its own challenges when it comes to AI and software. Despite a 10% rise in quarterly SaaS revenue, overall software revenue dropped 3%. Cloud revenue, which includes the company's infrastructure and AI capacity, grew a considerable 60%.

Looking ahead, Oracle's standpoint is that AI may change software interfaces, but it won't actually replace the software that lies beneath.

Meta’s new Muse AI platform would like the keys to your digital life to help run it for you. Muse is a personal AI agent that Meta built to complete tasks on your behalf, including sending emails, filling out forms, shopping, and pretty much any other activity with an online component.

The AI is available in the U.S. as an app, or through WhatsApp or the Muse.ai portal.

It's a familiar idea in some respects. Muse matches OpenAI and other AI developers in being able to open a browser inside its own cloud-based virtual computer and move between connected services. It returns when it has finished, encounters a problem, or needs permission to do something sensitive.

Meta describes the experience as having an agent that understands your goals and advances them independently. That can come off as sinister, even before it starts asking for permission to essentially be you online by having you sign in to all your online accounts.

Getting started is straightforward, although Muse is currently limited to U.S. adults. You can install the Muse app from your phone's app store, open Meta's Muse website or access it through WhatsApp. There is a free usage tier, while heavier users can pay $20 per month for Power or $100 for Maximum.

Once you open the app, the first thing the AI does is suggest you pick a nickname for it so you know when it is messaging you. I went with one of the suggested choices, and "Scout" proceeded to ask me what I'd like to do with it, offering a handful of popular options.

I asked Scout to do some shopping for me first, as the AI made it seem like a much smoother process than with other AI tools. I asked it to find me a pair of shorts. It asked my size and went off on its own for a couple of minutes, coming back with a couple of options and pointing to a sale on one particular set. I said okay, and it asked for my Amazon login to make the purchase on my behalf. For an everyday purchase, it was surprisingly pleasant to delegate.

That little interruption was reassuring and unsettling in almost equal measure. Meta says credentials entered this way are routed directly into secure credential storage and are not visible to the main Muse agent. Once stored, they can be inserted into the browser when needed without exposing the actual credentials to Muse's browser subagent. Muse does the legwork, while I remained the person responsible for deciding whether money actually left my account.

This is probably the easiest Muse task I would recommend trying yourself. Give it a product, let it browse, and take over whenever a login or other sensitive interaction appears. It demonstrates the agent's capabilities without immediately granting it access to years of personal correspondence.

Naturally, that was exactly what I did next.

I took the plunge and told Scout I wanted help with my email. I had to give it permission to go through my inbox and to write on my behalf, and it asked to use it to learn about me. With some trepidation, I okayed that, and it put together the kind of distorted image of my life you'd expect from someone basing their impression of you solely on your emails.

Scout also brought up an unopened email from the power company about needing to check my solar panels. It offered to write a reply if I could pick from the dates suggested for when they would visit. I did, and a minute later there was a draft pending my approval. It looked fine, and suddenly another little online errand was done.

It felt different from pasting an email into an AI chatbot. Muse's AI could retrieve the context itself rather than making me act as a courier between my inbox and the AI. Of course, it also felt a lot more personal. Meta has acknowledged how sensitive this access is and built specific defenses to prevent issues.

Muse's email connector filters out one-time tokens, password-reset links, and login links, while its Sentinel security layer controls what actions the agent is permitted to take outside its virtual machine. When an action requires my approval, the request comes through Muse's interface rather than simply relying on the agent to interpret a conversational yes.

I would keep that friction in place for email, particularly while getting used to Muse. Saving three minutes responding to a utility company is nice, but it is not worth discovering that your AI assistant has developed an unexpectedly adventurous correspondence style.

The more I engaged with Muse, the more the tandem senses of convenience and discomfort grew. Muse feels more frictionless than similar services with virtual browsers. And the combination of data Meta already has and the data it required permission to access made it feel more personal, too. Every improvement in its ability to help me came with another small moment where I had to decide how much access I was willing to grant.

Meta says conversations and VM data are not shared with its advertising systems, although browsing activity performed on your behalf can still influence advertising indirectly because websites may treat Muse's visits as your activity. Meta says sanitized agent interactions and tool activity can be used to train future models, but users can opt out with a switch in Muse's settings. Meta is also developing a Confidential VM mode intended to cryptographically prevent even Meta from accessing information inside the VM.

I was more impressed with Muse than I expected. But that only made me warier about it. Digital chores that consume more time than any one of them deserves are all too common at the moment, and Muse proved remarkably good at stepping into that gap. The catch is that the closer it gets to behaving like a genuinely useful personal assistant, the more personal information it needs to do the job.

If you're thinking of trying Muse then I would recommend starting gradually, beginning with public web tasks and keeping consequential actions behind approvals at first. The frustrating part is that Muse makes a very persuasive argument for personal AI agents. Meta has built something that makes handing an AI more of my digital life appealing, but not when it's attached to the current crop of tech giants offering those services.

• Anthropic and OpenAI are asking governments to work together to slow risky innovation
• US politicians are factoring in AI into their arguments as midterm elections approach
• Trump currently worries that taking the foot off the throttle could let China overtake

Tech leaders at the forefront of AI, including Anthropic CEO Dario Amodei and OpenAI CEO Sam Altman, are publicly calling for slow AI innovation in order to buy more time to assess AI risks.

Among the risks highlighted in Amodei's warning are that AI systems could become impossible for humans to control, cyberattacks could become worse and AI could even facilitate biological weaponry.

Subsequently, he's called for external evaluators to gain deeper access to their models and safety processes, but crucially, Amodei advocate for greater government involvement.

Anthropic's CEO is pushing for democratic countries to agree common AI safety standards and rules, and the eventual international coordination over the most dangerous AI capabilities, including with China.

And it's this international coordination that could prove key to slowing down risky innovation, because to date, US President Donald Trump has pushed back against warnings over worries that slowing down American companies would ultimately cause China to overtake the US.

"Whoever wins AI wins," Trump said (via CNBC).

"If Congress just races in and does some sort of emergency session to try to regulate AI, we will lose the race to China," House Speaker Mike Johnson, R-La., said.

And for the US in particular, now is a more important time than ever. Democratic nominee for Governor of Texas Gina Hinojosa recently described data centers, and therefore AI, as "the fight of this election season."

There's an increasingly narrow pre-election window for legislation as the technology increasingly shows divides not just between the two big parties, but also within them.

"We've reached a new chapter in AI capabilities, and that demands a new chapter for AI policy," OpenAI Chief Global Affairs Officer Chris Lehane wrote. And with the likes of OpenAI and Anthropic, right at the top of American AI, warning about AI's potential impacts, Senator Ruben Gallego, D-Ariz., likened the scenario to Dr. Frankenstein "telling us the monster is escaping."

With midterm elections just two months away, we're likely to see discussions around AI ramp up as politicians and influential leaders continue to get involved in guardrail discourse.

• Krafton announced PUBG: Dednet at Gamescom this year
• The '90s-inspired shooter features some bonkers abilities
• "We're kind of finding our own way here," explains game director Dave Curd

Players slithering along the ground like snakes, swords for hands, a tiny doll wielding a power drill driving in a toy car — some of these wild sights seen in the debut trailer for PUBG: Dednet seem completely at odds with the realistic and reserved approach the defining battle royale series is known for. When I bring this up to the game's creative director, Dave Curd, he tells me that is entirely the point.

"If you want to excite and delight people, you have to give them something fresh," he says me in an interview at Gamescom. "If you want a cool, stoic, mil-sim, take your pick; they're everywhere. But what everyone else can't do, and maybe they don't want to, is my take on this world, this lore, these characters, these abilities."

Curd explains that the tone of PUBG: Dednet is like "my version of the 90s filtered through a meatgrinder," and you can certainly see that from the debut trailer. It's zany, over-the-top, and drenched in color, with gunfights taking place in arcades, car chases through rural towns lit up by neon signs, and a grungy, punk vibe throughout. Safe to say, it stands out.

"The audience will forgive almost anything but being bored," suggests Curd. "So, I think this trailer will get a lot of love and hate.

"As long as they're feeling something passionately, I think we've done a good job," he continues. "But if people look past that and their eyes glaze over, then that would be worrying."

While Dednet is still effectively a battle royale, pitting multiple teams of three against each other in a contest to be the last ones standing, it continues to mix things up not just in the tone and character abilities, but also in how your game progresses over time with several roguelite elements.

It starts with the concept of runs, where you might nominate how many wins or placements you can achieve before you hit a certain number of losses. Win or lose, at the end of a match, you're presented with choices that can alter or upgrade your chosen character's abilities and play style.

Perhaps you'll lean into more of a support role to assist your teammates with heals or protection with a riot shield made out of a car door? Or maybe you'll take that aforementioned doll, who can ride on your back into battle or stealthily sit on your opponent's shoulder and be a nuisance.

"I'm pretty confident this isn't going to be in this year's Battlefield update," jokes Curd, when explaining how they came up with abilities like this for the multiplayer shooter. "I think our internal test is: does it make us laugh? Does it sound like an interesting challenge? And do we think about it the next day? We're kind of finding our own way here."

That neatly summarises how Dave Curd and the team are experimenting for PUBG: Dednet to create something unique and interesting in the space. It definitely caught my eye during this year's Gamescom, and if it got your attention too, you can pre-register for the closed beta now.

After a less-than-enthusiastic response to 2023's 360 Vis Nav, Dyson got the wheels rolling on its return to the robot vacuum market last year with its Spot+Scrub Ai. Now it seems momentum is building: this September the brand unveiled not one, but three new bots that would be joining the lineup.

There's the flagship R3 Nurovi Spot+Scrub UV — a successor to the Spot+Scrub Ai — alongside the R2 Nurovi Wash+Dry, and the R1 Nurovi Dry. I got a peek at all three at Dyson's IFA-adjacent launch event earlier in the month, and was intrigued to see some unique new features.

To get the inside scoop, I caught up with Nathan Lawson Mclean, a Dyson senior design manager who works across the brand's home products. Here are the five most surprising things I learned about the new Nurovi robot vacuum range...

The R2 Nurovi Wash+Dry has a rather unusual mopping setup. Instead of two circular discs, it uses a pair of rounded 'Reuleaux' triangles. These rotate 'eccentrically' — that is, the point of rotation isn't central. The pads move like a rotary engine, or a Spirograph, depending on your preferred analogy. The benefit is the shape can get much closer into corners.

What's interesting is that this design has been in Dyson's back pocket for a while now, just waiting to be added to a suitable product.

"These have always been in development," says Lawson Mclean. "I remember the first Reuleaux pads — those were initially developed back in 2019. We put it on the front of a brush bar in a cleaner just to try and get into corners. And what it ended up doing, you can imagine, [it was] a bit like riding a bicycle with square wheels. It caused too much ricocheting."

This is apparently not an unusual scenario at Dyson. "We're actually always developing these technologies in tandem," he continues. "It's just about what's the right timing; the platform that we're able to integrate it on. You'll see that we're starting to get to the point where we're packing [new products] full of our unique Dyson technologies."

All three of the new Nurovi robovacs have distinctive side sweepers. They feature a design that Lawson Mclean calls 'origami-inspired', but to me, looks more like a fish's fin. Apparently, the brand founder wasn't a fan originally.

"Side sweepers were always a bit of a faux pas with James Dyson," reveals Lawson Mclean. "He hated them. He thought they scattered dirt everywhere." For that reason, the brand's early models didn't have side sweepers at all — the 360 Vis Nav had a side duct that poked out when the bot sensed it was near the edge of a room.

"Side sweepers are fantastic. They are just a little chaotic. They also tend to wear out," continues Lawson Mclean. "More importantly, in James' eyes, they [end up getting] wrapped and covered in hair, which is a bit gross."

For the Nurovi, the Dyson engineers reimagined the traditional sweeper style to solve these issues, using "some of the advanced geometry" from the brand's conical cleaner heads found on the likes of the Dyson V16.

"It kind of has this really interesting over-molded pattern… that holds the nylon bristles at a very specific angle on the floor, helping us to avoid scattering this dust around, and corral things in a more controlled manner. It also stops hair wrapping around it so readily, too," says Lawson Mclean. "So it's a small, simple, effective, quality of life improvement."

The big, flashy upgrade found on the flagship R3 Nurovi Spot+Scrub UV is… well, UV. A UV light mounted onto the bot will highlight dried-on, invisible substances, ranging from sugary drinks to milk, tonic water and sparkling water. The R3 will then 'scrub' back and forth over the area to clear the mess before it gets sticky, or starts to smell.

"As the robot's running around your home on its mission, it will now expose these totally invisible stains that become breeding grounds for bacteria," explains Lawson Mclean. "You'd be surprised what fluoresces — a bit like a bowling alley in your own home.

It's increasingly rare to see a vacuum-only robot vac on the market these days, but Dyson has included one in its new lineup: the R1 Nurovi Dry. There were a multitude of reasons for this bot to exist, says Lawson Mclean. It's great for people who don't have have hard flooring in their home, or are looking for a more affordable option, or simply want to avoid — as he puts it — "a great big bloody dock like some robots have".

But it's also designed as an option for those who are wary of robo-mops. "There are many people who — I know for a fact, through user trials — don't trust robotic vacuums with their carpets. You know… we've ruined many of James' Persian rugs over the years," he recalls, presumably referring to brand founder James Dyson. "[It's] perhaps even a bit of an entry gateway to robotic vacuums, converting those people that don't really see the value of wet and dry robots just yet."

There are plenty of interesting design features, but it might turn out that one of the most significant upgrades is nothing to do with the robot itself at all. "I think when we talk about, 'Why are people not using this fantastic technology?', there's a lot of barriers. There are, just really pragmatically," says Lawson Mclean. "Even, I think, with people [in their 30s], they go, yeah, I don't really understand it, I don't really know what the setup is like."

Dyson's response has been to set up a 'white glove' onboarding service, which takes the form of an actual human who will, via video call, walk you through the setup process. That includes everything from unboxing and connecting the bot to mapping your home properly.

It's part of the new 'Dyson Concierge' service, and it's free with your purchase. (At time of writing, the service is being advertised on Dyson US, but not yet on the UK or Australian sites — I'm confirming if and when it'll be available in these territories.)

"When we started doing it, we just saw this huge uplift," recalls Lawson Mclean. "It wasn't a problem with the robots. It was just a problem with people having poor maps to begin with because perhaps they left a door closed, you know?"

Below you can see the Dyson robot vacuums currently available in your country.

Note: the R3 Spot+Scrub UV is not yet available to buy. In the US, it was meant to launch exclusively at CostCo in early September, but at time of writing (14 Sept) is hasn't arrived yet. It's due to arrive in the UK and Australia in 'early 2027'.

The Spot+Scrub Ai Robot Vacuum is Dyson's previous-gen robot vacuum — it'll be superseded by the R3 Nurovi Spot+Scrub UV when that model becomes available. It has a similar feature where it'll 'spot' stains and 'scrub' back and forth over them, but it's not powered by UV light.

Read our full review

• Good hardware
• Great at little-and-often cleaning
• Excellent self-cleaning
• Smart obstacle avoidance
• Auto vacuuming works well
• Bagless design

• Some navigation issues
• Unreliable self-empty
• Loud in every mode
• Large vacuum and dock
• Hair wrap on roller
• Transparent bins display dirt

Over the last decade, digital identity has primarily been linked with the internet security industry.

Businesses have been focusing heavily on fraud prevention, profile authentication and compliance measures, all designed to answer a relatively simple question - is this person who they claim to be?

But as AI transforms how consumers discover, engage and purchase from brands, digital identity has become something much more integral for businesses across the board.

It has become a critical layer of business infrastructure, one that sits at the intersection of trust, experience, personalization and growth.

Ultimately, the businesses that understand this shift, will be better positioned to compete in an increasingly automated digital world.

And those that don’t, are likely to find themselves struggling to build trust, protect margins and maintain direct relationships with their customer base.

When we take a glance back, the internet was never designed with robust identity systems in mind. For decades, businesses relied heavily on a combination of usernames, passwords, email addresses and manual verification processes to establish trust online.

Whilst imperfect, and at times vastly time consuming, these processes were efficient in an era of human driven interactions. However, in the world of AI, this is no longer the case.

Artificial intelligence is dramatically lowering the barriers to creating fake accounts, synthetic identities and automated purchasing behavior. At the same time, consumers are becoming more conscious of how their personal information is collected, stored and used.

This creates a difficult balancing act for businesses. They need greater confidence that customers are genuine, while customers expect less friction and stronger privacy protections.

The traditional response has often been to collect more information. Yet in many cases, more data creates more risk. Every additional piece of personal information collected becomes another asset that must be protected, governed and justified.

As cyber threats increase and regulatory scrutiny grows, businesses are beginning to recognize that the future of identity may not be about collecting more data, but about collecting less.

One of the most important shifts happening within digital identity is the move away from document-heavy verification models towards trusted verification networks. Rather than asking users to repeatedly upload sensitive documents or provide excessive personal information, businesses can increasingly verify eligibility or identity through trusted institutional sources.

This approach delivers benefits for both organizations and consumers. For businesses, it reduces the operational and security burden associated with storing personally identifiable information. For consumers, it creates a faster, less intrusive experience. The key principle is simple: verify only what is necessary.

If a retailer needs to confirm that someone is a student, for example, they don't necessarily need access to every piece of information contained within a university record. They simply need confidence that the individual meets the criteria required to access a student offer. This is where audience verification platforms are becoming increasingly valuable.

In practice, this tends to happen in one of two ways. Sometimes verification works through a secure database lookup, where an individual's eligibility is checked against records already held by a relevant institution, such as an enrolment system, without the retailer ever seeing the underlying record itself, only a confirmation of status.

In other cases, it works through a trusted single-sign-on style login, where the individual authenticates directly with their own institution and that institution simply confirms their status back to the retailer, again without exposing any personal data to either party.

What both approaches have in common is that they lean on relationships of trust that already exist, rather than asking the consumer to prove who they are all over again.

The result is a more efficient exchange of trust between brands and consumers. In many ways, this reflects a broader evolution in digital identity. The goal is no longer to know everything about a user. The goal is to know enough to establish trust and ultimately, these notions of trust, are quickly becoming an ever-growing business growth strategy.

Consumers are only becoming more demanding as they increasingly expect personalized experiences, relevant offers and seamless interactions. Yet, they also want transparency, control and confidence that their information is being handled responsibly. The brands that successfully balance these expectations gain more than compliance benefits. They build stronger customer relationships. Audience verification offers a useful example of this dynamic.

For a student, the value proposition is straightforward. They want access to relevant discounts and offers from brands they trust. The verification process itself is largely invisible, provided it is fast and frictionless. For the brand, however, the stakes are higher. Verification helps ensure promotional budgets reach the intended audience, protects against misuse and enables more effective customer acquisition.

Both sides benefit from a trusted exchange of value. This is why digital identity management should no longer be viewed purely through the lens of security teams. It has become a strategic capability that influences marketing effectiveness, customer acquisition, loyalty and brand trust.

The rise of AI introduces another important dimension to the identity conversation. As large language models (LLMs) and AI assistants increasingly shape how consumers discover products and services, businesses face a new challenge: maintaining trusted, direct relationships with their audiences.

In the future, many interactions may occur through AI-powered intermediaries rather than traditional websites or apps. Discovery, recommendation and even purchasing decisions could increasingly be influenced by intelligent systems acting on behalf of consumers. In that environment, trusted audience data and verified customer relationships become even more valuable.

Through such technology, businesses can confidently identify and understand their audiences and will be better equipped to personalize experiences, deliver relevant recommendations and maintain authenticity across increasingly fragmented digital ecosystems.

Those that rely solely on broad marketing reach may find themselves losing visibility as AI-driven discovery mechanisms become more influential. The organizations that thrive will be those that treat digital identity not as a compliance requirement but as a foundational capability underpinning trust, personalization and growth.

The next chapter of digital commerce will be defined by trust. Not trust built through lengthy forms, excessive data collection or intrusive verification processes. Trust built through intelligent, privacy-conscious systems that enable businesses to verify what matters while respecting consumer expectations.

Digital identity is no longer simply about proving who someone is. It is about enabling secure, trusted and meaningful relationships between businesses and the people they serve. As AI continues to reshape commerce, organizations that invest in modern verification frameworks and data-minimization integrations will be better positioned to navigate the changes ahead.

Ultimately, the future belongs to businesses that can answer a simple but increasingly important question: how do you establish trust without creating friction? And clearly… digital identity is a strong bet.

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This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

• Highly exposed occupations are seeing less wage growth due to AI productivity gains
• 5.8 million US workers are considered to be working in these roles
• The impacts could lead to reduced living standards

While sceptics have been warning of mass layoffs for years, a new report reveals that AI could actually be leading to weaker wage growth instead of human replacement.

US wage growth is already slowing compared with inflation, and a new study by Apollo Global Management has proposed that AI could be to blame.

According to the data, real wage growth in highly exposed occupations has been around 6.7 percentage points lower than less-exposed occupations since 2023, while employment itself is largely no different.

The white paper estimates that 5.8 million US workers, or around 3.7% of the US labor force, works in highly exposed jobs, and this is on the basis of earlier Anthropic work whereby at least half of the job's tasks can be replaced by Anthropic's AI tools.

"Companies are capturing AI productivity gains through wage compression rather than workforce reduction," Chief Economist Torsten Slok suggested. In other words, workers are getting more work done thanks to AI, so demand for additional labor has fallen and workers' bargaining powers have weakened.

Apollo estimates the effects of this could translate to around $28 billion in lost annual labor income, but this could be on the conservative side.

Crucially, Apollo's analysis shows that AI is more likely to be affecting the price of labor rather than the quantity of labor as human-AI hybrid workforces become more common.

Looking ahead, Apollo is warning that "profound implications for income inequality and living standards" could threaten workers globally.

While the research doesn't offer specific remedies, it does point toward government involvement and policymaking in order to slow down how quickly the transition happens and to offer greater support to impacted workers.

Welcome to our live coverage of Dreamforce 2026!

We're on the ground in San Francisco and ready to cover all the big news and events happening this week.

We'll see keynotes from CEO Marc Benioff, likely joined by a number of special guests, along with new product announcements and much more - so stay tuned to TechRadar Pro for all the latest updates.

Dreamforce 2026 is taking place Tuesday 15th - Thursday 17th September 2026.

Dreamforce 2026 kicks off at 10am PST on Tuesday 15 September, when CEO Marc Benioff starts things off with his usual opening keynote.

Dreamforce 2026 is taking place at the Moscone Conference Center (all of it, that's how big it is) and a variety of other downtown locations in San Francisco, California.

You can - but be quick! The last few tickets are selling fast.

You can indeed - the company is streaming much of the event on its Salesforce+ platform, where they will be a dedicated Dreamforce+ section showing 400+ sessions, virtual hands-on trainings, and more.

If you aren't already signed up, you can register for Salesforce+ for free today.

One of the best things about Dreamforce for us is that there's always so much going on - lots of news, product announcements and more.

From the Salesforce side, we're all set to hear about its latest and greatest AI announcements and updates. Last year was all about AI agents, and the company is now set to reveal more changes to Agentforce 360 which can help make workers more productive than ever.

As for Slack, it recently announced Slackforce, promising deeper connection with the Salesforce platforms, with AI agents now able to do more than ever before - so we'll doubtless hear more about that.

And alongside that, you've got Tableau, Mulesoft, and all of the company's other arms, all of which will doubtless have new things to shout about.

There's always room for something a little extra with Salesforce too - whether that's the traditional Ohana greeting, Matthew McConaghey-voiced intro videos, celebrity cameos and musical guests, it always keeps us on our toes.

Hello from San Francisco! We're excited for a week of Dreamforce, so stay tuned for all the latest updates as they happen.

The event kicks off tomorrow (Tuesday 15) so we'll try and get a sneak peek at the site (affectionally known as the Campgrounds) and anything else we spy.

Following the recent resignation of one of Anthropic’s leading researchers, multiple AI CEOs have suddenly begun calling for a slowdown in the development of AI technology to allow regulations and governance on the technology to catch up.

Speaking to the BBC after his resignation, Jacob Coxon warned, “I believe that if we don't slow down at the current rate of progress, there is a strong chance that we could all die in the immediate future.”

Following this, Anthropic head Dario Amodei, OpenAI CEO Sam Altman, and Grok founder Elon Musk have all apparently aligned in their calls for development to slow down. But there are some tricky waters to navigate - particularly around President Trump, China, and what guardrails should be put into place.

Over the weekend, Amodei posted an essay on “why the AI industry should slow down”. In it, he said, “I believe that if slowing down bought us even an extra year or two before models reach critical levels of capability, and we used that time to advance alignment, we could greatly reduce the risk that something goes seriously wrong.”

We Must Pace the Frontier: I’ve written a new essay on why the AI industry should slow down, with a three-part plan for doing so.Anthropic is unilaterally committing to the first of these steps. We’ll provide third-party evaluators with permanent, employee-level access to our systems, so that they can verify adherence to our safety measures, report on incidents, and assess models’ alignment during training.You can read the full post here: https://t.co/OGyPb7yaYtSeptember 12, 2026

Within the essay, Amodei outlined how AI could be ‘paced’ within the US, and globally, alongside a recommendation that AI companies put ‘evaluator’ teams into place to ensure AI models stay aligned to their tasks. Elon Musk replied to Amodei’s social media post, stating that the Anthropic head was “right”.

Sam Altman told Fortune the regulations and standards for AI further were “not at a place” to continue progressing AI development.

Got an opinion for us? Here’s how you can submit your perspective

But not everyone is convinced. US President Donald Trump has said that slowing down AI development is non-negotiable, as it would allow China to rapidly catch up to US AI capabilities. He told reporters that the US is “leading China on AI... and, frankly, I want to keep it that way,” adding that “whoever wins AI, wins”.

Trump also said that “very negative forces” were behind the growing opposition to AI, and said that fears were being stoked by “that won’t happen”.

China also isn’t convinced by what the AI giants are saying. Beijing labelled the calls for a slowdown as “fearmongering” from a “Cold War playbook.” In his essay, Amodei said that a “Chinese lead in AI would pose grave danger for the United States and the world.”

Chinese Foreign Ministry spokesperson Guo Jiakun said, “Fearmongering, confrontation and malicious competition will only disrupt the process of global AI governance and serve no one’s interests.”

• John Strand, Owner, Black Hills Information Security:

Up until this weekend, I was leaning toward believing that calls for an AI slowdown were purely performative. Then I woke up and read the news today and realized that it almost doesn’t matter.

We can talk about slowing down AI until we’re blue in the face, but when the United States is saying it doesn’t want to slow down because it’s competing with China, and China is aggressively pushing AI development as well, we’re talking about the two major economic and military powers on the planet having enormous incentives to keep moving.

This really feels like we’re entering an atomic arms race moment.

At that point, calls for a slowdown don’t have much bite.

I’d like to believe that Anthropic, OpenAI, xAI, and the other frontier model labs are working on better controls. But unless you can get the nation states and the major AI labs moving in the same direction, I don’t see how meaningful restrictions actually work.

This really feels like we’re entering an atomic arms race moment.

Stick with me here.

In 1950, physicist Leó Szilárd publicly discussed the idea of a cobalt bomb, essentially a doomsday weapon that could potentially produce enough radioactive fallout to make the Earth uninhabitable. He wasn’t proposing that somebody build the damn thing. He was trying to demonstrate where the technology could ultimately lead.

That’s the kind of moment I think we’re approaching with AI.

During the nuclear arms race, eventually the consequences became serious enough that competing nations had to at least start talking about limits, controls, and ways to keep competition from ending catastrophically.

I think we’re heading toward a similar problem with AI. Until China, the United States, and the major frontier model labs are all sitting at the same table, restrictions adopted by individual companies or individual countries are going to have a very difficult time holding.

Someone slowing down only works if they believe the other guy is going to slow down too.

• Ryan McCurdy, VP, Liquibase:

Slowing frontier development may give AI companies more time to understand and address the risks Amodei is describing. But enterprises can’t build their AI strategy around the assumption that AI is going to slow down.

AI is already moving from generating content and code to taking action across software delivery and production systems. The question for enterprises is how they adopt that capability without giving up control.

We can debate how quickly the frontier should move. Enterprises still have to prepare for where it’s going.

That means putting governance where AI decisions become real actions. Organizations need to define what an agent can access, what it can change, what it can decide on its own, and what policies have to be met before a change reaches a critical system. Those controls need to work whether the action comes from a developer, automation, or an AI agent.

We can debate how quickly the frontier should move. Enterprises still have to prepare for where it’s going.

• Tristan Watkins, director of services innovation, Advania UK:

Until recently, the major AI labs have been reluctant to slow their development efforts unilaterally. Over the last week this changed, with new commitments from OpenAI and Anthropic to prioritise AI alignment and interpretability research, to become more externally verifiable, and to establish safety precedents that governments could adapt.

Hopefully this underscores why we need governments to lead these efforts more proactively.

Given that these two organisations already allocate far more on AI Safety than their competitors, this bilateral leadership is extremely welcome.

It appears that other US labs may follow suit, but given the differences in AI Safety spending outside of Anthropic and OpenAI today, this will require investment more than lip service. Hopefully this underscores why we need governments to lead these efforts more proactively.

• Oleksandr Yaremchuk, CTO and Co-Founder, Manifold Security:

Pacing the frontier is the right conversation to be having, but it cannot become a substitute for securing the AI we have already put into the world. The uncomfortable reality is that we are debating how to quickly build more powerful agents while struggling to control the ones already operating with real credentials, real access and real-world consequences.

The incidents behind this debate make that clear. The Hugging Face attack was not just a failure of model alignment. Agents ran for days through an unmonitored system, with credentials that had not been rotated, and the victim spotted the activity before the people running the agents did. The problem wasn't simply what the model was capable of. It was that nobody was watching closely enough when it acted.

But if an agent can act autonomously on your systems today, you should already be able to answer three basic questions: what did it do, what did it have access to, and could you have stopped it?

A fitting analogy is with hazardous materials. We don't just wait for them to become more dangerous before deciding how they should be handled. We control their custody, monitor where they go, limit who can access them and establish clear accountability when something goes wrong. AI agents need the same thinking.

Independent evaluation of frontier models is important. But if an agent can act autonomously on your systems today, you should already be able to answer three basic questions: what did it do, what did it have access to, and could you have stopped it? If you don't know what it did or what it could access, you can't know whether you could have stopped it. Slowing down the next generation won't solve the problem you have right now.

• Heath Mullins, Chief Evangelist, ExtraHop:

AI leaders calling for a slowdown is confirming what the security industry has already been living through firsthand. This isn't a hypothetical risk, it's the threat landscape we're defending against right now.

While it is concerning to see the pace of innovation behind these AI models, the real challenge is that organizations haven't had the runway to build the infrastructure to defend against machine-speed threats.

This isn't a hypothetical risk, it's the threat landscape we're defending against right now.

Calls for caution surrounding the speed of AI development buys the security industry time to get proper visibility into AI activity.

Understanding AI activity within an organization is critical as we’ve seen models break out of sandboxes despite governance built into those models. Every organization will be relying on AI agents for machine-speed defense, and they need their own governance over how these models and agents operate inside their environment, starting with independent evidence of what they actually do, what they access, where they move data, what systems they talk to, and what actions they take.

You can't govern AI based on what a model is designed or permitted to do. Instead, you need real-time evidence of what models and agents are actually doing, because the gap between exponentially more capable AI and defenders' ability to see it is exactly where the next incident happens.

• Bri Frost, Director of Product Management, Cloud Range:

The answer is not necessarily to stop AI innovation but, we need to stop pretending innovation and security are advancing at the same speed.

When ChatGPT became publicly available in 2022, the models were dramatically less capable than they are today — and the guardrails were very easy to manipulate. The difference is that the models behind those guardrails are no longer the models of 2022. They can reason better, write and debug code. They can operate as agents. They can collaborate! And increasingly, they can interact and affect real infrastructure.

The faster we build the engine, the more important the brakes become.

Meanwhile, the model release cycle has gone from feeling like major capability jumps every year or two to seemingly every few weeks. That creates a dangerous asymmetry: AI capability is compounding faster than security.

Security and innovation have always been in conflict with each other. If every security problem had to be solved before we innovated, we’d never ship anything. But the opposite extreme is just as reckless: accelerating capability while just assuming we’ll bolt the security controls on afterward and they’ll be effective.

Every new release of AI capability expands the attack surface exponentially. Give a vulnerable model better reasoning, then tool access, then memory, then autonomy, then connectivity to production systems, and yesterday’s jailbreak isn’t just a clever prompt anymore — it’s an execution path. That’s the snowball effect we should be worried about.

Responsibility also must lie with the AI companies. If a SaaS company knowingly shipped software with weak security controls and customers were harmed, we wouldn’t excuse it because they were 'innovating quickly'.

So why are we treating AI differently?

You don’t get to race to build increasingly powerful, autonomous systems, profit from them, and then shrug when predictable security failures cause damage.

Sure the argument can be made that no product is perfectly secure - That’s not the standard. But if you ship the product, you inherit responsibility for securing it. And continuing to secure it better!

The conversation shouldn’t simply be “Should we slow AI down?”

It should be: Can our ability to test, validate, contain and secure AI keep pace with our ability to make it more powerful? Is there an equivocal kill switch?

Right now, the answer is no.

And if we’re going to keep accelerating — which I believe we will — then independent testing, adversarial evaluation, isolated testing environments, containment, continuous validation and security-by-design can’t remain optional steps we add after the innovation happens.

The faster we build the engine, the more important the brakes become.

• Denis Calderone, CTO, Suzu Labs:

Amodei's diagnosis is the most honest thing a frontier lab CEO has said publicly. The agent risk is real, recursive self-improvement is accelerating, and the competitive pressure is making both worse.

Where I get skeptical is the prescription. Democratic coordination among companies in a commercial race? Global pacing agreements with China? Amodei himself rates the hardest steps as unlikely. No lab has named a single model release they'll delay because of this essay.

No lab has named a single model release they'll delay because of this essay.

The one idea worth holding the industry to is embedded evaluators with independent publication rights. Give third-party safety researchers permanent access inside the labs, comparable to what bank examiners have inside banks, and let them publish what they find without the company controlling the narrative. That's a simple, concrete accountability mechanism. It doesn't require global coordination or antitrust waivers. Anthropic says they're committing to it unilaterally. Good. Now make the rest of the industry match.

• Donald McFarlane, Board Member, Xcape Inc:

AI does not develop an agenda; its operators do. When we give an autonomous system powerful access and ability to act at machine speed, they will continue to prove highly capable.

AI does not develop an agenda; its operators do.

Rules enacted in the name of safety must not become a moat against competition or progress. Enormous compliance costs may be manageable for the handful of companies already spending billions building frontier models, while becoming a substantial barrier to everyone behind them.

Government can help clarify accountability and duties of care, and facilitate strong information sharing and collective defense, which is an area where we sorely need more effective public-private partnerships.

But safeguards should focus on how these systems are used and deployed, rather than deciding who is allowed to build powerful AI in the first place.

The goal should be safer deployment without pulling up the drawbridge on innovation.

If you have an expert perspective you would like to share on an emerging story or particular topic, please get in contact here: benedict.collins@futurenet.com