Technology

Enterprises are deploying agentic AI at a pace that has outrun their ability to govern it.

Gartner predicts the average Fortune 500 enterprise will have over 150,000 agents in production by 2028, up from fewer than 15 in 2025.

Yet only 13% of organizations think they have the right governance in place to manage them.

The result is an execution gap: agents deployed in isolation, producing outputs nobody acts on, automating tasks rather than business processes and delivering unclear business value as a consequence.

Governance failures are an execution problem. Agents that can't interface safely with enterprise systems can't automate business processes in any meaningful way. They stay isolated helpers: producing artifacts, fielding customer queries, handling individual tasks.

The execution gap — the distance between what agentic AI promises and what it actually delivers inside the enterprise — remains largely unaddressed.

In 2026 and beyond, the guardrail problem poses an existential risk for enterprises. Adoption has outpaced controls, meaning that agentic AI is scaling faster than robust security measures can be implemented.

The speed of tech progress

The speed of tech progress can no longer stand as a rationalization for falling behind, and enterprises must address it before agentic becomes uncontrollable. Getting guardrails right will separate enterprises that realize full autonomy from those that stall out in pilots.

First, autonomy amplifies risk. Just because agentic AI can act on its own doesn't mean it requires zero human oversight. Autonomy does not equal autopilot. For agentic AI to generate real ROI, agents must do more than reason and respond. They must execute inside the business. That means interfacing directly with enterprise systems: ERP software, finance platforms, supply chain tools and the workflows that run the organization. Without that integration, agents remain one step removed from the work that actually matters.

Operational speed can compromise safety, compliance and reliability. Agents work at a blazing clip and on a more granular level than RPA. But speed becomes a moot point if agentic adoption leads to vulnerabilities such as sensitive data exposure.

Security and IT teams haven’t universally adapted to the new risk landscape. Among the risks agentic poses, "shadow AI" has emerged as a consequence of employees using unauthorized, unsanctioned AI tools or applications. When proper IT oversight or approval gets bypassed, it sets the stage for noncompliance and severe reputational damage. Departmental AI agents are proliferating without central oversight, creating security hazards and fragmented intelligence.

Governance lags far behind adoption. In this case, the guardrail gap might as well be a lack. Surveying more than 3,000 IT and business leaders worldwide, Deloitte found that just one in five enterprises reported mature governance to manage the risks of agentic AI. Autonomy without governance is a liability. This is particularly critical as we move toward the era of programmable finance, with Gartner predicting that 20% of monetary transactions will be programmable by 2030.

How to Lay the Rails Right

Agentic systems perform across a wide range of functions. When building guardrails, there must be no shortcuts. Guardrails bolted on after the fact can't account for the ways agents actually fail: corrupting data, contradicting decisions made elsewhere in the business and creating conflicts between teams acting on different outputs. Controls need to be built into how agents execute, instead of layered on top.

1. Practice measured orchestration

When enterprises accelerate AI adoption by stitching isolated tools across departments, security gaps grow harder to manage — because there’s no unified layer to anchor guardrails to. Start by scoping the broader business objective your agentic system needs to serve, not just the task.

Once you've determined what your agentic system will handle and which structured outputs will return to the workflow, built-in validation and guardrails become platform-level capabilities rather than afterthoughts bolted onto each individual agent.

2. Build governance capabilities

Without clear boundaries, agentic AI collapses. First, determine which decisions it can make independently versus those that need human approval. Real-time monitoring systems that flag anomalies and audit trails that capture the full chain of agent actions will enable accountability and continuous improvement.

3. Scale deliberately

No matter how sexy the pilot, agentic AI needs time to mature within the enterprise; you want to spot potential issues before they appear, not after. Start with lower-risk use cases and easy, single-task wins, as with fraud detection and remediation or vendor reconciliation. Avoid intricate processes with hundreds or thousands of inputs, such as the financial close of a business.

4. Guardrail gap = skills gap

While agentic AI excels at reasoning, the execution of reliable, repeatable business processes still demands deterministic systems — and human oversight to bridge the two.

To ensure smooth agentic operation in an enterprise, train your employees to move from triage, menial activities and repeated manual steps to judgment, governance and strategic decision-making roles. They absolutely require those skills. Scrum and Tiger teams can solve early problems and address early lessons, then pinpoint how agentic addresses your needs.

Putting it All Together: A Guiding Guardrail Principle

Yes, agentic AI scales productivity, but without strong guardrails, agentic AI scales risk even faster. Strategic observability and deterministic guardrails are required to ensure that non-deterministic AI stays compliant with regulatory and business standards, with reliable audit trails as well as rules for exactly when to escalate a decision or task to a human for complex exceptions or strategic oversight.

In the rush to embrace agentic, remember that the attendant tasks don’t represent a series of punch-list items. Veterans of software adoption and replacement projects know that it’s a holistic process where human actions and digital components fall into place with methodical synchrony.

Agentic AI, while it has altered the face of enterprise technology forever, rewards the same discipline every transformative technology before it has: lay the foundations carefully, and you won’t be fighting fires when it scales.

We list the best IT automation software.

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• Around half of UK retail workers don't feel confident with GDPR tasks
• One in five haven't received formal compliance training
• Many workers can't remember what their training involved

Nearly half (44%) of UK retail workers say they're not confident in handling sensitive customer data or don't know how to process it correctly, raising potential compliance issues, per Virtual College research.

According to the data, nearly one-fifth (19%) of retail workers have never received formal compliance training despite handling customer banking details, contact information and other personal data daily.

And those who have been trained say it's been sporadic without regular updates – only one in three (30%) have been trained within the last six months, with a further 11% trained 7-11 months ago.

Retail workers aren't up to speed on GDPR

The report raises questions around the frequency and effectiveness of such training, because nearly one in five (17%) couldn't remember what their last compliance training covered. Only 13% say it covered safeguarding.

And while training is still being delivered to many, only around half (49%) say they'd feel 'somewhat confident' in responding correctly to a compliance situation.

This data also comes at a similar time to Government data revealing that more than two in five (43%) businesses have experienced some kind of cyber breach or attack in the past 12 months, highlighting the vulnerability of personal and sensitive information.

"Ongoing, bite-sized training keeps compliance knowledge fresh and helps employees stay confident in fast-changing regulatory environments," Business and Strategy Director Jamie Ashforth wrote, urging employers to conduct regular audits to identify gaps.

Per the report, UK companies paid £490 million in compliance failure fines in 2025, but broader impacts of regulatory investigations and knock-on reputational damage are also highly plausible outcomes.

Ashforth suggests businesses should prioritize high-risk compliance areas first, including data protection and safeguarding. "Clear processes and regular reinforcement give employees the confidence to raise concerns and act appropriately when issues arise."

I'm feeling fresh and just a little bit smug today, because I spent last night sound asleep under a cool blanket of air provided by the Dimplex FlexBlade Tower Fan, which is now £123 (was £199.99) at Amazon. You can use it vertically to blow a column of air in your direction while you're working or cooking, but it really comes into its own turned horizontally, when it's just the right height to blow a breeze right across your duvet and help you beat the heat.

• See all Prime Day deals at Amazon

The FlexBlade looks a lot like the Shark TurboBlade, which is perhaps a bit cheeky of Dimplex, but it's half the price for Amazon Prime Day and very effective. If you struggle to get a proper night's rest in hot weather, I recommend giving it a try — and it's not too heavy to carry between rooms during the day. Oh, and it oscillates horizontally as well.

This Dimplex fan is a dead ringer for the Shark TurboBlade (but much cheaper) and creates a horizontal or vertical sheet of air to keep you comfortable. It works best at night, blowing a cool blanket over your bed.View Deal

It's not the quietest fan I've ever used (that would be the MeacoFan Sefte Pro Air Circulator, which is almost silent), but the Dimplex FlexBlade has a night mode that noticeably reduces noise while still producing a very effective sheet of air to beat the heat.

Looking for a different way to keep cool? Check out all Amazon's Prime Day deals on fans here, or scroll down for my pick of the best.

More cooling fan deals

This pocket-sized fan will keep you cool and comfortable anywhere this week, and this bundle with a carry case and cross-body strap is now cheaper than buying the fan by itself thanks to this great Prime Day deal.View Deal

At under £30, this little desk fan is a great buy on Prime Day — and I'd know because it's currently sitting on my desk at home. It folds flat, is rechargeable so you can take it anywhere, and packs a surprisingly powerful punch. View Deal

There's a 25% discount on this simple, quiet tower fan for Prime Day. Like the FlexBlade, it has a timer so you can set it to turn off automatically once you're asleep, and a remote control so you can operate it from bed.View Deal

Govee is best known for its smart lights, but it also makes some great cooling fans. Our reviewer gave the shorter 36-inch version of this fan four and a half stars out of five thanks to its smart looks, performance, and versatility.View Deal

More Prime Day deals in the UK

• Amazon Prime: sign up for a 30-day free trial
• Amazon Devices: Fire TV, Ring & Blink from £24.99
• Amazon Haul: up to 30% off
• Apple: AirPods Pro 3 for a record-low price
• Appliances: up to 45% off Ninja, Tefal & Sage
• Beauty: up to 60% off Philips & Oral-B
• Essentials: household goods from under £10
• Fashion: up to 50% off
• Father's Day: up to 50% off gifts & drinks
• Headphones: up to 50% off
• Laptops: from £149.99
• Tablets: Samsung & Lenovo from £125
• Toys: up to 25% off Lego and Tonies
• TVs: from £129.99
• Vacuums: up to 40% off Eufy & Roborock
• Wearables: Garmin & Huawei from £36.99

Cloudzy isn’t your run-of-the-mill web hosting provider. It specializes in cloud infrastructure and fairly bare-bones Virtual Private Server (VPS) plans. That means you get reasonably priced access to excellent hardware and resources, provided you have the technical skills to handle them.

The good news is that many things can be pre-configured, and you have a broad choice of options in everything from the choice of operating system (OS) to web apps. We’re not just talking about WordPress, but also advanced options like Forex platforms.

You also have an excellent range of server location options, though perhaps not as comprehensive as Google Cloud or AWS, which are on a different pricing tier altogether. What we didn’t like, though, was the discounts Cloudzy offers based on your location choice, which we felt was a bit unfair to customers who might require specific regions for efficiency and localization.

Be warned, though - Cloudzy is not really aimed at casual users building their first website. While you can technically host anything here, the core audience appears to be users who need virtual servers for web apps, trading bots, VPN setups, and the like.

Plans and pricing

(Image credit: Cloudzy)

Cloudzy primarily focuses on VPS hosting rather than traditional shared hosting packages. At the bottom of its offerings are Cloud VPS plans similar to those offered by hosts like DigitalOcean, Linode, and VULTR.

(Image credit: Cloudzy)

At Cloudzy, though, you get a broader range of pre-deployment options. For example, you can decide to go with a pure OS-only deployment, or get your server started with a full LAMP-stack supported web app, or almost anything else.

Cloud VPS plans start at 1 vCPU with 512MB RAM, 20GB of NVMe storage, and 1TB bandwidth/mo. This scales up to a whopping 16 vCPU, 64GB RAM, 1.5TB NVMe storage, and 16TB of bandwidth for $199.97/mo.

While there is no additional charge for pre-deployment options, your final price may be adjusted depending on server location. It’s likely that Cloudzy does this to help balance their location loads, but it’s unfortunate for customers who may be penalized because of their requirements for where their servers are located.

Aside from Cloud VPS, Cloudzy also offers more specialized solutions like high-performance GPUs, GPU-optimized servers, AI servers, and dedicated servers. Again, all of these options are fairly technical, especially their dedicated bare-metal servers.

Ease of use

(Image credit: Cloudzy)

The Cloudzy dashboard is a straightforward way to manage your servers. However, it’s more practical than informational. You can use it to deploy, rebuild, or configure instances. Server monitoring isn’t in the cards, though, and you’ll have to deploy any of those solutions on your individual servers if you need them.

When we initially discussed the pre-deployment option, it might have been misconstrued as saying Cloudzy is easy to use. That isn’t really the case. Once the deployment is made, you’ll still have to manage the stack on your own. For example, you have to keep your server OS and applications up to date and security-hardened, not just manage your web app.

This is typically done via SSH into the server (root access is provided). If you know what you’re doing, it’s easy-peasy. If not, you’re probably going to face an oncoming disaster.

Again, we don’t recommend Cloudzy as a first hosting provider for someone completely unfamiliar with VPS environments. If you’re looking for a first entry to the Cloud, try something with more management features like Cloudways. That, however, will cost a bit more, so be mentally prepared.

Speed and reliability

Cloud providers are always thought to be all-powerful, but keep in mind that much of it still depends on the hardware and configuration. For example, on the surface, Cloudzy offers some pretty good standard cloud VPS plans. However, the processing power on these compared to their high-performance options is very different. For example, the 2GB standard cloud VPS plan we tested includes a 2.25GHz AMD processor, while a comparable high-performance plan includes 4.2GHz processors.

The biggest surprise, though, is that Cloudzy is using AMD Ryzen 9 processors for their Cloud VPS plans. Servers typically run AMD EPYC chips, which are the dedicated server versions commonly used in web hosting. The Ryzen family is intended more for regular consumers or enthusiasts.

It’s possible that this led to the slightly disappointing test results below.

WordPress benchmark test

The standard WordPress benchmark test was run on our prebuilt WordPress site to maintain consistency. Results at Cloudzy were a letdown, with initial results showing worse performance than some budget shared hosting alternatives we’ve seen.

Siege test

On our load test, Cloudzy performed like a champ, acing results with increasing loads of 5, 9, and 15 concurrent users. It ran rock-solid and completed all transactions quickly. If we were to use this as a comparative factor against the easier benchmark test, Siege results should take priority as a more realistic indicator.

Customer support

Cloudzy offers customer support via tickets (for existing customers), a knowledge base, and, more interestingly, WhatsApp. Don’t be fooled by the WhatsApp chat support option, though. You don’t get an instant response.

Their knowledge base is also quite Spartan, with only 73 guides available. These articles are very straightforward and relatively technical, so you may have to know what you’re doing just to follow the language. It can be a challenge, but those are the preconditions for this type of hosting anyway.

Overall, the vibe you get from customer support is very corporate. We felt a notable disappointment here, especially coming off our recent Freehostia review. That was a free hosting plan, yet it came with near-instant customer support that was both polite and effective.

The competition

DigitalOcean is one of the most popular cloud infrastructure providers for developers and startups, and is similar in product offerings to Cloudzy. Compared to Cloudzy, DigitalOcean has a more mature ecosystem and a more professional customer dashboard. However, Cloudzy may appeal more to users looking for simpler pricing and lower-cost VPS deployments.

Linode has built a strong reputation among developers for reliability and straightforward cloud hosting services. Compared to Cloudzy, Linode offers more enterprise-level polish and documentation, though pricing can sometimes be higher for equivalent resources.

For those who want a fully hands-off approach, Hostinger is a beginner-friendly choice. Although primarily cheap for shared hosting, you can also get VPS hosting and other plans. Hosting is priced aggressively and offers strong localization expertise for ideal customer support.

Final verdict

To be honest, Cloudzy is a fairly run-of-the-mill cloud hosting provider. We don’t feel that it excels in any particular area, even though the host itself seems professional enough. What really turned us off was their slow customer support, even for sales queries.

Performance-wise, Cloudzy runs fine, even with Ryzen chips instead of enterprise-grade EPYC chips. It’s just that the choice left us feeling disappointed that they would cut corners in that way. We recommend considering one of the many cloud alternatives if you’re in the market for a budget, hands-on hosting plan.

Samsung’s PCIe Gen 5 flagship SSD has dropped to its best price since launch, with the Samsung 9100 Pro 2TB SSD down to $350 (was $680) at Amazon right now. For UK readers, the 9100 Pro 2TB drops to £304 (was £529) for Prime Day, too.

This is Samsung’s fastest consumer drive ever, and in our review, we said "it definitely delivers fantastic performance with the fastest write speeds I've ever tested." If you’re building or upgrading a system and want the best storage performance available right now without compromise, this is the drive.

The 9100 Pro capably offers best-in-class sequential read and write performance and impressive random read/write speeds. For anyone upgrading from a PCIe Gen 4 drive, the difference in large-file transfers and sustained read workloads is immediately apparent. But what really catches my eye is that it's 49% off for Prime Day right now.

Today's top Samsung 9100 Pro SSD deal

For ultra-fast speeds, the 9100 Pro from Samsung is a beast of an SSD that delivered best-in-class performance across the board during our tests. If you're a professional, we found that "there's none better than the 9100 Pro."

In the UK: now £304 (was £529)View Deal

More interestingly for business and creative users, we clocked that while we didn't quite hit the promised highs of 14,700MB/s sequential read speeds, it still offered blazing-fast speeds, particularly shining in its sequential write performance, making it a fantastic pick for professionals.

The 9100 Pro is Samsung’s first fully PCIe Gen 5 x4 consumer drive — a meaningful distinction from the 990 EVO, which used a hybrid Gen 4 x4 / Gen 5 x2 interface as a halfway measure. Full Gen 5 x4 doubles the available interface bandwidth over Gen 4, and at 14,700MB/s sequential reads, the 9100 Pro delivers on that headroom. For context, a high-end Gen 4 drive like the Samsung 990 Pro tops out at around 7,450MB/s reads — the 9100 Pro is almost exactly twice as fast at the interface level.

Future / John LoefflerFuture / John LoefflerFuture / John Loeffler

The 2TB capacity is the sweet spot in the line-up. It’s single-sided — meaning all components sit on one face of the PCB — which makes it compatible with a wider range of laptops and slim-profile systems that can’t accommodate double-sided drives. The 2TB model is also rated slightly faster than the 1TB model on sequential reads (14,700 MB/s vs 13,300 MB/s), and its 1,200 TBW endurance rating is generous for a consumer drive at this capacity.

The LPDDR4X DRAM cache (2GB at 2TB) is a meaningful inclusion that differentiates it from DRAM-less budget Gen 5 drives. DRAM cache significantly improves random I/O consistency — particularly relevant for workstation use cases involving large databases, virtual machines, or AI inference workloads where latency matters as much as peak throughput.

• Shop all Amazon Prime Day deals

• The UK is experiencing another heatwave, with temperatures expected to exceed 35°C
• Nintendo Switch users should be reminded of the risks of overheating their console
• Nintendo has previously said that the consoles can "malfunction" in temperatures above 35°C

As we enter another UK heatwave, Nintendo Switch users should be reminded of the risks of overheating their console.

Recent weather reports have forecast that temperatures in certain parts of the UK will exceed 35°C this week, reaching as high as 40°C.

An amber warning has been issued, in addition to a rare red extreme heat warning, for some regions and those spending time outside should be prepared for the sweltering heat. Even those indoors should take similar precautions to stay cool, especially if they have any running hardware that can contribute to the heat.

Whether it be a PC, PS5 console, or Xbox Series X, these devices do run the risk of overheating, particularly during a heatwave. The same goes for Switch and Switch 2 consoles, which Nintendo has previously cautioned can "malfunction" if temperatures are above 35°C.

"Using a Nintendo Switch or Nintendo Switch 2 in places with high temperatures may cause the console's temperature to rise," the company said in a post shared last year.

"This could potentially lead to malfunctions, so please use it in locations between 5–35°C. Lately, there have been consecutive days exceeding 35°C. Please take care when using it outdoors."

For this reason, we'd highly recommend avoiding using your Switch or Switch 2 when temperatures are at their highest.

In other news, Nintendo has officially announced The Legend of Zelda: Ocarina of Time remake, and it launches this year on Switch 2.

If you're hoping to pick the console up before the game drops, the Switch 2 just got an absurd Amazon Prime discount thanks to Amazon Prime Day.

The AI PC market has become incredibly confusing. Microsoft, Intel, AMD, Qualcomm, Apple and laptop makers are all selling 'AI PCs', but do you really know what you’re actually getting? And do you really need an 'AI PC' anyway?

Meanwhile, Microsoft appears to be expanding some Copilot+ features beyond dedicated neural processing units (NPUs), potentially blurring the distinction further.

What you need, then, is some way to tell whether you're buying a genuinely useful AI machine or just an expensive sticker. You want to be sure that whatever you buy, it will still be relevant in two years.

In short, there are five key things to check in order to make sure that your PC really is an 'AI PC'. They are:

• Minimum RAM
• NPU vs GPU
• Copilot+ requirements
• Does it have AI features you’ll actually use?
• Is there enough space on the SSD?

Let’s look at them in turn:

1. At least 16GB of RAM (preferably 32GB)

AI features are memory-hungry. If you look at the deals on Prime Day laptops this week you’ll see that a lot of them are discounted because they're older models with 8GB RAM. That's already becoming restrictive for modern Windows use, and it's especially limiting if you want to run local AI tools.

The main exception to the rule is the MacBook Neo from Apple, which only comes with 8GB of RAM, but thanks to a 16-core neural engine can run the new Siri AI. It’s a great laptop for experimenting with AI, but advanced users will require more RAM.

Rule of thumb: Skip any 'AI PC' with 8GB RAM, the MacBook Neo being the only exception.

2. A processor that actually supports Copilot+ features

Many laptops are being marketed as AI PCs simply because they contain an NPU. That doesn't necessarily mean they support the full set of Microsoft Copilot+ experiences such as Recall, Click to Do, Cocreator, Live Captions, and so on.

The NPU is much more efficient at AI tasks than a CPU or a GPU, so you’re still going to need one if you’re looking for a machine that’s equipped for AI.

For an AI laptop, running Windows I’d look for: Qualcomm Snapdragon X series, recent AMD Ryzen AI chips, or recent Intel Core Ultra chips that explicitly support Copilot+.

When it comes to Macs, avoid ones with Intel chips completely. You need an Apple silicon processor, which are designated M processors, or in the case of the MacBook Neo, the A18 Pro. The M1 is pretty old now, since it came out in November 2020, but it will still support Apple Intelligence features. To make better use of the newest Siri AI features, due in macOS 27 Golden Gate, this fall, get the latest processor you can afford. The current version is the M processor is the super-fast M5.

3. Battery life that benefits from AI hardware

One of the genuine advantages of NPUs is efficiency. If a laptop only manages five or six hours of real-world battery life, then the AI hardware isn't delivering one of its biggest promised benefits.

Rule of thumb: Expect all-day battery life if you're paying a premium for an AI laptop. If the laptop says less in its specs, then avoid.

4. AI features you'll actually use

Remember, you don’t need an 'AI PC' to just run ChatGPT or Gemini in a browser, or using their native apps. Since subscription services like ChatGPT and Gemini do all their processing in the cloud, the capabilities of your PC aren’t really the issue here.

However, to make use of AI features that are part of the operating system, like Copilot in Windows and Siri AI in macOS, you will need a machine that’s classified as being AI capable. Also, some apps, like Photoshop, make use of the NPU in your PC when generating AI images, so they'll perform better with the correct hardware.

The question to ask yourself is, are you really going to be using these things?

Ask yourself whether you'll realistically use features like Live translation, AI image generation, AI-powered search and AI photo editing? Many people are paying extra for features they'll never touch.

Rule of thumb: Buy the laptop first, the AI second.

5. A fast SSD with enough space for local AI

Some newer AI tools run locally rather than entirely in the cloud. If you’re going to be using these sorts of tools (and the application is usually in programming) then you'll need to consider the speed and size of your SSD.

So while a bargain laptop with 256GB storage and 16GB RAM might look attractive, you’ll find you hit the storage limits once Windows, some games, apps and photos have been installed. And if you’re even thinking of installing a local AI model, it won’t do at all.

Rule of thumb: Aim for at least 512GB SSD, ideally 1TB.

Today's best Prime Day AI PC deals (US)

This Microsoft Surface Laptop (2024) comes with Windows 11 and is a genuine Copilot+ PC. It has 13.8-inch Touchscreen Display, Snapdragon X Elite (12 core), 16GB RAM, 256GB SSD Storage. This Prime Day Deal features a massive 38% off.View Deal

This ASUS Vivobook S16 Laptop, Copilot+ PC has an AMD Ryzen AI 7 350 with XDNA NPU, 16GB Memory and 1TB SSD. The Amazon Prime Day deal knocks a healthy 20% off its price.View Deal

This Acer Aspire 16 AI Copilot+ PC has a large 16-inch WUXGA 120Hz 100% sRGB display, and comes with a Snapdragon X processor and 16GB LPDDR5X RAM with a 512GB SSD. This Amazon Prime Day deal knocks 21% off its price.View Deal

Today's best Prime Day AI PC deals (UK)

This Microsoft Surface Laptop is a Copilot+ PC with a 15-inch Touchscreen, Snapdragon® X Elite processor and a whopping 32GB Memory and a 1TB SSD. Thanks to Amazon Prime Day there's £300 off, making it a great deal.View Deal

The HP OmniBook 5 Next Gen AI 16-inch Laptop is a CoPilot+ PC with a Snapdragon X1-26-100 processor, 16GB RAM and a 512GB SSD. You'll find it at a very tempting £449.99 this Amazon Prime Day. View Deal

This ASUS Zenbook A14 OLED UX3407QA Copilot+ PC laptop has a 14-inch WUXGA (1920x1200) OLED screen, a Qualcomm Snapdragon X1-26-100 processor, a 16GB RAM and a 1TB PCIe SSD. You get 31% off thanks to Amazon Prime Day.View Deal

More Prime Day deals in the US

• Amazon Devices: Fire Sticks & Echo from $18
• Amazon Haul: viral gadgets, tech & appliances from $1.99
• Apple: MacBooks, AirPods & AirTags from $29
• Beauty: 50% off toothbrushes & hair tools
• Cheap TVs: smart TVs from $69.99
• Garden: tools, mowers, planters from $24.99
• Headphones: 50% off Beats, Bose & Samsung
• Laptops: Apple, HP & Dell from $199
• Mattresses: Sealy, Serta & more from $186
• Patio: outdoor furniture, rugs & decor from $19.99
• Sports: 50% off fitness gear, treadmills & clothing
• Vacuums: Dyson, Shark & Bissell from $34

More Prime Day deals in the UK

• Amazon Prime: sign up for a 30-day free trial
• Amazon Devices: Fire TV, Ring & Blink from £24.99
• Amazon Haul: up to 30% off
• Apple: AirPods Pro 3 for a record-low price
• Appliances: up to 45% off Ninja, Tefal & Sage
• Beauty: up to 60% off Philips & Oral-B
• Essentials: household goods from under £10
• Fashion: up to 50% off
• Father's Day: up to 50% off gifts & drinks
• Headphones: up to 50% off
• Laptops: from £149.99
• Tablets: Samsung & Lenovo from £125
• Toys: up to 25% off Lego and Tonies
• TVs: from £129.99
• Vacuums: up to 40% off Eufy & Roborock
• Wearables: Garmin & Huawei from £36.99

If you've been looking to buy a smart ring, this is a great bargain.

If, like me, you're having to use public transport this week, a personal fan will make your life a lot more comfortable — and I've found just the Amazon Prime Day deal for you. Right now, the Shark ChillPill Travel Bundle is just £119.99 (was £149.99) at Amazon. That includes not just the fan and its three cooling attachments, but a travel case to keep everything safe, and a cross-body strap so you can wear it and stay comfortable hands-free.

• See all Prime Day deals at Amazon

After testing this little fan myself, I loved it so much that I bought my own, and I've not regretted it for a second. My personal favourite is the misting attachment, which sprays you with a fine cloud of vapour when you fill it from your water bottle, but the regular fan and icy cooling plate are a joy as well. Whether you're on a bus or a train, your fellow commuters will be green (and sweaty) with envy.

This pocket-sized fan will keep you cool and comfortable anywhere this week, and this bundle with a carry case and cross-body strap is now cheaper than buying the fan by itself thanks to this great Prime Day deal.View Deal

Considering how high the temperatures are going to soar later this week, I wouldn't be at all surprised if this deal sells out, so I'd strongly advise grabbing it now if you're tempted. This deal only applies to the silver version, but personally I think that's one of the nicest colours anyway.

If you happen to be viewing this article from the US (hello!) then there's good news for you as well if you're feeling the heat — you can grab the Shark ChillPill for $99.99 (was $129.99) at Amazon for Prime Day. This deal doesn't include the carry case and strap, but it's excellent nonetheless, knocking $30 off the list price.

Shark's three-in-one fan has received its first ever price cut for Prime Day, and it's a big one, knocking $30 off. It earned a solid 4.5 stars in our review, and will keep you cool and comfortable at home, in the office, or on the move.View Deal

I'm not expecting the ChillPill's main rival, the Dyson HushJet Mini Cool Fan, to receive any Prime Day discounts, so this is likely to be the best offer we see on a personal cooling system this week.

More Prime Day deals in the US

• Amazon Devices: Fire Sticks & Echo from $18
• Amazon Haul: viral gadgets, tech & appliances from $1.99
• Apple: MacBooks, AirPods & AirTags from $29
• Beauty: 50% off toothbrushes & hair tools
• Cheap TVs: smart TVs from $69.99
• Garden: tools, mowers, planters from $24.99
• Headphones: 50% off Beats, Bose & Samsung
• Laptops: Apple, HP & Dell from $199
• Mattresses: Sealy, Serta & more from $186
• Patio: outdoor furniture, rugs & decor from $19.99
• Sports: 50% off fitness gear, treadmills & clothing
• Vacuums: Dyson, Shark & Bissell from $34

More Prime Day deals in the UK

• Amazon Prime: sign up for a 30-day free trial
• Amazon Devices: Fire TV, Ring & Blink from £24.99
• Amazon Haul: up to 30% off
• Apple: AirPods Pro 3 for a record-low price
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• Report finds public support for workplace robots is growing – especially for physical or dangerous tasks
• Willingness to accept a robot inside the home grows with real-life exposure
• Familiarity and clear governance are essential to overcoming public fear

Technological capabilities may no longer been the limiting factor when it comes to how and where robots can be deployed, with new Hexagon research revealing public support isn’t always there.

The company found much of the public is becoming more accepting of robots in the workplace, but only where they’re used for practical, physical or dangerous jobs.

However roles which require empathy, judgement or human interaction are still where support remains low.

Robots are most accepted in practical labor use cases

For example, more than half (56%) of the 1,000+ UK adults surveyed said they’d accept robots in lifting and transporting heavy items. Carrying and delivering any items (38%) and monitoring hazards and dangerous environments (34%) also received reasonable support.

With airports, some supermarkets and other public places now employing robots, 31% would even support their use in cleaning shared spaces.

Though the research fails to detail perception by age bracket, the company surveyed an equal number of UK children to reveal that heavy lifting, carrying and delivering is even more accepted among under 18s.

However, while repetitive physical work is generally well-accepted, 82% of UK adults want humans to care for sick, elderly and young people.

Only 5% say they’d choose a robot caregiver, making this the lowest support for any of the tasks included in the report. Even children seem reluctant to have non-human personal interactions, with 79% preferring human caregivers and 8% willing to choose a robot instead.

But Hexagon Technology Ethicist Dr Blay Whitby argues a simple reframing could skew these figures: “Ask people if they want to be cared for by a robot, and most say no… Ask if technology should help them remain independent in their own home for longer, and most say yes.”

Associate Professor in Moral Psychology Dr Jim Everett sees robots more as “assistive devices” in care homes and classrooms, rather than human replacements.

Exposure can drastically shift public perception

For now, the public still sees robots as industrial automation roles. More than half agree their natural homes are factories (53%) and warehouses (53%) – fewer consider them at home in hospitals and clinics (34%) or classrooms (30%).

Fear of the unknown could be another blocker, with only 28% of UK adults believing that having a robot colleague would be exciting – nearly half (46%) say it would be frightening. Humanoid forms are clearly unsettling, with twice as many preferring machine-like robots (27%) compared with human-like robots (14%).

Sci-fi fears about robots taking over could also be influencing public perception. Nearly all UK adults (88%) want clear rules governing what robots can do.

“Industrial environments are where the tasks for robots are the most defined, the safety cases are mature, and governance is in public view,” Hexagon CTO Burkhard Boeckem concluded.

Global comparisons back the fear of the unknown theory – while 30% of UK adults have encountered robots in real life, 75% have in China. A country that’s nearly twice as likely (63%) to accept robots into the home compared with the UK (32%).

For most of the last forty years, data center performance gains came from one place: smaller transistors. Moore's Law and Dennard scaling did the work.

Each new generation of silicon delivered more performance at the same or lower power, and thermal was a maintenance problem, not a performance limiter.

Cooling sat in the background. Operators measured it through PUE, optimized for it where convenient, and otherwise treated it as overhead.

That world is over.

Dennard scaling broke years ago, transistor efficiency gains are leveling off, and AI accelerator TDPs have climbed from 700 watts in the H100 generation to over 1,400 watts in current Blackwell deployments, with NVIDIA's upcoming Rubin platform expected to push further.

Thermal is no longer something that happens after the architectural decisions. It is now the binding constraint on how much performance a chip can sustain, and it is becoming one of the most strategic choices an AI data center operator can make.

Why this matters now

The macro numbers explain why this matters now. Data centers already consume up to 4.5 percent of total U.S. electricity production, a figure projected to reach 12 percent by 2028. McKinsey estimates global data center spending could approach $7 trillion by 2030, and that data center power demand will reach 220 gigawatts in the same window.

None of that capacity arrives quickly. New transmission lines and substations now take five to ten years to permit and build, which means operators cannot simply order more power when they need to scale.

The result is a hard pressure to extract maximum performance from the power they already have under contract. That pressure is what is reshaping how the industry thinks about cooling.

Cooling is no longer just an afterthought

For years, cooling was measured as an efficiency loss, captured through metrics like Power Usage Effectiveness (PUE) that quantified how much energy was burned on overhead before reaching the IT load. Today, the more meaningful metric is how much useful compute you extract per unit of power. NVIDIA's Jensen Huang now describes this as "performance per watt" or "tokens per watt" for AI workloads, and cooling plays a direct role in both halves of that equation.

Direct-to-chip liquid cooling has become the new baseline because it removes heat far more effectively than air. But even direct-to-chip is being pushed to its limit by 1,000+ watt accelerators, and most current deployments still require facility water around 30 degrees Celsius to stay within ASHRAE W2 and W3 envelopes, which means chillers running for much of the year in warm climates.

Better thermal management has effects on both sides of the tokens-per-watt equation. It reduces facility overhead, so more of the contracted power reaches the rack. And it allows chips to operate closer to their full thermal headroom, sustaining higher performance for longer.

Those gains compound. Recent UCLA study has shown that combining a 17 percent improvement in facility efficiency with a 15 percent gain in server-level performance per watt from better thermal management translates to roughly 35 percent more tokens per watt within the same power envelope. In a 10 megawatt facility, that is more than a megawatt of additional usable compute, with no additional grid commitment.

At GTC 2026, NVIDIA CEO Jensen Huang made this argument explicitly. He told the audience that beyond the silicon roadmap, infrastructure-level optimization across power and cooling represents another factor of two in performance still on the table. "There's no question in my mind there's a factor of two in here, and a factor of two at the scale we're talking about is gigantic," he said.

That gain does not come from a smaller transistor. It comes from rethinking how power and thermal energy move through the rack. Recent UCLA study suggests that at least one third of that infrastructure-level gain is attributable specifically to cooling. Cooling is no longer a support function. It is a primary lever for performance.

Water is becoming a hard constraint

Power is not the only pressure point. Water is emerging as an equally critical and often more immediate constraint on data center expansion. Traditional cooling architectures often rely on evaporative processes that consume vast amounts of water. According to the Environmental and Energy Study Institute, large data centers may use up to 5 million gallons per day, comparable to the daily water use of a town of 10,000 to 50,000 people.

This is drawing notice from regulators and communities in already water-stressed areas. The result is longer permitting cycles, higher project risk, and in some cases new developments paused entirely. States and municipalities are also implementing stricter reporting requirements and adjusting electricity rate structures specifically for data centers.

Operators now have to factor water alongside power into site selection. Facilities that minimize energy waste and reduce or eliminate water consumption are better positioned to navigate this environment.

The shift toward next-generation cooling

In response, the industry is entering a new phase of cooling innovation. Air cooling is no longer sufficient for high-density AI workloads. Liquid cooling has become the baseline, but within liquid cooling, not all approaches deliver the same efficiency or scalability.

The next wave of innovation focuses on improving heat transfer at the source: removing thermal energy more effectively at the chip level while reducing system-wide overhead. Some of these approaches draw on heat transfer techniques refined in other high-density power industries such as nuclear power generation, where the challenge of moving large amounts of thermal energy from a constrained physical space has been studied for decades.

The goal is straightforward. Better cooling enables higher rack densities, allows operation at higher facility water temperatures, and reduces or eliminates reliance on water-intensive heat rejection. Just as importantly, the next generation of cooling architectures is being designed to integrate with existing data center footprints, so operators can evolve their infrastructure rather than rebuild it from scratch.

NVIDIA's Vera Rubin platform, announced at CES 2026, was a clear signal of where this is heading. Vera Rubin is designed for 45 degree Celsius supply water, which means dry coolers can do most of the heat rejection year-round and mechanical chillers become optional in most climates. That is a fundamental shift in how cooling infrastructure will be designed for the next decade.

A defining moment for data center design

The data center industry is at an inflection point. AI compute demand is accelerating, and every resource needed to support it, power, water, physical space, is becoming harder to secure. Cooling sits at the intersection of all three.

It determines how efficiently power is used, how much water is consumed, and ultimately, where infrastructure can be deployed. The operators that recognize this now will have a sustained advantage. How to keep data centers cool under AI workload pressure has become one of the most strategic decisions in modern infrastructure.

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When the Sony WH-1000XM6 dropped last year, they had some big expectations to live up to.

They followed up a pair of headphones that had proven somewhat divisive, in the Sony WH-1000XM5. This model left some wearers conflicted owing to the lack of foldability, limited new features, and smaller 30mm drivers, in spite of stepping up in terms of looks and still offering great sound. For me, the XM5 just didn’t quite feel like the statement headphones that the legendary Sony WH-1000XM4 were — and in my view, the real task of the XM6 was to live up to the brilliance of that model.

And what do you know, Sony really did it — the company finally delivered a pair of XM4-beating headphones. The XM6 blended the beauty of the XM5 with the practical design of the XM4, all while delivering substantially better audio than their predecessors, alongside far greater noise cancelling capabilities and a more fleshed-out feature set.

And even though it’s been a year now, the XM6 remain my go-to headphones — even after hearing other flagship kids on the block, including the Bose QuietComfort Ultra Headphones Gen 2, Apple AirPods Max 2, and even Sony’s own 1000X The Collexion cans. But why do I keep reaching for the XM6? And what really sets them apart from the competition? Well, I’ll get to all of that and more as we take a look at my year of listening with the XM6.

What’s so special about the XM6?

(Image credit: Future)

For the uninitiated, allow me to give you the run down on the Sony WH-1000XM6. These are Sony’s best noise-cancelling cans to date, and even on flights, they can easily dispatch low-end rumble, high-pitched clamors, and sudden noises like doors closing. If you’re at the office, things like colleagues chatting, typing sounds, and vehicles passing outside the window will be drastically dulled too — if not totally inaudible.

That’s thanks to Sony’s QN3 noise-cancelling processor, which harnesses a system of 12 microphones to deliver some of the best ANC on the market right now.

The QN3 processor also features a noise-shaper, which pre-empts sudden sound changes, resulting in a more controlled listening experience. Pair that with LDAC for ‘hi-res’ Bluetooth listening as well as a more balanced sound signature than the XM5 and XM4 offered — in part thanks to Sony’s collaboration with leading mastering engineers — and you’re getting amazing audio from the XM6.

As you’d expect, these headphones aren’t producing true studio-grade neutrality or fidelity, but they sound more composed right across the frequency range. Still, bass is phenomenally dynamic and punchy, treble is vibrant and articulate, and there’s definitely an exciting listen to be had. Mids are also incredibly rich and well-weighted, and the XM6 offers a wider soundstage than its predecessor, all while supplying a tight and cohesive listen.

Other XM6 headlines include a new, more comfortable headband, the welcome return of foldability, and enhanced call quality. There are six beamforming mics in the XM6, and I’m yet to try any headphones that beat them for clarity and precision in the call quality department.

You also get the features that made the XM6’s predecessors great, including DSEE Extreme upscaling (which boosts the quality of lower-res audio files), scene-based listening, transparency mode, and the most responsive and accurate touch controls around.

How do they compare to the competition?

Here I am, holding up the Sony WH-1000XM6 and a pair of the Bose QuietComfort Ultra Headphones (Image credit: Future)

So, the XM6 sound pretty great so far, right? But you might be wondering how they compare against the competition. So, let’s see how they compare against some of their main rivals: the Bose QuietComfort Ultra Headphones Gen 2, the AirPods Max 2, and Sony’s own The Collexion headphones.

Let’s start with the QC Ultra, which are in my view the main competitor to the XM6 — they’re similarly priced, and each have a strong focus on ANC performance. But interestingly, I think this contest is a relatively straightforward one.

When it comes to ANC, these two are on very similar footing. I’d perhaps argue that the QC Ultra can deal with higher-pitched sounds ever-so-slightly better, but I’m talking very fine margins. Conversely, I’d consider the XM6 slightly ahead when it comes to those deeper, darker sounds like engines roaring.

But elsewhere, I think the Sony XM6 are just the better buy. For me, the Bose have a less revealing sound that lacks the refinement and attention to detail Sony can deliver. Sony also supplies better balance across the frequency range, and even more customizable sound, making them my clear favorite sound-wise.

The XM6 also have a more cohesive, sleek, and suave look in my opinion — I’m also more partial to the magnet-lock case that Sony bundles in. Both headphones are well-matched elsewhere, though, offering fully foldable designs, solid security and comfortability in-use, and 30 hours of battery life — essentially the standard for headphones in this price bracket.

Sony WH-1000XM6 next to the Apple AirPods Max 2 (Image credit: Future)

Moving onto the AirPods Max 2 now, and this is where things get interesting. Of course, these headphones have some features that are suited to Apple devices only — such as Spatial Audio and instant pairing — meaning brand loyalists may prefer these. But as someone with an Android phone, this is hardly something I’m interested in.

I’d also argue that the XM6 are generally better all-rounders than the AirPods Max 2. For instance, Apple’s flagship headphones only muster up a measly 20 hours of playtime with ANC on — something that really should’ve been improved from the first generation AirPods Max.

I also find the XM6’s use of precise touch controls to be more intuitive and user-friendly, and their more accessible price is an undeniable plus. The AirPods Max 2 come in at $549 / £499 / AU$999 — quite the increase over the $449 / £349 / AU$699 you’ll pay for the XM6.

The AirPods Max 2 still impressed me though — they offer significantly improved ANC that blocks external noise on a similar level to the XM6, and they performed very well in the audio department. They have a more spacious and expansive soundstage than the XM6, and the bass is full-sounding and beautifully controlled. While the XM6 sound pretty balanced, they undoubtedly retain a slight preference towards bass and treble from previous generations, but I personally prefer their tighter, punchier approach to the low-end.

Sony 1000X The Collexion beside the Sony WH-1000XM6 (Image credit: Future)

It’s an incredibly similar story for Sony’s own 1000X The Collexion headphones, which took aim at the AirPods Max with an incredibly broad, almost three-dimensional soundstage that results in a highly immersive listen.

The Collexion undoubtedly provide stellar detailing and incredible instrument separation, but again, I always reach for the XM6 — I find their dynamism and punch to add a bit more excitement, making funky tracks or hard-hitting anthems come through with more bite.

In addition, The Collexion add very little in the way of features that the XM6 won’t already provide. Sure, they have more 360 Upmix modes, but these sound pretty bad anyway. They also have weaker ANC and lower battery life, largely due to their slimmer build and larger ear cavities.

Don’t get me wrong, The Collexion look great, and their metallic details contrast the faux-leather casing nicely, but for me, the XM6 are stronger overall.

One year later: the verdict

The magnet-lock case for the XM6 is truly excellent (Image credit: Future)

So, even after testing some of the XM6’s biggest rivals, I still reach for them every time. Their combination of class-leading ANC, excellent features, and dynamic, punchy, yet well-balanced audio makes them my go-to time after time.

It’s also worth flagging that after a full year of use, the headphones have held up incredibly well. I can count a total of zero times where I experienced a fault or bug, they don’t have a single scratch (even after being folded and thrown in my bag countless times), and the earcups feel incredibly comfortable, with no signs of degradation whatsoever.

What’s more, I’ve accidentally kept the headphones on during rainy days from time to time, and despite lacking an IP rating, they seemed to have weathered the storm without issue. Would I recommend using them in harsher weather conditions? No. But the fact they’ve stuck it out a couple of times only hammers home their durability and high build quality.

I won’t pretend that the XM6 are cheap by any means. But they genuinely earn their price in every way imaginable. And they do go on sale quite a bit, so if you can find them going for less, I’d strongly suggest snapping them up, and treating yourself to superior sound.

I don't know if you've seen the price of a PlayStation 5 SSD lately, but they're absolutely cooked. Right now prices are easily triple what they were just a few years ago thanks to the pressure caused by AI demand, so I'd recommend other options instead.

Luckily Amazon Prime Day Is bringing some serious value, with the 5TB Seagate Game Drive PS5 external hard drive discounted to just £143.48 (was £207.99) right now.

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This is an external HDD, which means it functions a little differently to a regular SSD, but it's still designed for storing games. It's also officially licensed for PS5, and has a design that matches the console itself to keep your setup looking super slick.

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Generative AI has moved quickly from experimentation into early production use in many enterprises. However, very few can confidently forecast what it’s going to cost them in six months.

For a technology that has consumed so much board-level attention and capital, that reflects a lack of certainty, and one that some technology leaders may privately recognize as true of their own organizations.

The spend is real and the direction is clear, but the number at the end of the year can remain genuinely uncertain.

To capture a glimmer of the confidence driving the infrastructure race, Amazon’s CEO has indicated it expects to spend heavily on IT infrastructure to support AI, with an estimated $200 billion in AI capital spending, arguing it is “not going to be conservative” in how it invests in the tech.

In practice, what makes AI different from the infrastructure investments that came before it is not the scale of the commitment but the nature of the consumption.

Cloud computing was unpredictable when it arrived too, but it eventually settled into patterns that finance teams could learn to model. AI hasn’t settled in the same way yet, and much of the reason comes down to how it is being used.

A great deal of enterprise AI use remains exploratory, which is part of what makes forecasting harder. And unlike cloud, which stayed largely within technical teams for years before spreading, AI is moving across the whole organisation almost immediately. That changes everything about how you try to govern it.

The limits of financial visibility

On the surface, some forms of AI appear to offer what earlier infrastructure lacked: clean, granular, real-time data and what it costs. But across the rapidly growing landscape of technology providers leveraging AI in some way, many do not.

In some cases, token-based pricing is precise in a way that early cloud billing never was, and for finance teams accustomed to working with far less, it can feel like a step in the right direction for solving the visibility problem.

We unfortunately still have a long way to go, since simply understanding what was spent last month tells you very little about what will be spent next quarter, particularly once adoption moves beyond the teams who originally shaped the business case.

One must consider that teams across legal, HR, and customer operations are not thinking about token economics (tokenomics). They’re only thinking about whether the tool works.

Cost exposure builds not through any single decision but through dozens of small expansions, each reason in isolation, none of them reflected in a comprehensive forecast. By the time anyone joins the dots, the demand curve has already moved.

Extending the disciplines that already exist

The organizations who are doing a better job managing AI spend have tenured experience managing consumption-based technology. IT asset management (ITAM) teams for example often have more experience dealing with more fixed constructs like users or seats, which makes the consumption-based nature of AI far more challenging.

FinOps teams on the other hand have grounded experience in managing consumption that originated in public cloud. FinOps teams may therefore better positioned to deal with the new tsunami of AI consumption and spending, ensuring that it is governed as adoption scales.

FinOps has also been broadening its scope beyond the initial roots in public cloud, with AI cost management now sitting firmly within that remit for many, a shift reflected in how the FinOps Foundation is increasingly incorporating AI into its guidance. Part of that expansion is about forecasting demand that behaves differently from conventional workloads.

There is also growing interest in whether AI itself can support FinOps practices, particularly in anomaly detection, optimization and, over time, forecasting, as consumption patterns become harder to model.

The challenge is applying FinOps practices early enough so that governance shapes how AI scales, rather than scrambling to restore control once spend has already outpaced oversight.

The compounding difficulty of legacy environments

For organizations whose technology estates were built around consistency, extending governance into AI is harder than it sounds.

AI-first organizations design with cost in mind from the beginning, treating inference the way they would any other product input, with economic constraints shaping architecture decisions before commitments are made.

Retrofitting AI into legacy infrastructure means something different. Existing commercial commitments and operating models do not adapt quickly to a consumption model that is inherently variable, and that friction has a direct bearing on cost.

The difficulty is often that AI is being introduced into environments built around very different assumptions about how demand behaves, and that is part of what makes forecasting harder.

The challenge is not simply new spend, but expenditure ballooning in environments where oversight and control are already difficult to maintain.

Organizations navigating this will tend to run controlled experiments before broad rollout and are deliberate about how adoption spreads. In practice, that is often about containing unmanaged adoption early, before usage patterns, costs and dependencies become harder to unwind.

That same exposure increasingly carries beyond internal governance. As AI appears more often in customer procurement conversations, questions that were once largely internal are starting to be probed externally too.

For organizations whose governance has not kept pace, those questions can force a level of clarity they may not yet be prepared to provide.

From activity metrics to business outcomes

Beyond governance and cost control, there remains a harder question, which is whether AI investment is producing meaningful business value. Most leadership teams are not yet in a position to answer that with confidence, and the metrics currently reaching the board are not making it easier.

Model usage, inference volumes and compute consumed describe activity without explaining value. It is easy to build a compelling board update from consumption data without addressing whether any of it is moving the business.

What gets closer to an answer is understanding whether individual inferences are delivering something a customer would pay for, or something that meaningfully reduces cost or risk.

Incremental business outcome per pound or dollar of AI spend is a harder measure to produce, but it is closer to the economics that matter because it requires a clearer position on what AI is actually delivering.

That is precisely where many organizations are still finding the work harder than it looks, particularly as AI deployment moves ahead of the models used to understand cost and value.

That disconnect matters more as the market expands, because where those economics remain unclear, cost exposure can build in ways that are harder to recognize early and harder to contain later.

For many enterprises, the challenge ahead is scaling AI without allowing spend to outrun the value it is meant to create.

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I've been trying out Amazon's latest — and possibly greatest — e-reader, the Kindle Scribe Colorsoft, and while I love it for reading comics in full colour and note-taking, I've been waiting patiently for Amazon Prime Day to see how the device fares in the megasale.

As expected, it's seen a sizeable discount; 20% off, knocking it from £629.99 to £504.99, which is, to be honest, much closer to the value proposition I think the slate offers. Still, though, it's pricey for what it is; and the fact that it's actually cheaper right now to buy a Kindle, Kindle Scribe and a Kindle Colorsoft separately leaves me perplexed.

Right now, the Kindle (in graphite) is £79.99 (was £94.99) at Amazon, the 32GB Kindle Scribe (in tungsten grey) is £244.99 (was £399.99) and the Kindle Colorsoft is £154.99 (was £239.99). That totals £479.99; £26 cheaper than just one Kindle Scribe Colorsoft. Make it make sense.

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A notetaker's best friend, the Kindle Scribe is great for students, avid readers and productivity users alike, offering a satisfying and slick screen on which to doodle and annotate. We scored it 4.5 stars in our review.View Deal

If you mostly want the colour screen, you'll be just fine with the Kindle Coloursoft; as a comic reader, this is really all I want and need from my Kindle. While you can't ever match the vibrancy of an LCD or OLED screen in e-ink, it's a valiant effort that earned the device 4.5 stars in our review.View Deal

While not a factor in the Kindle Scribe Colorsoft pricing hoo-ha, it's worth noting the Kindle Paperwhite is also on sale with a neat £35 discount. We scored this model 4-stars in our review, praising its bright, white screen and long battery life.View Deal

The Kindle Scribe Colorsoft isn't without its selling points entirely; if you really do want to read comics and take notes on one device, it's the only Kindle that offers both functions... just not in tandem, so you can't annotate comics or manga.

That means the main benefit is access to colour pens and highlighters, which isn't a big enough sell for me to drop half a grand on an e-reader.

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If you were looking to get your hands on a PlayStation 5 ahead of the Grand Theft Auto 6 pre-order date this week, then this Amazon Prime Day deal is for you. Right now you can grab the console at a 16% discount over at Amazon, which takes its price down to just £479 (was £569.99).

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It's not the cheapest PS5 we've ever seen, but with the recent price increases, it's likely going to be the lowest it's available for some time. This is the Slim 1TB version of the console as well, with a disc reader fitted so you can buy the physical version of GTA 6 to keep on your shelf.

The deal is only on for a limited time, and stock is already flying off the shelves - with just under half of the available units sold already. This is a deal I'd recommend snapping up quickly!

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• Wearables: Garmin & Huawei from £36.99

Amazon's Prime Day sale is here (running from June 23 to 26, and exclusive to Prime members), and if a 360 camera has been on your wish list, it's the perfect time to act. Two of Insta360's best models are getting solid discounts in the sale — but the one I'd actually put in my basket might not be the one you're expecting.

I reviewed the Insta360 X5 last year, and its low-light performance was the standout feature for me. It remains, in my view, the best all-rounder Insta360 makes. At 21% off ($434.99, down from $549.99 for the Standard Bundle, a $115 saving), it's a pretty tempting buy in the Prime Day Sale.

But my colleague Peter Fenech has since put the newer Insta360 X4 Air through its paces, and with Prime Day discounts of 25% on the Standard Bundle ($299.99 at Amazon, down from $399.99) and 26% on the Starter Bundle ($324.99, down from $439.99, also a $115 saving), I think it's the smarter buy for most people.

The Insta360 X5 and X4 Air are both superb 360 cameras, and they're currently both on sale for Prime Day. (Image credit: Future / Peter Fenech)A baby X5, in the best sense

The X4 Air inherits a lot of what made the X5 so appealing. It uses the same easy-to-swap lens replacement system (which can be a real lifesaver if you scrape a lens on the ground), and it's waterproof to the same 15m depth without a housing.

At 165g, it's also noticeably lighter than the X5's 200g. It's not a huge number on paper, but you'll feel the difference after an hour of holding a selfie stick overhead.

The real divergence is in sensor size. The X5 uses larger 1/1.28-inch sensors, while the X4 Air steps down to 1/1.8-inch (still bigger than the original X4's sensors, for context). In daylight, you'd struggle to tell the two apart. It's only once the light fades that the gap opens up, with the X5's PureVideo mode giving it around a two-stop low-light advantage over the X4 Air.

That sounds like a point in the X5's favor, and it is. But I think that the vast majority of 360 footage gets shot in daylight — think travel clips, bike rides, beach days, family get-togethers — and the X4 Air handles all of that with ease. Peter was impressed by its image quality overall, and found its low-light performance better than expected even without PureVideo on board.

On the battery life front, the X5's larger 2,400mAh battery wins out for marathon sessions: its Endurance Mode can run for over three hours at 5.7K, versus around 105 minutes for the X4 Air with the same settings. But at 8K/30fps (the resolution most people will actually shoot in), both cameras land at roughly 90 minutes.

The X4 Air is slightly lighter than the X5, which will feel like a benefit on a long day of shooting. (Image credit: Future)

If you're a professional creator, you regularly shoot in low light, or you simply want the best 360 camera Insta360 currently makes, the X5 at 21% off remains an easy recommendation.

But if this is your first 360 camera, or you want something that genuinely disappears into a pocket, the X4 Air gives you almost everything that made the X5 special, for $100 to $135 less. That's where my money would be going this Prime Day.

Today's best Insta360 X4 Air and X5 deals (US)

Taking many of the X5 features but squeezing them into a smaller body, there's plenty to like about the X4 Air, especially with its first major discounts for Prime Day, now 25% off. View Deal

For 360-degree action cameras, it doesn't get any better than the X5 from Insta360. With huge sensors, the X5 delivers 8K video and excels in low light. It's also feature-rich with replaceable lenses to boot. Save $85 on the best action camera for shooting in 360.View Deal

Today's best Insta360 X4 Air and X5 deals (UK)

There's also 25% off the X4 Air for shoppers in the UK, taking the base package price down to a record-low £269. Not bad for a 'baby X5'.View Deal

My favorite 360 camera, with a healthy 25% off — it doesn't get any better! With huge sensors, the X5 delivers 8K video and excels in low light. It's also feature-rich with replaceable lenses to boot. Save $85 on the best action camera for shooting in 360.View Deal

More of today's best Insta360 dealsMore Prime Day deals in the US

• Amazon Devices: Fire Sticks & Echo from $18
• Amazon Haul: viral gadgets, tech & appliances from $1.99
• Apple: MacBooks, AirPods & AirTags from $29
• Beauty: 50% off toothbrushes & hair tools
• Cheap TVs: smart TVs from $69.99
• Garden: tools, mowers, planters from $24.99
• Headphones: 50% off Beats, Bose & Samsung
• Laptops: Apple, HP & Dell from $199
• Mattresses: Sealy, Serta & more from $186
• Patio: outdoor furniture, rugs & decor from $19.99
• Sports: 50% off fitness gear, treadmills & clothing
• Vacuums: Dyson, Shark & Bissell from $34

More Prime Day deals in the UK

• Amazon Prime: sign up for a 30-day free trial
• Amazon Devices: Fire TV, Ring & Blink from £24.99
• Amazon Haul: up to 30% off
• Apple: AirPods Pro 3 for a record-low price
• Appliances: up to 45% off Ninja, Tefal & Sage
• Beauty: up to 60% off Philips & Oral-B
• Essentials: household goods from under £10
• Fashion: up to 50% off
• Father's Day: up to 50% off gifts & drinks
• Headphones: up to 50% off
• Laptops: from £149.99
• Tablets: Samsung & Lenovo from £125
• Toys: up to 25% off Lego and Tonies
• TVs: from £129.99
• Vacuums: up to 40% off Eufy & Roborock
• Wearables: Garmin & Huawei from £36.99

Agentic AI is moving rapidly from boardroom ambition to enterprise reality.

Gartner forecasts that roughly 40% of enterprise applications will incorporate task-specific AI agents this year, up from just 5% last year.

This surge forces every CIO, CISO, and technology leader to consider: What should AI be allowed to access, and how should it operate once inside the enterprise?

Many organizations begin by embedding AI agents directly into legacy systems, connecting them to backend databases, APIs, and workflows in the name of speed.

While this inline approach can work in modern, well-governed environments, it often bypasses the approval workflows and controls that legacy systems were built around. Agents can access restricted data, skip approvals, or execute transactions without a complete, attributable record.

The result is a growing governance gap. Decisions tied to sensitive data can’t be reliably reconstructed or defended with the same confidence as human-driven work. Even advanced models stall in pilots because organizations can’t prove how outcomes were produced.

The solution is not to slow AI adoption. It’s to change how AI interacts with the systems that already run the business.

When AI bypasses the system, it breaks it

Consider a finance workflow in an ERP software system. An agent updates vendor bank details and pushes a payment through a fast-track path, bypassing a required approval step and segregation-of-duties check. Later, when the transaction is questioned, the organization can’t prove who approved the change, why it was made, or whether proper controls were followed.

That’s where accountability breaks down. Changes are made inside core systems, but the evidence is incomplete, inconsistent, or disconnected from the system of record.

Emulated human behavior offers a more secure and practical path. These agents operate exactly as a human employee would: logging in with standard credentials, navigating the existing user interface, reading screens in context, following established workflows, and executing tasks while remaining fully subject to every control already in place.

No new APIs. No raw backend data exposure. No rewriting of decades-old business logic or security rules. The guardrails designed to protect against human error or misuse — validations, permissions, approvals, and audit logging — remain 100% intact.

This UI-first approach is especially effective for organizations running mission-critical processes on older platforms. Building secure, governed APIs for legacy systems is expensive and time-consuming, often leaving out protections built into the interface layer.

While emulated human agents may not match the speed of direct backend calls, they provide far more valuable enterprise advantages: immediate deployability, ironclad accountability, and zero disruption to proven controls. Secure operation doesn’t require avoiding AI. It requires rethinking how it fits into the systems around it.

Preparing for emulated human in the enterprise

Three priorities can help organizations prepare for the emulated human approach as AI scales into critical workflows.

1. Place AI at the points where work happens

Most enterprise AI strategies assume deeper backend integration creates better automation. In environments shaped by legacy systems, it often does the opposite: introducing new complexity while bypassing the workflows and controls already built into the interface layer.

Instead, focus AI at the points where it can operate without requiring systems to be rebuilt. This approach dramatically reduces integration overhead, limits exposure of core systems, and allows AI to scale within existing operating models rather than forcing costly modernization.

2. Align AI accountability with human accountability

Agents should operate under named identities and the same policies as employees. They preserve approval workflows, follow role-based permissions, and generate the same audit artifacts — including log entries, change histories, tickets, and recorded approvals — that organizations already rely on to review human activity.

This removes the dangerous two-tier governance model where AI operates under different standards than employees. Organizations can maintain visibility, accountability, and established compliance and risk management controls as AI takes on greater responsibility.

3. Design for adaptability rather than brittle automation

Traditional robotic process automation (RPA) relied on rigid, click-by-click scripts that broke the moment screens changed or exceptions appeared. Emulated human agents interpret context in real time, adjust to variation, and continue operating, just as skilled employees do.

That adaptability is essential in dynamic enterprise environments where policies change, exceptions are common, and systems are rarely static. Instead of constant break/fix maintenance, organizations gain AI that can operate more resiliently inside real-world workflows.

Scaling AI with the systems already in place

As agentic AI scales, enterprises will be judged not only by the intelligence of their systems but by their ability to govern them. The pressure to balance innovation with control will only intensify.

The most durable strategies will be those that embed AI safely within the systems already in place, rather than racing around them. When an agent’s actions can be audited and justified with the same rigor applied to a human colleague, it’s finally ready for production.

That’s how secure, scalable AI will be defined in the enterprise.

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