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• Coveron and NordLayer found synthetic “digital Frankenstein” identities sold on dark web for ~$200
• Packages mix stolen data with AI‑generated names, deepfake selfies, and cloned voices to bypass KYC
• Researchers urge credit freezes, layered verification, and monitoring to counter rising synthetic identity fraud

You can now get your own “digital Frankenstein” for as little as $200, which will pass automated know-your-customer (KYC) checks on your behalf, and help you register fraudulent accounts with banks, cryptocurrency exchanges, and similar services. This is no longer a fringe, niche cybercriminal offering - it’s basically mainstream.

Recently, researchers from identity theft protection services Coveron and threat exposure management platform NordLayer Intelligence sifted through dark web forums and Telegram Channels, analyzing 22 queries over 362,000 posts related to identity fraud, deepfake services, and something they call “synthetic identity creation”.

A synthetic identity is essentially a fake, non-existent person, but created in a way that can fool many automated identity verification systems. It combines real stolen data, such as a Social Security number, with AI-generated fake information such as names, addresses, deepfake selfies, and cloned voices. The researchers call these identities” digital Frankensteins”, and claim they are “fully capable” of passing ID checks.

Rising popularity

Apparently, the number of posts and inquiries for synthetic identities is blowing up. In Q1 2024, there were roughly 40 posts a month discussing deepfakes. By Q2 2026, the number rose to 307 per month, an eightfold increase. It wasn’t a steady increase, either. Throughout 2025, the numbers remained similar to the year prior, and relatively flat. Only in 2026 the monthly averages jumped to 255 posts, the researchers warned.

Over the past year, there were more than 10,000 posts offering complete identity data, bundled with deepfake selfies and matching documents. All of this is being sold for around $200. To make matters worse, criminals don’t even have to purchase the entire package. They can buy parts of it (a deepfaked selfie, or a cloned voice), for as little as $10.

To protect against synthetic identity fraud, users should monitor personal data and act quickly if they discover a breach. Credits should be frozen if you’re not applying for new accounts, and everyone should be skeptical of unusual identity verification requests, Coveron explains. Businesses, on the other hand, should layer their verification systems and use identity theft protection services.

• Coveron and NordLayer found synthetic “digital Frankenstein” identities sold on dark web for ~$200
• Packages mix stolen data with AI‑generated names, deepfake selfies, and cloned voices to bypass KYC
• Researchers urge credit freezes, layered verification, and monitoring to counter rising synthetic identity fraud

You can now get your own “digital Frankenstein” for as little as $200, which will pass automated know-your-customer (KYC) checks on your behalf, and help you register fraudulent accounts with banks, cryptocurrency exchanges, and similar services. This is no longer a fringe, niche cybercriminal offering - it’s basically mainstream.

Recently, researchers from identity theft protection services Coveron and threat exposure management platform NordLayer Intelligence sifted through dark web forums and Telegram Channels, analyzing 22 queries over 362,000 posts related to identity fraud, deepfake services, and something they call “synthetic identity creation”.

A synthetic identity is essentially a fake, non-existent person, but created in a way that can fool many automated identity verification systems. It combines real stolen data, such as a Social Security number, with AI-generated fake information such as names, addresses, deepfake selfies, and cloned voices. The researchers call these identities” digital Frankensteins”, and claim they are “fully capable” of passing ID checks.

Rising popularity

Apparently, the number of posts and inquiries for synthetic identities is blowing up. In Q1 2024, there were roughly 40 posts a month discussing deepfakes. By Q2 2026, the number rose to 307 per month, an eightfold increase. It wasn’t a steady increase, either. Throughout 2025, the numbers remained similar to the year prior, and relatively flat. Only in 2026 the monthly averages jumped to 255 posts, the researchers warned.

Over the past year, there were more than 10,000 posts offering complete identity data, bundled with deepfake selfies and matching documents. All of this is being sold for around $200. To make matters worse, criminals don’t even have to purchase the entire package. They can buy parts of it (a deepfaked selfie, or a cloned voice), for as little as $10.

To protect against synthetic identity fraud, users should monitor personal data and act quickly if they discover a breach. Credits should be frozen if you’re not applying for new accounts, and everyone should be skeptical of unusual identity verification requests, Coveron explains. Businesses, on the other hand, should layer their verification systems and use identity theft protection services.

Evanston, Ill., became the first U.S. city to compensate Black people for historical discrimination. The Justice Department is trying to kill its program before other cities follow suit.

(Image credit: Candace Dane Chambers for NPR)

Mobile data can get expensive when you need hundreds of gigabytes every month, especially if you're using it as an alternative to fixed broadband. So, this 1000GB Data SIM deal, which gives access to Three and Vodafone networks, is the perfect fix.

• Best for: Remote workers, off-site travellers, and high-volume data users who want to pay a small amount upfront with no monthly charge or contract.

• The deal: 1000GB Three Data SIM for £58 (was £276) at Scancom when you use code HUKDHOT!!!. That works out at under £2.65 a month.

• Why it matters: This is a staggering saving on a mass-data SIM card. The SIM runs until July 2028 and your 1,000GB allowance renews on the 8th of every month. It also provides automatic access to both Three and Vodafone networks where available, and you can choose between a physical SIM and eSIM.

• The catch: There are no voice calls or texts included on this SIM, and no number porting. It's strictly for mobile data. Don't be misled by the £48 price on the page - that's the cost without VAT.

Today's best SIM deal

1000GB Data SIM: was £275.99 now £57.96
1,000GB monthly data, automatic Three and Vodafone network access, physical SIM or eSIM, July 2028 expiry, pre-activated service, no calls, texts or roaming, and monthly allowance renewal on the 8th. For the full discount, use code HUKDHOT!!! (yes, that's three exclamation marks, I'm not just showing excitement). View Deal

Why we recommend it

The 1,000GB monthly allowance means you'll have plenty of capacity for streaming, downloading large files, video calls and using a compatible device as a mobile hotspot.

Scancom says its SIMs are already activated and ready to use, and it uses MOCN, or Multi-Operator Core Network, technology to provide access to both Three and Vodafone networks, potentially improving coverage depending on where you're using it.

Price context & historical value

The standard price is £275.99, but applying code HUKDHOT!!! cuts it down to £48.30 before VAT and £57.96 after.

Unlike a conventional mobile contract, you're making a single upfront payment rather than paying another bill every month. With the service continuing until July 2028, this is an amazing deal.

Should you buy it?

✅ Buy Three's 1000GB data SIM if...

You need a huge amount of mobile data for a router, hotspot or another compatible device and qualify for the service. The combination of a 1,000GB monthly allowance, dual-network access and £57.96 upfront price is an incredible deal.

❌ Skip Three's 1000GB data SIM if...

You're looking for a conventional phone SIM or need to transfer your current number. There are no calls, SMS or roaming included, and number porting isn't supported.

The Catch: What to know before you buy

The advertised £48.30 discounted price you get in your basket when you apply the code doesn't include VAT. With it added you'll actually pay £57.96. This deal isn't available to everyone, either. Scancom states that customers must be businesses or sole traders, and individuals need to be registered as sole traders to qualify.

You should also check Three and Vodafone coverage before buying, as dual-network availability can vary by location. There's no built-in data-usage monitor, so you'll need to track consumption through your device or a third-party app.

If you exceed the 1,000GB allowance, your data resets rather than continuing beyond the limit. The service also has a content lock, although you can contact Scancom support to request its removal.

Mobile data can get expensive when you need hundreds of gigabytes every month, especially if you're using it as an alternative to fixed broadband. So, this 1000GB Data SIM deal, which gives access to Three and Vodafone networks, is the perfect fix.

• Best for: Remote workers, off-site travellers, and high-volume data users who want to pay a small amount upfront with no monthly charge or contract.

• The deal: 1000GB Three Data SIM for £58 (was £276) at Scancom when you use code HUKDHOT!!!. That works out at under £2.65 a month.

• Why it matters: This is a staggering saving on a mass-data SIM card. The SIM runs until July 2028 and your 1,000GB allowance renews on the 8th of every month. It also provides automatic access to both Three and Vodafone networks where available, and you can choose between a physical SIM and eSIM.

• The catch: There are no voice calls or texts included on this SIM, and no number porting. It's strictly for mobile data. Don't be misled by the £48 price on the page - that's the cost without VAT.

Today's best SIM deal

1000GB Data SIM: was £275.99 now £57.96
1,000GB monthly data, automatic Three and Vodafone network access, physical SIM or eSIM, July 2028 expiry, pre-activated service, no calls, texts or roaming, and monthly allowance renewal on the 8th. For the full discount, use code HUKDHOT!!! (yes, that's three exclamation marks, I'm not just showing excitement). View Deal

Why we recommend it

The 1,000GB monthly allowance means you'll have plenty of capacity for streaming, downloading large files, video calls and using a compatible device as a mobile hotspot.

Scancom says its SIMs are already activated and ready to use, and it uses MOCN, or Multi-Operator Core Network, technology to provide access to both Three and Vodafone networks, potentially improving coverage depending on where you're using it.

Price context & historical value

The standard price is £275.99, but applying code HUKDHOT!!! cuts it down to £48.30 before VAT and £57.96 after.

Unlike a conventional mobile contract, you're making a single upfront payment rather than paying another bill every month. With the service continuing until July 2028, this is an amazing deal.

Should you buy it?

✅ Buy Three's 1000GB data SIM if...

You need a huge amount of mobile data for a router, hotspot or another compatible device and qualify for the service. The combination of a 1,000GB monthly allowance, dual-network access and £57.96 upfront price is an incredible deal.

❌ Skip Three's 1000GB data SIM if...

You're looking for a conventional phone SIM or need to transfer your current number. There are no calls, SMS or roaming included, and number porting isn't supported.

The Catch: What to know before you buy

The advertised £48.30 discounted price you get in your basket when you apply the code doesn't include VAT. With it added you'll actually pay £57.96. This deal isn't available to everyone, either. Scancom states that customers must be businesses or sole traders, and individuals need to be registered as sole traders to qualify.

You should also check Three and Vodafone coverage before buying, as dual-network availability can vary by location. There's no built-in data-usage monitor, so you'll need to track consumption through your device or a third-party app.

If you exceed the 1,000GB allowance, your data resets rather than continuing beyond the limit. The service also has a content lock, although you can contact Scancom support to request its removal.

The appetite for AI in the market has never been greater. According to Gartner, over 90 percent of CIOs globally are increasing funding in AI, making it the fastest‑growing area of enterprise technology spend. As organizations look to integrate AI-powered workflows, from real-time analytics to personalized customer experiences, this ambition is accelerating investment in data initiatives.

Additional research shows that enterprises now spend an average of $29.3 million per year on data programs – which encompasses data movement, ingestion and preparation tooling, recurring cloud ingest and compute costs, and the internal engineering capacity required to keep pipelines running.

While this shift in spend mirrors the demands of scaling AI (organizations with successful AI initiatives invest up to four times more in data and analytics foundations), higher budgets do not automatically result in high‑quality data. Many businesses continue to miss out on the transformative impact of AI, held back by underlying weaknesses in their data architecture that slow delivery and limit returns.

Almost two thirds of data initiatives are underperforming

Despite unprecedented levels of investment, the majority of enterprise data initiatives continue to underperform – with 73 percent of organizations reporting their data initiatives are falling short of expectations. At the same time, nearly 62 percent report low levels of data maturity, pointing to a persistent gap between what organizations want their data and AI initiatives to deliver, and what their infrastructure is equipped to support.

Weak data foundations constrain innovation and carry measurable consequences for enterprise performance. In large organizations, downtime caused by data pipeline failures now exceeds 60 hours a month, disrupting productivity and costing an estimated £50,000 per hour in business impact. Data teams are also affected, as they spend over half of their engineering capacity on pipeline maintenance, rather than advancing new use cases.

Open Data Infrastructure as the foundation for AI

Beyond the day‑to‑day costs of downtime and maintenance, the deeper impact of unreliable data foundations is consistent disruption of AI initiatives. For AI systems to thrive, organizations need democratized, interoperable data programs, where access to data is fast, governed and reliable. In response, Open Data Infrastructure (ODI) has emerged as the foundation for AI.

ODI is an architectural approach that gives organizations greater control over how data is accessed, moved and used, by allowing tools and platforms to work together through shared, open standards. Instead of relying on tightly coupled, proprietary systems, ODI is built on a modular, standards‑based foundation that separates storage from compute, enabling each layer to evolve independently.

As data and AI workloads continue to grow, this creates a unified data environment where analytics and AI can scale more efficiently.

ODI is also emerging as a direct challenge to vendor lock‑in. The industry is seeing a shift towards data becoming more restricted, both technically and commercially. Often, these constraints show up as hidden costs or dependencies that push companies toward specific walled-garden ecosystems.

This problem is amplified when AI entities become an organization's primary data users. Indeed, studies suggest that non-human entities are present in modern enterprises at a ratio of 82:1 compared to humans.

For AI agents to work effectively alongside human users, a shared source of truth is essential. Dashboards, operational workflows, machine learning models and AI agents may all draw from the same underlying data, but often operate in separate environments with different definitions and models.

When those definitions drift, the result can be misaligned decisions, unreliable AI outputs and additional engineering overhead. ODI helps address this by giving every system, human or automated, a consistent view of the business.

Furthermore, AI agents generate exponentially more queries than humans, but closed ecosystems often route them through the same expensive compute infrastructure. Agents can only optimize for cost – opting for cheaper compute engines when appropriate – when open architectures afford them the opportunity to choose. And the cost considerations don’t stop there.

Organizations using legacy systems pay significantly more per data pipeline, which, when multiplied by the hundreds of pipelines at enterprise scale, adds up to a significant, ongoing expense.

Modern data management: flexible, portable, trusted

As investment in AI tools continues to ramp up, organizations must think ahead to alleviate the strain on both budgets and engineering resources. They should ensure AI systems have consistent access to fresh, trustworthy and context-rich data while maintaining control of their data and architecture to avoid lock-in.

Those that prioritize open foundations will create the right conditions for innovation and enable their data teams to focus on delivering real business value, from predictive modelling and real-time analytics to faster agent production.

The impact is ultimately reflected in performance outcomes. Research shows that organizations with modern, managed and open data foundations are nearly twice as likely to exceed their ROI targets than those relying on legacy systems – evidencing the direct correlation between data maturity and measurable success of AI initiatives.

We've featured the best AI website builder.

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

The appetite for AI in the market has never been greater. According to Gartner, over 90 percent of CIOs globally are increasing funding in AI, making it the fastest‑growing area of enterprise technology spend. As organizations look to integrate AI-powered workflows, from real-time analytics to personalized customer experiences, this ambition is accelerating investment in data initiatives.

Additional research shows that enterprises now spend an average of $29.3 million per year on data programs – which encompasses data movement, ingestion and preparation tooling, recurring cloud ingest and compute costs, and the internal engineering capacity required to keep pipelines running.

While this shift in spend mirrors the demands of scaling AI (organizations with successful AI initiatives invest up to four times more in data and analytics foundations), higher budgets do not automatically result in high‑quality data. Many businesses continue to miss out on the transformative impact of AI, held back by underlying weaknesses in their data architecture that slow delivery and limit returns.

Almost two thirds of data initiatives are underperforming

Despite unprecedented levels of investment, the majority of enterprise data initiatives continue to underperform – with 73 percent of organizations reporting their data initiatives are falling short of expectations. At the same time, nearly 62 percent report low levels of data maturity, pointing to a persistent gap between what organizations want their data and AI initiatives to deliver, and what their infrastructure is equipped to support.

Weak data foundations constrain innovation and carry measurable consequences for enterprise performance. In large organizations, downtime caused by data pipeline failures now exceeds 60 hours a month, disrupting productivity and costing an estimated £50,000 per hour in business impact. Data teams are also affected, as they spend over half of their engineering capacity on pipeline maintenance, rather than advancing new use cases.

Open Data Infrastructure as the foundation for AI

Beyond the day‑to‑day costs of downtime and maintenance, the deeper impact of unreliable data foundations is consistent disruption of AI initiatives. For AI systems to thrive, organizations need democratized, interoperable data programs, where access to data is fast, governed and reliable. In response, Open Data Infrastructure (ODI) has emerged as the foundation for AI.

ODI is an architectural approach that gives organizations greater control over how data is accessed, moved and used, by allowing tools and platforms to work together through shared, open standards. Instead of relying on tightly coupled, proprietary systems, ODI is built on a modular, standards‑based foundation that separates storage from compute, enabling each layer to evolve independently.

As data and AI workloads continue to grow, this creates a unified data environment where analytics and AI can scale more efficiently.

ODI is also emerging as a direct challenge to vendor lock‑in. The industry is seeing a shift towards data becoming more restricted, both technically and commercially. Often, these constraints show up as hidden costs or dependencies that push companies toward specific walled-garden ecosystems.

This problem is amplified when AI entities become an organization's primary data users. Indeed, studies suggest that non-human entities are present in modern enterprises at a ratio of 82:1 compared to humans.

For AI agents to work effectively alongside human users, a shared source of truth is essential. Dashboards, operational workflows, machine learning models and AI agents may all draw from the same underlying data, but often operate in separate environments with different definitions and models.

When those definitions drift, the result can be misaligned decisions, unreliable AI outputs and additional engineering overhead. ODI helps address this by giving every system, human or automated, a consistent view of the business.

Furthermore, AI agents generate exponentially more queries than humans, but closed ecosystems often route them through the same expensive compute infrastructure. Agents can only optimize for cost – opting for cheaper compute engines when appropriate – when open architectures afford them the opportunity to choose. And the cost considerations don’t stop there.

Organizations using legacy systems pay significantly more per data pipeline, which, when multiplied by the hundreds of pipelines at enterprise scale, adds up to a significant, ongoing expense.

Modern data management: flexible, portable, trusted

As investment in AI tools continues to ramp up, organizations must think ahead to alleviate the strain on both budgets and engineering resources. They should ensure AI systems have consistent access to fresh, trustworthy and context-rich data while maintaining control of their data and architecture to avoid lock-in.

Those that prioritize open foundations will create the right conditions for innovation and enable their data teams to focus on delivering real business value, from predictive modelling and real-time analytics to faster agent production.

The impact is ultimately reflected in performance outcomes. Research shows that organizations with modern, managed and open data foundations are nearly twice as likely to exceed their ROI targets than those relying on legacy systems – evidencing the direct correlation between data maturity and measurable success of AI initiatives.

We've featured the best AI website builder.

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

Samsung has just brought back its semi-regular cashback offer, allowing you to get up to £350 when you buy one of its latest phones, smartwatches, earbuds, or SSDs — including the Galaxy Z Fold 8, Galaxy Watch 9, and Galaxy Buds 4 Pro.

Accessing the offer is simple: buy an eligible product from an eligible retailer between now and October 9, then submit a claim through the dedicated Samsung Cashback site within 30 days of purchase.

Retailers participating in the offer include the big names and usual suspects, such as Amazon, Currys, Argos, AO, Very, and, of course, the official Samsung Store. Several major phone networks and retailers are also taking part, so you can choose to pick up a device on a contract with the likes of Tesco Mobile, Carphone Warehouse, and Mobile Phones Direct.

To get into some specific deals, the offer means you can pick up the brand-new Samsung Galaxy Z Fold 8 at the Samsung Store for £1,349 (was £1,699) after the £350 cashback — plus get up to an extra £730 off with a trade-in. That's a tempting one for me, after seeing our hugely positive 4.5-star review of Samsung's fascinating foldable.

The Samsung Galaxy S26 Ultra, meanwhile, comes with £300 cashback, dropping the price to £1,399 (was £1,699). And if you choose to buy the S26 Ultra from the official Samsung Store, you can get a guaranteed £150 off when you trade in any smartphone in any condition.

I will just point out that the cashback is provided in the form of a virtual prepaid Mastercard in the Samsung Wallet app. It's not as clean as cash being sent directly to your nominated bank account, but the card is eligible to be used in-person or online on whatever you like. An annoying extra step, but at least it's not restricted to specific retailers or uses.

If you're interested in checking out the promotion, I've listed some of the biggest eligible retailers below with links that take you directly to all of their latest deals on Samsung tech.

Samsung Cashback promotion — eligible retailers

• Amazon
• Samsung
• Currys
• Argos
• Very
• AO
• John Lewis
• Carphone Warehouse
• Mobiles.co.uk

• The AFC01 is Smeg's first standalone air fryer
• It has seven presets for different foods, and an optional steam mode
• It has a minimalist design, with an unusual boxy shape and clean lines

Smeg has launched a new air fryer, with seven cooking presets and an optional steam mode — and it looks like no other fryer on the market. The Smeg AFC01 Dual Flavour Air Fryer has an unusual square shape with a matte finish, and cooks food in a lift-out basket rather than a drawer, keeping the outside looking clean and smart, with no bulky handles.

The lid of the AFC01 flips open for easy access to the basket, and the top section of the fryer is translucent, so you can easily check on the progress of your food using the internal light. The fryer is operated using a touch-sensitive control panel, which avoids the need for physical dials and buttons.

There are seven cooking presets to choose from, and two cooking modes: Crispy, which works like a standard air fryer and is ideal for foods like chips, and Juicy+Crispy, which uses steam to keep foods like fish and chicken moist on the inside. Pour cold water into a reservoir on top of the AFC01, and it will be released as fine droplets to prevent your food drying out during cooking.

When you've finished cooking, the whole basket can be lifted out and cleaned in your dishwasher.

In February, Smeg launched its first microwave/air fryer combo, the MOC02 (Image credit: Smeg)

The AFC01 is Smeg's first standalone air fryer. In February this year, the brand released a microwave and air fryer combo, the MOC02, which also works as a fan oven and grill, and can switch modes in sequence for multi-stage cooking (ideal for dishes that require crisping or browning after cooking).

The AFC01 follows the same design language, with straight edges and rounded corners, and comes in the same four matte colours: Black, Storm Blue, Emerald Green, and White. It's available now direct from Smeg for £199.95. I'm hoping to test it soon to see whether it can earn a place in our roundup of the best air fryers.

For years, physical security sat outside most technology discussions.

CCTV, access controls and alarms were typically managed by facilities or security teams, purchased independently from the wider IT estate and reviewed only when equipment reached the end of its life.

That separation no longer reflects how organizations operate.

Modern physical security systems run on cloud platforms, connect with enterprise networks, generate vast amounts of operational data and increasingly rely on artificial intelligence to help people find information faster and respond more effectively.

They have become part of the technology ecosystem that organizations depend on every day, bringing them firmly onto the CIO's agenda.

Physical security is fast becoming another connected enterprise platform for businesses, and technology leaders have a growing role in deciding how these systems are deployed, integrated and governed.

Physical and cyber security are becoming inseparable

One of the biggest changes for physical security is that organizations can no longer treat physical and cyber security as separate risks. Security incidents increasingly span both worlds.

A compromised badge, an unsecured entrance or unauthorized access to a building can quickly become a cybersecurity incident if attackers gain access to corporate devices or networks.

Likewise, cyber attacks can disable physical security infrastructure, affecting everything from access control to video surveillance.

Red team exercises regularly demonstrate how closely these risks are linked. In one example, a team posing as contract cleaners entered an office building, connected to the corporate network and remained inside for hours before being challenged.

From a cybersecurity perspective, every firewall and endpoint protection system was functioning exactly as intended. The weakness was physical access.

Most organizations have invested heavily in protecting their digital perimeter. Yet, if someone can simply walk through the front door and reach critical IT infrastructure, those investments become significantly less effective.

That is why conversations about enterprise resilience increasingly involve both CIOs and CISOs alongside physical security leaders. Protecting the organization now requires a joined-up view of people, places, devices and data.

Legacy systems are becoming harder to justify

CIOs should be just as invested in physical security as digital security. However, many organizations still rely on physical security infrastructure that was designed for a very different era. On-premise video management systems often require dedicated servers, regular software upgrades, specialist maintenance and significant time from internal IT teams.

As estates grow, so does the complexity of managing multiple vendors, ageing hardware and disconnected systems across different locations.

For many CIOs, this creates a familiar problem. Technology teams are expected to modernize infrastructure, reduce operational complexity and improve resilience, yet physical security frequently remains outside those programs despite facing the same challenges as other legacy technology.

The discussion should no longer focus solely on the upfront cost of replacing equipment. Total cost of ownership matters just as much. Maintaining ageing systems often consumes far more time, budget and internal resources than organizations initially expect.

Cloud-based platforms offer a different operating model. Software updates happen automatically, systems can be managed centrally across multiple sites and organizations gain greater visibility without continually investing in new infrastructure.

For IT leaders already overseeing cloud migration across other business systems, extending that thinking to physical security becomes a logical next step.

Physical security provides value far beyond security

CIOs shouldn’t just be interested in physical security from an organization defense perspective - there is also a lot of digital value in the large amount of data produced by these modern physical security systems.

Historically, organizations reviewed security footage after an incident had taken place. Today, AI-powered search and analytics mean that video, access events and environmental sensors can provide instant operational insight across the business.

Retailers can better understand what’s happening in stores, whether it’s queue wait times or occupancy trends, and adjust staffing schedules accordingly. Manufacturers can identify operational bottlenecks or prevent health and safety incidents with real-time alerts.

Facilities teams can understand building usage and gain a clearer picture of how workplaces function throughout the day. None of these outcomes replace human judgement or intervention, but rather empower those workers with hard data rather than forcing them to rely on anecdotal feeling when it comes to how buildings and systems are being used.

The organizations seeing the greatest value are those treating physical security as another enterprise data source rather than an isolated security system.

AI raises the importance of governance

As AI capabilities continue to evolve, governance becomes even more important. The ability to search video using natural language, automate investigations or surface relevant events can significantly improve productivity.

At the same time, organizations need confidence that these capabilities are deployed responsibly, with appropriate controls around privacy, access permissions and data retention. Those are familiar challenges for CIOs.

Across the enterprise, technology leaders are already establishing governance frameworks for AI, assessing risk, managing vendors and ensuring compliance with evolving regulation. Physical security should not sit outside those conversations simply because it has traditionally belonged to another department.

Like every other enterprise platform, it needs clear ownership, defined policies and ongoing oversight. Physical security has changed significantly over the past decade. It is no longer just about protecting buildings. It supports business continuity, operational efficiency and organizational resilience while generating data that can help organizations make better decisions.

As those capabilities continue to expand, CIOs have an opportunity to ensure physical security evolves alongside the rest of the technology estate. The organizations that take that approach will be better equipped to manage risk, simplify operations and build a more resilient business for the years ahead.

Looking for the best cloud storage? These are our top picks.

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

They own car dealerships, law firms, dental practices, and restaurant chains. Collectively, these overlooked business owners hold far more wealth than the Forbes 400 — and wield considerable political power.

Strap in for the chaos... the Harrigans are returning to the small screen in MobLand season 2.

This time around, the dysfunctional family struggles to show a unified front as rising rivals threaten their fractured criminal empire.

'Fixer' Harry Da Souza (Tom Hardy) must walk a dangerous tightrope when tensions within the family intensify. As violence spills into every corner of their lives, loyalties snap, safety proves temporary, and the battle for power leaves no room for mercy.

Just another day for this lot, by the sounds of it. But when does MobLand season 2 episode 1 arrive on Paramount+?

What time can I watch MobLand season 2 episode 1 on Paramount+?

MobLand season 2 episode 1 will drop on one of the world's best streaming services in the US and Canada on Friday, September 18 at 12am PT / 3am ET.

Here's when it will be released in other nations globally:

• US – 12am PT / 3am ET
• Canada – 12am PT / 3am ET
• UK – 8am BST
• India – 12:30pm IST
• Singapore – 3pm SGT
• Australia – 5pm AEST
• New Zealand – 7pm NZST

When do new episodes of MobLand season 2 come out?

(Image credit: Paramount+)

MobLand season 2 will have a total of 10 episodes, with new entries airing weekly. That gives us the following schedule:

• Episode 1: September 18
• Episode 2: September 25
• Episode 3: October 2
• Episode 4: October 9
• Episode 5: October 16
• Episode 6: October 23
• Episode 7: October 30
• Episode 8: November 6
• Episode 9: November 13
• Episode 10: November 20

Strap in for the chaos... the Harrigans are returning to the small screen in MobLand season 2.

This time around, the dysfunctional family struggles to show a unified front as rising rivals threaten their fractured criminal empire.

'Fixer' Harry Da Souza (Tom Hardy) must walk a dangerous tightrope when tensions within the family intensify. As violence spills into every corner of their lives, loyalties snap, safety proves temporary, and the battle for power leaves no room for mercy.

Just another day for this lot, by the sounds of it. But when does MobLand season 2 episode 1 arrive on Paramount+?

What time can I watch MobLand season 2 episode 1 on Paramount+?

MobLand season 2 episode 1 will drop on one of the world's best streaming services in the US and Canada on Friday, September 18 at 12am PT / 3am ET.

Here's when it will be released in other nations globally:

• US – 12am PT / 3am ET
• Canada – 12am PT / 3am ET
• UK – 8am BST
• India – 12:30pm IST
• Singapore – 3pm SGT
• Australia – 5pm AEST
• New Zealand – 7pm NZST

When do new episodes of MobLand season 2 come out?

(Image credit: Paramount+)

MobLand season 2 will have a total of 10 episodes, with new entries airing weekly. That gives us the following schedule:

• Episode 1: September 18
• Episode 2: September 25
• Episode 3: October 2
• Episode 4: October 9
• Episode 5: October 16
• Episode 6: October 23
• Episode 7: October 30
• Episode 8: November 6
• Episode 9: November 13
• Episode 10: November 20

China's Ministry of Foreign Affairs on Monday hit back at a call from the head of Anthropic for the U.S. to curb China's artificial intelligence capabilities.

(Image credit: Ng Han Guan)

Lockly released a new type of smart lock, with a stylish keypad and features made specifically for rentals, vacation homes and Airbnbs. I tried it all.

The Asus Zenbook line of laptops has consistently impressed us in tests thanks to a great blend of performance and ultra-portability. And AO just knocked £350 off the Asus Zenbook 14 touchscreen laptop.

• Best for: Business professionals and students who want a lightweight laptop they can easily carry to multiple locations, and need an OLED display without paying a premium.

• The deal: The Asus Zenbook 14 OLED is reduced to £849 (was £1,199) at AO with free delivery. AO members can save another £38, bringing the total price down to £811.

• Why it matters: Combines a 14-inch WUXGA OLED touchscreen with an Intel Core Ultra 7 255H processor, 16GB of LPDDR5X RAM and a 1TB SSD. It also weighs just 1.2kg and offers up to 18 hours of battery life, built for working at and away from a desk.

• The catch: There's no discrete GPU for heavy 3D rendering or gaming. While the screen is a gorgeous OLED, it's a standard WUXGA panel, not a high-resolution 2K or 4K model. I wouldn't consider this a deal-breaker for work and university tasks.

Zenbook 14 OLED Laptop: was £1199 now £849
It's powered by an Intel Core Ultra 7 255H processor, 16GB LPDDR5X RAM and a 1TB SSD. It comes with a 14-inch WUXGA OLED touchscreen, Intel Arc graphics, Wi-Fi 7, Thunderbolt 4, 75Wh battery and a backlit keyboard.View Deal

Why we recommend it

The 14-inch OLED touchscreen has a 1920 x 1200 resolution, 400-nit brightness and a 1,000,000:1 contrast ratio. Its 16:10 aspect ratio provides a little more vertical space than a conventional 16:9 screen, which is handy when you're working on documents or browsing the web.

Intel's Core Ultra 7 255H combines 16 processor cores with integrated Intel Arc 140T graphics and can reach speeds of up to 5.1GHz. You also get two Thunderbolt 4 ports, USB-A and HDMI 2.1, along with Wi-Fi 7 and Bluetooth 5.4.

For more top performers, see our guide to the best business laptops we've tested, as well as our best student laptops.

Also consider

Zenbook 14 OLED Copilot+ Laptop: was £1099 now £769
Prefer AMD? This black Zenbook model has a Ryzen AI 7 processor, 16GB LPDDR5X memory, and 1TB SSD. Grab this one if you need an AI-ready laptop with up to 50 TOPS NPU for official Copilot+ features.View Deal

Price context & historical value

AO has slashed the price of the Zenbook 14 OLED laptop from £1,199 to £849, saving you £350, or around 29%. AO members get an additional £38 discount. If you're not already a member, joining costs £39.99 a year, so just £1.99 more than the saving, which might be worth it if you're thinking of buying something else from AO this year.

I haven't found this exact configuration cheaper elsewhere right now, but it has been as low as £729 in the past.

Should you buy it?

✅ Buy the Asus Zenbook 14 OLED if...

You need a portable laptop for university, commuting or regularly working away from home. The combination of a compact aluminium chassis, 16GB of memory, 1TB of storage and up to 18 hours of battery life means it offers plenty of power for everyday work.

❌ Skip the Asus Zenbook 14 OLED if...

You want a laptop primarily for gaming. The integrated Intel Arc 140T graphics can handle some games, but there's no dedicated GPU, and the OLED display is limited to 60Hz, making it better suited to productivity, streaming and creative work.

The Catch: What to know before you buy

The display is OLED, but it's not one of the higher-resolution 2.8K or 3K panels found on some Zenbook models. You get a 1920 x 1200 resolution and 60Hz refresh rate, which are fairly basic specifications for a laptop originally priced at £1,199.

The memory is also LPDDR5X, which is typically soldered to the motherboard rather than installed in replaceable modules. That means you should consider 16GB as the maximum amount of RAM for this laptop.

• Shop all laptops at AO

A Formula 1 pit stop looks like a split-second sporting decision, but behind that call is a more complex challenge: making the right decision from constantly changing data, while there is still time to affect the outcome.

As artificial intelligence (AI) moves deeper into business operations, every industry is facing their own version of the pit-stop moment, whether that’s a bank deciding to approve or block a transaction, a telco detecting network degradation before customers notice, or a logistics provider rerouting a delivery before disruption becomes delay.

In each case, AI is only useful if it can understand what is happening now, interpret that information in context, and support action.

F1 is already solving this problem. It’s time for organizations to catch up.

Lesson 1: AI needs to see the race as it unfolds

No F1 team can make the right pit decision from an incomplete picture. It needs to know the condition of the tires, the position of competitors, the driver’s pace, and how the race is changing lap by lap. The same is true for enterprise AI. A retailer trying to manage availability needs to see demand, inventory, orders, and fulfilment constraints as they change.

This is where many organizations still find themselves held back. They’re not short on data. The problem is that their data often sits across different systems, applications, teams, and environments. Some data moves in real time. Some arrive in batches. Some is clean and trusted, while some needs work before it can be used safely.

For all the excitement around AI models, getting the value from AI starts with something more basic, which is the ability to sense what is happening across the business as it happens.

Lesson 2: Context turns signals into judgement

Visibility alone is not enough. In F1, live telemetry data only becomes useful when it is understood in context – a tire temperature spike means one thing on fresh rubber and another after 30 laps.

Similarly, in banking, a suspicious transaction cannot be judged by the amount alone. The system has to understand the customer’s normal behavior, recent activity, location, merchant, account history, and relevant risk policies before it can recommend whether to approve, block or investigate.

For AI to have any business value, it needs context. That lesson is especially important as enterprises move from AI assistants to agentic AI. Giving an AI system access to every database and application may make for an impressive pilot, but it does not guarantee the system understands what matters, what is current, or what can be trusted. In production, weak context turns speed into risk, particularly where money, trust or safety are involved.

Lesson 3: Let events trigger the next best action

Once AI has the right context, the next challenge is embedding that into the flow of the business. In many organizations, AI still sits one step removed from the operational process. Someone asks a question, reads a summary, and then decides what to do next.

A better approach is to connect AI to the business events already moving through the organization. In a streaming architecture, a delivery delay can become the signal that prompts an AI system to assess what is happening, draw on the relevant context and recommend the next best action.

F1 makes the criticality of this easy to see. The pit wall does not just need an interesting observation about tire degradation during a Grand Prix. It needs a clear, trusted recommendation based on what is happening in the race: box now or stay out.

The same logic applies to enterprise decisions. A logistics update is only useful if it can feed into routing, customer communication or inventory planning. The value comes from planting AI where operational decisions are actually made, rather than leaving it as a separate row of analysis.

Lesson 4: Every decision should improve the lesson

The final lesson is that real-time AI does not end with action. Every strategic call must become part of the next decision. Did the pit stop gain positions? Did the tire strategy hold up? Did the team act early enough?

That requires more from enterprises than logging the fact that AI recommended an action. Businesses need to connect recommendations to outcomes, so they can understand whether the decision improved the result. In practical terms, that means capturing the event that triggered the decision, the context the AI used, the recommendation it produced, the action taken, and the eventual business outcome.

Each review helps teams refine the data pipelines, evaluation criteria, and operational rules that shape the next action. Over time, the business gets better at understanding which interventions work and where AI needs more context before it can be trusted.

The race for real-time artificial intelligence

F1 is an extreme environment, but every industry has its own high-pressure moments. As AI moves from pilots and copilots into live business operations, its value will be decided in these moments. The winning advantage will go to organizations that can turn live signals into trusted context into better decisions – before the opportunity to get ahead has passed.

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In his latest book, the world-renowned physicist draws on science and philosophy to explore the notion that the university and reality are fully knowable.

• Domestic kill switches are no longer feasible, UK government warns
• AI companies and government need to work together to reduce the risks
• OpenAI and 100+ other companies warn of "limited window to strengthen" defenses

The UK Government has reportedly rejected calls to create an emergency AI kill switch, per BBC reporting, and it's largely because there are simply too many parties and factors to consider at this stage.

The Cabinet Office told the BBC that it "cannot simply turn AI off" because preventing access to a model or shutting down certain infrastructure would not stop the same model being developed and hosted, thus misused, elsewhere.

This is in response to MPs pushing for a statutory trigger that the government could pull in the event of an emergency.

UK government rules out AI kill switch

The government also implied that the responsibility lies with AI companies, and that developers have their own responsibility to build products with the appropriate safeguards.

Former OpenAI researcher Danial Kokotajlo also agrees that one country building a legal or technical kill switch would not be feasible, but Kokotajlo does see companies working together as one potential solution.

"Switching off access to an AI model in an emergency will do little to protect you," Kokotajlo explained in relation to a domestic kill switch. "You're still going to be steamrolled by the super intelligences created in the US."

The latest kill switch debates have emerged from a September 1 discussion in the House of Lords, partly fueled by an open letter warning of a "limited window to strengthen cyber defenses." More than 100 companies, including OpenAI, Anthropic, Google, Microsoft, AWS and Adobe issued the stark warning, urging governments, cybersecurity companies and frontier AI developers to come together.

"Our security services and regulators possess no specific agile statutory mechanism to compel a physical or digital shutdown," Lord Clement-Jones warned earlier this month about the potential of a rogue AI.

As for what's next, while an AI kill switch may be technically infeasible, we can certainly hope that the companies and bodies at the forefront of AI and legislation collaborate more effectively to reduce future risks.

Earlier this year, OpenAI launched a feature on ChatGPT meant to help people at risk of suicide connect with someone they trust for support. But its setup may prove challenging to someone in crisis.

(Image credit: Malte Mueller/Getty Images)