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The prepaid carrier Mint Mobile has been making headlines recently with its huge discounts on the latest Android flagships. Last week, I was shouting out the carrier's $500 discount on the Samsung Galaxy S26 series, but I've just spotted another great option.

It's a record-breaking $650 upfront discount on the latest Google Pixel 10, which is just $150 at the carrier today without the need for trading in. While you'll still need a plan, Mint Mobile is also offering a full year of unlimited data for just $180. That means a device and plan for just $329 upfront.

Getting such a decent phone for so cheap isn't to be ignored, and these types of deals have been incredibly popular at Mint Mobile over the past few months. Just a few weeks ago, the Galaxy S26 series sold out at the carrier, so I wouldn't be surprised if this Pixel 10 series deal did too.

This particular deal is listed as exclusive to new customers, though, so you may be excluded if you already have a line with Mint Mobile. As always, these deals are very much aimed at people looking to bundle up one of the latest phones with a super-cheap plan that really undercuts the traditional big carriers.

Record-breaking Google Pixel 10 deal at Mint Mobile

Google Pixel 10: was $799 now $149, plus one year of unlimited data for $180 at Mint Mobile
Mint Mobile's offered plenty of deals on the excellent Google Pixel 10 series recently, but none have come close to this week's record-beating discount. Right now, you can get a massive $650 off the device if you buy it upfront with a new plan. No trade-ins are needed at all here, and the carrier is also offering a full year of unlimited data for just $180 — that's just $15/mo on average.View Deal

• See more: check out all of today's deals at Mint Mobile

While you can technically get the Pixel 10 alongside any plan at Mint Mobile, the carrier has every plan listed at $180, so it makes sense to go for the option that's usually the priciest. And, it's a good plan, too. You get unlimited talk, text, and 50GB of high-speed 5G data per month for one of the most competitive prices on the market.

Note, if you're just interested in the plan and not the phone, then Mint Mobile also has some great 'bring your own device' summer specials currently. I've listed those out, alongside today's deal on the Galaxy S26 series, just below.

Also available at Mint Mobile this week...

Samsung Galaxy S26 series: $500 off, plus up to $400 off with a trade-in at Mint Mobile
Mint Mobile's latest deal on the Galaxy S26 series is one of the best I've ever seen from the well-known prepaid carrier. Not only can you get a record-breaking $500 upfront discount on a brand new device, but you'll also get a full year of unlimited data for just $180 — that's half price. On top of that, you can also trade in for an additional discount of up to $400 off, which is enough to cover the entire cost of the standard Galaxy S26.

Samsung Galaxy S26 Ultra: was $1,300 now $1,100
Samsung Galaxy S26 Plus: was $1,100 now $600View Deal

Mint Mobile unlimited data plan: was $360 now $180
If you've been curious about trying Mint Mobile, then now's a great time to jump on board. The carrier has just brought back its best-ever deal on its already good-value unlimited plan. Right now, you can get a full year of service for just $180 upfront, which equates to half price and just $15/mo on average.View Deal

The prepaid carrier Mint Mobile has been making headlines recently with its huge discounts on the latest Android flagships. Last week, I was shouting out the carrier's $500 discount on the Samsung Galaxy S26 series, but I've just spotted another great option.

It's a record-breaking $650 upfront discount on the latest Google Pixel 10, which is just $150 at the carrier today without the need for trading in. While you'll still need a plan, Mint Mobile is also offering a full year of unlimited data for just $180. That means a device and plan for just $329 upfront.

Getting such a decent phone for so cheap isn't to be ignored, and these types of deals have been incredibly popular at Mint Mobile over the past few months. Just a few weeks ago, the Galaxy S26 series sold out at the carrier, so I wouldn't be surprised if this Pixel 10 series deal did too.

This particular deal is listed as exclusive to new customers, though, so you may be excluded if you already have a line with Mint Mobile. As always, these deals are very much aimed at people looking to bundle up one of the latest phones with a super-cheap plan that really undercuts the traditional big carriers.

Record-breaking Google Pixel 10 deal at Mint Mobile

Google Pixel 10: was $799 now $149, plus one year of unlimited data for $180 at Mint Mobile
Mint Mobile's offered plenty of deals on the excellent Google Pixel 10 series recently, but none have come close to this week's record-beating discount. Right now, you can get a massive $650 off the device if you buy it upfront with a new plan. No trade-ins are needed at all here, and the carrier is also offering a full year of unlimited data for just $180 — that's just $15/mo on average.View Deal

• See more: check out all of today's deals at Mint Mobile

While you can technically get the Pixel 10 alongside any plan at Mint Mobile, the carrier has every plan listed at $180, so it makes sense to go for the option that's usually the priciest. And, it's a good plan, too. You get unlimited talk, text, and 50GB of high-speed 5G data per month for one of the most competitive prices on the market.

Note, if you're just interested in the plan and not the phone, then Mint Mobile also has some great 'bring your own device' summer specials currently. I've listed those out, alongside today's deal on the Galaxy S26 series, just below.

Also available at Mint Mobile this week...

Samsung Galaxy S26 series: $500 off, plus up to $400 off with a trade-in at Mint Mobile
Mint Mobile's latest deal on the Galaxy S26 series is one of the best I've ever seen from the well-known prepaid carrier. Not only can you get a record-breaking $500 upfront discount on a brand new device, but you'll also get a full year of unlimited data for just $180 — that's half price. On top of that, you can also trade in for an additional discount of up to $400 off, which is enough to cover the entire cost of the standard Galaxy S26.

Samsung Galaxy S26 Ultra: was $1,300 now $1,100
Samsung Galaxy S26 Plus: was $1,100 now $600View Deal

Mint Mobile unlimited data plan: was $360 now $180
If you've been curious about trying Mint Mobile, then now's a great time to jump on board. The carrier has just brought back its best-ever deal on its already good-value unlimited plan. Right now, you can get a full year of service for just $180 upfront, which equates to half price and just $15/mo on average.View Deal

"Extreme heat" is in the forecast this summer. How do people cope if they don't have air conditioning? Here are suggestions from a heat researcher who grew up in a very hot, AC-less place.

A new customer booking system, a bespoke CRM, or an app that can be sold as a new revenue stream. Small businesses are rarely short of great ideas, but often lack the time, funding, or technical expertise to go from idea to functional app.

This is the gap that vibe coding aims to fill, helping small businesses launch apps by combining plain English prompts with AI.

I caught up with Yoav Orlev, Head of Product at Base44, to get some insight into how small businesses can get the most out of vibe coding platforms. We also discuss some of the common pitfalls and risks associated with vibe coding and how to overcome them.

Vibe Coding has a lot of buzz around it, but what does it actually mean for the small businesses that can benefit from it?

The same quality output without the same budget

Instead of needing to know how to build an application, small business owners can just describe what they want and it gets built. They’re essentially having a conversation with AI instead of wrestling with tools, templates, or code. There are significant advantages to vibe-coding, including:

Removing the “gatekeepers"

Previously, a small business owner who wanted a professional website had two options: pay a developer (expensive) or spend hours learning code (time-consuming). Vibe coding collapses both into a single conversation. A florist, a personal trainer, a local accountant, anyone can now describe their business and get a professional application without any technical knowledge.

Speed to market changes everything

A small business can go from idea to functional application in minutes, not weeks. For a new business owner, that's the difference between launching now and launching never.

Iteration becomes effortless

Want to change your text? Swap your color scheme? Add an agent? Instead of digging through menus or calling a developer, you just type what you want changed via natural conversion. Small businesses can now move and adapt as fast as their ideas do.

The playing field levels out

Enterprise businesses have had dev teams, agencies, and big wallets for years. Vibe coding gives small businesses access to the same quality output without the same budget. This is a significant shift, letting smaller businesses compete with larger ones.

Vibe coding means that for the first time, the barrier to having a custom application is no longer technical skill or budget. That's a meaningful unlock for millions of small business owners who previously felt locked out of the growing digital economy.

For years, small businesses have benefited from drag-and-drop tools. How has vibe coding changed this approach? What new benefits does it bring to the table?

Users are now not operating a tool but collaborating with one.

Drag-and-drop was a genuine breakthrough. It opened up web creation to anyone, regardless of technical skill or budget constraints. Users needed to know what they wanted, where to put it, and how to make it look right, but they had more access and guidance than ever before.

Vibe coding starts the create-and-build process with a conversation. Users describe their business and goals, and the platform builds around that. It's a fundamentally different kind of interaction than drag-and-drop. Users are now not operating a tool but collaborating with one.

Vibe coding isn't here to replace drag-and-drop, and that's an important distinction. Both have real advantages. Vibe coding wins on speed and ease of use. Drag-and-drop gives users precision and hands-on creative control. The real breakthrough for small businesses is having both working together seamlessly by describing what they need, letting AI get there fast, then fine-tuning the details manually without ever switching platforms or starting over.

That combination is what gives small businesses a truly holistic way to build and grow an online presence. Less time building and more time focusing on their business.

If an entrepreneur wanted to build a tool for their business today, where should they start? What does a good prompt look like?

A first prompt doesn't need to be perfect. Get something on the screen, react to it, and refine from there.

The best place to start is with the problem, not the solution.

Before opening any tool or writing a single prompt, an entrepreneur should get specific about what's actually slowing their business down. Is it taking bookings manually over the phone? Chasing invoices? Answering the same customer questions over and over? The clearest prompts come from the clearest problems.

When it comes to writing a good prompt, specificity is everything.

A weak prompt sounds like "build me a website for my business." A strong prompt sounds like "I run a mobile dog grooming service in Chicago with three employees. I need a way for customers to book appointments online, see my pricing by dog size, and get automatic confirmation texts."

The more context users give, such as industry, customer, specific workflow, and the outcome that’s trying to be achieved, the more useful the result. Think of it less like a search query and more like briefing a new hire on their first day. The AI works best when it understands not just what you want, but why you need it.

From there, iteration is your best friend. A first prompt doesn't need to be perfect. Get something on the screen, react to it, and refine from there. The most effective builders treat it as a back-and-forth conversation rather than a one-shot request.

What are some common examples of small businesses using vibe coding to build internal tools? Which do you believe are the most valuable and why?

The range of tools small businesses are building with vibe coding is remarkable. We're seeing everything from custom booking and scheduling systems, to lightweight CRM and lead tracking tools, client-facing portals, invoice generators, staff onboarding wikis, loyalty program trackers, and more.

The most valuable apps tend to be the ones replacing a manual process that was quietly costing the business time or customers. Custom booking systems are one standout. For service-based businesses, time is the product, and a system built around their exact workflow has a direct and immediate impact on revenue. Lightweight CRM tools are another reason because most small businesses aren't losing customers due to bad service; they're losing them because follow-up falls through the cracks. A tool built around how they actually sell, rather than how generic software thinks they should, makes all the difference.

The common thread is fit. What makes vibe coding genuinely powerful for small businesses is that they can build exactly what they need and tailored for them, rather than settling for something “close enough.” That's a shift that levels the playing field in a very real way.

Can entrepreneurs also use vibe coding to build customer-facing tools and new revenue streams? What are some good examples of this?

Absolutely! This where vibe coding starts to look less like a productivity tool and more like a genuine business accelerator. The same technology that helps a small business automate internal processes can also help them build entirely new products, services, and revenue streams that simply weren't accessible before without a development budget.

The examples are wide-ranging. A personal trainer can go beyond selling sessions and build a branded fitness app where clients track workouts and access custom programs, turning a one-to-one service into a scalable product. A marketing consultant can build a self-serve audit tool that generates leads while they sleep. A local chef can launch a meal planning subscription with a custom interface rather than relying on a third-party platform that takes a cut of every transaction. A retailer can build a personalized product recommendation quiz that increases average order value without touching their core website.

What all of these have in common is that they were previously only realistic for businesses with developer resources and big pockets. Vibe coding changes that entirely. The barrier to launching a new revenue stream is no longer technical and costly. It's just having the idea and the ambition to act on it.

Some business owners (myself included) have found ourselves stuck in a loop where AI fixes one issue, but breaks several others. What are some golden rules users can apply to get back on track when the ‘vibe’ goes wrong?

1. If possible, try to break down your request into smaller pieces. Sometimes, when trying to add too many features at once, the agent makes a mistake.
2. If something doesn't work at first, be very specific and clear. In many cases, it can also be helpful to state what the AI shouldn't do. For example, tell AI to change the layout, but make sure not to change any colors in the app.
3. Almost all vibe coding platforms allow users to revert. So if you are failing to add something 3 or 4 times in a row, then revert to the last successful version and try in a slightly different way.
4. Search the tool documentation. There are usually many examples and “how tos” that can carry you over a certain hurdle.

What are some of the pitfalls and risks that entrepreneurs should be aware of when vibe coding internal tools and potential products? 

There are 2 main pitfalls we see.

1. Not giving your product to users. We talk to a lot of users who keep building more and more features, since it's so easy, yet they hold off releasing the product, fearing it's too early. Don't. AI is all about moving as fast as possible. If you have a working product that will help someone, put it in the hands of users and get feedback as quickly as possible. Worry less about the perfect product and more about usage.
2. Security is huge. Most tools nowadays offer security scans, but as a builder, make sure you take the time to really understand how the scan works, what it covers, and what issues you might face. Most tools will cover you, but only if you know how to leverage them. Take the time to learn it or consult someone who can walk you through it.

A new customer booking system, a bespoke CRM, or an app that can be sold as a new revenue stream. Small businesses are rarely short of great ideas, but often lack the time, funding, or technical expertise to go from idea to functional app.

This is the gap that vibe coding aims to fill, helping small businesses launch apps by combining plain English prompts with AI.

I caught up with Yoav Orlev, Head of Product at Base44, to get some insight into how small businesses can get the most out of vibe coding platforms. We also discuss some of the common pitfalls and risks associated with vibe coding and how to overcome them.

Vibe Coding has a lot of buzz around it, but what does it actually mean for the small businesses that can benefit from it?

The same quality output without the same budget

Instead of needing to know how to build an application, small business owners can just describe what they want and it gets built. They’re essentially having a conversation with AI instead of wrestling with tools, templates, or code. There are significant advantages to vibe-coding, including:

Removing the “gatekeepers"

Previously, a small business owner who wanted a professional website had two options: pay a developer (expensive) or spend hours learning code (time-consuming). Vibe coding collapses both into a single conversation. A florist, a personal trainer, a local accountant, anyone can now describe their business and get a professional application without any technical knowledge.

Speed to market changes everything

A small business can go from idea to functional application in minutes, not weeks. For a new business owner, that's the difference between launching now and launching never.

Iteration becomes effortless

Want to change your text? Swap your color scheme? Add an agent? Instead of digging through menus or calling a developer, you just type what you want changed via natural conversion. Small businesses can now move and adapt as fast as their ideas do.

The playing field levels out

Enterprise businesses have had dev teams, agencies, and big wallets for years. Vibe coding gives small businesses access to the same quality output without the same budget. This is a significant shift, letting smaller businesses compete with larger ones.

Vibe coding means that for the first time, the barrier to having a custom application is no longer technical skill or budget. That's a meaningful unlock for millions of small business owners who previously felt locked out of the growing digital economy.

For years, small businesses have benefited from drag-and-drop tools. How has vibe coding changed this approach? What new benefits does it bring to the table?

Users are now not operating a tool but collaborating with one.

Drag-and-drop was a genuine breakthrough. It opened up web creation to anyone, regardless of technical skill or budget constraints. Users needed to know what they wanted, where to put it, and how to make it look right, but they had more access and guidance than ever before.

Vibe coding starts the create-and-build process with a conversation. Users describe their business and goals, and the platform builds around that. It's a fundamentally different kind of interaction than drag-and-drop. Users are now not operating a tool but collaborating with one.

Vibe coding isn't here to replace drag-and-drop, and that's an important distinction. Both have real advantages. Vibe coding wins on speed and ease of use. Drag-and-drop gives users precision and hands-on creative control. The real breakthrough for small businesses is having both working together seamlessly by describing what they need, letting AI get there fast, then fine-tuning the details manually without ever switching platforms or starting over.

That combination is what gives small businesses a truly holistic way to build and grow an online presence. Less time building and more time focusing on their business.

If an entrepreneur wanted to build a tool for their business today, where should they start? What does a good prompt look like?

A first prompt doesn't need to be perfect. Get something on the screen, react to it, and refine from there.

The best place to start is with the problem, not the solution.

Before opening any tool or writing a single prompt, an entrepreneur should get specific about what's actually slowing their business down. Is it taking bookings manually over the phone? Chasing invoices? Answering the same customer questions over and over? The clearest prompts come from the clearest problems.

When it comes to writing a good prompt, specificity is everything.

A weak prompt sounds like "build me a website for my business." A strong prompt sounds like "I run a mobile dog grooming service in Chicago with three employees. I need a way for customers to book appointments online, see my pricing by dog size, and get automatic confirmation texts."

The more context users give, such as industry, customer, specific workflow, and the outcome that’s trying to be achieved, the more useful the result. Think of it less like a search query and more like briefing a new hire on their first day. The AI works best when it understands not just what you want, but why you need it.

From there, iteration is your best friend. A first prompt doesn't need to be perfect. Get something on the screen, react to it, and refine from there. The most effective builders treat it as a back-and-forth conversation rather than a one-shot request.

What are some common examples of small businesses using vibe coding to build internal tools? Which do you believe are the most valuable and why?

The range of tools small businesses are building with vibe coding is remarkable. We're seeing everything from custom booking and scheduling systems, to lightweight CRM and lead tracking tools, client-facing portals, invoice generators, staff onboarding wikis, loyalty program trackers, and more.

The most valuable apps tend to be the ones replacing a manual process that was quietly costing the business time or customers. Custom booking systems are one standout. For service-based businesses, time is the product, and a system built around their exact workflow has a direct and immediate impact on revenue. Lightweight CRM tools are another reason because most small businesses aren't losing customers due to bad service; they're losing them because follow-up falls through the cracks. A tool built around how they actually sell, rather than how generic software thinks they should, makes all the difference.

The common thread is fit. What makes vibe coding genuinely powerful for small businesses is that they can build exactly what they need and tailored for them, rather than settling for something “close enough.” That's a shift that levels the playing field in a very real way.

Can entrepreneurs also use vibe coding to build customer-facing tools and new revenue streams? What are some good examples of this?

Absolutely! This where vibe coding starts to look less like a productivity tool and more like a genuine business accelerator. The same technology that helps a small business automate internal processes can also help them build entirely new products, services, and revenue streams that simply weren't accessible before without a development budget.

The examples are wide-ranging. A personal trainer can go beyond selling sessions and build a branded fitness app where clients track workouts and access custom programs, turning a one-to-one service into a scalable product. A marketing consultant can build a self-serve audit tool that generates leads while they sleep. A local chef can launch a meal planning subscription with a custom interface rather than relying on a third-party platform that takes a cut of every transaction. A retailer can build a personalized product recommendation quiz that increases average order value without touching their core website.

What all of these have in common is that they were previously only realistic for businesses with developer resources and big pockets. Vibe coding changes that entirely. The barrier to launching a new revenue stream is no longer technical and costly. It's just having the idea and the ambition to act on it.

Some business owners (myself included) have found ourselves stuck in a loop where AI fixes one issue, but breaks several others. What are some golden rules users can apply to get back on track when the ‘vibe’ goes wrong?

1. If possible, try to break down your request into smaller pieces. Sometimes, when trying to add too many features at once, the agent makes a mistake.
2. If something doesn't work at first, be very specific and clear. In many cases, it can also be helpful to state what the AI shouldn't do. For example, tell AI to change the layout, but make sure not to change any colors in the app.
3. Almost all vibe coding platforms allow users to revert. So if you are failing to add something 3 or 4 times in a row, then revert to the last successful version and try in a slightly different way.
4. Search the tool documentation. There are usually many examples and “how tos” that can carry you over a certain hurdle.

What are some of the pitfalls and risks that entrepreneurs should be aware of when vibe coding internal tools and potential products? 

There are 2 main pitfalls we see.

1. Not giving your product to users. We talk to a lot of users who keep building more and more features, since it's so easy, yet they hold off releasing the product, fearing it's too early. Don't. AI is all about moving as fast as possible. If you have a working product that will help someone, put it in the hands of users and get feedback as quickly as possible. Worry less about the perfect product and more about usage.
2. Security is huge. Most tools nowadays offer security scans, but as a builder, make sure you take the time to really understand how the scan works, what it covers, and what issues you might face. Most tools will cover you, but only if you know how to leverage them. Take the time to learn it or consult someone who can walk you through it.

When a trusted friend recommends a product or service to you, it can alter the way you think about the potential purchase. You tend to lower your guard, with the knowledge that some of the filtering work has already been done on your behalf.

This is particularly true when that friend understands your tastes and priorities, and how much you’re looking to spend; the recommendation carries weight before you even visit the website or look at the product page. By the time you click, a large part of the decision has already been made.

Now there is evidence that AI recommendations can have a similar effect on consumers.

We recently analyzed web traffic and conversion data from more than 35,000 ecommerce brands using Shopify and it revealed something significant: referrals from AI tools such as ChatGPT are converting at an average rate of 3.6%, compared with 1.23% for traditional Google search traffic. AI referrals are also generating around 30% higher revenue per session.

For ecommerce businesses, these findings point to an important change in consumer behavior that presents both an opportunity and a challenge.

The buying journey is changing

For years, digital marketing strategies have been built around search engines. A user enters keywords, compares links, visits multiple sites and eventually makes a decision. Brands compete to win the click, then persuade the customer after they arrive.

AI is changing the sequence.

Consumers are no longer simply typing broad phrases like “best running shoes” or “cheap Bluetooth speaker”. Instead, they are asking the likes of ChatGPT highly detailed questions tailored to their exact needs.

Where previously the user might have received a list of product websites to explore, now they are being given a specific tailor-made recommendation.

In effect, AI platforms are compressing the consideration stage of the buying journey. Much of the evaluation happens before the consumer reaches the brand’s website. By the time they click through, they already have a degree of confidence in the recommendation they have been given – much like the case of the recommendation from a friend.

This creates a different type of visitor altogether.

Traditional search traffic can often be broad and exploratory. AI-referred visitors, however, increasingly resemble ‘pre-qualified’ leads. They arrive with clearer expectations and stronger buying intent, which helps explain the higher conversion rates.

Why visibility now means something different

For brands, the opportunity is clear: higher intent traffic generally means stronger revenue per visitor and more efficient acquisition.

The challenge, however, is that many ecommerce businesses are still measuring success using frameworks built for the ‘traditional’ approach.

A large proportion of marketing strategies remain heavily focused on traffic volumes, click-through rates and keyword rankings. Yet AI recommendation systems rely on different signals. Visibility inside AI-generated answers depends less on traditional advertising tactics and more on credibility, authority and contextual relevance across the wider web.

Brands are no longer only competing for search rankings. They are competing to become trusted sources within the information ecosystem AI tools rely upon.

That has major implications for how companies think about content and discoverability.

Reviews become more influential because AI systems frequently incorporate them into recommendations. Third-party editorial coverage matters more because it contributes to authority and trustworthiness. Community discussions on forums and social media also gain importance because they help establish credibility and context.

The businesses that perform well in AI-driven discovery are likely to be those with strong reputations spread consistently across multiple trusted sources, rather than those relying purely on aggressive performance marketing.

Rethinking marketing measurement

There is another important lesson in this data. Many businesses may currently have an incomplete understanding of which channels are genuinely driving growth.

One of the perennial challenges with digital advertising is ‘attribution distortion’. In simple terms, platforms optimize for conversions, often retargeting existing customers or users who were already close to purchasing. This can create inflated perceptions of acquisition performance.

At the same time, AI-referred traffic may still be under-measured inside many organizations because it remains a comparatively new source of inbound visitors.

The danger is that businesses continue over-investing in channels that appear successful according to legacy metrics while underestimating emerging forms of high-intent traffic.

This matters because AI-driven discovery is likely to become more important over time.

Consumer expectations are evolving rapidly. People increasingly want answers tailored to their exact circumstances rather than broad lists of generic options. AI interfaces are naturally suited to that type of interaction because they can process nuance and context in ways traditional search engines struggle to replicate.

What brands should do next

Brands therefore need to rethink not only where they advertise, but how they present their offer online altogether.

That starts with understanding how the business appears across the wider digital landscape. Are reviews consistent and trustworthy? Is the brand being referenced by credible publications and communities? Is product information clear, accurate and useful?

It also means creating content that answers real consumer questions in detailed and genuinely helpful ways, rather than simply targeting high-volume keywords.

None of this means traditional search is disappearing overnight. Search engines remain hugely important, and publishers continue to play a central role in shaping the information AI systems consume and reference.

What is changing is the path consumers take before making decisions.

The era of winning attention purely through visibility is gradually giving way to an era of winning trust before the click ever happens.

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When a trusted friend recommends a product or service to you, it can alter the way you think about the potential purchase. You tend to lower your guard, with the knowledge that some of the filtering work has already been done on your behalf.

This is particularly true when that friend understands your tastes and priorities, and how much you’re looking to spend; the recommendation carries weight before you even visit the website or look at the product page. By the time you click, a large part of the decision has already been made.

Now there is evidence that AI recommendations can have a similar effect on consumers.

We recently analyzed web traffic and conversion data from more than 35,000 ecommerce brands using Shopify and it revealed something significant: referrals from AI tools such as ChatGPT are converting at an average rate of 3.6%, compared with 1.23% for traditional Google search traffic. AI referrals are also generating around 30% higher revenue per session.

For ecommerce businesses, these findings point to an important change in consumer behavior that presents both an opportunity and a challenge.

The buying journey is changing

For years, digital marketing strategies have been built around search engines. A user enters keywords, compares links, visits multiple sites and eventually makes a decision. Brands compete to win the click, then persuade the customer after they arrive.

AI is changing the sequence.

Consumers are no longer simply typing broad phrases like “best running shoes” or “cheap Bluetooth speaker”. Instead, they are asking the likes of ChatGPT highly detailed questions tailored to their exact needs.

Where previously the user might have received a list of product websites to explore, now they are being given a specific tailor-made recommendation.

In effect, AI platforms are compressing the consideration stage of the buying journey. Much of the evaluation happens before the consumer reaches the brand’s website. By the time they click through, they already have a degree of confidence in the recommendation they have been given – much like the case of the recommendation from a friend.

This creates a different type of visitor altogether.

Traditional search traffic can often be broad and exploratory. AI-referred visitors, however, increasingly resemble ‘pre-qualified’ leads. They arrive with clearer expectations and stronger buying intent, which helps explain the higher conversion rates.

Why visibility now means something different

For brands, the opportunity is clear: higher intent traffic generally means stronger revenue per visitor and more efficient acquisition.

The challenge, however, is that many ecommerce businesses are still measuring success using frameworks built for the ‘traditional’ approach.

A large proportion of marketing strategies remain heavily focused on traffic volumes, click-through rates and keyword rankings. Yet AI recommendation systems rely on different signals. Visibility inside AI-generated answers depends less on traditional advertising tactics and more on credibility, authority and contextual relevance across the wider web.

Brands are no longer only competing for search rankings. They are competing to become trusted sources within the information ecosystem AI tools rely upon.

That has major implications for how companies think about content and discoverability.

Reviews become more influential because AI systems frequently incorporate them into recommendations. Third-party editorial coverage matters more because it contributes to authority and trustworthiness. Community discussions on forums and social media also gain importance because they help establish credibility and context.

The businesses that perform well in AI-driven discovery are likely to be those with strong reputations spread consistently across multiple trusted sources, rather than those relying purely on aggressive performance marketing.

Rethinking marketing measurement

There is another important lesson in this data. Many businesses may currently have an incomplete understanding of which channels are genuinely driving growth.

One of the perennial challenges with digital advertising is ‘attribution distortion’. In simple terms, platforms optimize for conversions, often retargeting existing customers or users who were already close to purchasing. This can create inflated perceptions of acquisition performance.

At the same time, AI-referred traffic may still be under-measured inside many organizations because it remains a comparatively new source of inbound visitors.

The danger is that businesses continue over-investing in channels that appear successful according to legacy metrics while underestimating emerging forms of high-intent traffic.

This matters because AI-driven discovery is likely to become more important over time.

Consumer expectations are evolving rapidly. People increasingly want answers tailored to their exact circumstances rather than broad lists of generic options. AI interfaces are naturally suited to that type of interaction because they can process nuance and context in ways traditional search engines struggle to replicate.

What brands should do next

Brands therefore need to rethink not only where they advertise, but how they present their offer online altogether.

That starts with understanding how the business appears across the wider digital landscape. Are reviews consistent and trustworthy? Is the brand being referenced by credible publications and communities? Is product information clear, accurate and useful?

It also means creating content that answers real consumer questions in detailed and genuinely helpful ways, rather than simply targeting high-volume keywords.

None of this means traditional search is disappearing overnight. Search engines remain hugely important, and publishers continue to play a central role in shaping the information AI systems consume and reference.

What is changing is the path consumers take before making decisions.

The era of winning attention purely through visibility is gradually giving way to an era of winning trust before the click ever happens.

We've tested the best email marketing platforms on the market.

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

AI took enterprises by storm, with many opting for integration as fast as possible in fear of falling behind the more ambitious tech adopters. But speed alone isn’t always an advantage and as a result, 95% of enterprise pilot programs still failed to deliver measurable financial returns just last year.

Now that we’re a few years past the initial AI explosion, the pressure is on to prove true ROI from these projects.

Businesses have most frequently poured resources into AI tools aimed at boosting productivity and automating workflow in hopes to target the most universal, longest standing business goal: doing more with less. But what leaders should be doing is identifying where the technology can solve the biggest issues specific to today’s business climate. One of those issues is cash flow forecasting.

This year, 52% of American CFOs named cost management as their most worrisome internal concern. While a well-oiled cost management strategy remains critical for creating a strong financial cushion and remaining resilient, balancing fixed operations with constantly shifting real world variables is never easy.

As companies increasingly look for ways to remain nimble and improve decision-making, those that can leverage AI to forecast trends in cash flow demand, churn risk, and spending pattern shifts will find themselves on a quicker path to ROI. Doing so requires harnessing the right data, and these financial signals are hidden in the transaction layer.

While businesses have long mined transaction data for traditional analytics and reporting, it’s far under-utilized in AI strategies. There needs to be a shift from viewing these insights as archival records of past performance to real time indicators of what’s to come.

Making revenue forecasting more adaptive

There are several revenue indicators that lie within bottom funnel operations that AI has the ability of turning into actionable insights. From frequently adjusted terms within contract renewals to the average time it’s taking customers to finalize transactions, purchase signals like these can help AI systems make smarter predictions about demand or accounts receivable.

To provide a more granular view into the value of this data layer, let’s look at upgrade or renewal activity for example. Customer retention is a key element to maintaining predictable cash flow and is among the first to go during an economic shakeup.

Tracking accounts that consistently upgrade a product or service on time to see that they suddenly miss a milestone could immediately flag eventual churn risk. These deviations should also be compared across similar accounts to segment risk based on geography, product lines, or size and industry.

From there, leaders can act proactively with strategies like targeted discounts or incentive measures to encourage retention. Alternatively, accounts that are expanding faster than expected could provide predictions into other customers who might be ready for higher value offerings.

Identifying cues like those that often precede cancellations, along with delayed payments, reduced usage, or smaller order size for instance, can equip finance or leadership teams with rolling forecasts. Whereas on the other hand, monthly or quarterly forecasts typically only rely on historical averages and don’t provide the real time guidance needed for a quickly shifting marketplace.

This can manifest into a powerful decision-making engine. One that is dynamic enough to support flexible cost management strategies. Seeing where cash-flow is moving allows leaders to make more informed decisions.

For example, if it’s consistently being found that these customers are upgrading at slower rates then it may be a good indicator to preemptively reduce inventory or relax timelines for product development teams. In turn, leaders can avoid allocating too many resources to demand that may not end up materializing.

This also gives teams more flexibility to adjust spending and production before any cash flow pressure sets in.

An important element to keep in mind is that these purchasing behavior insights often sit across separate systems. While sales teams may have insights into average order values, only legal or finance may know how payment terms are changing across clients.

First mapping where all of these metrics currently live is critical to then unify them into one place for predictive models to cross-analyze everything against each other and make stronger recommendations.

Connecting to ROI directly

Many businesses have revolved their AI projects around generative AI for efficiency gains in producing content or developing software for instance. But not only are these task-level initiatives harder to prove a measurable impact from, in some cases they end up hurting productivity in the long run with added time spent reviewing and editing AI outputs.

When it comes to analyzing data for forecasting and predictions, AI has shown immense value and is tied to more tangible business outcomes. Now, forecasting real time insights tied directly to revenue can help leaders remain adaptable in an increasingly unpredictable economy, offering a fast track to ROI on these projects.

We've featured the best AI website builders.

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

AI took enterprises by storm, with many opting for integration as fast as possible in fear of falling behind the more ambitious tech adopters. But speed alone isn’t always an advantage and as a result, 95% of enterprise pilot programs still failed to deliver measurable financial returns just last year.

Now that we’re a few years past the initial AI explosion, the pressure is on to prove true ROI from these projects.

Businesses have most frequently poured resources into AI tools aimed at boosting productivity and automating workflow in hopes to target the most universal, longest standing business goal: doing more with less. But what leaders should be doing is identifying where the technology can solve the biggest issues specific to today’s business climate. One of those issues is cash flow forecasting.

This year, 52% of American CFOs named cost management as their most worrisome internal concern. While a well-oiled cost management strategy remains critical for creating a strong financial cushion and remaining resilient, balancing fixed operations with constantly shifting real world variables is never easy.

As companies increasingly look for ways to remain nimble and improve decision-making, those that can leverage AI to forecast trends in cash flow demand, churn risk, and spending pattern shifts will find themselves on a quicker path to ROI. Doing so requires harnessing the right data, and these financial signals are hidden in the transaction layer.

While businesses have long mined transaction data for traditional analytics and reporting, it’s far under-utilized in AI strategies. There needs to be a shift from viewing these insights as archival records of past performance to real time indicators of what’s to come.

Making revenue forecasting more adaptive

There are several revenue indicators that lie within bottom funnel operations that AI has the ability of turning into actionable insights. From frequently adjusted terms within contract renewals to the average time it’s taking customers to finalize transactions, purchase signals like these can help AI systems make smarter predictions about demand or accounts receivable.

To provide a more granular view into the value of this data layer, let’s look at upgrade or renewal activity for example. Customer retention is a key element to maintaining predictable cash flow and is among the first to go during an economic shakeup.

Tracking accounts that consistently upgrade a product or service on time to see that they suddenly miss a milestone could immediately flag eventual churn risk. These deviations should also be compared across similar accounts to segment risk based on geography, product lines, or size and industry.

From there, leaders can act proactively with strategies like targeted discounts or incentive measures to encourage retention. Alternatively, accounts that are expanding faster than expected could provide predictions into other customers who might be ready for higher value offerings.

Identifying cues like those that often precede cancellations, along with delayed payments, reduced usage, or smaller order size for instance, can equip finance or leadership teams with rolling forecasts. Whereas on the other hand, monthly or quarterly forecasts typically only rely on historical averages and don’t provide the real time guidance needed for a quickly shifting marketplace.

This can manifest into a powerful decision-making engine. One that is dynamic enough to support flexible cost management strategies. Seeing where cash-flow is moving allows leaders to make more informed decisions.

For example, if it’s consistently being found that these customers are upgrading at slower rates then it may be a good indicator to preemptively reduce inventory or relax timelines for product development teams. In turn, leaders can avoid allocating too many resources to demand that may not end up materializing.

This also gives teams more flexibility to adjust spending and production before any cash flow pressure sets in.

An important element to keep in mind is that these purchasing behavior insights often sit across separate systems. While sales teams may have insights into average order values, only legal or finance may know how payment terms are changing across clients.

First mapping where all of these metrics currently live is critical to then unify them into one place for predictive models to cross-analyze everything against each other and make stronger recommendations.

Connecting to ROI directly

Many businesses have revolved their AI projects around generative AI for efficiency gains in producing content or developing software for instance. But not only are these task-level initiatives harder to prove a measurable impact from, in some cases they end up hurting productivity in the long run with added time spent reviewing and editing AI outputs.

When it comes to analyzing data for forecasting and predictions, AI has shown immense value and is tied to more tangible business outcomes. Now, forecasting real time insights tied directly to revenue can help leaders remain adaptable in an increasingly unpredictable economy, offering a fast track to ROI on these projects.

We've featured the best AI website builders.

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

You know what Rick and Morty season 9 has been missing so far? Something marginally normal. Thankfully, Morty and Summer are off to summer camp (the season, that is — they didn't name the camp after her) in this week's episode.

Obviously, I'm being hopelessly naive in thinking that this is going to resemble anything like a routine summer-camp adventure, especially seeing as Beth and Rick are being left home alone in the meantime; I mean, what could go wrong — at either venue?

It's exhausting even trying to guess at what's coming, so I might as well stop trying, and answer the question you're here to have answered: when does Rick and Morty season 9 episode 9 arrive on Adult Swim, Hulu, and HBO Max?

What time can I watch Rick and Morty season 9 episode 9 on Adult Swim, Hulu, and HBO Max?

In the US, Rick and Morty season 9 episode 9 will debut on Adult Swim on Sunday, July 19 at 8pm PT / 11pm ET.

Viewers elsewhere, as well as in the US, have two streaming options: Hulu and HBO Max. Episodes should appear on these platforms 24 hours after they've aired on Adult Swim, meaning you can expect episode 9 to land on Monday, July 20.

These are the timings you need to take note of:

• US – 12am PT / 3am ET
• Canada – 12am PT / 3am ET
• UK – 8am BST
• India – 12:30pm IST
• Singapore – 3pm SGT
• Australia – 6pm AEST
• New Zealand – 8pm NZDT

When do new episodes of Rick and Morty season 9 come out?

(Image credit: Adult Swim)

Rick and Morty season 9 is set to have 10 episodes. As long as there are no unexpected delays, we can expect it to follow the following release schedule:

• Episode 1: out now
• Episode 2: out now
• Episode 3: out now
• Episode 4: out now
• Episode 5: out now
• Episode 6: out now
• Episode 7: out now
• Episode 8: out now
• Episode 9: July 19
• Episode 10: July 26

You know what Rick and Morty season 9 has been missing so far? Something marginally normal. Thankfully, Morty and Summer are off to summer camp (the season, that is — they didn't name the camp after her) in this week's episode.

Obviously, I'm being hopelessly naive in thinking that this is going to resemble anything like a routine summer-camp adventure, especially seeing as Beth and Rick are being left home alone in the meantime; I mean, what could go wrong — at either venue?

It's exhausting even trying to guess at what's coming, so I might as well stop trying, and answer the question you're here to have answered: when does Rick and Morty season 9 episode 9 arrive on Adult Swim, Hulu, and HBO Max?

What time can I watch Rick and Morty season 9 episode 9 on Adult Swim, Hulu, and HBO Max?

In the US, Rick and Morty season 9 episode 9 will debut on Adult Swim on Sunday, July 19 at 8pm PT / 11pm ET.

Viewers elsewhere, as well as in the US, have two streaming options: Hulu and HBO Max. Episodes should appear on these platforms 24 hours after they've aired on Adult Swim, meaning you can expect episode 9 to land on Monday, July 20.

These are the timings you need to take note of:

• US – 12am PT / 3am ET
• Canada – 12am PT / 3am ET
• UK – 8am BST
• India – 12:30pm IST
• Singapore – 3pm SGT
• Australia – 6pm AEST
• New Zealand – 8pm NZDT

When do new episodes of Rick and Morty season 9 come out?

(Image credit: Adult Swim)

Rick and Morty season 9 is set to have 10 episodes. As long as there are no unexpected delays, we can expect it to follow the following release schedule:

• Episode 1: out now
• Episode 2: out now
• Episode 3: out now
• Episode 4: out now
• Episode 5: out now
• Episode 6: out now
• Episode 7: out now
• Episode 8: out now
• Episode 9: July 19
• Episode 10: July 26

• New York State has temporarily banned new, large-scale data centers
• One-year moratorium affects new 50MW+ campuses
• NY wants to assess community, environmental and grid impacts

New York State has banned the construction of new hyperscaler data centers, marking the latest step as mounting local opposition against AI and cloud facilities builds, with communities citing concerns over rising electricity costs, water consumption and other environmental factors,

State Governor Kathy Hochul is responsible for introducing the first statewide moratorium on new campuses, which imposes a one-year pause while the state looks into the environment, energy supply and communities.

Projects that have already been permitted will still continue as expected, but new buildouts will face restrictions and delays until the moratorium is lifted.

Data centers banned in NY - for one year

The one-year ban buys the state time to evolve regulations to address some of the challenges presented by large hyperscaler data centers, including strained grid supplies, emissions and other environmental impacts, and stresses on local communities.

Under the new ban, campuses that require at least 50MW of electricity will be affected, which for an AI data center isn't all that much. Some of the largest measure power consumption in the hundreds of megawatts, or even gigawatts in the case of high-profile, flagship campuses like OpenAI's Stargate Project.

"[The moratorium] comes as the direct result of immense public pressure from people across the state demanding their elected leaders protect them from Big Tech's assault, which threatens the state's clean air and water and New Yorkers' financial security," New York State's Food & Water Watch Director Laura Shindell said.

"New York has always been at the forefront of innovation and change but we’ve also always guaranteed that New Yorkers benefit," Hochul noted.

Although New York represents the first statewide temporary ban, other regions have also been looking to pause buildouts as they assess the damages. Just last month, Seattle also voted to ban new projects for a year.

• New York State has temporarily banned new, large-scale data centers
• One-year moratorium affects new 50MW+ campuses
• NY wants to assess community, environmental and grid impacts

New York State has banned the construction of new hyperscaler data centers, marking the latest step as mounting local opposition against AI and cloud facilities builds, with communities citing concerns over rising electricity costs, water consumption and other environmental factors,

State Governor Kathy Hochul is responsible for introducing the first statewide moratorium on new campuses, which imposes a one-year pause while the state looks into the environment, energy supply and communities.

Projects that have already been permitted will still continue as expected, but new buildouts will face restrictions and delays until the moratorium is lifted.

Data centers banned in NY - for one year

The one-year ban buys the state time to evolve regulations to address some of the challenges presented by large hyperscaler data centers, including strained grid supplies, emissions and other environmental impacts, and stresses on local communities.

Under the new ban, campuses that require at least 50MW of electricity will be affected, which for an AI data center isn't all that much. Some of the largest measure power consumption in the hundreds of megawatts, or even gigawatts in the case of high-profile, flagship campuses like OpenAI's Stargate Project.

"[The moratorium] comes as the direct result of immense public pressure from people across the state demanding their elected leaders protect them from Big Tech's assault, which threatens the state's clean air and water and New Yorkers' financial security," New York State's Food & Water Watch Director Laura Shindell said.

"New York has always been at the forefront of innovation and change but we’ve also always guaranteed that New Yorkers benefit," Hochul noted.

Although New York represents the first statewide temporary ban, other regions have also been looking to pause buildouts as they assess the damages. Just last month, Seattle also voted to ban new projects for a year.

For years, the central question around AI was whether it really works the way much of the market’s hype says it does.

That debate is settled, and we’ve seen what AI can do. The more important question now – and one most organizations still aren’t asking – is whether we’re working alongside it the right way.

That shift in framing matters. Budgets have been allocated, tools deployed, and pilot programs have graduated into full-scale production.

And yet, something is still missing.

IBM’s Institute for Business Value found that only 25% of AI initiatives have delivered their expected ROI, and just 16% have successfully scaled across the business despite years of investment and genuine enthusiasm for what the technology can do.

The problem isn’t AI itself; the bottleneck stems from what organizations have or have not built around it.

That’s a leadership problem, and fixing it will require more than buying better tools or scheduling more trainings.

Stop Investing in the Wrong Places

The instinct for most organizations has been to buy the latest platforms, stand up a few pilot programs, and bring in a vendor to train their workers. That approach addresses the surface-level challenge, but misses the greater underlying issue. The truth is the greatest barrier to AI maturity is the lack of investment in the human infrastructure needed to support it.

The companies seeing the strongest AI outcomes are rarely those with the most sophisticated or expensive models. They’re the ones that have fundamentally rethought how their people work. Among organizations that Boston Consulting Group designated as AI leaders, roughly 70% of resources went towards people and process changes, 20% to IT infrastructure, and only 10% to the AI models themselves. Most organizations have that ratio backwards.

When leaders become hyper-focused on deploying the right tools and launching the right uses cases, they neglect the organizational muscles that are essential to using AI responsibly and consistently. All the tools in the world won’t close that gap without the right training, guardrails, and policies to back them up. And building that support structure must be a leadership priority, not an afterthought.

The Productivity Gains Are Real, But Fragile

None of this is to say AI isn’t creating real value. It absolutely is – at least, for the companies using it well. But those gains are more fragile that many leaders realize. They evaporate when companies lack support for their employees across their interactions with the technology, or when they fail to clearly communicate where human judgement and critical thinking are still essential.

The data here is hard to ignore. Among employees who use AI on the job, less than 8% report receiving extensive training with their tools. And that number has barely budged despite a sharp increase in daily usage. Moreover, 60% say it often takes them longer to figure out how to accomplish a task with an AI tool than it does to simply do it themselves.

Companies are deploying AI faster than they are enabling people to use it, and in doing so, may be creating exactly the friction and confusion they were trying to eliminate.

What Leaders Owe Their People

This is where leadership has to show up differently. The gap between AI potential and AI reality isn’t going to close through procurement decisions or new rollout announcements. It closes with deliberate, ongoing investment in people. That means three things:

Focus trainings on people, not just tools: AI is evolving faster than training curriculums can keep up. Invest in training role-specific judgements, helping people understand where AI makes them faster and where it introduces challenges or risks.

Move beyond adoption rate metrics: If 80% of your organization is using AI and productivity is still flat or declining, adoption is the wrong metric. Measure time-to-completion on real work tasks and be honest about what you find. Some use cases that are slowing people down simply shouldn’t be using AI.

Stop treating AI policy as a compliance checkbox: Companies getting this right have built AI governance into how they plan and execute work daily, not appended into and acceptable use document. That means leaders who model where they use AI and where they don’t, and who are willing to explain why.

Making AI Potential a Reality

The technology is ready. But leaders need to be able to do more than allocate budget and monitor usage.

They need to decide when AI should and should not be used, what to rebuild rather than automate, and how to support their teams throughout all of it.

Those are the questions most organizations are still failing to ask, and until they do, the ROI gap isn’t going anywhere.

We've ranked the best HR software.

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

For years, the central question around AI was whether it really works the way much of the market’s hype says it does.

That debate is settled, and we’ve seen what AI can do. The more important question now – and one most organizations still aren’t asking – is whether we’re working alongside it the right way.

That shift in framing matters. Budgets have been allocated, tools deployed, and pilot programs have graduated into full-scale production.

And yet, something is still missing.

IBM’s Institute for Business Value found that only 25% of AI initiatives have delivered their expected ROI, and just 16% have successfully scaled across the business despite years of investment and genuine enthusiasm for what the technology can do.

The problem isn’t AI itself; the bottleneck stems from what organizations have or have not built around it.

That’s a leadership problem, and fixing it will require more than buying better tools or scheduling more trainings.

Stop Investing in the Wrong Places

The instinct for most organizations has been to buy the latest platforms, stand up a few pilot programs, and bring in a vendor to train their workers. That approach addresses the surface-level challenge, but misses the greater underlying issue. The truth is the greatest barrier to AI maturity is the lack of investment in the human infrastructure needed to support it.

The companies seeing the strongest AI outcomes are rarely those with the most sophisticated or expensive models. They’re the ones that have fundamentally rethought how their people work. Among organizations that Boston Consulting Group designated as AI leaders, roughly 70% of resources went towards people and process changes, 20% to IT infrastructure, and only 10% to the AI models themselves. Most organizations have that ratio backwards.

When leaders become hyper-focused on deploying the right tools and launching the right uses cases, they neglect the organizational muscles that are essential to using AI responsibly and consistently. All the tools in the world won’t close that gap without the right training, guardrails, and policies to back them up. And building that support structure must be a leadership priority, not an afterthought.

The Productivity Gains Are Real, But Fragile

None of this is to say AI isn’t creating real value. It absolutely is – at least, for the companies using it well. But those gains are more fragile that many leaders realize. They evaporate when companies lack support for their employees across their interactions with the technology, or when they fail to clearly communicate where human judgement and critical thinking are still essential.

The data here is hard to ignore. Among employees who use AI on the job, less than 8% report receiving extensive training with their tools. And that number has barely budged despite a sharp increase in daily usage. Moreover, 60% say it often takes them longer to figure out how to accomplish a task with an AI tool than it does to simply do it themselves.

Companies are deploying AI faster than they are enabling people to use it, and in doing so, may be creating exactly the friction and confusion they were trying to eliminate.

What Leaders Owe Their People

This is where leadership has to show up differently. The gap between AI potential and AI reality isn’t going to close through procurement decisions or new rollout announcements. It closes with deliberate, ongoing investment in people. That means three things:

Focus trainings on people, not just tools: AI is evolving faster than training curriculums can keep up. Invest in training role-specific judgements, helping people understand where AI makes them faster and where it introduces challenges or risks.

Move beyond adoption rate metrics: If 80% of your organization is using AI and productivity is still flat or declining, adoption is the wrong metric. Measure time-to-completion on real work tasks and be honest about what you find. Some use cases that are slowing people down simply shouldn’t be using AI.

Stop treating AI policy as a compliance checkbox: Companies getting this right have built AI governance into how they plan and execute work daily, not appended into and acceptable use document. That means leaders who model where they use AI and where they don’t, and who are willing to explain why.

Making AI Potential a Reality

The technology is ready. But leaders need to be able to do more than allocate budget and monitor usage.

They need to decide when AI should and should not be used, what to rebuild rather than automate, and how to support their teams throughout all of it.

Those are the questions most organizations are still failing to ask, and until they do, the ROI gap isn’t going anywhere.

We've ranked the best HR software.

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

Iran threatened to block all oil exporting routes in the region on Wednesday in response to the U.S. maritime blockade of Iranian ports in the Strait of Hormuz.

(Image credit: AFP via Getty Images)

Reflecting on my time with Tomb Raider: Legacy of Atlantis at Summer Game Fest 2026, I really can’t wait to fight more dinosaurs and solve more puzzles as Lara Croft once more — but I’m yearning to see more to get a better idea of the reimagining at work.

Playing one area complete with lush rainforest setting, puzzles, waterfalls, and dinosaurs, I, first and foremost, was instantly having a great time, and the experience scratched both my Tomb Raider and my Uncharted itch.

However, it was quite a self-contained preview, and my overwhelming emotion after finishing it — after basking in its beauty, at least — is that I really need to see more to get a better handle on the reimagining and the specifics of how that differs from a remake. I got a glimpse into Lara’s Peruvian adventure, but not much more.

Welcome to the jungle

(Image credit: Crystal Dynamics)

What I can categorically say, however, is that this is a reimagination for the modern day, well and truly. The visuals are stunningly beautiful, and the rendition of the jungle that this iteration of Lara Croft finds herself in is exquisite.

The lush and verdant vegetation, beautifully detailed ruins, and fabulous water effects all combine to make for a really beautiful setting, and this may be the best-looking Lara Croft game ever once it comes out — which is saying something after the Survivor trilogy. Full of secret tunnels and routes, as well as overgrown passages to cut down and spectacular jumps to make across ruins and walkways, the game’s environments are set to be spectacular playgrounds.

The core of the segment I previewed involved Lara solving an ancient water and gear puzzle to progress past a giant gate, and presumably open a route to find treasure. The challenge itself was well done and featured a good mix of what I would call the b*****d-hard puzzles of older games, with some parts that were more intuitive. It felt well-balanced between giving you hints and giving you nothing.

Such was the attraction of the area and to explore all it had to offer, the inner looter in me took great glee in searching every nook and cranny for shiny ornaments, trinkets, and secrets, but I was left wondering whether these are just things to be found and stuffed away in a menu, or whether these, hopefully, are secrets that lead to something greater or play into side quests, or similar. One can only hope.

It’s got the moves

(Image credit: Crystal Dynamics)

Lara herself is a joy to play again, and this version did not disappoint. Wonderfully voiced and acted by Alix Wilton Regan, I really felt like this version of the icon felt more ‘human’ than ever before.

Away from some gravity-defying jumps, this mainly came from a weightier, more realistic move set that felt more grounded. Even the flair moves and acrobatics felt believably human through my controller. She also feels more vulnerable, less of a video game behemoth with overpowered guns, and much more breakable, which adds a bit of peril too.

The modernization of Lara’s tools feels well done; gadgets are intuitive to use and helpful without spoon-feeding you too much, while they are also well implemented in terms of how they look on screen, with a scan’s net wrapping around ruins, for example.

Lara also has a new focus ability to add to her modern skillset that works a lot like bullet time from Max Payne and is satisfying to use — and to build up, by deploying well-timed dodges and acrobatic moves.

(Image credit: Crystal Dynamics)

This all came to the fore toward the end of my preview when I encountered some iconic enemies: dinosaurs! Taking on three velociraptors with only Lara’s trusty handguns shone a light on how much skill you need to dodge and acrobatically move out of the way of attacks, but also how valuable it is to use the focus ability to gain an edge.

Finishing the preview with the famous Tyrannosaurus Rex chase scene was a thrill too, and in this new beautiful guise, the game managed to brilliantly capture the adrenaline-fueled, panic-ridden affair spectacularly. If this is a microcosm of the spectacle and adventure that’ll fill the entire game, then it’ll be a special ride; and as a result, it really does feel like the time is right to jump back into Lara's boots.

Having said all that, I really would like to see more to get a proper, meatier look at what this reimagining is going to look like on a grander scale. The mix of modern takes on gameplay, action, and combat mixed with some old-school approaches that hark back to the origins of one of gaming’s finest icons has got me incredibly keen and excited to see how more of it comes together.

Until we hear more, though, I’ll just have to wait until the game releases on February 12, 2026, for PlayStation 5, Xbox Series X and Series S, and PC.

Reflecting on my time with Tomb Raider: Legacy of Atlantis at Summer Game Fest 2026, I really can’t wait to fight more dinosaurs and solve more puzzles as Lara Croft once more — but I’m yearning to see more to get a better idea of the reimagining at work.

Playing one area complete with lush rainforest setting, puzzles, waterfalls, and dinosaurs, I, first and foremost, was instantly having a great time, and the experience scratched both my Tomb Raider and my Uncharted itch.

However, it was quite a self-contained preview, and my overwhelming emotion after finishing it — after basking in its beauty, at least — is that I really need to see more to get a better handle on the reimagining and the specifics of how that differs from a remake. I got a glimpse into Lara’s Peruvian adventure, but not much more.

Welcome to the jungle

(Image credit: Crystal Dynamics)

What I can categorically say, however, is that this is a reimagination for the modern day, well and truly. The visuals are stunningly beautiful, and the rendition of the jungle that this iteration of Lara Croft finds herself in is exquisite.

The lush and verdant vegetation, beautifully detailed ruins, and fabulous water effects all combine to make for a really beautiful setting, and this may be the best-looking Lara Croft game ever once it comes out — which is saying something after the Survivor trilogy. Full of secret tunnels and routes, as well as overgrown passages to cut down and spectacular jumps to make across ruins and walkways, the game’s environments are set to be spectacular playgrounds.

The core of the segment I previewed involved Lara solving an ancient water and gear puzzle to progress past a giant gate, and presumably open a route to find treasure. The challenge itself was well done and featured a good mix of what I would call the b*****d-hard puzzles of older games, with some parts that were more intuitive. It felt well-balanced between giving you hints and giving you nothing.

Such was the attraction of the area and to explore all it had to offer, the inner looter in me took great glee in searching every nook and cranny for shiny ornaments, trinkets, and secrets, but I was left wondering whether these are just things to be found and stuffed away in a menu, or whether these, hopefully, are secrets that lead to something greater or play into side quests, or similar. One can only hope.

It’s got the moves

(Image credit: Crystal Dynamics)

Lara herself is a joy to play again, and this version did not disappoint. Wonderfully voiced and acted by Alix Wilton Regan, I really felt like this version of the icon felt more ‘human’ than ever before.

Away from some gravity-defying jumps, this mainly came from a weightier, more realistic move set that felt more grounded. Even the flair moves and acrobatics felt believably human through my controller. She also feels more vulnerable, less of a video game behemoth with overpowered guns, and much more breakable, which adds a bit of peril too.

The modernization of Lara’s tools feels well done; gadgets are intuitive to use and helpful without spoon-feeding you too much, while they are also well implemented in terms of how they look on screen, with a scan’s net wrapping around ruins, for example.

Lara also has a new focus ability to add to her modern skillset that works a lot like bullet time from Max Payne and is satisfying to use — and to build up, by deploying well-timed dodges and acrobatic moves.

(Image credit: Crystal Dynamics)

This all came to the fore toward the end of my preview when I encountered some iconic enemies: dinosaurs! Taking on three velociraptors with only Lara’s trusty handguns shone a light on how much skill you need to dodge and acrobatically move out of the way of attacks, but also how valuable it is to use the focus ability to gain an edge.

Finishing the preview with the famous Tyrannosaurus Rex chase scene was a thrill too, and in this new beautiful guise, the game managed to brilliantly capture the adrenaline-fueled, panic-ridden affair spectacularly. If this is a microcosm of the spectacle and adventure that’ll fill the entire game, then it’ll be a special ride; and as a result, it really does feel like the time is right to jump back into Lara's boots.

Having said all that, I really would like to see more to get a proper, meatier look at what this reimagining is going to look like on a grander scale. The mix of modern takes on gameplay, action, and combat mixed with some old-school approaches that hark back to the origins of one of gaming’s finest icons has got me incredibly keen and excited to see how more of it comes together.

Until we hear more, though, I’ll just have to wait until the game releases on February 12, 2026, for PlayStation 5, Xbox Series X and Series S, and PC.

• The US Treasury has sanctioned First VPN's administrator for aiding ransomware attacks on American infrastructure
• Another suspect was targeted for selling "cryptors" that cloak malware from security systems
• The move follows a May 2026 takedown by European law enforcement and the FBI that seized the VPN's infrastructure

The United States government has officially issued sanctions against the operators of a notorious free virtual private network, escalating a global crackdown on digital infrastructure used to facilitate ransomware attacks.

On Monday (July 13), the US Department of the Treasury’s Office of Foreign Assets Control (OFAC) designated First VPN Service (also known as 1VPNS) and its Ukrainian administrator, Dmytro Rashevskyi, for abetting cybercriminals. The service, which has operated since 2014, was heavily favored by ransomware gangs targeting American hospitals, municipalities, and businesses.

While the best VPN services are designed to protect everyday consumer privacy, rogue networks like First VPN provided malicious actors with the tools to "hide the origins of their attacks, deploy malware, and manage exfiltrated data," according to a Treasury Department press release.

As part of the same action, the Treasury also sanctioned Yegeniy Vladimirovich Silayev, a Belarusian national accused of selling "cryptors" to ransomware operators.

While Silayev is not directly affiliated with First VPN, his inclusion in the sanctions package highlights a broader strategy of targeting the entire cybercriminal supply chain. Cryptors are tools specifically built to disguise ransomware as harmless files, preventing security systems from detecting or deactivating the malware.

A haven for cybercriminals

(Image credit: Shutterstock)

The US Treasury's latest move is an update to an ongoing international operation against First VPN.

In a massive May 2026 takedown, a coordinated effort led by European law enforcement agencies and the FBI successfully seized the service's website and server infrastructure.

Prior to the takedown, Rashevskyi aggressively marketed First VPN on dark web forums. To lure cybercriminals, he promised total anonymity and boasted that the network "does not keep logs of users' identities or activities, and that it refuses to cooperate with law enforcement investigations into illegal activity originating from the servers it rents to customers".

According to the US Treasury, Rashevskyi went to great lengths to keep the operation running. He utilized false identities, such as "Maksim Sorin" and "Roman Chabanenko," to "buy infrastructure from companies that might otherwise refuse to do business with him because of complaints of abuse from internet service providers about illegal activity originating from 1VPNS servers".

Disrupting the cybercriminal ecosystem

This latest wave of sanctions was coordinated alongside the United Kingdom's Foreign, Commonwealth & Development Office (FCDO) and carries severe consequences for the designated individuals.

Under the new sanctions, all property and interests belonging to Rashevskyi and Silayev within the US are blocked, and US citizens are strictly prohibited from engaging in any transactions with them. Beyond the immediate financial freeze, OFAC sanctions serve as a massive reputational blow designed to choke off future revenue streams.

By focusing on the service providers and tool suppliers who facilitate these attacks, rather than just the ransomware operators themselves, authorities are aiming to maximize their impact and disrupt multiple gangs at once.

"Under President Trump's leadership, Treasury is using every available tool to disrupt the cybercriminal ecosystem and protect the American people," said Gene Lange, who is performing the duties of the Under Secretary for Terrorism and Financial Intelligence. "We will continue targeting the actors who enable ransomware attacks against Americans and our critical infrastructure".

• The Mandalorian and Grogu's digital release date has been announced
• It'll be available to rent or buy in late July
• The new Star Wars movie won't come to Disney+ anytime soon

The Mandalorian and Grogu is heading to a TV screen near you very soon — but not via Disney+.

Yesterday (July 15), Lucasfilm and parent company Disney announced the latest Star Wars movie will be available to watch at home from Tuesday, July 21 onwards. If you didn't catch it in theaters or have been waiting to re-watch it from the comfort of your couch, then you'll be able to do so via numerous premium video on demand (PVOD) platforms in less than a week.

Be the first to watch at home.Buy Star Wars: The Mandalorian and Grogu on digital July 21 and own it on 4K Ultra HD August 25. pic.twitter.com/QT6oR0HOS9July 14, 2026

As for the services it'll land on, the usual suspects, such as Amazon Prime Video, Apple TV, and Fandango, should be your first ports of call. Right now, there's no indication that The Mandalorian and Grogu will be available to rent and/or buy, but I'd be shocked if viewers were only given the option to temporarily or permanently add one of 2026's many new movies to their digital film collection.

Want to know if the first Star Wars flick in over six years is worth seeing? Read my review of The Mandalorian and Grogu for more details.

Why han't The Mandalorian and Grogu arrived on Disney+ yet?

You won't be able to stream The Mandalorian and Grogu on Disney+ for a while (Image credit: Lucasfilm)

If you're wondering why The Mandalorian and Grogu isn't coming to Disney+, aka one of the world's best streaming services, yet, you're not alone. After all, it's been over two months since the Pedro Pascal-fronted sci-fi adventure not only landed in theaters, but subsequently failed to meet expectations from critical and commercial standpoints.

Wouldn't it make sense to just drop the movie on Disney's primary streamer, then? Simply put: no.

For one, releasing it on digital platforms first is a sure-fire way for Lucasfilm and Disney to continue making money from The Mandalorian's big-screen sequel.

Sure, adding it to Disney+'s movie library might persuade some to sign up for the streamer to watch it. However, Disney is far more likely to bring in extra cash through rentals or permanent purchases than new Disney+ subscriptions, especially if the cost of renting or buying The Mandalorian and Grogu is greater than the most expensive tier on Disney+ in your world region. For instance, US fans have to pay $18.99 every 30 days for an ad-free experience, so if Disney sets The Mandalorian and Grogu's digital price at $20, it's obviously going to earn more from the latter.

Regardless, the Jon Favreau-directed film will eventually come to Disney+, so you'll just have to be patient if you're waiting for it to its official streaming debut. While you wait, see if you agree with my Disney+ release date prediction for The Mandalorian and Grogu.