Are AI PCs and NPUs Worth Paying For in 2026? Copilot+ PCs Explained

Walk into any laptop shop in 2026, including ours, and you’ll see the same two letters everywhere: AI. “AI PC.” “Copilot+ PC.” “Ryzen AI.” “Intel Core Ultra with AI Boost.” “Up to 80 TOPS of AI performance.” Stickers, boxes and spec sheets all compete to tell you how much AI power is inside.

It’s become one of the most common questions customers ask us: “Do I need an AI PC?” Closely followed by, “What actually is an NPU, and is it worth paying extra for?” And honestly, the marketing dont make it easy. Every chip maker measures its AI performance differently, the features change with each Windows update, and a lot of what’s advertised as “AI” actually runs in the cloud and has nothing to do with the chip in your laptop.

So let’s cut through it. In this guide we’ll explain what an AI PC actually is, what an NPU does and how it differs from your CPU and graphics card, what TOPS means and why the numbers can mislead, what features you actually get with a Copilot+ PC, which chips are on the market, what NPUs are genuinely good at and where they fall short, and finally, whether you should pay extra for one. We’ll also cover desktops, which are a slightly different story.

Short answer up front: for many people buying a new laptop in 2026, you’ll end up with an NPU whether you seek one out or not, and that’s fine. But paying a large premium specifically for “AI” is rarely justified. The details explain why.

The short version, if you’re in a hurry

What an AI PC is: a computer with a dedicated neural processing unit (NPU), a chip designed to run AI tasks efficiently. Most new laptop processors from Intel, AMD and Qualcomm now include one.
Copilot+ PC: Microsoft’s label for Windows PCs with an NPU of at least 40 TOPS, at least 16GB of RAM and at least 256GB of storage. These get some extra Windows AI features, like Recall, Click to Do, and enhanced Studio Effects and live captions.
Current chips: Qualcomm’s Snapdragon X2 Elite leads on paper at around 80 TOPS. Intel’s Panther Lake (Core Ultra series 3) is rated around 50 TOPS. AMD’s Ryzen AI 400 series is around 50 to 60 TOPS depending on the source and model. All clear the Copilot+ bar.
What NPUs are good at: small, always-on AI tasks with very low power use: background blur and eye contact in video calls, noise cancellation, live captions and translation, on-device search, and some photo and video effects. This helps battery life.
What they’re not good at (yet): running large AI models like local chatbots at speed, image generation and heavy AI work. A graphics card is far more powerful for those.
Is it worth it? For laptops: choose based on battery life, screen, build, performance and price first. If two laptops are otherwise similar, the Copilot+ model is a reasonable tiebreaker. For desktops: an NPU is mostly irrelevant, a good graphics card matters much more for AI.

What’s in this guide

What is an “AI PC,” really?
CPU, GPU and NPU: who does what
TOPS explained, and why the numbers mislead
Copilot+ PCs and the features you actually get
The chips: Qualcomm, Intel, AMD and Apple
What NPUs are genuinely good at
Where NPUs fall short
Cloud AI vs on-device AI
Privacy and Recall
Desktops: does an NPU matter?
Should you pay extra? Our recommendations
Buying tips for Pakistan
Myths and misunderstandings
Frequently asked questions

Part 1: What is an “AI PC,” really?

The term “AI PC” started appearing around 2023 and became a major marketing push in 2024 and 2025. At its simplest, it means a computer whose processor includes a dedicated chip, or more accurately a dedicated section of the processor, designed to run artificial intelligence workloads. That section is the NPU.

A marketing term more than a technical one

Here’s the thing to understand: “AI PC” isn’t a strict technical standard. Intel, AMD and Qualcomm each use it for their chips with NPUs. Laptop makers use it to sell new models. Microsoft has its own, stricter label, “Copilot+ PC,” with specific requirements, which we’ll get to.

Any computer can run AI. Your CPU can run AI models, slowly. Your graphics card can run them much faster. Cloud services run them on huge servers. What makes an “AI PC” different is specifically the NPU, which is designed to run certain AI tasks very efficiently, using very little power.

Why the industry pushed it so hard

There are a few reasons the whole PC industry jumped on AI PCs at once:

AI is the hot topic. After ChatGPT, every tech company wanted an AI story, and PC makers were no exception.
A reason to upgrade. PC sales slumped after the pandemic boom. “AI PC” gave the industry a new reason to encourage people to buy new computers.
Battery life. Laptops increasingly run AI-powered features like video call effects. Running them on the CPU or graphics drains the battery. An NPU does them far more efficiently.
Competition with Apple. Apple has included its “Neural Engine” in Macs since the M1 chip in 2020 and in iPhones for years before that. Windows PC makers needed an answer.
Cost of cloud AI. Running AI in the cloud costs companies like Microsoft a lot of money. Moving some AI work onto users’ own devices reduces those costs.

That last point is worth thinking about. Some of the push for on-device AI benefits the companies as much as the users. That doesn’t make it bad, on-device AI genuinely helps with privacy, speed and offline use, but it’s worth keeping in mind when you hear the marketing.

How common are they now?

Very. In 2026, nearly all new mid-range and premium laptop processors from Intel, AMD and Qualcomm include an NPU. If you’re buying a new laptop at anything other than the very lowest prices, you’ll probably get one whether you specifically want it or not. Desktop processors are more mixed, which we’ll cover in Part 10.

So for most laptop buyers, the question isn’t really “should I get an AI PC?” but rather “should I pay extra for a more powerful NPU, or a Copilot+ label, or choose one laptop over another because of its AI features?”

Part 2: CPU, GPU and NPU: who does what

A modern laptop or desktop processor is really several processors in one package. Understanding what each part does is the key to understanding NPUs.

The CPU: the generalist

The central processing unit is the general-purpose brain of the computer. It runs your operating system, your apps, and almost everything else. CPUs are very flexible and good at complex, varied tasks with lots of decisions. They have a relatively small number of powerful cores.

CPUs can run AI, but not very efficiently. AI involves enormous numbers of simple, repetitive maths operations, mostly multiplying and adding large grids of numbers. CPUs aren’t built for that kind of massive, parallel number crunching.

The GPU: the parallel powerhouse

The graphics processing unit was designed to draw images, which involves doing the same simple calculations on millions of pixels at once. That turns out to be very similar to what AI needs. GPUs have thousands of smaller cores that work in parallel, making them excellent at AI. That’s why Nvidia’s graphics chips power most of the world’s AI data centres.

Laptops and desktops can have integrated graphics (built into the processor) or a dedicated graphics card. A powerful dedicated graphics card is by far the fastest way to run demanding AI on a PC, as we discussed in our guide to running AI on your own PC. The downside is power: GPUs draw a lot of it.

The NPU: the efficiency specialist

The neural processing unit is designed specifically for the kind of maths AI uses, and nothing else. It strips away everything not needed for AI, which makes it very efficient. An NPU can run suitable AI tasks using a fraction of the power a CPU or GPU would need.

The trade-off is flexibility and raw scale. NPUs are typically smaller than powerful GPUs, often have less memory bandwidth available, and only run AI software specifically designed or converted to use them. They’re brilliant at small, continuous AI tasks, less so at big, demanding ones.

An analogy

Think of a restaurant kitchen. The CPU is the head chef, capable of cooking anything, making decisions, coordinating everything, but only one person. The GPU is a big team of line cooks, fantastic at preparing huge volumes of the same dish quickly, but they need a lot of space and energy. The NPU is a specialised machine, say a very efficient bread maker, that does one kind of job brilliantly and cheaply, but can’t cook a steak.

A well-run kitchen uses all three for what they’re best at. That’s the idea behind modern processors: send each task to the part that handles it best.

Who does what in practice

NPU: background blur and eye contact correction in video calls, noise suppression, live captions, on-device search and indexing, small always-on AI features, some photo effects.
GPU: running larger AI models like chatbots and image generators, video effects, 3D, and anything needing a lot of AI horsepower.
CPU: everything else, plus coordinating the other two, and running AI in software that doesn’t support the NPU or GPU.

Software decides which part to use. If an app isn’t written to use the NPU, the NPU sits idle no matter how powerful it is. This is a really important point we’ll come back to.

A short history of the NPU

NPUs aren’t as new as the 2024 marketing made them seem. Phones got them first. Apple introduced its “Neural Engine” in the iPhone’s A11 chip in 2017, and Qualcomm and other phone chip makers added similar AI hardware around the same time. Phones needed it early because features like face unlock, portrait mode photos and voice assistants had to run constantly without draining a small battery.

Apple brought the Neural Engine to the Mac with the M1 chip in 2020. On the Windows side, AMD added its first “Ryzen AI” NPU to some laptop chips in 2023, and Intel’s Meteor Lake laptop chips, the first Core Ultra processors, brought an NPU in late 2023. Those early PC NPUs were modest, around 10 to 16 TOPS, and few apps used them.

The big jump came in 2024. Microsoft announced the Copilot+ PC standard requiring 40 TOPS, and Qualcomm launched its Snapdragon X Elite and X Plus chips with 45 TOPS NPUs. Intel’s Lunar Lake and AMD’s Ryzen AI 300 series quickly followed with qualifying NPUs. Since then, each generation has pushed TOPS higher, to the 50 to 80 TOPS range of 2026’s chips.

The history teaches a useful lesson. On phones, the NPU went from a marketing bullet point to a component that quietly powers dozens of features people use every day without thinking about it, like photo processing and voice recognition. PCs may follow the same path, with the NPU becoming an invisible, useful part of the system rather than something you shop for. We’re partway along that road in 2026.

Part 3: TOPS explained, and why the numbers mislead

Every AI PC is advertised with a TOPS number. “45 TOPS.” “50 TOPS.” “80 TOPS.” It’s become the headline spec, like megapixels on cameras used to be. And like megapixels, it tells you something, but much less than the marketing suggests.

What TOPS means

TOPS stands for Trillions of Operations Per Second. It’s a measure of how many simple maths operations a chip can theoretically do each second, specifically the kind used in AI. An NPU rated at 50 TOPS can, in theory, perform 50 trillion operations every second.

Why it’s not the whole story

Here’s where it gets slippery. TOPS figures are usually:

Theoretical peaks. The maximum under ideal conditions, not what you’ll see in real software.
Measured at low precision. TOPS are usually quoted for INT8 (8-bit integer) operations, and sometimes even lower precision. Real AI software may use different precisions where the chip is slower.
Not standardised. Different companies calculate and present their figures differently. As one 2026 analysis put it, NPU TOPS figures aren’t standardised across vendors and can be inflated.
Sometimes combined. Some marketing quotes “total platform TOPS,” adding up the NPU, GPU and CPU together, which produces a bigger number that isn’t comparable with an NPU-only figure. Always check whether a figure is for the NPU alone.

Most importantly, TOPS ignores memory. For many AI tasks, especially running language models, the limiting factor isn’t how fast the chip can calculate, it’s how quickly it can get data from memory. A chip with huge TOPS but limited memory bandwidth may perform worse than a chip with fewer TOPS but faster memory access. As we explained in our local AI guide, memory bandwidth is what largely determines how fast an AI model generates text.

The software factor

Even a powerful NPU only helps if software uses it. A 50 TOPS NPU that the app you’re using doesn’t support does nothing for you. Software support for NPUs has grown a lot, but it’s still uneven, particularly across the three chip makers, each of which has its own NPU design and software tools. Microsoft has been working to standardise this through Windows, but many apps still target one vendor’s NPU better than another’s.

So how should you use TOPS?

Treat it as a rough guide and a threshold, not a precise performance measure:

Over 40 TOPS on the NPU means the PC qualifies for Copilot+ features (if it meets the other requirements).
Comparing NPUs from the same company across generations, higher TOPS generally means more capable.
Comparing across different companies, small differences in TOPS mean very little. 50 versus 60 TOPS won’t make a noticeable difference to most people.
For real performance in a specific task, look at reviews that test actual software.

One 2026 buying guide made a good point: buying a laptop with exactly 40 TOPS means buying at the bottom of the current tier. That matters only if you plan to rely on NPU features heavily over the next several years.

Part 4: Copilot+ PCs and the features you actually get

Microsoft introduced the “Copilot+ PC” label in 2024 for Windows PCs that meet a specific hardware standard. It’s the closest thing to an official definition of an AI PC in the Windows world.

The requirements

To qualify as a Copilot+ PC, a computer needs:

An NPU capable of at least 40 TOPS.
At least 16GB of RAM.
At least 256GB of storage.
A recent version of Windows 11.

The first Copilot+ PCs in 2024 all used Qualcomm’s Snapdragon X chips. Intel and AMD followed with qualifying chips, and in 2026 most premium laptops from all three vendors meet the bar.

The features

Copilot+ PCs get Windows features that use the NPU. The exact list evolves with Windows updates, and some features vary by region or language, but key ones include:

Recall: takes regular snapshots of your screen and lets you search your history using natural language, like “that spreadsheet with blue charts I looked at last week.” It runs on-device. It’s been controversial for privacy reasons, which we’ll discuss in Part 9.
Click to Do: lets you take actions on whatever is on your screen, like summarising text, looking up an image, or extracting information.
Improved Windows search: describing what you’re looking for in plain language, for files, settings and photos, rather than needing exact file names.
Windows Studio Effects: background blur, eye contact correction, automatic framing, and lighting improvements for your webcam, running on the NPU so they don’t drain the battery as much.
Live Captions with translation: real-time captions for any audio on your PC, with translation from many languages into English.
Image and photo features: AI tools in apps like Paint and Photos, such as generating images from sketches, removing objects, upscaling and relighting.
AI features in Settings and apps: including an agent in Settings that can find and change settings from a plain-language description.

Some of these features are also available in limited forms on non-Copilot+ PCs, running in the cloud or on other hardware. The Copilot+ versions run locally on the NPU, which typically means faster response, offline availability, and better privacy.

How useful are they really?

This is were opinions vary. From our experience and what customers tell us:

Studio Effects and noise suppression are genuinely useful if you’re on video calls a lot. Background blur and eye contact correction work well, and running them on the NPU helps battery life.
Live Captions with translation is impressive and genuinely helpful for watching foreign language content, accessibility, and understanding calls in noisy environments.
Improved search is convenient when it works, and gets better over time.
Click to Do and photo features are nice to have, though many people try them a few times and then forget about them.
Recall divides opinion strongly. Some people find it genuinely useful for finding things they’ve seen. Others find the concept uncomfortable and turn it off. It’s off by default and opt-in.

One honest experience shared in a 2026 review of living with a Copilot+ PC for three months reflected what many people find: the AI features are pleasant extras, but the biggest day-to-day improvements were battery life and responsiveness, not the AI itself.

Features that don’t need an NPU

Here’s something the marketing doesn’t emphasise: most of the AI you use day to day, including ChatGPT, Microsoft Copilot (the chat assistant), Gemini, Claude, and AI features in Office, Google Docs and Canva, runs in the cloud. They work the same on any PC with a browser and an internet connection. An NPU doesn’t make them faster. If those are the AI tools you actually use, the NPU isn’t doing much for you.

Part 5: The chips: Qualcomm, Intel, AMD and Apple

Here’s an overview of the main AI PC chips on the market in 2026. NPU figures are manufacturer peak ratings, and as we’ve explained, they’re not directly comparable across brands.

Qualcomm Snapdragon X2 Elite

Qualcomm’s second generation of Windows laptop chips, built on the Arm architecture. Signal65’s testing listed the flagship with an 80 TOPS Hexagon NPU, and some sources list top models at up to 85 TOPS, making it the leader on paper.

Strengths: the most powerful NPU by rating, excellent battery life, and strong efficiency. Qualcomm’s chips have a reputation for laptops that last all day and wake instantly like a phone.

Considerations: because Snapdragon chips use Arm rather than the x86 architecture Intel and AMD use, some older Windows software runs through emulation. Microsoft’s Prism emulation has improved a lot and most apps work well, and many major apps now run natively on Arm. But some specialised software, certain drivers, older peripherals and some anti-cheat and security software can still have issues. Check that your important apps and devices work on Windows on Arm before buying. We covered Arm Windows laptops in depth in our article on Nvidia’s RTX Spark.

Intel Core Ultra series 3 (Panther Lake)

Intel’s latest laptop chips, built on Intel’s 18A manufacturing process, arrived in laptops during 2026. The NPU is rated at up to around 50 TOPS on top models, and the chips include Intel’s Xe3 integrated graphics, which also contribute significant AI performance.

Strengths: full x86 compatibility, meaning every Windows app works natively; strong integrated graphics; good efficiency improvements over previous Intel generations; and broad availability across many laptop brands.

Considerations: NPU rating lower than Qualcomm on paper, though as we’ve said, that matters less than the marketing suggests.

AMD Ryzen AI 300 and 400 series

AMD’s laptop chips with XDNA NPUs. The Ryzen AI 400 series is rated at around 50 to 60 TOPS depending on model and source. AMD also offers the Ryzen AI Max series, with powerful integrated graphics and up to 128GB of shared memory, which is popular for running large AI models locally, though that’s mostly thanks to the graphics and memory rather than the NPU.

Strengths: full x86 compatibility, strong CPU and integrated graphics performance, and in the Ryzen AI Max, a unique option for running big AI models in a laptop or mini PC.

Considerations: battery life varies a lot between laptop models. NPU software support is good for Windows features but can lag in third-party apps.

Apple M-series

Apple has included a Neural Engine in its Mac chips since the M1 in 2020. Apple doesn’t use the “AI PC” label, but Macs have dedicated AI hardware and Apple Intelligence features that use it. Macs also have unified memory, which, on models with lots of memory, makes them excellent for running larger AI models using the GPU.

Strengths: excellent efficiency and battery life, mature AI software integration, and high memory configurations for serious local AI.

Considerations: macOS rather than Windows, higher prices, and memory can’t be upgraded after purchase.

Nvidia

Nvidia doesn’t make NPUs. Instead, it argues that its RTX graphics, with dedicated Tensor Cores, are the real AI PC hardware, offering far more AI performance than any NPU, at higher power. For heavy AI work, that’s true. Nvidia’s RTX Spark chip for Windows on Arm laptops, which we covered in a previous article, combines an Arm CPU with powerful RTX graphics.

Which is best?

For AI specifically, the differences between NPUs from Qualcomm, Intel and AMD matter much less than other factors. Choose based on:

Software compatibility: if you rely on specialised or older Windows software, x86 (Intel or AMD) is the safer choice.
Battery life: Qualcomm has a strong reputation here, though Intel and AMD have narrowed the gap, and it varies a lot by laptop model.
Graphics performance: Intel’s Xe3 and AMD’s integrated graphics are stronger for light creative work than Qualcomm’s, though all three have improved.
The laptop itself: screen, keyboard, build quality, ports, weight and price matter more than the chip for most people.

Part 6: What NPUs are genuinely good at

Let’s give NPUs their due. They’re not just marketing. They do some things genuinely well.

Efficient, always-on AI

The NPU’s superpower is running small AI models continuously with very little power. That makes it ideal for features that need to be on all the time or for long periods:

Video call effects. Background blur, eye contact correction, auto framing and noise suppression during a long video call. On the CPU or GPU, these noticeably drain the battery and can make the laptop warm and noisy. On the NPU, they barely register.
Noise cancellation. Removing background noise from your microphone and others’ audio in real time.
Live captions and translation. Continuously transcribing and translating audio.
On-device search and indexing. Understanding the content of files and images in the background so you can search by description.
Presence detection. Some laptops use the NPU with sensors to lock when you walk away, wake when you return, or dim the screen when you look away, saving power and improving security.

Battery life

This is the practical benefit most people actually notice. Offloading AI features to the NPU means the CPU and GPU can stay idle, saving power. For people who spend hours on video calls on battery, that adds up. The better battery life of many 2026 AI laptops isn’t only because of the NPU, newer chips are more efficient overall, but the NPU contributes.

Privacy and offline use

Features that run on the NPU process data on your device rather than sending it to the cloud. Your webcam feed for background blur, your audio for captions, and your screen content for search stay on your PC. They also work without an internet connection.

Responsiveness

Local AI features respond instantly, without waiting for a round trip to a server. For things like live captions and video effects, that low latency matters.

Small AI models in apps

Some apps use the NPU for specific features: photo editing tools for subject selection or noise reduction, video editors for effects or automatic reframing, music apps for separating vocals from instruments, and productivity apps for on-device summarisation using small language models. Support is growing, with Adobe, DaVinci Resolve, CapCut, and various others adding NPU acceleration for some features. Microsoft has also been building small language models designed to run on NPUs into Windows.

How to check your NPU and see if it’s being used

If you have a recent laptop and want to know whether it has an NPU and whether anything is using it, Windows makes it fairly easy:

Open Task Manager (press Ctrl, Shift and Esc together).
Go to the Performance tab.
If your PC has a supported NPU, you’ll see an NPU entry alongside CPU, Memory, Disk and GPU. Click it to see its usage.
Now try an NPU feature, for example, open the Camera app or join a video call and turn on Windows Studio Effects background blur from the quick settings panel. You should see NPU usage rise, while CPU and GPU usage stay low.

You can also check whether your PC is a Copilot+ PC in Settings, and see which Copilot+ features are available to you. If you don’t see an NPU in Task Manager, your processor may not have one, or it may need a driver update from your laptop maker.

Watching the NPU in Task Manager for a day is quite revealing. For many people, it sits at zero most of the time, then springs into action during video calls or when using specific features. That’s not a failing, it’s exactly what it’s designed for: efficient, occasional or background AI work.

Part 7: Where NPUs fall short

Now the other side. There’s a gap between what “AI PC” marketing implies and what NPUs can actually do in 2026.

Running large AI models

The biggest misconception is that an AI PC lets you run ChatGPT-like assistants locally at speed. In practice, for running capable language models, a graphics card with plenty of VRAM is far more powerful than any current NPU. As one 2026 buyer’s guide put it, the NPU is good for small, sustained on-device models, but not large local language models, where a discrete GPU wins.

There are a few reasons:

Scale. A 50 TOPS NPU sounds impressive, but a modern graphics card offers many hundreds or even thousands of TOPS of AI performance.
Memory bandwidth. Language model speed is limited mainly by how quickly the hardware can read the model from memory. NPUs share the laptop’s system memory, which is much slower than a graphics card’s dedicated VRAM.
Software support. The popular tools for running local models, like Ollama, LM Studio and llama.cpp, are built primarily around CPUs and GPUs. NPU support exists in some tools and is improving, but it’s not where the performance or the ecosystem is today.

Small language models can run on NPUs, and Microsoft and others are using them for on-device features. But if you want a capable local AI assistant, look at our local AI hardware guide, and focus on graphics and memory, not NPU TOPS.

Image generation and heavy creative AI

Generating images with tools like Stable Diffusion, AI video effects, and other demanding creative AI work runs much faster on a graphics card. Some apps can use the NPU for lighter versions of these features, but for serious work, a GPU is the tool.

Fragmented software support

Each chip maker’s NPU is different, and software has to support each one. Microsoft provides frameworks to help, and support has improved, but many apps still only use the NPU on certain chips, or not at all. You can’t assume a given app will use your NPU.

Features that move or change

Windows AI features have evolved quickly, with some features delayed, reworked, limited to certain regions or languages, or changed between updates. Recall, for instance, was delayed and reworked after privacy concerns. Buying a laptop for a specific promised AI feature carries some risk that the feature changes.

The idle NPU problem

For many people, the NPU spends most of its time doing nothing. If you don’t use video calls much, don’t use Recall, and use cloud-based AI tools, the NPU might be idle 99% of the time. Thats not harmful, it just means you’re not getting value from it.

Part 8: Cloud AI vs on-device AI

Understanding the difference between cloud and on-device AI helps clarify why NPUs matter, and why they don’t matter as much as the marketing suggests.

Cloud AI

Most powerful AI tools run in the cloud: ChatGPT, Microsoft Copilot chat, Gemini, Claude, and AI features in Microsoft 365, Google Workspace and countless other apps. Your request goes to the company’s servers, which run very large models on very powerful hardware, and the result comes back.

Advantages: access to the most capable models, works on any device, no special hardware needed, always up to date.

Disadvantages: needs an internet connection, your data leaves your device, often requires subscriptions for full features, and can be slower due to network delay.

On-device AI

On-device AI runs on your own hardware, using the NPU, GPU or CPU.

Advantages: privacy, works offline, no subscription for the processing, instant response for small tasks.

Disadvantages: limited by your hardware, so models are smaller and less capable than cloud models, especially on NPUs.

The hybrid future

The industry is heading towards a hybrid approach: small, frequent, privacy-sensitive tasks on your device, and big, complex tasks in the cloud. Your laptop might use its NPU to understand what’s on your screen or transcribe your voice, then send a complex question to a cloud model. The NPU’s role is handling the small, constant tasks efficiently, not replacing the cloud.

For most people in 2026, the AI tools that make the biggest difference to their work still run in the cloud. That’s important context when deciding how much to pay for on-device AI hardware.

Connectivity considerations in Pakistan

One factor that makes on-device AI more appealing here: internet reliability. During outages, load shedding that takes down your router, or when travelling, cloud AI tools stop working. On-device features like live captions, video call effects and local search keep working. For people who rely on AI features and face patchy connectivity, that’s a genuine plus for capable on-device hardware, whether NPU or GPU.

Part 9: Privacy and Recall

No discussion of AI PCs is complete without Recall, the feature that caused more controversy than any other.

What Recall does

Recall takes snapshots of your screen at regular intervals and uses on-device AI to make them searchable. The idea is that you can find anything you’ve seen on your PC by describing it: a document, a website, a photo, a conversation. It’s like a photographic memory for your computer.

Why it was controversial

When Microsoft first announced Recall in 2024, security researchers raised serious concerns. Storing snapshots of everything you’ve looked at, including potentially passwords, private messages, financial information and confidential documents, creates an attractive target for malware or anyone with access to your PC. Early versions stored the data in a way researchers showed could be accessed relatively easily.

Microsoft delayed the feature, reworked it significantly, and relaunched it with stronger protections: Recall is opt-in (off by default), requires Windows Hello authentication to access, encrypts its data, processes everything on-device, lets you exclude specific apps and websites, and attempts to filter out sensitive information like passwords and credit card numbers. You can also delete snapshots or remove Recall entirely.

Should you use it?

That’s a personal decision. Things to consider:

Who else uses your PC? On a shared computer, Recall’s history could expose your activity to others, though Windows Hello protection helps.
What do you do on it? If you handle highly sensitive information, like client data, medical records or financial details, the risk may outweigh the convenience. Many businesses disable it by policy.
Do you need it? If you often struggle to find things you’ve seen before, it can be genuinely useful. If not, there’s little reason to turn it on.

If you do use it, use the exclusion settings for sensitive apps and websites, like your banking site, password manager and private messaging.

Other privacy considerations

On-device AI is generally better for privacy than cloud AI, because your data stays on your PC. But “AI PC” doesn’t mean everything is local. Many AI features on any PC, including some built into Windows, still send data to the cloud. Check the privacy settings in Windows and in individual apps, and understand which features work locally and which don’t.

Where NPUs are heading

It’s worth looking ahead a little, since a laptop bought today should last several years.

More TOPS, but that’s not the main story. NPU ratings have climbed from around 10 TOPS in 2023 to 50 to 80 TOPS in 2026, and leaks suggest Intel’s Nova Lake will bring stronger NPUs to desktops in 2027. Raw numbers will keep rising. But as we’ve explained, memory bandwidth and software matter more than TOPS for many tasks.

Better software support. This is the bigger change to watch. Microsoft has been building frameworks that let developers write AI features once and run them on any vendor’s NPU, rather than separately for Intel, AMD and Qualcomm. As those mature, more apps should use NPUs without developers needing special effort for each chip. Microsoft is also building small language models into Windows itself, designed to run on NPUs, which app developers can use for on-device features like summarising and rewriting text.

Smarter splitting of work. Future software is likely to split AI tasks more intelligently between NPU, GPU and CPU, using the NPU for efficient background work and handing heavier tasks to the GPU automatically. You won’t need to think about which part is doing what.

Agents on the device. As we discussed in our guide to AI agents, AI that can take actions on your behalf is a major trend. Some agent features, like understanding what’s on your screen, are a natural fit for efficient on-device processing. That’s one area where NPUs could become more important over the next few years.

The honest uncertainty. There’s also a chance NPU features remain “nice extras” for most people, while the AI that really matters keeps running in the cloud or on graphics cards. Nobody knows for sure. That uncertainty is exactly why we advise against paying a big premium for NPU performance today: you’d be betting on a future that might not arrive in the form you expect.

Part 10: Desktops: does an NPU matter?

Most of the AI PC conversation is about laptops, and for good reason. The NPU’s main advantage is power efficiency, which matters most on battery. On a desktop plugged into the wall, the picture is different.

Which desktop chips have NPUs?

Intel Core Ultra 200S (Arrow Lake) desktop chips include a small NPU, rated at around 13 TOPS, well below the Copilot+ threshold.
AMD Ryzen 9000 desktop chips don’t include an NPU. Some of AMD’s desktop APUs, like the Ryzen 8000G series, include a modest NPU, and reports indicate newer Ryzen AI desktop parts carry more capable NPUs.
Intel Nova Lake, coming to desktops in 2027, reportedly includes a much stronger NPU, around 74 TOPS according to leaks, as we discussed in our Nova Lake vs Zen 6 guide.

Why it matters less on a desktop

Power isn’t as critical. A desktop can run AI tasks on the CPU or GPU without worrying about battery life. Running background blur on the GPU uses more power than an NPU would, but on a desktop, that’s a few watts.
Desktops often have powerful graphics cards. A desktop with a modern RTX or Radeon graphics card has vastly more AI performance than any NPU. For local AI, image generation and AI-assisted creative work, the graphics card is the real AI engine.
Copilot+ features are mostly laptop-oriented. Microsoft’s Copilot+ program has focused on laptops. Some features, like Recall and Studio Effects, require a qualifying NPU, so they may not be available on desktops without one, but most people don’t miss them on a desktop.

Our desktop advice

For desktops, don’t pay extra for an NPU. If AI matters to you, put that money into a graphics card with more VRAM, as covered in our graphics card buying guide. A 16GB graphics card will do far more AI work, far faster, than any desktop NPU. If your chosen desktop CPU happens to include an NPU, great, it’s a bonus, but it shouldn’t drive your decision.

Part 11: Should you pay extra? Our recommendations

Here’s our honest advice for different types of buyers.

Students and general users buying a laptop

Choose the laptop with the best combination of battery life, screen, keyboard, build quality and performance for your budget. Most mid-range and premium laptops in 2026 have NPUs anyway. If you’re choosing between two otherwise similar laptops, the Copilot+ model is a sensible tiebreaker. Don’t pay a big premium just for “AI.” Prioritise 16GB of RAM, which youll want regardless, and a fast SSD.

Remote workers and people on lots of video calls

Here, NPU features genuinely help. Studio Effects, noise suppression and live captions running on the NPU improve call quality and save battery during long meetings. A Copilot+ laptop is a good fit. Also prioritise a good webcam, microphones and speakers, which affect call quality as much as AI effects do.

Business buyers

Copilot+ PCs offer useful features for productivity and calls, and IT departments increasingly standardise on them for future-proofing. Consider your security and privacy policies around features like Recall, which you may want to manage centrally. Check compatibility of your business software, especially if considering Arm-based laptops. And remember that most business AI tools, like Microsoft 365 Copilot, run in the cloud and require their own licences regardless of hardware.

Creators: photo, video, design

Some creative apps use the NPU for specific features, which is a nice bonus. But for serious creative work, a laptop with a capable dedicated graphics card matters more. If you need both portability and creative power, look for a laptop with both a good NPU and a dedicated graphics card, or one with strong integrated graphics and plenty of memory.

Developers and AI enthusiasts

If you want to run local AI models, focus on GPU and memory, not NPU. A laptop with an RTX graphics card with plenty of VRAM, an AMD Ryzen AI Max system with lots of shared memory, or a Mac with lots of unified memory will run local models far better than any NPU. NPU development is interesting if you build apps targeting on-device AI features, but it’s a specialised area.

Budget buyers

At the lowest prices, you may find laptops without NPUs or with older ones. That’s okay. All the cloud AI tools work on any laptop with a browser. Prioritise enough RAM (at least 8GB, ideally 16GB), an SSD rather than a hard drive, and decent battery life. An NPU is the last thing to worry about at this budget.

Desktop buyers

As covered above, an NPU barely matters. Spend on a graphics card if AI is important to you.

Three real-world buyers, three different answers

To make this concrete, here are three typical customers we’ve helped this year, with details changed.

The consultant on calls all day. A management consultant who spends five or six hours a day on video calls, often from cafés and client offices, with unreliable power. For her, a Copilot+ laptop made a lot of sense. Studio Effects kept her looking professional in any setting, noise suppression handled noisy cafés, live captions helped on calls with poor audio, and the battery comfortably lasted a full working day even with calls running. The NPU wasn’t the only reason the battery was great, the efficient chip helped overall, but the AI features genuinely improved her daily work.

The engineering student. A student needing a laptop for university, with CAD software, MATLAB and some programming, on a fixed budget. The AI label was nearly irrelevant for him. What mattered was software compatibility (which ruled out an Arm laptop because one of his required programs had issues), 16GB of RAM, a decent CPU and integrated graphics for CAD, and a reasonable price. His chosen laptop happened to have an NPU, but he’d have been equally well served without one. We steered him away from paying more for a higher-TOPS model and towards a bigger SSD instead.

The AI hobbyist. Someone who wanted to run local language models and generate images. He’d assumed an “AI PC” laptop with the highest TOPS was the answer. After we explained the difference, he chose a laptop with an RTX graphics card with more VRAM instead. His local models run many times faster on the graphics card than they would have on any NPU. The laptop has an NPU too, which handles his video call effects, but it’s the graphics card doing the heavy AI lifting.

Three buyers, three different right answers. That’s why we always start by asking what you’ll actually do with the machine, not how many TOPS it has.

The future-proofing question

“Should I get an NPU to future-proof?” It’s a fair question. Microsoft and app makers are adding more NPU features over time, and a laptop you buy today might last four or five years. If you’re buying a premium laptop anyway, getting one that meets the Copilot+ bar makes sense, since it costs little extra at that level and keeps you eligible for future features. But be wary of paying a significant premium on the assumption that NPU features will become essential. That hasn’t happened yet, and the most important AI tools still run in the cloud.

A simple checklist

Is the laptop good on the basics (screen, keyboard, battery, build, performance) for your budget?
Does it have at least 16GB of RAM?
Do all your important apps and devices work on it (especially for Arm laptops)?
Do you do lots of video calls or want features like live captions? If yes, Copilot+ adds real value.
Do you want to run local AI models? If yes, focus on GPU and memory, not NPU.
Is the AI premium small or large? Small is fine. Large needs a good reason.

What to look for in a 2026 laptop besides the NPU

Since we keep saying the basics matter more than the NPU, here’s what we mean in practice.

Screen. You look at it all day. Look for at least a 1080p (or higher) IPS or OLED panel with decent brightness (300 nits or more for indoor use, more if you work near windows or outdoors). Colour accuracy matters for creative work. A dim, washed-out screen will annoy you far more than a missing AI feature.
Battery life. Check independent reviews for real-world battery tests. All-day battery life is genuinely achievable in 2026 on many efficient laptops.
RAM. 16GB minimum for a smooth experience in 2026, and 32GB for heavier use. Check whether it’s soldered.
Storage. A 512GB SSD is a comfortable minimum for most people. 256GB fills up quickly.
Keyboard and trackpad. Try them if you can. A cramped keyboard or poor trackpad affects every minute of use.
Ports. Make sure it has what you need: USB-C with charging, USB-A for older devices, HDMI for projectors and monitors, a headphone jack, and possibly an SD card reader.
Webcam and microphones. A 1080p webcam and good microphones make a real difference for calls, more than AI effects alone.
Build quality and weight. If you carry it daily, weight and durability matter.
Cooling and noise. Some thin laptops get loud or hot under load, particularly in warm rooms.
Warranty and service. Especially important for laptops with soldered components.

Get these right and you’ll have a laptop you enjoy using for years, whatever its TOPS rating.

Part 12: Buying tips for Pakistan

Check the exact model and chip

Laptop model names often cover several configurations with different chips. A model advertised as an “AI PC” in one configuration might have an older chip without a Copilot+ NPU in another. Check the exact processor model, RAM and storage of the unit you’re buying, not just the series name.

RAM can’t always be upgraded

Many thin laptops, including most Copilot+ laptops, have memory soldered to the motherboard, which means you can’t add more later. Buy enough at the start. 16GB is the minimum for Copilot+ and a sensible baseline. 32GB is worth considering if you multitask heavily, run virtual machines, or want headroom for local AI. With memory prices high in 2026, as covered in our memory crisis article, higher RAM configurations carry bigger premiums than before, but upgrading later usually isn’t an option.

Language and region features

Some Windows AI features launch first in certain languages and regions, and availability can vary. Live Captions translation supports many languages into English, but check current support if a particular language matters to you. Urdu support in AI features is improving but not always complete.

Warranty and service

Premium laptops are a significant investment. Buy with a proper local warranty, and check how service works for the brand you’re choosing. Laptops with soldered components are harder to repair, which makes warranty even more important.

Power and battery

Long battery life is one of the genuine benefits of modern AI laptops, and it’s especially valuable during load shedding. Look at independent battery tests for the specific model rather than manufacturer claims, which are usually measured under ideal conditions. Using a laptop with good battery life on a small UPS for your router gives you hours of productive work through outages.

Heat

Thin laptops can run hot in our summers. Efficient chips help, and NPU features reduce load for some tasks, but check reviews for thermal performance and consider a laptop cooling pad for heavy use in hot rooms.

Arm laptops and local software

If you’re considering a Snapdragon laptop, double-check that any locally used software works, such as specific banking or tax software, older accounting packages, printer and scanner drivers, and any specialised tools your work or university requires. Most mainstream software is fine, but it’s worth confirming.

Questions to ask before you buy

Whether you’re buying from us or anyone else, these questions will cut through the AI marketing quickly:

“What is the exact processor model?” Not just “Core Ultra” or “Ryzen AI,” but the full model number, so you can look up its NPU and performance.
“Is this unit a Copilot+ PC?” Some versions of the same laptop model qualify and others don’t.
“How much RAM does it have, and can it be upgraded?” If it’s soldered, buy enough now.
“Is the AI TOPS figure for the NPU alone, or the whole platform?” Platform figures are bigger but not comparable.
“What does the warranty cover, and where is service done?”
“Is the price difference compared with the non-AI version worth it?” Ask for both options side by side.
For Snapdragon laptops: “Will my specific software and devices work?” Name them, and check.

A good seller will answer these clearly. If you get vague answers about “AI performance” without specifics, be cautious.

A note on price premiums in 2026

In 2024, Copilot+ laptops often carried a noticeable premium over otherwise similar models. By 2026, as NPUs became standard in mid-range and premium chips, that premium has largely disappeared in many segments. You’re often not paying extra for the NPU itself, it simply comes with the modern processor. What does cost more is RAM: the 16GB minimum for Copilot+ and the higher memory configurations have become pricier with the memory shortage. So when comparing prices, look at what you’re actually getting (processor, RAM, storage, screen), rather than assuming the “AI” label is what you’re paying for.

Part 13: Myths and misunderstandings

Myth: “You need an AI PC to use AI.”

Most AI tools people use, like ChatGPT, Copilot chat, Gemini and Claude, run in the cloud and work on any computer with a browser and internet connection. An AI PC adds on-device features, but it’s not required to use AI.

Myth: “More TOPS means a faster AI PC.”

TOPS is a theoretical peak figure that isn’t standardised across companies and ignores memory bandwidth and software support. Small differences in TOPS mean little in practice. Real-world performance depends on the specific task and software.

Myth: “An NPU lets me run ChatGPT locally.”

NPUs can run small language models for specific features, but for capable local AI assistants, a graphics card with plenty of VRAM, or a system with lots of fast unified memory, is far better. The NPU isn’t where local chatbot performance comes from in 2026.

Myth: “An AI PC is always better than a non-AI PC.”

An AI PC with a poor screen, weak battery or cramped keyboard is worse than a well-made laptop without an NPU for most people. The NPU is one feature among many, and rarely the most important.

Myth: “Copilot+ means Microsoft Copilot runs locally.”

The Copilot chat assistant runs in the cloud on any PC. Copilot+ refers to a hardware standard that enables specific on-device Windows features like Recall and Studio Effects.

Myth: “Recall is spying on you.”

Recall, in its relaunched form, is opt-in, processes data on-device, encrypts it, and requires Windows Hello to access. That doesn’t make it right for everyone, and the concept of capturing your screen history raises legitimate concerns, but it’s not sending your screen to Microsoft. You can turn it off or remove it.

Myth: “Desktops need NPUs too.”

On desktops, a graphics card offers far more AI performance, and power efficiency matters less. An NPU is a minor bonus on a desktop at best.

Part 14: Frequently asked questions

What is an NPU in simple terms?

A neural processing unit is a part of the processor designed specifically to run AI tasks efficiently, using much less power than the CPU or graphics would for the same task.

What does Copilot+ PC mean?

It’s Microsoft’s label for Windows PCs with an NPU of at least 40 TOPS, at least 16GB of RAM and at least 256GB of storage. They get extra on-device Windows AI features.

Is a Copilot+ PC worth it?

If the laptop is good on the things you care about and the Copilot+ version doesn’t cost much more, yes, it’s a sensible choice. If it costs a large premium, think about whether you’ll actually use the AI features. For people who do lots of video calls, the features are genuinely useful.

Which has the best NPU: Intel, AMD or Qualcomm?

On paper, Qualcomm’s Snapdragon X2 Elite leads at around 80 TOPS, with Intel’s Panther Lake around 50 TOPS and AMD’s Ryzen AI 400 around 50 to 60 TOPS. In practice, the differences matter much less than battery life, software compatibility and the laptop itself.

Can I add an NPU to my existing PC?

Not in a practical way for most people. NPUs are built into processors. Some add-in AI accelerator cards exist, but for consumers, a graphics card is the practical way to add AI performance to a desktop.

Will an NPU make my laptop faster?

For normal tasks like browsing, office work and most apps, no. The NPU only helps with AI tasks that software sends to it. It can indirectly help by freeing the CPU and GPU from AI work and improving battery life.

Do I need an NPU for Windows 11?

No. Windows 11 works without an NPU. You only miss some Copilot+ specific features.

Is a Snapdragon laptop a good choice?

For many people, yes, with excellent battery life and strong performance. Check that your important software and devices work on Windows on Arm first, especially specialised or older software.

Should I wait for better NPUs?

NPUs will keep improving, but that’s true of every component. If you need a laptop now, buy one that’s good overall. The NPU is unlikely to be the factor that makes it feel outdated.

Is an AI PC good for running Stable Diffusion?

Some lighter image generation can run on NPUs in supported apps, but for serious image generation, a dedicated graphics card is much faster.

Does the NPU work with Urdu?

The NPU itself doesn’t care about language. It’s the AI models and features that do. Language support depends on the specific feature and model. Some features support Urdu, others don’t yet. Check the specific feature you’re interested in.

A quick glossary

AI PC: a marketing term for a computer with a dedicated NPU.
NPU: neural processing unit, dedicated hardware for efficient AI.
TOPS: trillions of operations per second, a theoretical measure of AI processing capability.
Copilot+ PC: Microsoft’s standard for Windows PCs with a 40+ TOPS NPU, 16GB+ RAM and 256GB+ storage.
Recall: a Copilot+ feature that makes your screen history searchable, opt-in and on-device.
Studio Effects: NPU-powered webcam effects like background blur and eye contact correction.
On-device AI: AI processed on your own computer rather than in the cloud.
Small language model: a compact AI language model designed to run efficiently on devices like laptops and phones.
Arm / x86: two processor architectures. Qualcomm and Apple use Arm; Intel and AMD use x86.
Emulation: running software designed for one architecture on another, as Windows on Arm does for older x86 apps.

The bottom line

AI PCs and NPUs are real technology, not just marketing. NPUs genuinely help with efficient, always-on AI features like video call effects, noise suppression and live captions, and they contribute to the excellent battery life of many 2026 laptops. On-device AI is also better for privacy and works offline.

But the marketing promises more than NPUs deliver today. The AI tools most people use every day run in the cloud and work on any computer. NPUs aren’t powerful enough to run capable local AI assistants at speed, a job where graphics cards and fast memory still rule. TOPS figures are a rough guide at best. And on desktops, an NPU is barely relevant.

Our advice: buy a laptop that’s great at the basics for your budget. If it’s a Copilot+ PC, that’s a nice bonus and a reasonable tiebreaker, and genuinely useful if you’re on video calls a lot. Don’t pay a big premium for AI stickers. And if you want serious AI power, whether for local models, image generation or creative work, look at graphics and memory, not NPU TOPS.

If you’re trying to choose a laptop and the AI labels are confusing you, bring us your shortlist. We’ll help you work out which features actually matter for how you use your computer.

Sources

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