Qualcomm AI wants to follow you everywhere, not just live on your phone

Qualcomm Doesn't Want AI to Live on Your Phone, It Wants AI to Follow You Everywhere

Snapdragon platform is uniquely positioned to power AI workload The year 2026 can be largely related to the widespread adoption of Artificial Intelligence (AI) and the year of agentic AI. We have seen all the major brands building new AI agents, whether it be Meta, OpenAI, Google, Anthropic, and more. However, only a handful of players are focusing on the hardware that can power the new AI features. A few years down the line, the conversation around chips used to be fairly simple: faster cores, better cameras, longer battery life, and more. However, today the same chip that powers your smartphone is also expected to run a plethora of AI features. That said, though many big players are adapting to this fast-paced AI environment, one brand has invested in infrastructure even before the era of AI began. Yes, we are talking about Qualcomm. The company has spent the last several years pushing its Snapdragon architecture well beyond smartphones, into PCs, wearables, XR glasses, cars, robotics, and now data centres. The company is now betting on a future where intelligence will become distributed across an ecosystem of products, moving seamlessly between different gadgets and cloud infrastructure, depending on the task at hand. We had the chance to speak with Nitin Kumar, Vice President of Product Management for Snapdragon Chipsets at Qualcomm., to understand how silicon can help drive the new agentic AI era. From Chips to a Full Compute Continuum For years, Qualcomm has been associated with the smartphone business. Snapdragon processors became synonymous with premium Android experiences, with popular brands like Samsung, Xiaomi, OnePlus, OPPO, Vivo, and countless others using their chipsets on their mid-range to flagship models. However, this identity has now changed entirely in 2026. Qualcomm now has silicon products spanning an extraordinary range of computing categories. At one end of the spectrum are earbuds and wearables operating within milliwatt power budgets. At the other end are AI infrastructure products designed for data centre deployments consuming thousands of times more power. "We have a large spectrum of Qualcomm device portfolio that we're offering that we showed yesterday, right from earbuds to wearable devices to XR glasses... to smartphones, to PCs, to tablets, to automobiles, to robotics, all the way to data centre," Kumar explained. He revealed that the credit for this continuum goes to the years of upfront investment rather than a sudden pivot. "We have invested over many years in our technology stack across all different IPs, whether it's CPU, GPU, AI capability, audio capability, from devices that will be sub one watt and actually milliwatt kind of a use case scenario, whether it's your earbud devices, all the way into like kilowatt kind of a scenario, which would be on the data center," he explained. The breadth of that portfolio, ranging from a few milliwatts to the AI200 data centre rack at roughly around 160 kW, matters because the next generation of AI experiences will almost certainly not be confined to a single form factor. The challenge for the industry is figuring out how these experiences connect. However, for Qualcomm, this gives it an edge over rivals that specialise in just one end of this range. "We're the only ones who can run an AI in a sub one-watt device and all the way into a kilowatt kind of a device," Kumar said. The Next Computing Era May Not Belong to a Single Device Qualcomm's AI vision is not focused on a specific product category, but a conglomerate of all. Kumar revealed that owning silicon across categories matters the most for the next phase of AI. "If you look at all your personal device categories for a second... I have my Windows PC here, I have my smartphone here, I'm wearing a watch powered by Snapdragon, and I'm wearing my Ray-Ban Meta glasses that are also powered by Snapdragon. Because it is powered by Snapdragon, and for the next generation of AI experiences, having that context will be super important to drive contextual AI," he said. Nitin Kumar, Vice President of Product Management for Snapdragon Chipsets at Qualcomm. He further added that this provides a structural advantage that no other silicon vendor currently offers. "Because all these are powered by Snapdragon, it gives us a unique advantage in terms of like, we're the only silicon player that can tie a common thread between an XR glasses that are available today to a wearable to my earbuds that I have in my pocket to a PC to a tablet to a smartphone. It gives us that unique ability to stitch this contextual thread together and drive the best experience across all these devices powered by Snapdragon, so that there is an enhanced capability that you're able to get out of your device," Kumar said. Local vs Cloud: Who Decides Where AI Should Actually Run When asked who decides when a workload should stay local or when it should escalate to larger cloud models, Kumar revealed that there is no fixed rulebook for it. "The world is actually changing very fast... as models evolve, the capability of the models evolves, the accuracy of the model gets fine-tuned, the space is changing in terms of what might exist or what did exist in terms of capability last year versus what exists now will be very different from what might even exist in one year," he noted. He believes that the future belongs to neither camp completely, but to what he called "distributed compute". "The general theme from us is very clear, that we believe in more of a distributed compute, if you will, that the best application from a user perspective is when the technology just blends in the back, and the user just gets the output that they are looking for in terms of the capability," he said. He added that this depends heavily on how capable the underlying hardware is at any given time, since models themselves keep shrinking. "A lot of that depends on the capability of the platform, the system capability of the platform, which by itself is evolving as models get quantised to a smaller footprint by maintaining the accuracy to an acceptable degree. That intelligent orchestration is where we'll have an advantage in how we can distribute the workload," Kumar explained. AI Is Becoming the New User Interface The AI space is changing rapidly. There was a time when AI was used only for trivial matters; now it is a full-blown experience for consumers. Talking about the future of AI and whether the next breakout consumer AI experience will be fully local, cloud-assisted, or a hybrid mix, Kumar reveals that the space is evolving at a rapid pace. "So it's what was there a year ago is very different today, and might be very different. It really changes very fast, every few months, I think," he said. Qualcomm showcased a bunch of AI usecases along with its Dragonwing at Computex 2026. However, he believes that as the world is moving towards agentic AI, there will be a bigger shift in how people will interact with their devices altogether. "The landscape changes very fast -- every few months, I think. But one thing is clear if you look at the trend: the world is moving towards more AI. The world is moving towards agentic AI. In fact, our belief is that AI is the new UI as well," he reiterated. As of today, he explained that users are the ones giving commands to AI. However, this will change in the near future as agentic AI comes into play. "Right now, we are the ones giving AI commands as users. In tomorrow's world, agents themselves will be giving more AI commands, in terms of how they orchestrate between local, cloud, or some form of hybrid or distributed AI workloads," he further explained. That said, he still believes that, even with an agentic AI future in mind, on-device AI will still depend on the cloud to some extent. "I believe that as the world continues to evolve and the demand for space continues to evolve, it will always remain a distributed AI approach. As much of the AI as possible will run locally, and then there will be certain applications that will require cloud usage," he added further. Nitin says that the capability of local devices will continue to improve exponentially, enabling them to run a lot more. At the same time, demand for more AI is increasing at a very aggressive pace. "I believe distributed AI will be the right architecture, one that fits across a variety of needs for users. A user can buy a smaller capable machine, a large capable machine, or a really powerful machine locally. But some use cases might still exceed local capability, and for those, you may want to go to the cloud," he explained. What Actually Makes a Device Agent-Ready As agentic AI becomes more popular each day, one question that remains uncertain is how to gauge whether a device is agent-ready. When asked what the minimum technical requirement should be for a device to qualify as agent-ready in this new AI era, Kumar revealed that it is a difficult question to answer "because the AI agent space is also very, very wide." Qualcomm has been quietly building AI into its chipsets even before AI took centre stage. "Let me give you a couple of wide-spectrum use cases on both, on both sides. Okay, take a smartphone as an example. Believe it or not, AI is, on a relative basis, a new term. An NPU integrated into an SoC is a new term. Qualcomm has been integrating an NPU on a mobile chip for maybe about 12, 13 years," he said. The Dragonwing IQ10 Robotics Reference Design. " If you go back several years, you would take a picture and be able to blur the portrait out of it, which was called the bokeh effect. That was using an NPU, an AI engine integrated on the chip. When you can use a feature like Hey Snapdragon on a smartphone, and the phone wakes up, that is also running on a very tiny NPU that is part of the audio engine we have. It is a very small engine, but it is still an AI engine. It is an NPU actually running a neural network whose one job is to detect context from the world around it. The reason it requires AI processing is that it has to do that all the time, listening continuously at much lower power," he explained. "On the other side of the spectrum, like, on a PC, we have an 80 TOPS of NPU capability, and as you go into the server side, we have far more AI capability that exists in several of the offerings that have been announced, and more to come on that," Kumar said. Given how wide that range is, he revealed that it is really hard to set fixed parameters for a device to be labelled as agentic AI-ready. "It is very hard to say what the minimum size is and what the maximum size is, as the use cases are very wide in spectrum. One thing is for sure, that we'll have the best solution that will provide capability for that solution within the constrained form factor of that device," he said. How Qualcomm is Building an Ecosystem for the Agentic AI Era Qualcomm is ready for the agentic AI revolution. Kumar says that the company is offering an end-to-end solution for the developers. "Leveraging Qualcomm Stack, Qualcomm toolchain, Qualcomm processes, Qualcomm support, they can optimise an AI algorithm on Snapdragon architecture, and then run that on a smartphone, run that on a PC, run that on a tablet. That gives them a unique advantage," he said. "We are working with several of our ISV partners across different segments, whether it's from content creation, document summarisation, music creation, or different vertical industries, where we are enabling the partners to leverage the on-device AI capability and offer a different use case than it was non-existent," he explained. That being said, Qualcomm is building an ecosystem of silicon while using its expertise in the performance-per-watt compute. "Our DNA has been in terms of providing the best performance while preserving battery life, that is a performance per watt advantage that we have had for decades now, and the reason we are like that is that our back of the house wealth has been from a mobile industry," he said. He explained that engineers at Qualcomm always design a new architecture with power optimisation and power saving in mind. Whether it be an architecture for earbuds to XR glasses or a Windows PC, the core philosophy remains the same: deliver the maximum performance while preserving the battery life. "We will continue to innovate and lead the market in that direction. That is in our DNA, that is our core strength, and our technology stack is the proof point of that. We continue to invest very heavily in our technology stack to make sure that we maintain a leading position, because that is the fundamental promise that Snapdragon provides to the end customer, and we must deliver on that promise. When you are buying a Snapdragon device, there are some fundamental things that you are going to get from that device, no matter what device category it is. And one of them is best-in-class performance per watt," he explained.

AI is super capable, but cannot replicate human emotions: Nitin Kumar, Qualcomm

In almost every sci-fi movie, there is a moment where an AI model or a machine becomes intelligent enough to challenge or even compete with human beings. Sometimes it tries to take over the world (The Terminator), sometimes it becomes a friend or emotional companion (Her), or sometimes it becomes a terrorising maniac who wants to rule over the human race (Avengers: Ultron). But no matter the storyline, one question always remains the same: what happens when artificial intelligence (AI) becomes powerful enough to do almost everything we can? In 2026, the answer is right in front of our eyes, and the reality is no longer science fiction. Let me explain. Today, AI can write emails, generate images, summarise meetings, edit videos, and even hold conversations that feel almost natural. The technology is evolving so quickly that it often feels impossible to predict what the next big breakthrough will be. Yet, amidst all the conversations around what all AI can do, Nitin Kumar, VP, Product Management for Snapdragon Chipsets at Qualcomm, believes there is one thing machines will struggle to replicate: human emotions and empathy. 'AI can be incredibly capable, but emotional connection and empathy are deeply human traits. And I think that will remain true for a very long time.' Now this is an interesting perspective from someone helping build the hardware that powers the AI revolution. During Computex 2026, we got in touch with Nitin Kumar to talk about the rise of AI agents, the idea behind Qualcomm's new Snapdragon C series processors, and much more. Here are the key excerpts from the conversation: Qualcomm is calling 2026 the year of agents. What is the one thing that you think an AI agent will be able to do soon that today's assistants just cannot? The AI world is changing really, really fast. AI applications, model growth, model evolution in terms of use cases, and the capability of what you would expect an AI model to do are evolving at a very aggressive pace. From a PC perspective, which is the business that I have, the Snapdragon X Series launched with leading on-device AI capability. We see that the world is moving toward more AI, and you would want to run more AI locally on the device. Initially, we demonstrated running a 7-billion parameter model, then 13-billion parameter models, and now we can run 20-billion and even 30-billion parameter models locally on the device. A lot of work has happened, and a lot more is ongoing. When we launched our X2 product portfolio, we increased on-device AI capability on our NPU from 45 TOPS to 80 TOPS. That number itself is important, but what's more important is what it enables. Productivity applications, document summarisation, image editing, photo editing, video editing, audio applications, content creation, music generation. All of these use cases leverage AI on the device. When you look at how the world is changing, tying back to the point that you raised, we strongly believe that as more agents come online, those agents themselves will begin issuing AI commands on their own. That is the true replication of an agentic AI world. And these agents helping you complete tasks will drive a huge need for AI capability on-device and much better orchestration between local AI and cloud AI. It is all changing at a very rapid pace. Qualcomm announced the Snapdragon C chipset during Computex 2026. Tell us more about that. Why did the company decide that now was the right time to launch this chipset? Snapdragon X stands on three pillars. The first is that we have to provide the best performance. No matter who you are as a user, a student, an employee, or a casual user, a laptop is ultimately a productivity device. You want the best performance. The second promise is that we will deliver the best performance, but we will not compromise the battery life. It's not a trade-off, and users don't have to choose between the two. The third promise is that with a device powered by Snapdragon, we will deliver the best on-device AI capability that you can get from a laptop. You will get the best AI. And we have been leading on that for more than a decade in our AI research. Now, if you look at our journey here with the Snapdragon X series, it began with the Snapdragon X Elite portfolio in June 2024. We started with Snapdragon X Elite for premium devices priced around $1,000 and above. Then we expanded to Snapdragon X Plus, bringing devices closer to the $800 range. Later, we introduced Snapdragon X, bringing devices closer to the $599 segment. So our goal has always been to bring those three pillars to a broader audience. But when you look below that segment, around $300, $400, or under $500, there is a very large market of users. That is where Snapdragon C comes in. The idea is to deliver the same three promises in that segment: best performance, exceptional battery life, and AI capabilities. AI is practically non-existent in that class of devices today, and we want to change that. Speaking of bringing AI PCs to a larger audience. There are many consumers who still don't understand why they need an AI laptop. What is Qualcomm's response to that? The best use of AI is actually when it works completely behind the scenes. A user doesn't need to know whether something is AI-powered. They simply need to see the result. For example, when you take a portrait photo on a Snapdragon smartphone, and it automatically blurs the background and applies effects, the user doesn't manually choose to run an AI model. They simply say, 'Remove my background.' The AI works in the background and delivers the result. And the same applies to PCs. There are features like background noise cancellation that run locally on devices using Snapdragon AI. Here too, the user isn't consciously running AI. The device understands the context and applies AI automatically. So users will simply see exciting new features. Behind the scenes, those features are powered by Qualcomm's NPU and AI capabilities. Qualcomm has successfully expanded from smartphones into PCs. What do you think is the next major device category where Qualcomm can create a similar disruption? If you look at consumer electronics broadly, you have earbuds, smartphones, smartwatches, and AR glasses. I'm actually wearing AR glasses powered by Qualcomm's Snapdragon XR platform right now. So there are new categories of devices that are just coming along. And most of these devices will be battery-powered. And that means that power consumption is going to be super critical. Also, they're all mobile. You want to use them and have them with you all the time. Finally, all of these are going to be contextually aware and will need to have the best AI capability because that's where the magic will happen. Now, if you look at all these parameters, you can see that Snapdragon is in the best position because we have all those ingredient pieces to make any of these categories of devices successful. Whether it's smartphones, earbuds, or AR glasses, the core requirements remain largely the same. These devices need to be power-efficient, battery-operated, and capable of delivering advanced AI experiences. And those are exactly the areas where Snapdragon has built its expertise over the years. Do you believe hardware innovation can keep up with the pace of AI development? Innovation is happening rapidly on both sides. Hardware is evolving quickly. AI models are evolving quickly. Quantisation techniques are evolving. Accuracy is improving, and new use cases are constantly emerging. My view is that the pace of innovation today is much faster than it was ten or twenty years ago. Both hardware and software are evolving rapidly, and the entire industry is moving very quickly to adapt. Speaking of how quickly things are changing, what device do you think people will be carrying five years from now that doesn't exist today? I wish I were a futurist who could predict that. But I think it will be some kind of device that can understand your environment contextually and provide value based on that understanding. Glasses are a good example. When I'm talking to you right now, the glasses can hear what I'm hearing and see what I'm seeing. That gives them a tremendous amount of context. Future devices may be health devices, wearable devices, or entirely new categories. But one thing will remain consistent: the more a device understands about you, what you see, hear, think, and do, the more useful it becomes. And those devices will be highly personalised. My AI experience could be very different from yours because the device understands me differently. I believe the world is moving in that direction. And I also believe the smartphone will continue to remain a central device because communication is still its primary purpose. Everybody talks about AI replacing human tasks. What is the one thing humans will still do better than AI ten years from now? AI will become an incredible productivity tool. Perhaps the greatest productivity tool humanity has ever created. It will write code, automate tasks, manage schedules and will help people accomplish more. But I believe there is a fundamental human element that AI will struggle to replace: human-to-human emotional connection. In one word: empathy. There is something about genuine human connection that cannot easily be replicated. AI can be incredibly capable, but emotional connection and empathy are deeply human traits. I think that will remain true for a very long time.