Livestream: Qualcomm Investor Day 2026

Good afternoon, ladies and gentlemen. A very big round of applause for Tony, first of all. Welcome. Dragonfly is here. I run Qualcomm's automotive, industrial, and robotics businesses. As someone who's been with the company for over 30 years, there has not been a more exciting time to be at Qualcomm. Each of these three businesses is quite different and unique, requiring different strategies. But over the years to diversify Qualcomm, we've built new muscle that strengthens over time. We see the next several years belonging to physical AI and the massive transformative change that physical AI is going to drive — especially robotics becoming a key catalyst. Physical AI is the next great computing wave. It doesn't run in the cloud. It runs on the edge — in factories, warehouses, retail, hospitality, hospitals — and robots are going to be a very important part of physical AI. If you look at how physical AI is moving into our lives, you've seen human-facing AI, you've started to see machine-facing AI, and ultimately embodied AI. These three layers are highly interwoven and they compound over time. Human-facing AI has changed our interaction layer — first with chatbots and digital assistants, but now with body cameras and XR glasses. Instrumented AI, machine AI, is about embedding AI into sensors and cameras — making endpoints situationally aware. The real economic unlock is physical AI and embodied AI — the ability for devices to perceive, reason, and actuate with the goal of completing physical tasks. That evolution is just starting, and we see a massive edge content upgrade cycle ahead. In automotive over the next seven years, you will see 500 million vehicles produced with AI cockpits and L2 to L4 autonomy. 50 billion IoT endpoints by 2035. Over a million robots deployed globally. What is today a $300 billion addressable market is going to become over a trillion dollars within the next decade. Our ambition is simple: we need to own the solution — the silicon, the software, and the stack for physical AI. We will win in automotive, disrupt industrial, and define robotics. We introduced our first generation of automotive compute products 10 years ago. Today we are one of the largest automotive compute and advanced connectivity players globally. Five generations of compute silicon delivered in 10 years. We've brought the timeline from first silicon to start of production down to 15 months — as fast as consumer product lifecycles. We now have over 500 million Snapdragon cars on the road, 90 million cockpits powered, and we only entered the cockpit business in 2016. We've launched 450 new car models since 2021 — two new models every week for the last five years. The Snapdragon Digital Chassis is the underpinning of vehicle compute and connectivity globally. We will exit fiscal year '26 at $6 billion in annualized revenue after delivering 23 consecutive quarters of double-digit year-over-year growth. We have built a $65 billion design pipeline. Our content value from Gen 3 to Gen 5 has uplifted eight times. We are engaged with over 70 automakers and over 100 tier ones and tier twos globally. We are on track to become the largest automotive semiconductor supplier across all pure-play automotive. We designed Gen 5 for mixed criticality — customers can run cockpit and ADAS applications separately or together. We are running 30 billion parameter models on the cockpit today, commercially. We can run L2 to L4 stacks concurrently. The software-defined vehicle has become an AI-defined vehicle because we can run agents directly on top of SDV with access to vehicle context. A car drives into a parking lot, sees a QR code, scans it, pays for it — that's an agent. ADAS was a new space for us about three years ago. We are now at 25 OEMs. We have a dozen different stack partners and we're building our own stack as well. We debuted the Snapdragon Ride Pilot stack last year with BMW and are now validated in 60 countries. Stellantis is the latest OEM to deploy the entire Snapdragon Digital Chassis starting SOP28. We see robo-taxis scaling by the end of this decade. We will build accelerators connecting our SoCs and HBC Gen 2 to provide that same tech to automaker customers. We're also seeing token generators inside the car for federated use cases, and IML use cases for powertrain, drivetrain, and battery management. This is why we keep winning: full system architecture of a car, global footprint, multi-generational silicon roadmap, deepest and widest software and AI stack in the industry, years of safety expertise, and tremendous supply chain resilience. Automotive is a playbook for diversification, and as AI is upon us, we are very well prepared. Now let me share what we've done in industrial and embedded. The OT or operational plane in any enterprise has traditionally never needed edge processing — it was all about sending data to the cloud. Now with AI, you have enough information at the edge to process and get to specific outcomes — detecting anomalies, extracting analytics. The OT plane is being rearchitected, creating a once-in-a-generation opportunity. Over the last 18 months, we built Dragon Wing — a variety of vertical-focused solutions powering AI boxes, connected industrial gateways, edge appliances, industrial PCs, payment terminals, smart home appliances, drones, and body cameras. We focus on three vertical categories — industrial, commercial, and mobility — segmented across 12 verticals. Vision AI is a major unlock in industrial. We've built an entire video AI stack from camera chips and AI boxes to on-prem appliances to a full video AI service, deploying across retail, smart cities, venues, and more. We also made three key acquisitions to become more developer-centric: Arduino brought us 33 million developers and a massive global footprint; Edge Impulse enabled model training and tuning at the edge; and Foundries allowed us to manage industrial-grade Linux. We launched Arduino Uno Q and are about to launch Ventuno Q in August — 40 TOPS of AI, octa-core, 12 cameras, full upstream Linux. Our indirect revenue is up 77% from '24 to '26. Tens of thousands of unique customers, over 200 hardware and tech solutions, more than 35 leading distributors, and 45 global GSIs. AI is rearchitecting the operational plane, creating an upgrade cycle across billions of endpoints — a massive market opportunity. We have rebuilt our entire product portfolio, developer platform, and vertical go-to-market in 18 months. Now let me talk about robotics — where embodied AI gets physical. The objective is to perform human tasks: mobility and motion, perception and reasoning, actuating and manipulating in physical space. These are systems that sense, think, and act. This is at least a trillion-dollar opportunity over the next decade requiring a very broad set of technologies that no general-purpose chipmaker has today. Robotics tasks exist on a continuum of complexity. Starting with inspection — reporting status, visually documenting. Then transportation — moving goods, tools, packages, people. Then interaction with the physical world — pick and place, sorting, assembly. This builds up to multi-robot fleets working in coordination, and finally consumer robotics in the home. A robot is not one computer — it's three computers working in concert. System two is the reasoning brain — the cerebrum — handling heavy AI workloads requiring deliberative thinking. System one is the action layer that plans motion. System zero is executing motion — the reflex system, millisecond control, the nervous system. This is a heterogeneous compute problem, and we are the only company architecting across all three domains. The Dragon Wing IQ10 is our central compute SoC — purpose-built robotic silicon that is already commercial. It includes perception IP for visualizing the world across multiple modalities, motion control IP for trajectory and balance, actuation and control IP at the servo motor level, wireless and wired IP for time-sensitive networking, and always-on sensing. Think about a robot picking a jug of water and pouring it into a paper cup. As it pours, the weight and shape of the cup changes, requiring the robot's hand to sense and adjust grip pressure in real time. That is the complexity of a robot. Three systems are active simultaneously — the brain controller perceiving the embodiment's shape and degrees of freedom, the body controller managing limb movement, and the reflex controller handling real-time motor control at the extremities.

Hand to go to the jar. Knows where the cup is and actually takes that motion on. It coordinates that movement. System zero is actually able to sense the grip pressure, the tactile feedback, the temperature, the moisture, the weight, which allows it to act reflexively across these different systems. We have multiple real-time local loops that run within a system and we have slower loops that are running across systems, and we are building embodiment across all these three different systems. We are also building a full software and application stack complete with support and SDKs for manipulation to write to various types of sensor, and we will ship sample applications: pick and place robotic arms, office scout applications, AMR for navigation, follow me applications. This is open to every developer ecosystem including the Arduino ecosystem that we just enabled. The other aspect of robotics development is the simulation data and training model flywheel. We are building this environment in house. We are building, as you can see on the left, a simulation platform where before a robot ever touches the real world, you have to be able to train it in a virtual world. It has to be aware of the physics, the sensors, and the rendering as to how that will take place in the real world. This saves you tremendously in terms of the physical involvement of trial and error. Then we have the data pyramid. That's the fuel for these systems. We combine real world data that Qualcomm has access to, synthetic data that we generate ourselves, and a lot of open source data. And then on the right, we train the foundation model. This is a single model that can take multimodal input like vision, depth, touch, natural language, and it generalizes across use cases. We train these models with simulators, with behavior cloning, and teleoperations, and with reinforcement learning. So the workflow is end to end. We build the hardware, we generate the data, we develop the models, we deploy them into the customer environment. We announced our IQ10 reference design at Computex in June, and this is purpose-built silicon which is shipping today. We also have IQ9 and IQ8 for simpler embodiment. And we already designed into the Neura robots, which you can see outside in the demo area, with whom we offer a complete reference design that powers the Neura cognitive robot arm as well as the 4N1 humanoid. These robots are trained in the Neura gem with the robotics foundation model, and they run the neurov application platform. This is a full stack silicon solution with a key customer, a key partner in less than six months. Today we are powering every type of embodiment, and several are shipping already. We have over 100 engagements spanning the entire robotic stack with companies like Neura and Figure. We are working with several drone OEMs, many AI sensor and embodiment partners. With physical AI upon us, IQ10, the robotics reference design, the end-to-end solution stack ensures that customers and partners design with us. We are taking the same approach that has allowed us to scale very quickly in other businesses. Robotics is already a reality at Qualcomm, and we are very excited to be powering this next generation of physical AI where we believe we are very well positioned. To conclude, a few takeaways. Automotive, I hope you are all believers, is now a track record. We've had 23 consecutive year-over-year double-digit quarters of growth. We don't expect to let you down anytime soon. $65 billion in design-win pipeline. We have delivered and we are still accelerating. And we are on track to becoming the largest automotive semiconductor player globally. We are now a category leader in every domain we enter. And that's not easy to do. Industrial and embedded IoT is now scaling. 18 months in, we have built a product portfolio with Dragon Wing. We've built developer muscle with three acquisitions, four with Modular, and a full vertical stack that goes from silicon to solutions, and robotics is happening now. It's already shipping. Dragon Wing, IQ10, IQ9, and IQ8 are all in production. Partners are integrating them into every embodiment from humanoids to quadrupeds, from cognitive arms to AMRs and drones. Three industries, one IP foundation, one physical AI platform. Thank you very much. And before I turn it over to Cristiano, I would like to play a video from one of our partners, David from Neura. Thank you.

Maybe just add a few things to try to answer your question on supply chain. As we outlined, we have visibility right now of $5 billion in fiscal 27 for that revenue. We have secured capacity as well, secured memory. So even our customer commitments right now on the high-bandwidth compute technology—we have secured memory as well. We're not a small company. We have a capacity allocation. We consume a lot of leading-node wafers. I also think our suppliers are betting on Qualcomm and want Qualcomm to succeed, and I think that is reflected in the capacity commitments we have for the projected revenue we made of fiscal 27 of $5 billion.