Next up is the AI Devices Track. HP is putting the AI PC front and center again this year, two years in, and the real question is whether enterprise refresh cycles are actually pulling forward or whether this is still a category hunting for the killer use case. Ryan, you know a lot about AI PCs. HP is arguing that the PC is becoming a personal intelligence device. Is that a real category shift, or is this just marketing frame on top of AI PCs? I think it is a real shift in the market, right? I'm sure there's some marketing on top of it as well. But it is a new category, and I think we're seeing some of this in a lot of the work that we're doing at Signal65, where we're starting to look at not just do these AI PCs integrate an NPU, or what the performance is, or if they have higher end GPUs, but memory capacity is becoming something that's very important as well as people look to extend what the size and capabilities of the models that they really have on there. I think the arguments about data locality, and where that memory is resident at is really important to the conversation. I think something that we want to pay attention to is what are the procurement and RFPs at these giant enterprises really starting to look like? I think more and more of them understand the potential value of running this AI locally, both from a security, privacy standpoint, but also just raw cost savings as well. I think there's some interesting changes that have to happen on the software side for that to really take off. But people should be thinking through, what does my hardware need to look like today to be a part of that near-term future? Nick, what do you think? Yeah, I just had another kind of enterprise sort of lens on that. It is whether IT actually has any policies in place for deciding which workloads belong on device versus what would belong on the cloud or elsewhere. You could think in some ways the hardware is, the capability of that is slightly ahead of that decision making. Until that catches up, the sort of personal intelligennce device branding is, I would say in some ways, it is kind of a technical shift that enterprises in the whole are not necessarily positioned to fully exploit. I think there is definite value in the devices, is whether how it fits into that whole IT sort of coherent framing. Yeah, it is interesting. Once again, we get back to this question of where will inference live? To your point, Nick, the hardware can handle it. It is a question of getting ahead of governance and policy in terms of where workloads will run. The other interesting aspect to this is, you go back to tokenomics, for lack of a better term. Just think of how much money you can save if you are not going out to some massive data center to generate work that you can do on your laptop that you have already paid for. As those costs are truly exposed, I think that enterprises are going to get on board with this move to more inference out at the edge. Let us go ahead and kick off the device or the AI Device Track, with Ketan Patel. He is President of Personal Systems at HP, and he is going to be talking on the subject of, is the PC becoming a personal intelligence device? Welcome to The Six Five Summit 2026. The theme of this year is AI Unleashed. Daniel, it is amazing over the last three years, all the twists and turns. I guess three years in regular is like 30 years in AI time. Yeah. It's seven years of The Six Five Summit and how AI became just the epicenter for three years. Yeah. Yet we're still unleashing it, and it's funny because despite the fact that we're so far into this process- Yeah. -it still feels very early to me. I don't know. For sure. One of the biggest trends that we're seeing is, the conversation used to be with AI was all about data center. Now it's very clear. You're looking for sovereignty, you're looking for token efficiency, you're looking for spreading all the love out, in the enterprise. Quite frankly, with consumers, that is going to be the client device and devices is going to be as important. We are here with the AI Devices Track opener, and I would like to introduce Ketan Patel, President of Personal Systems at HP. Great to see you, Ketan. It's been a pleasure to get knowing you outside of the video and our meetings. Anyway, welcome. Thank you, Pat, and congratulations for The Six Five Summit. I appreciate that. Yeah, it's just, Ketan, every year and it's moved so fast and you're in the middle of it, and it's a really exciting time. Your job here is really talking about this shift that's going on and there's been some stop, some start, some acceleration. I think we're all realizing that we've entered this era, this time, where we're going to want to bring some workloads onto the device. Yeah. There's an economic story there. There's a convenience story there. A lot of us have been doing it for a long time, just kind of subconsciously just on our phones, but on our PCs. You've been talking about this for some time, the personal intelligence device. I'd just like to kind of get your broader thoughts on this. What's going on here, and what's shifting? What's driving the big shift right now? This is an amazing time in the world of personal computing. PCs, as all of us know, for the last two decades, have been a tool you operate fundamentally click, type, g ive some commands, and it executes. That's how it has been, and it has really served the purpose very well across enterprise, small businesses, and consumers. The world which we are now seeing is completely different in the world of personal computing and moving to personal intelligence. I say this because there are three fundamental shifts which are driving this. Number one, as of today, almost 72% of the organizations are almost deploying or piloting agents. Clearly, as agents start getting deployed, you will see intelligence increasing on the devices more than ever, because agents will be autonomous. It will really help user try to have work, which is like a companion for themselves, and agents work autonomously for them, rather than user giving commands to the machine. So a lot of intelligence will be built just because of agents coming into the environment. That's trend number one. Number two, in the world of agents, humans and agents still will have to work together, because eventually it is about how the agents are actually driving personalized experience for individual, because you and me will have different needs, different context, different requirements, and how they work with each other becomes super critical. Most important is about governance and security associated, because how I want to operate my agents with a certain governance is different than probably yours. So that's where PC is the right platform where you have ability to interact through right level of governance and security. Third is PCs are becoming more and more powerful. Now you see the latest silicon architecture and the way we look at system design. The data center is coming to the PCs, as you see some of this new generation architecture can actually even host 120 billion parameters models locally on the device and really take care of a lot of this token efficiency topic, which we can talk more. These three fundamental shift is also now giving software players a lot of investments they are prioritizing of developing capabilities directly on the PCs, which was just 2% in 2024. There is a huge shift happening. This world of personal intelligence is exciting as these three vectors are coming through, and we are at the center of it and feel very good about how we want to take it forward. Yeah. Ketan, you have talked about, and you have said the future is hybrid AI, and I think for the most part, if you would have said that a year ago, people would have looked at you cross-eyed. I think those inside the industry and those who are talking to customers realize that this is true. Will you break this down for us? In the end, it is about unlocking value, right? Yeah. It is less about- Yeah. -the cool factor, although I like cool factor and whiz-bang technology, but how does it deliver better results? Absolutely. I think the way things started on AI is about all model training. Of course, it was all on the cloud, and it was very important starting point. We believe that that trend will continue as the models will get continuously refined. As you think about workloads coming into the real user environment across enterprises, inferencing is now the important thing in terms of how you use the models and actually utilizing for your use cases, for your workflows, for different personas within an environment. As you think about how people started deploying initially, the tokens just maxed out as token maxing and token economics is a big topic nowadays. I was with some customer roundtable just a few weeks back, and we got inputs that, hey, a certain customer spent $20 million previous year as they started implementing some of these models access to their employees. This year, the bills are up to $200 million- $300 million and increasing by the day, and it is becoming a CFO topic in terms of how to really manage this entire equation. On one side, you want employees to get the latest and greatest. Right. On the other side, you want to see the economics of it and what's the ROI the company is getting. This is about really from experimentation or pilots to maybe moving to profits is something which is going to be super important as customers look at the overall cost associated. That's why essentially we believe the future of inferencing is going to be distributed or hybrid. Cloud will remain essential for large-scale model training, deep reasoning work, and certain personas who will have to go more, to access that. A lot of workloads, which are in the enterprise by industry type or personas, can be managed on-prem, as you can actually now load lot of open source models on-prem as well as on device. Just to give you an example, a laptop which we have today can have a 20 billion open source model hosted onto it. Then as you go to on-prem, it can actually even host up to trillion parameters of models. How can now you as a enterprise deploy solutions across the enterprise which can access model on device or on-prem or go on cloud seamlessly, but the user gets the best experience, the organization gets the best economics, and you are able to effectively run in a right, secure, and governed environment. That's where the trend is going in terms of how we see this architecture coming through, just combination of economics. The second big area apart from economics is security and governance. One of the other challenges a lot of customers are dealing with is how data flows across on-prem or cloud. There is certain data, one is okay to move, and certain data they want to make sure that remains within the premises. That is another trend which we believe is going to be super important as we think about distributed AI, where the data remains on-prem, and then the signal goes to the cloud, and then you are able to process the right query for a specific customer. Data sovereignty conversation was discussed a lot about three years ago. That kind of, I don't know, it went to bed, it hung out, and then even recently, in the last six months, it has become this major conversation that is at the boardroom, right? It is. It is beyond the CIO when there is this potential conversation about intellectual property leaking into a model. Then it is a very strategic conversation at this point. Oh, yeah. Just to add on that, because a lot of customers don't want to your point, on the sovereign data, their own IP and intelligence to become public information. Right. How do they otherwise differentiate, while they definitely want to access the latest and greatest, but they want to keep their proprietary information themselves. Yeah. That presents a big challenge. It also opens up opportunities for whether it's on-device, whether it's open source. Of course, the frontiers are having a lot of fun, and they're building really great technology. Yeah. We're thankful for it- Yeah. -because the open source wouldn't be coming, and we wouldn't be building around it. But at the same time, the economics, to your point, don't necessarily make sense. You guys sponsor the Ferrari. Yes. I like the analogy that you don't need to drive the Ferrari F1 car to go pick up your coffee from Starbucks. There's a lot of workloads, and I think I saw a figure that you guys had come out with something like $650,000 per 1,000 employees- Yes. -could be saved. I would actually argue it might be larger, because that's the assumption based on almost linear thinking of what we know they do now agentically. But I know when we were talking, we said maybe it's one human employee for 10 agents, 20 agents, but that number's going to be thousands and maybe eventually more. Companies that are making decisions at the board level, CFO level, then at the technology level, can probably create an incredibly compelling TCO- Oh, yes. -to have a hybrid and distributed strategy. Oh, yes. I think the example which we gave of $650,000 for 1,000 employees is just for very basic queries. Yeah. Which can be run by a very basic local model. As models get more sophisticated for local hosting, including the example I gave of imagine a 100 billion parameter model sitting there, it can even start running other tasks. That $650,000 per 1,000 employees can just move in terms of savings to a very different level. Hence, this entire TCO or economics across the distributed layer is going to be critical for business leaders and CFOs to look at what they get and at what cost. Let's just pivot a little bit here. Every company across the tech stack right now is trying to tell the customer how they help. The model companies, the infra companies, the device companies, the middleware, the applications, they all are kind of, "Here's how to apply AI." And one, it's both incremental, it's additive, hopefully it's productive and efficient to the business, but you need to figure out your own strategy. What is HP's to help customers harness the power of AI? And I love that the word harness is in there, because then it becomes- Exactly. -like a real dorky thing we can talk about, too, is- That's nice and nerdy. -harness, but cert. Yes. Let's keep it at the high level. How are you guys helping? Yeah. Our approach is pretty simple. We want to think about three fundamental layers we want to help customers with. Number one, we have devices. Clearly across PCs, printers, rooms, workstations, peripherals, and many other products which HP has. There is a device, but on device, we want to make sure how we drive our unique HP experience layer through which customers can access all of this on-device thing which I was talking about. That's layer one. Layer two is about workplace ecosystem, because along with the device, there's a workplace ecosystem which is around, and how do we make that seamless for the customers? The third is about for IT, how do you make it a good control plane? Because as you imagine, IT was managing, let's say, 300,000 devices in the past. Tomorrow, they'll be managing 300,000 devices or even more, but also manage 3 million agents at the same time. Right. How do you really provide that unified experience from an IT perspective, also, of ensuring some of these things are seamlessly working? Let me give you our approach across the three layers. From a device layer, we want to make sure that we are able to bring intelligent devices. When I say intelligent devices, what do I mean? The current PC has a certain capability, as we started the conversation on. But the PC of the future will have more context awareness, the surroundings across audio- Yeah. -video, the sensing capabilities which it can have. It is the only device which actually will have both personal and professional context in the most optimized way. We want to make sure that that context becomes a pretty critical pillar for any outcomes which the customers will get delivery of. That is number one. Number two is about the ecosystem experience, which we want to make sure as PC gets connected to the entire workplace, it could be all products which we do, like printers and peripherals, but any other device in the ecosystem, how does it seamlessly operate? Because it is not about an agent on the PC alone. Right. An agent on a PC should operate seamlessly across the infrastructure to have a seamless experience for the user. That is another layer of ecosystem where we want to make it super smooth for the user to have a unified experience. Third, as I spoke about, the HP Workforce Experience Platform and the HP Wolf Security stack which we have are two big properties we want to make sure IT is able to use to, as I said earlier, deploy all the devices, manage all the devices, drive the right level of security policies, because one of the biggest pains IT is going to deal with is about governance of these agents and driving the right level of policy. That layer is super critical. Then the whole security stack which we have in order to help how IT will manage the entire infrastructure. Those are the three areas how we are thinking about making sure that what role we play- Yeah. -in the entire infrastructure. Eventually, our fundamental role also is going to give token economics, TCO, to our customers, saying, "Hey, bringing these loads into the distributed or hybrid AI gives you this kind of an advantage. Great conversation. I want to go macro again and talk about the opportunities that agentic AI brings to the PC industry, and it's interesting. Historically, it comes in waves, right? Yeah. Whether it was multimedia, DOS to Windows, the internet transition, the sub-$1,000 PC, so many, gaming drove PC gaming, and when we were all working from home, right? That was another piece. I am curious, and let's put the memory things aside right now. What is the long-term opportunity here that you're seeing for the PC industry? It's a phenomenal opportunity as some of the trends which we spoke about, because the category itself is transforming at a very different level versus a regular, I would say, addressable market which you would have seen in the past. I look at it from a perspective that agent-based AI market is almost a $6 trillion TAM by 2028 as a total agent-based AI opportunity. Within that, there is certain area where the PC industry can play, and I think the devices and some of the ecosystem thing which I spoke about will drive huge premiumization in the category. We spoke about the example of a $650,000 for 1,000 employees, likely to move to a $2 million, let's say, per 1,000 employees, and so on. If you start saving as a customer almost $1,000 to $2,000 per user on a PC, the premiumization in terms of getting some of these agentic capabilities and the local models which I spoke about, it will only increase premium on the PC. This entire opportunity of premiumization of the PC is only going to go and give tremendous opportunity to all of us. The other big area which we believe we have a huge role to play is in this entire local on-prem deployment and driving cost economics, ROI-based outcome for the customer. That's another area. Apart from the devices play, that is an opportunity unlock for everyone who is in this place, and we are, of course, the frontrunner, and we want to make sure we are leading in this space. Lastly, because we are going to unlock a lot of new experiences through agentic and the personalization thing which we spoke about earlier, it gives opportunity to the industry to get into a new software solutions and other revenue and margin unlock which the category has not seen before. Yeah. If you look at all these three layers, the opportunity is going to be now unlocking value beyond selling hardware and making transactional margins. At the same time, making money and profit for you and your investors, but you are now adding tremendous value to the customer as they are going through their AI deployment transformation, and that, to me, is going to be a huge value which we can add as an industry as customers go through this journey. Good answer. Okay. I agree. Vote of approval. The seal of approval. Patrick Moorhead. That is the seal of approval here. Whatever that is worth, folks. We will see. Kicking off the AI devices track here at The Six Five Summit. Ketan, I want to thank you so much for making the time to be with us here. Thanks for having us into your home. Thank you. Thank you, Dan. This isn't really his home, but it's the home of HP. Yes. I don't know. We don't know how many hours he works. Maybe it is his home. Yeah. Home-ish. Thank you, everybody, for being part of this year's Six Five Summit. You just heard it here. Ketan Patel, President of Personal Systems at HP, kicking off our AI devices track. Be part of our Six Five Summit. Stay tuned with all of our other content. Check us out at sixfivemedia.com. We appreciate you.