AWS’ New Enterprise AI Push, OpenAI Deal with Broadcom, Big Tech AI Ad Planning | Oct 13, 2025

Key Takeaways

[Applause] [Applause] Welcome everyone to the information TI TV. My name is Akash Pasicha. It is Monday, October 13th. Hope you had a great weekend. We have got a big show planned for you today. OpenAI and Broadcom are announcing a major chip deal over the next four years. Our cloud reporter will be up very shortly to put up the news in context. The chief marketing officer of Amazon Web Services is coming on in just a few minutes. So, do not go anywhere. I'm excited for that conversation. We are also talking about the tokenization of realworld assets, which frankly is something I'm really trying to wrap my head around it. So, I'm excited for that chat. After that, we're going to be talking about the AI talent wars with someone who has built a big business in the land of executive search. And finally, we have got a great story about how Salesforce, Google, and Microsoft plan are planning their AI powered ad tech push. There is a lot to get to, so let's get right into our first guest. OpenAI and Broadcom are teaming up. They announced a plan to roll out 10 gawatt of custom AI chips over the next four years. Here to put the news into context is Ana Gardez, our cloud and compute reporter here at the information. Ana, it's a busy morning. How you doing? I'm doing well. Happy to be here. Akos, >> so let's talk about another chip deal that that OpenAI has done with another chip company. Give us the details of what we know and then we'll talk about the bigger picture here. >> This morning, OpenAI and Broadcom announced a a major partnership um to deploy 10 gigawatts of custom AI chips for OpenAI. And it was broadly known within the industry that OpenAI was working with Broadcom on its own chip effort um to help reduce its reliance on Nvidia. But I think you know the publicly the the company's publicly talking about it today and putting a figure on it 10 gawatt over four years really shows how serious the two companies are and you know OpenAI does need to raise a lot of money for this effort. So, I think we should expect maybe, you know, the next couple Mondays we might be on TITV talking about them. >> And it's kind of funny because over the last couple weeks, as we've seen OpenAI do a deal with Nvidia or Nvidia announcing its its letter of intent to invest more money into OpenAI, then we saw the OpenAI AMD deal. I mean, the question that we kept asking folks is, well, what does this mean for OpenAI's own chip efforts? Because we knew that they were going to be working on their own chip. And I guess this is sort of the the closest look we've had at saying, yeah, we're doing it and and we're we're doing it in a big way with Broadcom as well, >> right? I mean, 10 gigawatts really isn't a joke and and that's the exact amount of the, you know, strategic partnership between OpenAI and Nvidia. Of course, OpenAI expects to get Nvidia chips through other deals, but you know, given that this now internal chip effort is the same size as the strategic partnership, I think it really puts into context how much OpenAI does not want to be reliant on one company or even two companies. They they sort of want many companies helping them reach their compute goals. >> And Jensen can't be happy about that. >> My guess is is not really, especially given the way that this was announced today. Um I I think the main takeaway was that you know OpenAI and Broadcom are not just working on a chip. They're working on the entire data center system including networking and other things you need to run run a system. And that is sort of Nvidia's pitch. They they always say that we do more than just building a chip. And so today that is kind of what Broadcom announced as well. And this is one of the things that we've talked about on the show is that Broadcom has sort of some of those products that help build out sort of that full uh data center infrastructure. It's not just the chip itself. >> Exactly. And and I think that's probably why OpenAI was drawn to a partner like Broadcom. Of course, we'll have to see how this all shakes out. We haven't really seen any examples of these Broadcom chips in action yet. So, um you know, with all these announcements, we're going to have to see what happens. But the intent is very clear, >> right? as you're looking for this story to develop further, what are you watching for? >> Well, well, one thing that we noticed this morning was um Broadcom's president um was on TV this morning talking with Greg Brockman and he was asked the question, "Oh, well, is this your $10 billion customer that CEO Hawk Tan talked about on the last earnings call and he kind of made it seem like OpenAI was not that $10 billion customer?" So, definitely one of the big questions today is uh is that true? And who is a $10 billion customer? Because Broadcom might have another relationship that they aren't publicly talking about. That is still going to be important. >> Right. Well, Ana, thank you so much for coming on short notice. That is the beauty of breaking news. We look forward to having you back on as we see more of the developments in this story planning out. That is Ana Gardez, our cloud and compute reporter here at the on TITV. Okay. Amazon Web Services made big news last week with a new suite of enterprise focused AI tools that could challenge the traction of fast growing enterprise search companies like Glean. Some of AWS's tools are new, but some of them are also kind of a repackaging of older AI tools and has already had in the market. Of course, AWS also has a lot more under the hood with its cloud business and its own chip efforts, but never before has there been more competition on both those fronts. And so, I want to bring on Julia White, the chief marketing officer of AWS. It is her first time on the show. Welcome Julia. It's great to have you. >> Well, so great to be here, Akos. Thank you. >> So, I'm excited to talk about some of the announcement you guys made last week. One of the fundamental questions I do have is you guys unveiled Quickswuite. How is Quick Suite different from Q, which is another product that we that we talked a lot about here at the information. Well, Quicksweet really builds on the learning we've gotten from Cube for business as well as uh QuickSite as you also alluded to and then it really germinated from watching our internal employees and the tools they were using and the needs that they had and we brought all that together and as you know better than anyone right the space is moving fast and so our ability to really watch learn pivot and adapt and bring them into a cohesive experience as we call uh Amazon quick suite uh is really the evolution that we're bringing to market this week. So, so Q is does Q fit inside quick suite or how does that work? >> It's really the next generation. So, our Q business customers are being evolved into the quick suite uh application. So, it takes over those capabilities. Of course, if you're on Q business, as we do with any enterprise, we continue to support that. But really, it is the evolution of that and it will replace it in the fullness of time. Well, one one of our reporters wrote about it last week and and one of the things he mentioned is it felt a little bit more like a rebranding than an introduction of new products. Do you not see it that way? >> Well, we bring a lot together that is brand new. for example, you know, have like industry-leading quick research which is one of the capabilities in it where you can go deep deep deep and you know understand what's happening across a whole industry sector put a whole strategy together for you as an example but then the entire uh user experience and the application experience itself is new and and kind of again germinated out of watching our internal comps as well as our external customers and bringing those pieces together. Hm. One of the neat uh parts of of Quick Suite is sort of the enterprise search tool and the ability to use this product across all of your other software that you have installed. It's something that we've talked about in the show in the context of fast growing startups like Glean. One of the challenges that we've written about here at the information is this idea that that some software companies may block or may uh throttle access to their own to to the data that is hosted inside uh their own programs from AI companies uh who were looking to access them. This is the whole issue around corporate data wars. I mean how much of a challenge is that for you right now? Well, we've had in market our index that's now part of the quick suite again quick index that is enabling you know customers ourselves and others to tap into things like Salesforce and Slack and thirdparty and obviously all of the data sitting in AWS which is where most of the world's data actually sits. Uh so we have access to all of that but then the new aspect of it as well is also your kind of your own personal information like Microsoft 365 your docs your PowerPoint your email and u we don't see in terms of we're using public uh APIs we're working in partnership with these organizations and so to your point of u we don't see that uh on the horizon but understand the concerns >> understand the concerns and so but but you're saying that it you don't foresee it being an issue even though it could be one way it goes. I think we're you we're doing it in partnership with so many of these um companies again and so many of them are customers and partners with AWS as well and so very much doing it in partnership with them. >> Right. I want to talk about the ROI that that some businesses are are trying to get out of AI. It's something that has been difficult for some businesses given that these projects can be expensive and also you might not know the right ways in which to use the technology and agents are specifically one area of AI where people have have kind of been scratching their head saying hey I'm I'm trying it and it's slow I mean you know I'm not seeing the impact just yet. Are your customers actually seeing ROI or are these all just sort of pilot projects that they're just playing with the technology right now? But we definitely seen the kind of as people call it that the pilot purgatory right uh and I think that's why we made the learnings we've had again that we've been able to watch learn pivot with quick suite the getting up and started is like zero zero friction right so as a user um you already have your data set up to send your organizations put that in place but you can also just immediately bring in again your documents your access to BI dashboards even information sitting in like snowflake and so the user can get moving very very quickly which again gets you out of just I'm stuck in pilot and I'm actually can use it in a real world way right these tools get access to all the business data you're not just trying to work around it which is usually the problem of getting ROI so again just within my own organization we now run every marketing review using quick sweep because my team can pull everything together instantly we know what kind of insights we're looking for and then it can put it into a review for all of us to share so then that's you're now measuring from an ROI perspective okay if my team now takes half the time to get their business review pulled together what's the value of that and their ability to go instead work on another marketing campaign using those insights versus that two hours to actually just find the insights, >> right? But a as you're talking to customers, I what is the biggest challenge that they have or what is the biggest factor that is preventing them from spending more on AI right now? >> Mostly it is about uh it's interesting. It's such an old world problem, but about data silos, right? And that's what slows down the um the benefit of so many of these tools is getting access to the right data, bringing it together, making it useful. And so again, one of the things we spent so much time on was quick index, making sure that that data silos could be harmonized. Uh and again, take a different approach, right? A lot of the other people in this space are doing it application specific or data silos specific kind of aentic experiences where we looked very broadly again you know taking from our history of being a uh of AWS and a broad uh broad set of infrastructure and data systems that we could bring that forward into the application layer as well because that's what slows people down and that's what makes it not as useful and where the ROI struggles when you can't get access to the right data >> right AWS has its own tools to help people develop their own agents We also saw last week OpenAI unveiled a similar tool in that category. What did you make of their release last week? >> I think you know the Aentic space is moving incredibly fast. I think we're going to see a lot of experimenting and then continuing to evolve. Um and as you seen us bring out you know Kirao our Aentic IDE for developers and seeing really really wonderful success in terms of adoption with developers and what they're doing with it now with Quick Seat Suite for all of the employees and kind of users that organization. And then even just today our new agentic platform called uh bedrock agent core is in G. So all the different tools whether you're a developer whether you're building out the whole infrastructure for agentic systems or you're an enduser kind of covering all those different bases >> right and one of the other things that we've written about here at the information is sort of the the margin pressure that comes up for cloud providers given how expensive some of the underlying technology can be for renting out the these AI chips. How are are you guys seeing any of that margin pressure in your own business? You >> know, our our business continues to be quite healthy and as you see in our earnings and kind of the way we look at it and report it continues to be um quite steady. >> And what about the the tranium uh chip that that you guys have? It's it's it's an interest I mean we were just talking earlier uh on the segment before you about OpenAI's own ambitions to develop their own chip. Uh it's something that we were waiting for more details on. Of course, Amazon has has had this effort going for for a long time. Can you talk about the extent to which AWS customers are actually asking to say, "Hey, we want to use that chip or or you know, we want to use the the compute associated with that chip instead of something like Nvidia, which they might have been used to doing for the last 2 three years. Are they actually making the ask to transfer right now?" Well, as you said, I think our investment, our long-term investment in our own chips with tranium being kind of the most current example is really a wonderful advantage for us, right, from a price performance perspective. And so if you just look at our customers using bedrock, right, our AI platform, over half of that is powered by Tranium. So over the half of customers of many many that are using Bedrock are already using that as well. And then our big big investment called project reineer our super AI uh kind of buildout with in partnership with Anthropic also powered largely by tranium as well. And so I think proofs in the pudding in terms of seeing tranium pay off and the price performance we can provide. Of course by the way we're wonderful partners with Nvidia. We host you know more more of their chips than anyone but uh it's a opportunity for customers to have um variations. >> Right. And I I mean I I just wondered if if internally the company had a goal in saying you know we we I think I just missed that detail. You said half of Bedrock customers are are are using uh >> over Yeah. over half of Bedrock is powered by tranium. Right. So okay by uh by uh by definition then half the customers using bedrock are powered by tranium. >> Right. Great. Well Julia I want to thank you for coming on the show. It was an exciting week of news last week and uh it very much is something that we've been interested to see how it plays out. Uh thank you for coming on the show. We appreciate it and as you have more news, uh, please come back on the show and tell us more about it. That is Julia White, the vice president and chief marketing officer at AWS here on TITV. We have talked a lot on this show about ways in which AI is changing the advertising landscape. It also means big changes are coming for the ad tech sector. Today, the information published a story not just about how existing ad tech giants like Google and Amazon are using AI, but also about how other big tech companies like Salesforce and Microsoft are getting into the game. I want to bring on Katherine Pearloff, our advertising reporter, to tell us more about the story that she wrote. And also joining us in the conversation is Robert Webster, CEO of TA Marketing Solutions. Katherine and Robert, it's great to have you both on the show. Welcome to TITV. >> Yeah, thank you. Great to be here. So Katherine, let's start about let's let's talk about this story that you wrote. You know, one of the things that we've talked about is sort of the marketplace for ads alto together. And this was kind of an interesting story because this is a story one level up. It's about how companies are sort of planning and and evaluating these advertising campaigns that they do. And so tell us a little bit about some of the challenges that exist with respect to people uh planning these campaigns. I mean you've got so many different platforms. What are some of the challenges? Yeah. Um, you know, so the system for buying ads, um, is very complicated. There's a ton of different technologies of involved, especially if you want to buy ads, um, on the web or on TV. Um, there's a whole different system of different ad technologies you have to use. The other challenge is, you know, it's typically seen as a little bit easier to buy ads on like Meta or YouTube, but it's very hard to compare the effectiveness of campaigns across those channels because, you know, Google might use different metrics or count things differently than meta. So, it's very hard to sort of know where exactly you should put your dollars and how well campaign the campaign worked, which then sort of is like a loop because, you know, if one campaign worked, then you should spend more money in that channel. So it's very hard to kind of plan across the top and um AI um I you know agent agents can help sort of simplify some of that potentially by >> creating an easier workflow and being able to be smarter about making decisions about the data. But one of the interesting things that you reported is despite how many big tech companies are in the advertising game, there actually seems to be a movement here where even more tech companies, companies like Salesforce that I have never associated with advertising, they are also looking into getting into this space. How are they looking to do that? Tell us about what you found. Yeah. So, Salesforce, to be clear, has been in the marketing space before, but it's been more sort of like I mean, they've had some media um analysis capabilities, but their kind of main bread and butter that most marketers know them for is email marketing and then like storing your data, which is obviously very related to their core business of just like storing customer um information. And uh I think that you know with um their their new kind of they have this agent force technology that they've been pushing recently and with that technology it doesn't just analyze which campaigns are working and which aren't and maybe do that in a more sophisticated way but it also can take an action for you. So if your Google campaign isn't working it can go ahead and like stop it. Um, and I think it this kind of technology like there it's kind of jargony but there's kind of been two different sets of tech in the industry. Martekch and adtech. Um, martekch being sort of this more just sort of storing your information maybe uh your customer information you know sending them emails sending them texts. And I think with AI those sort and those uh that distinction from adtech which is more about uh executing on media is sort of collapsing a little bit. And I think this is a story we're seeing across enterprise technology that AI is sort of bleeding these distinctions between different types of companies and we're seeing that kind of in the advertising space as well which means more different players can get involved. >> Robert, how are your clients thinking about using AI in the context of of this story? Yeah. So I think as as Katherine said, it's about how you you bring data uh together to make more holistic decisions and a lot of it is around how do you drive uh uh efficiencies. Yeah. How can you remove a lot of that busy work that that has to happen uh that takes a long time and how do you actually use your talent to do more creative um uh better work. So the objective here really is definitely an efficiency saving on time but also driving uh better results. Yeah, we mentioned people like Salesforce like Adobe getting into this space. When you've got customer data also being used to make advertising decisions, >> uh that's just going to drive uh uh uh better results in a very safe fashion. >> And I I'm curious, one of the things that we've been talking a lot on the show is the ROI that comes with using AI and agents. And it's something that businesses are really trying to find really given that AI in many cases can be very expensive and the cost savings the the revenue uplift it can be a little bit vague in some cases. Are you seeing you know really tactical ROI uh that is coming from using these agents in the advertising space or is it still sort of hey we're just trying to figure out how to use it in the first place? >> No, no, the ROI is here now. You've got to think the agents already really been ready for about 12 months and marketing workflows are quite specialized. You know, it's kind of it's kind of bespoke sort of skill set with some awful lot of industry jargon and in the past required experience. So if agents been ready and available for a year, it's probably taken most of this year to get them used. But you're now seeing early adopters getting you big returns on efficiency but also ROI on this. And yeah, talk about how h where is that ROI coming from? >> Well, so if you're trying to make decisions now, you can make better decisions uh faster. >> In a world, let's say you're trying to plan all the media you want to you want to buy. I haven't met a planner yet who knows TV, search, meta, Tik Tok, all in equally well and equally is able to use all of the data sets um equally well across the top. Then also make that global. Let's say imagine you making a decision globally about how to run all your media in like 50 markets. No human can do that. But an AI with a great human alongside them can do that in, you know, 10% of the time to a to a high degree of accuracy. >> Katherine, I want to end with you here. Google is a giant in this space. Second to Google. Who is the company closest on their tail right now? And talk about that ROI point that Robert was talking about here because I think this is it's important. If Robert is saying, "Hey, the the ROI is here." This is actually something it's an enterprise use case of AI that we haven't really talked about as much. You know, it might be the low hanging fruit, something that we should be paying more attention to. >> Yeah. Um, you know, Google, I guess, in adtech, qua adtech, you know, Google probably is a le is the leader. Um, Amazon has been catching up to them this year. It's been a priority. uh there's some other smaller firms that are well known and well used in the industry like the trade desk. But you know in terms of this sort of new area for media planning with AI I think that this is a capability that hasn't really um been as as much a focus for tech maybe it's maybe been like you know I don't know if Robert you know what you think here but like you know it seems like it's been something more kind of like that agencies and ad buyers would just do themselves. So I think it's just adding a new layer where tech companies compete and I don't think that there is a clear winner right now. That's that's why it's kind of exciting to see um in terms of um return on investment. I mean I think that like yeah the the sort of like classic marketing adage that uh is has been said throughout uh history or I don't know maybe the past 20th century is like you know I know 50% of my budget work but I don't know which 50%. And I think that like there was a promise of technology to solve that because oh now we know who's looking at the ads and we can trace that to the purchases. It's honestly made it a lot more complicated because there's way more channels. People aren't just watching one TV show anymore. Like the the media ecosystem is really complicated. The data is really complicated and I don't know if we're actually closer with all this technology to answering that question. Which ad actually drove uh spend? And I think there's a lot of wasted spend going on right now because marketers don't really know where to put their money. So I there's a lot of potential for gain if we can really answer this question. I mean some of it I think is a little bit like how do you really measure if something is persuasive? Some of it might not really be possible. I think some of it's kind of >> outside of the realm of science and technology, but I think some of it we could really measure a lot better. And I think that's why this is interesting. >> Well, look, it's a fascinating space and and it's a it's an application of AI that I don't think we talk enough about on this show. And so I'm excited to have you both back on in the coming weeks and months as the story develops to talk more about this. Thank you Katherine and thank you Robert for joining us. That is Katherine from the information and Robert from tow marketing solutions here on Titv. Okay. When the crypto sector isn't talking about stable coins these days, realworld tokenization is another idea that has everybody energized. We're going to get into what this concept actually means in a second, but more and more companies have started to build products in this category, not the least of which is Robin Hood. Securitize is another company in the arena. The company is reportedly considering going public through a spa at a $1 billion valuation according to Bloomberg. I want to bring on founder and CEO Carlos Domingo to talk about where he sees his business going. Carlos, welcome to TIV. It's great to have you. >> Yeah, thanks for inviting me. It's my pleasure to be here. So I'm excited to talk to you about this business of real world real world tokenization. I do want to start with the news though. So Bloomberg has a report out saying that you are looking to go public through a spa at a $1 billion valuation. Is the Bloomberg report true? >> I cannot comment on that. The only thing I have I can say is that you know the industry has been exploding and has been the largest player and the the one that has been around for the longest. We've been benefiting greatly from that and obviously public markets are very open. You know the circle IPO was amazing and >> right >> then bullish and many other companies went public. So we're considering all the options. >> So okay so you are not going public in the near future. >> I can't comment on on >> you are going public this information. So >> okay well but I I do want to talk broadly about you know the the trajectory of the company. And as you as you see sort of this decision possibly coming down the line whether or not to go public or not. I mean how do you think about the different uh trajectories your business could take and the different options of going public? I mean we saw Coinbase chose one route. We also have the spack route then we have the IPO which seems to be like h it's boring you know. So how do you think about the different options there? I think that the the first there's two things right one is the decision to go public or not that every company needs to analyze their own uh you know particular situation etc but you know look I'm older than you obviously and I remember the times when when going public was the goal of most companies right and companies like Amazon went public when they were very small like couple of hundred million market cap or 200 million etc and somehow throughout the way um you know it just became that everybody stayed private for as long as possible >> so I think that um you know with more avenues to go public as you mentioned you know spaxs and uh which are back from the 2021 time and indirect IPOs like Coinbase did or or just traational IPOs I think there's more options for for companies now and right >> and obviously being public you have the ability to have capital markets provide transparency towards your financials etc so but obviously every company needs to do their own analysis and and in terms of >> what's the right mechanism I would say that >> the mechanism as as far as you execute correctly doesn't matter like the the what it matters for a when it goes public is how do they perform after right so first of all they go public and how they perform after you know 2021 a lot of companies that maybe should have been public went public and have >> and that that's sort of why the you know the the I the part of the report that surprised me most was that the spa part of this I mean you know I think we thought we saw the spa era come and go we're seeing it come back into the conversation h how do you think about the spa as a mechanism of going public >> I think that look many companies that went public in 2021 fun whether they did spaxs or they did IPOs they some of them have performed very well some of them have underperformed right so the mechanism shouldn't be the uh the deciding factor for going public or not you every company should just analyze what's best for for them I don't have anything particularly in favor against IPOs or spaxs so I just think that different mechanisms to go public and what you do after is what matters >> so let's talk let's talk about the fundamentals of the business you are in the business of real world tokenization explain to everyone what it is securitiz and how you fit into that story. >> So you can think of us as a as a service provider for you know taking you know real world assets which for the most part is either you know funds or or equities or bonds etc and then bring them into this new ledger technology called a blockchain to be able to manifest a lot of the advantages of this very uh you know modern ledger technology. Everything capital markets is about updating ledgers right? So you buy a stock, somebody needs to update the ledger saying the stock has changed hands and they need send money and they need to update the ledger of the cash etc. So so ledgers are very antiquated in the industry and they're disconnected with each other. So so blockchain has a a massive uh promise of like being this distributed cryptographically secured ledger where capital markets can be modernized and that's essentially what we do. >> Right. So one of the things you've talked about in previous interviews is this idea that look the the infrastructure on which the financial system is built. It is old. It is outdated. There is certainly an argument for updating that. Maybe blockchain plays a role in that. The question I want to ask you is is why it's beneficial to move towards tokenization for example from the customer and the the consumer's perspective. I mean you know we we've heard companies uh look into tokenizing stocks for example. Why is that beneficial when I mean as far as I could tell people are trading stocks right now seems to work fine for their purposes >> that's true so f first I guess it depends on the geography where you live like obviously in the US uh from the perception of an end user trading stocks is very efficient even though there is a lot of inefficiencies behind the scenes that that the companies uh like Robin could do a very good job of of isolating you from but um there's a scenario where you know tokenized stocks or tokenized other assets have more utility than the non-tokenized versions, right? You can move them around. You can transfer them easily. Like if you try to move today's stocks from shop to Robin Hood, it's going to take you like two or three days. And if you want to borrow against them, it's going to be very difficult. And you know the you're not paying fees uh you know payment for order flow behind the scene. That is uh something that somebody's paying for uh etc. So I don't think that I think that definitely stocks in the US um are perceived as something very efficient but I think there is room for improvement but also in other geographies this a pure accessibility problem right like how do you actually buy stocks? >> We had a busy market in the crypto it was a busy weekend in the crypto markets the past three days uh and we should say you know we we we booked this conversation with you weeks ago we didn't know what was going to happen happened. Um what are people around you in your orbit talking uh what are they saying about the past 3 days in in crypto market movements? I think this just shows uh uh more the the benefit of what we do, right? Because what we do as you said is the real world assets, right? These are not you know that like a lot of these tokens that went down these are tokens that don't have any intrinsic value um that they you know they're just pure speculative assets and obviously they're very liquid and then when they go down they go down hard right like what happens on the on the weekend and people get liquidated and you know then it goes down faster etc. So I think that if anything what we see is is validating our uh thesis that bringing to the crypto economy real world assets that have intrinsic value uh and solid backing it's actually something that more people should be considering. >> Great. Well, Carlos, thank you so much for coming on the show. We really appreciate it. It's an interesting business and an interesting time for your business as well. Uh, look, I'm not going to press you further on it, but if if and when you do decide to go public, come back on the show and tell us more about your plans for the business. >> You'll be one to hear from me. You'll be one of the first me. >> All right. Well, that is Carlos Domingo here on TITV, the founder and CEO of Securitize. >> Thank you. >> Okay. The talent wars have been one of the most interesting parts of the AI boom, and few people have a closer seat to these musical chairs and executive search consultants who help companies find the talent that they need. I want to bring on Chris Davis, managing partner at executive search firm Russell Reynolds Associates to talk about what he's seeing in the market. Chris, welcome to TITV. It's great to have you. >> Hey, great to see you and thanks for having me. I was going to say, Chris, you know, you and I have talked a lot on the phone, but we've never actually seen each other face to face. So, it's it's great to finally put a face to the name. We we we've talked a lot over the years about uh the musical chairs that happened uh in in tech broadly. Look, I I do want to talk about, you know, AI and and the talent wars in AI. We've seen these huge pay packages being thrown around by big big tech companies. You know, at the same time on this show, we have a lot of startup founders who are quickly attracting people from big tech companies to come join join their companies. And so I wondered, you know, as you sort of look at the market broadly for AI talent, what's your sense of are there more people interested in working at the big tech companies right now where there is like unlimited resources in some cases for compute? Um or on the flip side, are you seeing more people move to startups and saying, "Look, I I just can't build what I want fast enough. It's such an important time for uh my my industry." How are you seeing that story play out? >> You know, honestly, I think it probably just segments out like you would see in other roles where, you know, people in a tech forward type of business, some gravitate to high growth opportunities where they want to change the world and you know, the sky is the limit. it could be a unicorn and some will say hey you know I I want to really do this at scale and you know transform like a legacy organization. So it does really depend. I think uh you tend to see different profiles I would say when you segment out those that gravitate to the large orgs versus the smaller ones. The smaller ones I think tend to be folks that are really looking to productize and commercialize the AI opportunities that you see before you and and really you know um take on some some level of risk. Whereas I would say that folks that gravitate to the larger are probably looking to maybe more incrementally transform things perhaps drive more organizational transformation than necessarily focus as much on building new product if that makes sense. >> Right. What what are the the researchers looking for most? I'm sure you you talk to a lot of these high-profile researchers. They are the talent that everyone is after. What do they look for in in so far as how they're considering their next role beyond just, hey, who's going to pay me the most? >> I mean, I think really it just comes down to, you know, the quality of the prompt engineering, the quality of, you know, in some ways it's the curiosity, too. I mean, you know, a lot of this is technical skills, but some of it is the creative skills as well to really think about the scope of what's possible with these models and frankly, not just to be siloed within the world of research, but also to engage with the broader technology organization and maybe even more importantly the business to say, hey, like, you know, we could actually develop new revenue models, new business models with with with model ideas that we have. So I would say it's a combination of just be having sort of had the track record to really understand how to prompt engineer very very well and build these models but also the ability to kind of engage with folks in the business to figure out like what is the scope what's possible and where could we really step change our growth or take the cost for that matter you know through creative new modeling >> right do you do you work with folks at all in the in the chip ecosystem folks that are looking for the next role there at Paul, >> I personally don't. Some of some of the folks at Russell Reynolds will work with manufacturers. >> Yeah. And and the reason I was asking question, I I wonder if you have any insight into this at all, is just the same talent wars that are playing out with the model researchers. I mean, my guess was that there are still a limited number of people that know how to design AI chips very well. I imagine that the talent war must be playing out there and these huge pay packages must be going to those hardware engineers as well. No, >> I would definitely think so. I mean I don't I don't really work on the hardware side as much as the software side. So I I I don't want to say definitively. I think at the end of the day I mean the Talon wars are really happening in the world of AI and you know that they are um resulting in sort of prices ratcheting up folks you know really um sort of sizing up you know what are the alternatives out there and the market's pretty fluid right now. So people are I mean not necessarily as loyal as they used to be. they they move around quite a bit you know it's the next best opportunity >> and last question for you I do want to talk to you about what other seuite positions AI startups and fast growing AI companies are looking to hire most for I I think when you and I had spoken about a year ago we talked about the the uh need for chief marketing officers for example or AI companies sort of building out their sales teams you know are those still the C3 positions that are highest in demand or is it still very uh technical focused you know looking for um CISOs in some cases or or or CTO's >> um I would say uh probably it has shifted a little bit from marketing actually um most definitely the CTO role or the CIO role is one which tends to you know run a lot of the AI and even you know some of the broader kind of AI and organizational transformation but the other area that's really you know really doing a lot of work in AI is product right because at the end of the day you know you see a lot of investment going into AI and the you know one is looking for a return and that often comes through you know the commercialization of these AI use cases into products >> so in both in financial services as well as in tech or fintexs you know I'd say that the the product roles now the chief product officer is very focused on like how do we embed AI and all the different um kind of workflows um actually how do we AI our products >> we make our products more agentic so I would say that you know maybe maybe it's even more product than it was a year ago when we spoke and I would say probably product next to the CTO is what's really getting a lot of attention you know getting a lot of >> well I mean that that would certainly make sense given that openai hired Fijimo as as the CEO of applications and and and that really is an acknowledgement that hey, we have these this underlying technology. We got to figure out what to actually make with it so that we have things to sell. Uh I think it's a great point, Chris. Thank you so much for coming on the show. We really appreciate it. There's going to be a lot more hiring news to come and so I'm excited to have you back on the show to talk more about it. That is Chris Davis, a managing partner, managing director I should say, at Russell Reynolds Associates. Okay, well that does it for today's show. A reminder that we are on this stream Monday through Friday at 10 a.m. Pacific, 1 p.m. Eastern. I want to thank Amazon Web Services, who is our presenting sponsor for this production. And I want to thank you for tuning in. We really do appreciate your viewership. I am already excited for our next show tomorrow. And so until then, have a great rest of your Monday. Bye-bye for now.