Transcription
Let's talk about whether AI will have us all transacting within chatbots and whether your purchase data might help AI agents give you better recommendations. We're joined today by Rubel Burwalker, the global head of growth products and strategic partnerships of Visa, in a conversation brought to you by Visa and Rubel. It's so great to see you. Welcome.
Thanks for having me, Alex. Okay, so let me start with this question of conversational commerce, or, um, you know, that's a jargon way of saying maybe we'll just all kind of talk to the things that, to talk to chatbots and then be able to purchase right within them. It's been a, it's been a dream of, of social media companies, of messaging companies for a long time, that maybe one day, um, because the messaging app will have your context and maybe some of your preferences, that you'll prefer to shop there versus, like, let's say, you know, a website with a graphical user interface. Um, but some are saying that maybe generative AI is the technology that can finally get the industry there, that can finally get people saying, you know what, ChatGPT, for instance, knows me, and so therefore I'm going to ask it, you know, uh, what jersey should I buy or what gift should I get, and then it will go ahead and facilitate that. Do you believe that this is going to be the thing that finally enables this sort of, uh, long, long-running tech dream to come true?
Uh, look, TLDDR, I think the answer is yes. Um, but the long-form answer to your question is, we've actually seen commerce get intelligent quite, in a, in a relatively quick evolutionary manner over the last 15-ish or so years. And what we're seeing that's happening with agentic is, it's just like, what we call the next evolution of how intelligent it could really, really get. Look, as, as, as someone who's been at Visa for a very long time, I think I, I see myself as a little bit of a historian, which is, we've seen about in the last 35 years or so, we went from what we called originally online commerce, which was the original, you know, sort of like tea leaves or e-commerce was headed. And e-commerce was all about access, because you wanted to access goods and services and pay or get paid without actually being in, in front of a merchant or a seller or a buyer. Then came mobile commerce, which became all about accessibility, which was, you wanted to be able to buy, pay, get paid while on the move. And finally, I think in the agentic era, which is like another step in what we call intelligence in the way commerce is going to move, it's going to be all about autonomy and personalization, which is, everything you did, you can now do it better with better data payloads, with better personalization, with, you know, almost a better way of identifying who you are as a human being and what sort of, like, preferences you really, really have. So, I, again, I think the short answer is yes. Um, and, you know, the tools that are going to get there, a lot of those tools have been in development for a very, very long time. And I think now with the advent of what LLMs and ChatGPT and a bunch of other AI companies are doing, I actually think, yeah, it's going to get, it's going to get really, really fun.
Okay. So, you are a believer then in this vision. And it sort of leads me to a natural follow-up, which is, do the chatbots sort of become the storefronts of tomorrow? Are they going to be the place where we do most of our transacting? How does a chatbot fit into the picture of, you know, transacting online?
Uh, it's, it's the, the way we think about it, Alex, is, you know, before online commerce existed, um, you know, you walked into an AMC theater to buy a movie ticket. Then you decided to buy sometimes online. Then you sometimes decided to buy it because you clicked on an ad on a social media website through their app. And that doesn't mean that physical commerce went away. It just, they were like, the share shifted toward more channels in the way human beings actually interacted with it. And we think with agentic, you're just going to see another channel that's going to be very helpful in certain types of commerce, in certain segments of commerce. Um, which doesn't mean that, you know, the existing channels are going to go away. I just think there's going to be a good amount of migration from how things work today to a portion of that is going to move to agentic. So, like, that's right, that's that's that's that's the hypothesis we are working with.
Yeah. It's sort of like, you know, they, we, we have these conversations, okay, is the AI device going to replace the phone? And the answer is always like, no, it's not, but it's going to be there. It's going to factor. Um, I, I wonder though, in terms of commerce, it's very interesting because, um, these bots, you know, I, when I was reporting, for instance, on this, uh, this was 10 years ago, Facebook Messenger had this platform where they wanted, I'm sure you remember it, they wanted you to transact there. And one of the things that they always told me is, if you're in a messaging app, you're effectively, you have a single source of your conversation. So they know who you are, they have your payment information stored. Um, with LLM, it's even more advanced, right? It's like, they know who you are. They have your payment information, uh, probably, and they have a deep understanding of your interests, your preferences, sometimes who's in your life. So the potential there, to me, seems vast.
Indeed. And I think what's changed from the example you pointed, correctly pointed out, is now take all of that personalization and context, and then you add how the LLMs and the agents interact with the outside world and their understanding of the outside world, and then connecting those back to your preferences, which is where you start to really, really connect the dots. So while you may have had a payment credential stored in a messaging app, for example, and, you know, we've seen wallets in parts of Asia, Latin America do this very, very well. Ultimately, it was still, while it was intelligent, it's still dependent on sellers like onboarding themselves onto these platforms to make themselves available, um, to consumers with their preferences. And I think in the new agentic world, I think that becomes an even easier sort of, like, connection to make. So I think what he's saying is accurate. And I think it's going to become even more real with how quickly we're seeing, how quickly we're seeing these agentic bots like be so useful in things that human beings would ordinarily spend a lot of time doing.
Right. Explain how it becomes easier, because that's sort of, it seems counterintuitive to me, because you would imagine that, you know, storefronts or whatever still have to go through the same process to onboard. Is it that the, when you, let's say you're using, for instance, I don't know, the Atlas browser from OpenAI, and you say, book me a plane ticket, you don't really need United to participate, you know, for the, for the browser to go in and and make that deal. Um, I'm just, I'm just spitballing here. Talk a little bit about these connections.
Yeah. Actually, in some ways, in, in the use case that you just pointed out, I think United becomes even more important. Because I am a, you know, like ardent United user. They know exactly what I like. They know I like the aisles, aisle versus window. They know what kind of meal preferences do I have. They have a long amount of history on how I like to fly. They have a very, very good understanding that typically when I'm trying to go to say, Asia, I try to like fly direct, like at, you know, like usually at night, because then I can just sleep and wake up and go, go to the office. Now, United has an enormous amount of history, and I typically try and stick to United, although today, if I'm looking for flights to go to Asia, I could have probably have cheaper options, but I prefer to just stick as a loyal member of United. Similarly, sometimes I like using a specific bank card that I like, that I have a lot of loyalty toward. So that definitely matters a lot. I think, you know, brands and brands knowing users and their preferences, and sometimes it's guest money cost as a way to enroll. But I also believe, like, you know, how does a brand feel like, say, you're flying Singapore Airlines, and you really like the soft product and the way you get treated as a customer, and those things don't really go away just because there is a better convenience of sort of like getting to the end answer. I almost might sort of like restate the problem statement, which is, if I am using an agentic surface, whether it's a, aentic browser or a, um, conversational commerce type interface, the question, at least in my, in my experience and everything that we hear from, you know, clients and merchants, is typically less to do with, go book me a plane ticket. It almost always starts with a much, much broader funnel of discovery, which is, and I'll give you my personal example, I have two daughters, they're very, and we're trying to plan to go to Hawaii this Thanksgiving. So my question actually starts with, book me tickets to Hawaii. It's usually like, hey, I'm trying to go to Hawaii, sometimes around, sometime around Thanksgiving. What do you recommend is a good island to go to? What might be a good day to fly? Where do you think I should probably stay? And so it's starting like much, much further up funnel before I even have decided which island to go to, which airline to take, which day to fly. And that sort of, like, leads me to doing an entire discovery process until I sort of, like, get to, okay, I've decided I'm going to fly the day before Thanksgiving and I'm going to come back on the Sunday morning of, so we can get some sleep because I have to go back to work the following day. I'm going to try and go to Maui and I'm going to try and stay at Marriott because, you know, I'm a big Marriott loyalty Bonvoy member. And by the way, I really like it because they have like, you know, three extra pools which my seven-year-old daughter will really, really enjoy going to. So payment, at this point, I'm not even thinking about making a, it's not even commerce yet, it's still discovery. And as I go through the discovery journey, there is going to be an enormous amount of like, you know, brand influence, personalization influence. And I think the LLMs and the agentic surfaces can actually truly make that process so much easier. If I tried to do this a couple of years ago, um, it would have taken me a couple of hours. But now, I think with the help of these tools, it's made it so much easier. And then the last mile, which is when you, when you sort of go through your discovery process and then it gets converted into an actual commerce, is where all the focus is. I don't know if that answers your question, Alex.
Yeah, it definitely does. And it's very interesting for me to hear your perspective because, of course, you're coming from Visa. That's why this conversation is interesting, right? Because you, you are in active discussions with the platforms about the way to facilitate this in the best way. Um, and of course, you, I think Visa has ways, if you're, if you're a Visa user, you, you might want, Visa to help make this, you know, make the recommendations more personal. I'm just spitballing again, but talk a little bit about the conversations that you're having with the platforms and how, um, you know, Visa might be able to enable this, uh, in a way that, you know, we haven't seen yet.
Yeah. I think, uh, look, there's one thing we pride ourselves at Visa amongst many, many things. The one thing is, you know, I wake up, but Alex, do you have a Visa card?
Of course I do.
Um, and where you based again, remind me, are you East Coast?
East Coast, yeah.
So, you know, you can, in New York, you can probably, you know, get on a, get on a plane from three airports that are close to you and fly to what, 150, 170 countries around the world. You can whip out your Visa card and it works exactly the same way, no matter where you are. And there is some form of magic in how that works, and you feel like your money is safe. And if you didn't get the good or the service that you paid for with your Visa card, you feel like you can call your bank issuer for the card, um, you know, with the Visa guarantee and the brand and what it represents to a user. Now, that's just true about what we try to do, regardless of which channel a Visa card is being used, whether, you know, you know, Alex flew to like Azerbaijan or Colombo, Sri Lanka, and decided to make a purchase, or you decided to buy something from a seller in the Philippines, or you decided to use your, a mobile app and bought, you know, like, you bought some stable coins, or you bought a bunch of Bitcoin. It almost doesn't matter how you want to, how you, which channel and which market you want to use. You kind of want to use your Visa card and you expect it to work almost exactly the same way, no matter where you are. And there is an enormous amount of machinery and work that goes in to make that real, because remember, every market is different. Every market has different nuances. It has different regulation. It has different data localization requirements. It has different, you know, things and the requirements that you need to meet. And when we think about agentic commerce, I think we are enormously focused on, as these new, incredibly great technology platforms come, come to pass and consumers use them, we want to make sure that their Visa card in those platforms, for any type of commerce that they want to do, works exactly the same way, regardless of what they're buying, whom they're buying it from, and where they're buying from. So, a lot of this is like, not super sexy stuff, but it is the stuff that we want to make sure that works with as little friction and as little fraud as possible. And we spend an enormous amount of time with these platforms, with big tech companies, with our acquiring community, with the merchant community, with the issuing community to solve those problems. And obviously, I think you asked about personalization, and we actually think that personalization in general can be a very, very helpful barometer to even further get to better discovery with the right consumer consent. We are big believers in data privacy. We are big believers in giving consumers full control over where their data is and things like that. That we've introduced things like data tokens to help consumers with better signals that they have associated with their credentials that, you know, platforms can use to provide a better discovery process. So, so we spend, we spend a lot of time doing these things.
I'm curious to hear you talk a little bit more about what the discovery process could look like because this idea that, you know, we might provide the LLM with lots of information about us, I think we, we're already there. I mean, we probably share more with LLMs than anything else. And we're being honest, some of us are in love with these things. Not me, but some people. So, how could this discovery process, uh, look as, as Visa gets involved?
Um, I think the simplest way to think about it is, you know, you use your card to do a number of things in life, and a lot of those are frankly not used at LLMs, right? You walk down the street to like Pete's or Starbucks coffee, and you like to stay at the Ritz-Carlton versus like a Motel 6, and you typically like to fly United versus Spirit Airlines. Now, those are just things that while your agentic platform surface area LLM may have a lot of information about you, those are just like personal preferences tied to your long-term spending preferences. And what we believe is, if the data is private, if it has full consumer consent, if it is totally tokenized and no raw data has actually moved anywhere, but can there be a bunch of signals that, you know, you compared to like other spenders that an agent or a company can sort of like consume based after you've like fully consented to it and after consuming, say, you say, I want to go to Tokyo and I want to live in the, I want to stay in the Ginza district in Tokyo for a week. Um, you know, and give me hotel recommendations. Now, knowing that you like to stay at the Ritz-Carlton, or knowing that you generally have a propensity to stay in like a signal that tells that you have a propensity to actually stay in a luxury hotel, would be very helpful for an LLM to say, oh, you know what? Here are the options which we think could be a lot better fit for you than a bunch of other options that might not. And at the same time, you might like living in hostels, and you might like being, you know, closer to the community, or you like, you know, some form of like a Airbnb type share rental. And I think all those signals really, really matter to give you a much, much more richer personalized, some like recommendation. And if you get a much more personalized recommendation, that recommendation getting converted into a commerce transaction just increases by a lot, lot more. For us, all in the service of, you know, making sure that we're making true commerce happen.
Definitely. I was going to say that it, it even makes sense, like, let's say I'm, you know, as I'm starting to use LLMs more and more for search, you know, I have, I say, can I, you find me a hotel? If it knows I have a certain hotel brand I like, like you were saying, um, then maybe it goes there. Or even as simple as like, hey, I'm at this conference, where can I get a cup of coffee? Uh, and what's open now? If it knows I'm more of a Starbucks than a pizza person, you know, maybe that's where it goes. And to me, that's sort of, again, it's like the getting to this utility thing of where, where you want to end up in conversational commerce, where it's easier, uh, than everything else. Seems to me like that's the only way for it to take off. That's how it gets there.
Totally. And, and, and, and the, and the positive of that is that it's actually saving you an enormous amount of time, adding more discovery searches to get to the answer you really want. And it's sort of like, almost like solving a time problem, a discovery problem in ways which we think is very, very positive for the end user. Now, here's a question. So, we've talked a lot about agentic stuff, uh, and we talk about agentic, uh, AI and what's real and what's not, and the risks and the benefits of it a lot, uh, on this channel. And I can't help but thinking as we talk, um, we're obviously going to put a lot of trust into these things. Um, what, what is the Visa approach going to be if, um, let's say my AI agent goes out and uses my Visa card and buys a lot of stuff for me, uh, that I didn't want? You mentioned you can trust Visa, you go anywhere, use Visa, uh, Visa's got your back. Does it have my back if an agent goes out and buys some stuff that I really didn't want?
Um, look, that's, that's the fundamental question. We spend an enormous amount of time, um, fixing and thinking about. And again, like, I can give you a parallel, right? What does that really, really look like in an e-commerce world that's not agentic yet? You know, someone can't actually take your card and actually use it. You know, PII and PAN data get, gets leaked all the time. You know, hackers have access to like credit card information, stuff always happens. And so everything that we design and build, we are deeply, deeply focused on how do we make the, make sure that the vectors and the surface area of fraud is as minimal as possible. So in the Visa Intelligent Commerce APIs that we introduced earlier this year, and some of the work that we're doing with our partners, we are uber focused on ensuring that any Visa credential that is used in an agentic environment has a high level of trust and security associated with that. So let me explain what that means. So if, say, if you have a Chase Sapphire card that you're using for a specific, you know, agentic app on your iPhone 16. Now, if we can tie your root of identity to that app on that device, and we can assign a token where if someone actually tried to use it anywhere else, not like that's not you, or not in that app, or not in the device, that transaction just wouldn't work. So we actually upfront are working very, very hard to create like high authentic, high authentication when a Visa credential is actually added for a purchase transaction in the beginning, because that in itself just reduces the amount of fraud that could potentially occur when that happens. That's one. Then we, we're working, you know, with the industry about figuring out like, how do you make sure that the right biometric authentication is captured at the time of giving a purchase intent, right? Just because you have a card associated with an agentic app doesn't mean you're actually using it, but at some point, you're like, actually, I want to, want you to go use this card to buy Taylor Swift tickets for next Friday, and it might ask for like a biometric authentication of some kind, assuming, you know, you haven't really used that card for a purchase before. So, like, and by the way, those tend to have like, very, very, very, very high levels of network security that we work with the industry to ensure that happens. And then the third thing is, we, as this becomes more and more common, or will become more and more common in the coming months and years, we've introduced incremental data payloads on things, what we call in our APIs, called payment instructions and signals, where we actually try to match the consumer natural language intent to the thing the agent is going to buy before we, in, before we actually release the credential to be able, what we call like a cryptogram, before the credential can actually even be used for a Visa, for like a Visa transaction. So now, again, those are the controls and limits we are trying to sort of like introduce in the payment journey to make sure that we're trying to keep as much fraud, you know, friendly fraud, synthetic, merchant, bad agent behavior out. We don't, and again, again, we're very, very early days, so it's very, very hard to tell what the data is going to tell us. In some ways, we, we're going to be like mapping and looking at this data very, very closely, as we've done in the e-commerce world, as we see more and more transactions occur and start from an agentic environment. Like, what kind of, like, you know, behaviors are we seeing? Are we really seeing, you know, where you ask for a black bag and the agent bought a blue bag? Are we really seeing mistakes are going to happen at the merchant end? Are we really going to see some hallucination? We don't, we don't know yet, but we've made, we've added the controls in place to make sure that we can try and reduce it. And as we learn and sort of like get more mature and smarter about the space, you know, we're going to evolve our product to make sure that it actually fits the consumer needs. It's a little bit of a trade-off between making sure that there's not a lot of consumer friction, but a consumer's money is being safe, is kept safe. And we're going to hopefully sort of like use some of this data to do better on disputes and chargebacks and hopefully, you know, make sure that we are getting smarter and our community is getting smarter. So when you actually do call your bank and say, I ordered a blue bag and a black, not a black bag, and if you have the captured data that actually said, you actually said a blue bag, it'll be a lot more easier for us and the banks and others to adjudicate whether the dispute was actually valid or not. So there's like, it sort of like falls through the entire Visa ecosystem, that let's make sure that we reduce the, the vector of fraud and then do the best we can to try and use data to make better judgment calls on, like, what does this really look like, and then, you know, tweak our product to see how this all of this evolves in the coming months and years.
How long do you think it's going to be till you have that data?
Um.
I guess that's a way of asking, like, how, when is this going to be real?
Look, I think we're, I think you're seeing starting to see versions of it become real, but it's again, very early days, and these tend to be like, you know, very, very specific transactions. You're starting to see, you know, some of this go live in, you're already seeing some form of agentic transactions in different way, shapes, and forms with like various AI platforms. But again, it's very early. It's like at limited merchants. It's like, you know, in beta, is largely in the United States. I, I'd say in about six months or so, we'll start to see like some early statistically relevant enough data sets where we can start to like draw conclusions. That's like my best guess, but, you know, it all remains to be seen how quickly some of these things get adopted.
Okay, so six months. I mean, that's pretty soon. So, we will really start to see how this stuff is going to, uh, look like when it's out in people's hands, which is, which is, I think, you know, it's good news if you're counting on this to be a, a real, uh, movement, uh, within technology. And, you know, it's so interesting. We, um, we often talk about like, you know, you know, Assistant X, just go book my flight, like it's like the most easy thing in the world. U, but as actually hearing you talk about it, it's a very serious technology problem. I mean, a lot of work has to go on to, m, into making sure that that is something that actually, uh, can happen, especially if it's going to use your credit card.
Yeah, that's totally right, Alex. And like, and it's especially important that we get this right, even though there's a lot of hard work involved in making sure, you know, the industry comes together and does this, because unlike say, you know, when was Joe Pesci born? You can get the date wrong and nothing's, you know, not great. Exactly. But the money, right? Like, you know, every line of code we write, every protocol that we release, every token that we issue on every card, like, just ensures that,
you know, a student's paying their fee, you know, a parent is sending money home, a small business is making another sale. And we take that responsibility very, very seriously when it comes to like the Visa ecosystem.
Now, there is some work on the back end here, uh, to make this stuff work more seamlessly. For instance, uh, Visa is working on something called the Trusted Agent Protocol. Can you tell us a little bit more about that?
Yeah, um, I'm, I'm happy to. So, one thing that we're starting to realize is, as and when agents have payment credentials associated with them to make purchases, you know, you're going to see some really, really good applications of that in, you know, some of the things that, you know, some OpenAI and others have released, like ACP is a good example, AP2 is another very good example. And, you know, we're working with them to figure out like, how do we make sure that cards are safe and tokenized and all of that. But ultimately, you know, we still, we still have to make sure that there are like two to 300 million merchants around the, in nearly 200 markets. And ultimately, agents are going to go have to transact at them on behalf of consumers with, depending on, you know, you can debate how much level of autonomy they're going to have. And we want to make sure that the existing web infrastructure that that works today for e-commerce also works for an agentic commerce world. But in order for that to happen, there are different problems that have arisen. Now, remember, in the regular e-commerce world, bots, bots were not a good thing, right? For the last 30 years, like bots meant things. Yeah. I mean, the, you know, the e-commerce industry have spent a lot of time trying to keep bots out because typically it meant that someone was actually trying to get in and do bad things. Now, in the new world, typically bots can actually represent a good thing, which is, bots can come in and, you know, they can either like scrape through your website and maybe commoditize you and do price discovery, which is not so great as a merchant. But they can also make a purchase on behalf of a user. So how do we make sure we differentiate in the existing web infrastructure, what's good and what's bad? So we've done a bit of work with a number of our partners, including, you know, partners like Cloudflare, that do a really good job at the CDN level to analyze bots and bot traffic and what to make available in a merchant environment, like, you know, pricing or product discovery or product pages, you know, deploy that data to merchants to make those decisions. And when a bot, which has sort of like gone, which has a Visa token associated with it, Cloudflare can now recognize and say, oh, okay, so this has an intent to buy, which is great. So I can, we can make that thing available to the merchant, and the merchant can actually make it accessible to like parts of the website they do want to access. You know, and, you know, obviously merchants have a lot of work to do to upgrade their infrastructure to make it merchant-readable, to make it agent-readable. But, you know, if they know there's an intent to buy, that's a positive sign. Then in addition to that, if we are able to pass some form of a consumer identifier to say, oh, it's really alex@gmail.com, I already have sold something to alex@gmail.com in the past, and I know Alex's preferences, I can actually give it a better select rate, I can give it a better product experience internally. That's helpful. And if a, you know, merchant can know it has some form of like a payment credential associated with it, doesn't have to be a card, it could be any payment credential, that's very, very helpful for me to know. So what we're trying to do through our Trusted Agent Protocol, that, you know, we like that the industry has adopted, including all the networks, which is, it's positive in a way that it provides additional data for end merchants to make better decisions on, can I let this agent in? Does this agent have a consumer identifier that's going to help me provide a better sort of like, you know, product outcome to the agent to to buy? Does this p, does this agent have a better pay, like a payment credential that I could use for a payment experience? And we think ultimately the world is going to, you know, it's going to be, you know, we're going to see a lot of like fragmentation in the near term. We're going to see a lot of interesting protocols and a lot of different ways and experiences where this is going to work. And we're going to support all of them because we'd like to, we want to make sure everything is compatible in the way Visa cards work with our authenticated tokens. But I think the Trusted Agent Protocol just makes it very, very easy to use the existing infrastructure the way it works with no real work from the merchants to be able to let agents shop on their websites. So that's where we're very, very focused on right now.
Okay. So we started big picture. Let's end big picture. One thing I like to say about this movement or industry or technology is there's still a lot of ifs. I mean, even Sam Altman talks about how some of the investment might be a little too frothy. Um, we know it's, it's very useful today in some areas. Uh, and then the question is, can it, how will it, whether it will reach its potential? You know, will LLMs keep, you know, keep scaling? And will, um, reasoning actually prove out as a, as a valuable, uh, technique that scales? Um, is the investment going to pay off? So let me turn it to you and ask you, uh, how real do you think this gets? Is this a, a truly transformative technology, or do you think we're like still in wait and see mode? And if you do believe it's transformative, what makes you confident about that?
Um, it's an excellent question, Alex. I'll tell you, purely from a commerce payments perspective, I truly do think it'll be very, very transformational. Um, and I can say this with a lot of confidence because, you know, we actually do a lot of, um, survey sampling with a lot, with a, with a lot of users around the world. We talk to a lot of merchants. We, like, and like a good example is, we recently talked about how, like, four or five months ago, we had seen an increase of roughly about 1,200% in, in agentic traffic to merchant websites. That number in itself has 4xed in the last five months. So that's just data telling us that the traffic to websites for merchants that are, you know, selling to pay to get paid is increasing exponentially. That's just data. Like, that's not a hypothesis. That's just what the data is telling us. Which means that clearly there is a level of discovery interest that is showing up. And ultimately, the thing that we've learned is, it's all, it's all about the funnel. So, you know, you, if you're in a mall, and the more foot traffic you get, some of that foot traffic is eventually going to get converted into actual purchases. And it's really, really hard to argue with that premise if, like, you're going to have a lot of users using agentic platforms to look at goods and services and things to look at and buy at at all these merchants, it is eventually going to get converted into commerce. So, like, that's just what the data tells us. Personally, for my personal life, like I use, I use agentic models like for like six, seven hours a day in my daily life, in almost everything that I do. And almost everyone that I work with, you know, as anecdotal as that is, it is, it is becoming a very, very integral part of how we do work, how we do commerce, how we do discovery. And it's, it's hard not to imagine a world where some of that is truly going to get converted into, like, real tangible commerce. Now, how big and how large would that be and how quickly that would be? Like, there's like no crystal ball for us to know. But so far, the, everything that the data tells us is, has exceeded every expectation that we had, even like a year ago, for what it's worth.
Rebella, if people want to learn more about what you're up to, what Visa is up to, or if you have any favorite podcasts or blogs that you, you know, subscribe to that you want people to check out, anything you want to throw out there for our viewers at the end here?
Um, well, I think this, this podcast is as good as, as, as, as, as detailed a conversation we've had about agentic commerce in a while. So,
Okay, love to hear that. Okay, Rubel, thank you so much. Really appreciate you joining.
Thanks, Alex.
All right, thanks. Thanks, everybody. We will be back on the channel with another video soon. Thank you for watching.