AI Commerce Innovators Podcast Episode 1: Nobody’s Browsing Anymore. They’re Asking.

Our host, Anna Luo, spoke with Chip Knicker of Accenture, Diaz Nesamoney of DaVinci Commerce and Emily Pfeiffer of Forrester about how shopping is becoming a conversation with AI. They explored what that means for how shoppers discover and compare products, and how brands help AI understand their products while creating an experience that feels like their brand.

Video Transcript

The AI Commerce Innovators Podcast is created for change makers in commerce who challenge the status quo. We help brands and retailers across industries navigate what’s next with hardearned lessons and real world experience. This podcast is made possible by DaVinci Commerce and hosted in partnership with AI realized shopping used to start with a search bar. More and more it starts with a question going to an AI. I’m Anna Luo, your host and welcome to Nobody’s Browsing Anymore, They Are Asking. In this episode, I’m pleased to introduce three speakers who are leading authorities on Agentic Commerce in their own right. Chip Nicker, managing director and Agentic Commerce lead at Asenture. Emily Feifer, principal analyst of Forester. Das Nessamoneyi, founder and CEO of DaVinci Commerce. I’m kicking off this episode with Chip, who’s here to share Accenture’s latest research on where Agentic Commerce is headed and how different industries respond to this tectonic shift. Welcome, Chip.

The term agentic commerce has been thrown around in recent days. How does look at it and what does the transformation of commerce look like? Yeah, we see it uh as a very foundational shift. You know, we’ve been in the era of digital commerce for, you know, the better part of 25 years where we’ve all been familiar with, um, you know, buying products online and, you know, the Accenture team has been helping, you know, clients of ours set up the technology to, uh, to enable digital commerce. And so, um, been a great great, uh, time in in our professional lives, a lot of growth for our clients there. But as we move into the agentic, you know, commerce world, we see this this seismic shift or tectonic shift, like you said, where, you know, we’re getting to a point where um all of the, you know, users and and folks that are searching for a product are are looking for for things using intent searches, you know, saying they’re, you know, looking for um a pair of shoes for an event they’re going to and, you know, starting very general without brands listed and and brands are re or the LLMs and are recommending products back to the customer uh based on their searches that don’t necessarily um have a brand involved and may not list a product in the same way they used to.

So there’s a lot of concern about that in terms of visibility, discoverability. And so that’s kind of where we are now. And I think as as this continues to evolve, we’re going to see a lot more autonomous orchestration. So perhaps an agent buying something on your behalf. I think we’re also going to end up seeing some agent agent collaboration uh as we get into more um support and and change in the in the um operation of a commerce business. So, if you put all that together, you know, we see we see this as just the you know, perhaps the biggest uh transformation since the onset of of digital commerce. When you talk about transformation, I’m really interested in the evolution, right? Because before commerce is just literally going to the shop. It’s on the shelf, physical shelf. And then after that you’re seeing ecommerce and you have the digital shelf. And now what we have is what we call a gentic shelf. Can you elaborate on that?

Yeah, I mean I think what you’re seeing now is is customers um you know putting in an intent search as I mentioned earlier and you know what shelf they see is really based upon what um the LLM tool provides to them and based on the you know understanding that that tool has about not only the search and the context you provide but also what other um uh research and what other data that that that LLM has found for for that type of product or that type of search. So, so you know, you’re not seeing um recommended uh pages or recommended products, I should say, based on what our, you know, clients have have built or put the top of their um their search results that you’re not seeing kind of what we have always provided in terms of um product recommendations to folks. You’re seeing what the LM recommends.

And you may see something a product that um is on the kind of the tail of their assortment. it might be in uh in kind of you know classical way to think about it the fourth or fifth page of a search result um and now you’re getting served that as the recommended product and um you know really changes the whole nature of a digital shelf you’re getting maybe one or two products recommended um and you’re not getting to kind of scroll through the whole shelf like we’ve been used to. So um yeah really good question and it’s it’s a puts a I think a sharp sharp edge on kind of what’s different these days. Yeah, I think we’re going to dive deeper into discoverability, right? because if only one or two products gets recommended, it’s like how do I get that onto, you know, to the answer? But before we even get into that, um what are some of the solutions currently available? Yeah, there there’s there’s a number of different things. You know, we we do spend a lot of time with clients um what we call offplatform visibility.

So that’s that is discoverability um GEO kind of AEO the terms that we are using these days. So, you know, there’s a lot of um um ability for customers and clients of ours to to measure um what their uh how their products are showing up in LM today, how they rank against competitors, what the citations look like that are driving those recommendations. So, we spend a lot of time in offplatform uh discussions. Uh we’re also focused a lot on what we call on platform. So all the surfaces that you own u be it your.com site, your mobile app, um there’s other you know kind of clientelling um applications that get used. So you know that sits in the on platform um kind of area or offering for us and that’s an important one to really think about how your your sites function today. Um and then the third grouping Anna that that we think about quite a bit is um what we call gentic commerce operations. So starting to think about all the ways um the way your business um runs today could change.

And some good examples there are like your merchandising team. You know there’s there’s some really effective ways to be much more efficient in terms of how you merchandise your products. Looking at loyalty, looking at service, looking at historical trends, data uh data that you have on all those different elements and then providing an agent-based recommendation is really going to change the way in that merchandising example how merchandising works. Um, and you could, you know, play that across your supply chain. You could play it across replenishment. Um, and certainly, you know, kind of recommendation engine. So, we we put a lot of kind of future focus on that agent commerce operations offering. Thank you, Chip. Let’s talk about recently published research paper called make your brand unmissable. In it is this interesting chart showing the impacts of different industries as AI agents get more and more involved in shopping.

The simulated results show industries like travel and hospitality, beauty and personal care, um health and wellness and groceries will more likely see net new demand with medium execution risk. Um the results also show that home furnishings, automotive, apparel, shoes, accessories are skewing towards lower net new demand and higher execution risk due to AI. Please talk us through the simulations you ran and what it all means in terms of risk and reward for different industries as a result of AI. Yeah. Yeah. So, so we you the make your brand admissible, you know, content is something we’re we’re we’re proud to put in market. So, um we actually used a simulation of um with a partner called ARU. So, we we simulated 50,000 users across uh across a number of countries um to really kind of get a sense for um what the shift is and what it means to different industries.

Um and and so what you see here is you know we we’ve kind of ranked um where we think kind of new demand will show up based on industry and again this is our um data across the simulation that we ran and we see there’s certainly some some execution risk and you know think kind of complexity of the change across this and so just interesting data points here. Um you you can see on the right hand side obviously you know in an automotive kind of world that there’s going to be some some challenge because you have complicated fitment and you have complicated parts and service connection they’d be really you know thoughtful about making sure all the LLMs are uh are kind of ready for that and so you see that kind of rank on the higher and execution risk. Then you can see some other stuff towards the top, you know, with travel and hospitality and and beauty and personal care and health and wellness products and, you know, grocery gets talked about a lot from a commodity and and repeat purchase perspective.

So, we see there’ll be a lot of demand in the next 18 to 24 months from that perspective and a little less on the execution risk. Um, still hard. you know, all these clients we work with have a lot to do um to to kind of transition and move into this new space, but just a bit of a kind of ranking or stratification based on our our research. Yes. And what I find interesting is industries that make high consideration products like cars, luxury watches, and major home appliances. they are expensive or complex and shoppers are likely to regret if they don’t research the products carefully and compare options. And then there are industries that make low consideration products these impulse buys like toothpaste, general purpose vitamins. They’re inexpensive and very little personal risk if the shopper makes the wrong choice. Should these factors affect how brands and retailers make decisions on their agentic commerce strategy?

Yeah, I think if you know if you look at the the analysis we did it, you’ll see some of the more considered products, you know, kind of on the financial service and and utilities sort of near the near the bottom ranking there in terms of net new demand. But what what I’d say to that um you would be um every product and every industry is going to be impacted. You know, it probably already is in some form or fashion. you know, um I myself am um searching for and and and looking for things that are not that you know, considered, you know, what’s a you know, what’s what’s a a new supplement to get. I I actually did a search like that just the other night and got some good recommendations back. Kind of a a simpler um you less kind of personal personal risk with that, but just made a simple recommendation.

And then I’m doing stuff as complicated as, you know, kind of looking for, you know, like just for fun, looking at some different automobile configurations with, you know, just so many different options and engine type and, you know, wheel type and interior and options. And that’s a really considered purchase. And, you know, you can do a lot now in LLM. And I think as that continues, we’re going to see, you know, both, you know, the spectrum of, you know, very kind of repeatable um transactions that we’re comfortable kind of in a grocery orientation or consumables orientation. And I think that’s probably going to be makes sense that’s going to be first in terms of change. Then I think the considered purchases are going to have um I think a pretty fast follow. So what’s interesting about that graph is you see all the industries on their different rankings based on our current analysis. But you know we think it’s going to impact you know every every dot and every industry you see on this uh this chart.

How would you advise brands and retailers in these industries to build a strategy around a commerce so they will be unmissable? how should they use AI or AI agents? Yeah, the consideration and you know we we also put together in our research there’s this um concept of of kind of a horizontal and a vertical agent. Um, and I’ll answer your question kind of using some of that framing, Anna. You know, um, you know, whether it’s travel and hospitality or or kind of beauty and personal care, you know, the first thing we’re recommending is, um, you know, kind of, you know, really be present uh, with horizontal agents. And that’s kind of more general purpose systems. Think think like a chat GPT that are recommending products back to customers. You have to really be thoughtful about um about how you show up in those horizontal agents. And um you know an example um or another part of that same kind of idea we have is if you have horizontal agents you also have vertical agents.

And so you know we’re seeing and we’ve done some work with some clients on you know creating a a vertical agent that’s owned an own surface that allows um allows a a brand to be really personal in their recommendations and be much more um data driven and and specialized in how they’re offering their products. And so the thought here is, you know, you create uh kind of a vertical agent to, you know, draw people in and and create, you know, really good connection based on that owned property. And so they’re kind of two different decisions to make. And you the way we we like to talk about this and and I’ll just kind of finish with this comment is um you know there’s there’s something that every organization needs to do which is become the choice of agents and we call that a bit of a baseline. So that’s you know being present in all the horizontal discussions and tools that are out there.

Um, and then there’s a decision for clients to make in that beauty example I shared, you know, um, if a client of ours would like to become an agent of choice. So that could be a competitive advantage if you want to focus there. It’s much more deep in terms of domain, there’s first-party data in play, you know, a lot of specialized recommendations. And just to close out your your uh answer for your question is, you know, kind of beauty brands if they want to, you know, do that and become kind of a vertical destination. Um, I think that that could be a real choice of uh or real a real real place of advantage. Yeah, it’s interesting that you brought up the horizontal and vertical agents. I’d like to dig deeper into your agent of choice. This sounds quite similar to a brand having a brand store built in the chat GPT app environment, for example, where the brand can curate all the content in it, speak to the shoppers in its own voice. the brand has full control over the shoers’s experience and creates a much more personalized interaction with the shopper.

Yeah, I think it’s a good example of that and I I think that the brand store app within chat GPT is a great place to start for a lot of our you know clients. It gives you a chance to, you know, be present in a very used and useful tool, you know, chat GPT in this instance and um gives you a chance to to create your own branded environment, you know, with some curation um in there. And and I I do think that’s, you know, it’s a it’s a great example of a vertical vertical kind of agent, but you can create that almost within the horizontal, you know, type orientation. So, yeah, we’ve started to to work with with, you know, clients doing that and partnered with Da Vinci on some of that um as well. And so it’s it’s exciting to see, you know, some of these kind of early um manifestations, if you will, of the different um ways to to help our, you know, clients and help brands sort of be present, but then also be present in a way that creates a bespoke um you experience much like the the brand stores enables clients to do.

Speaking of the Agentic Commerce projects that Asenture and DaVinci Commerce work together with brands across so many industries, right, like luxury, beauty, personal care, retail, telecommunications, CPG, finance, travel, automobile, and interesting enough, these brands pretty much represent all the industries impacted by AI from your earlier chart. chart. It’s impressive to see trailblazers in each of these industries. So, broadly, can you comment on the patterns you’re seeing in how they approach Agentic Commerce? Yeah, I think it’s um you know, everyone’s started their journey with Agentic Commerce. You know, I think all the clients you work with are have started, right? There’s some doing discover discoverability and GEO kind of analysis a starting point. They’re measuring and they’re kind of figuring out where to go next. Um, and I and I think some of the the folks that are a little more trailblazing are taking some other steps.

And I think the partnership we have with Da Vinci is a good example of of a few of those customers that want to have more of a curated and owned experience. They feel like they can differentiate, you know, there and and they want to test and learn and see how that goes as well. So, we’ve had a couple different um clients we’ve worked with in different industries. So, it’s interesting to see, you know, kind of how those the trailblazing nature kind of extends beyond um industry, too. So, um, yeah, I think it’s just a really great way to start to, um, you know, bring this this change to life and and do so, you know, with with a tool chatbt and within a tool chatbt that allows people to have a real branded um, and customized experience. That was Chip Nicker, the Aente Commerce expert from Asenture.

Chip shared with us the evolution of commerce, the current state of a gente commerce, how AI impacts many industries, and why it’s important for products, both high and low consideration products across different industries, to be discoverable and chosen by AI answering engines. Here I’m sitting down with Emily and Das to dig into the very question that everybody is asking. How does my brand and more importantly how do my products get discovered and chosen by answering engines and be experienced in a way unique to my brand? But first Emily, let’s set a baseline to help everyone understand the state of Agentic commerce. So in a few sentences, what are the key differences between generative AI, Agentic AI and AI agents? And also what is the current state of the agentic commerce? I’m so glad you’re asking. These are terms that we hear all the time right now and sometimes not quite accurately. So generative AI or Gen AI means um any AI system that’s generating content. AI has been around a really long time.

Genai is kind of available to the public um only for the past few years or so. It might generate images or conversations or copy, right? So genai is is creating content. Agentic AI, agentic anything technically means autonomous. So when you hear the term agentic, technically it means that there’s an AI agent that’s doing something without a human expressly telling it to do that. The term is used a lot of the time uh to mean there are AI agents, which I’ll explain in a second, or there’s something h happening that’s conversational, right? Folks use it to mean a lot of different things. And as it becomes more a part of the vernacular, we’ll all probably have to accept that and I’ll have to stop being such a stickler about it. But in the meantime, technically, agentic means autonomous. those AI agents that I mentioned um are easy to confuse with a chatbot because we think about a customer service agent as a person that we’re conversing with. Uh but that’s a limited way of thinking.

They’re not people these agents which is hard to remember because we say that they have training and they learn like we personify them a lot. An AI agent is just a a system that a program that is trained in a very specific type of task. So there might be an AI agent whose job is to interact and have a conversational experience with a human user. There might be an AI agent whose job is to interpret an image and decide what product attributes the product has based on the photo. Right? There are AI agents that do lots of different things and even the conversational ones. One might be trained in customer service and other is trained in product discovery. So the agents are really the thing kind of under the covers that end users don’t know are there um doing the work in the background. Great. Thank you for that clarification. And what is the current state of the gentic commerce? Yeah. So again agentic commerce is one of those terms that I could argue about the technical definition of but it doesn’t really matter.

Everybody is using it to mean um some genai agent or conversational experience that helps us find, discover, learn about or buy a product. So let me dig into your research report. Um it is called the state of agentic commerce and you said and I quote today com um conversational commerce is almost prevalent for product discovery activities in both owned meaning your own website and non-owned the environment which could be answering engine or the marketplace. This speaks to the maturity of how consumers use AI powered commerce today. Can you share a few highlights? Happy to. Yeah. So, I want to make sure that we understand, as you said, the difference between the owned and the non-owned environment. And for the folks who can see uh the video right now, I’m I’m going to show a slide that explains the owned and non-owned experiences that we can have. So, in an owned environment, this is the website or your app. It’s it’s whatever the merchant can control. And non-owned is a marketplace or an answer engine like chat GPT.

It’s anything that’s outside of the purview of the merchant, the spaces that they can’t control. And there are these sort of bands of types of experiences that we can have in both environments. So conversational product discovery is the first type of experience on the owned website, the owned environment. That might look like a product discovery chatbot on the website. We’re seeing this migrate a little bit from a little chatbot bubble in the bottom righth hand corner to sometimes like an AI assistant popup with a button up next to the search bar. Either way, it’s conversational and it’s a place where a customer can say, “Hey, I’m looking for a product with these attributes or something I want to take on this type of trip.” So, that’s you may see that as as you’re shopping that’s happening more and more. Non-owned environments. This is literally what an answer engine is. It’s a conversational experience that increasingly consumers are using to discover products that they might like to buy. So this is sort of assistive.

Technically, I would not call it agentic. It’s more assistive. But this is the most prevalent kind of flavor of agentic commerce if we’re generous with ourselves and call it that today. There’s also commerce transactions, agents purchasing on behalf of customers and then agents transacting autonomously with each other, agent to agent. And so these are sort of I don’t want to call it maturity levels because it may not happen linearly, but these are the types of experiences that we can overlay over the owned and non-owned environments. Today really all we have is conversational product discovery as I described in both owned and non-owned. And there’s kind of a little bit of answer engines that can handle commerce transactions and offer native checkout that comes and goes. There are some major answer engines that have actually pulled that off of their sites at least for now. So that’s most of what’s there today, but it continues to evolve.

Yeah, I think your analysis of the conversational commerce resonates well with DAS’s view on the importance of how individual consumers discover and experience products that they may or may not have thought about buying. A question for you, Das. You’ve talked to a wide range of retailers and brands spanning industries that includes alcohol, beverage, health and wellness, beauty, luxury, fashion, travel, and hospitality. banking and the list goes on. What strikes you as their biggest challenge and concern in the discovery phase and what does being discovered mean? Yeah, sure. Um I have indeed spoken to many uh customers across across the board and it’s quite quite interesting uh because if you look at how LLMs uh work and they were originally not designed for commerce uh they were just designed to aggregate all kinds of information right so uh they primarily acquired knowledge about products and so on by crawling right so they just went to all these sites and pulled whatever they could so you end up uh if you’re a brand looking at how the LM is described I mean, you use a hodgepodge of of information.

Some of it could be good. Uh you’re happy you got discovered, but you’re maybe not happy because of the way you’re being described or your products are being described. So, that’s a big challenge, right? And for brands that really uh you know value all of the time and effort they put put in building their brand, now all of a sudden they have this LLM trying to describe them. Um and then of course when you talk about commerce there’s a second r isue which is that commerce is about products right it’s about buying products and the consumers want are looking to buy products and brands want to show them their products so this whole area is the area of uh discoverability right which is how do a brand’s products get found uh on LLMs and so crawling clearly is not a very good way to do it so the LMS as they got more into commerce started coming up with um more structured ways by which product content can be uh uh essentially published to the LM.

So you’ve got ACP, UCP and uh JSON LD, a few different standards by which a brand can publish their content. Now um that’s a great start, but then you run into the other problem which is that the way consumers ask questions on LLMs is not that they go in there and just ask for a product. In fact, most consumers think of LLMs as advisers or friends. So, they kind of ask them questions like, I’m going to my friend’s wedding and it’s going to be a hot weekend. What should I wear? Right? And so, the question is, how do you match that up to a product? And that’s a huge challenge, right? Because, you know, in search it was easier. People know to knew to look for specific products, but here they’re describing needs, they’re describing occasions and so on. That’s quite challenging. That’s where you know uh it becomes quite important for brands not just to publish their cataloges into the LMS but actually to spend time enriching the content and describing their products in a way that match how consumers are asking for or expressing their needs.

Right. Anything to add, Emily? I mean I I completely agree. I think part of the problem with all of the the scraping right where where the LLMs were saying I I want all this product data. I want to be able to show it, so I’m going to crawl websites and scrape the product data off of them. Is that they never could see um inventory and delivery information. Right. To your point, DZ, commerce is hard and it requires operational data. It requires promises that you can’t get by saying, “Well, I know this product was available on the website at the time that I scraped it.” Okay, how many? When will it arrive? Right? So, it it was I agree. was a really big miss and starting to figure this out in a way that’s more intentional and planful is going to be really important for digital and I think the other interesting thing is that they and the elems are designed primarily for text you know and so initially it was just descriptions of products but nobody buys products just by reading about them right and and even now they struggle with kind of you know during the crawling they’re not bringing up the rich experiences that are available on a brand’s website and so it’s it’s a subpar experience for consumers but you know consumers are there by the billions literally so uh the whole industry is trying to figure figure out how to make that happen.

Yeah. Okay. My next question is to Das. Can you give us a few examples of challenges that brands are facing from different industries? What are some common threats you’re seeing and some differences that you can highlight for us? Yeah, sure. Um, first it’s it’s great and this is not that wasn’t true even 6 months ago that brands are starting to recognize the importance of this very large consumer base on LLMs that are starting to look for their products. I do occasionally run into a few that are saying, “Oh, the numbers are small and well actually they’re they’re not the numbers you’re seeing on your website might be small and that again goes back to the fact that they’re not seeing you on on these LLMs.” Uh but there are several other issues by industries. For example, some industries are highly regulated, right? So you know that there’s guard rails they need to have before their content can be published. You know, alcohol is a good example.

So you know, we’ve had to build capabilities into our our platform to make sure that the guardrails are there like age gating and so on so forth. Um there’s also even right now as we speak um even the structured ways by which uh product content can be published doesn’t cover service products right so you know uh if you’re a financial services firm or if if you don’t have physical goods to sell oddly enough you can’t publish that content. So if you’re if you’re a services business like insurance for example like how do you create visibility there? Um and so those industries are I mean they want to be in front of consumers that are looking for loans or insurance products but they’re trying to figure out how to get around some of these limitations. Um and you know there there’s a lot of such challenges. So I think I think the mechanisms that Google and and uh open came out with as the first cut ACP used were designed for basically commerce of products, right?

They’re just replicating the e-commerce sites, but they weren’t designed for general discoverability of other services and other products. Now all these brands want to be there. They’re trying to figure it out, but the infrastructure is not not quite there yet. Yeah, Emily, you talk to a lot of your clients too, brand clients, retailers. Um, how are they responding to the challenge challenges that Das was just mentioning? With sheer panic description. I would I would kind of agree with that. Yeah. Right. Like everyone sort of feels like everybody else already has this figured out and you know I’m way behind. Everybody else knows what they’re doing and I don’t. What’s a UCP? Right? I have no idea what to do. they it’s I feel like I just I want to tell all of our watchers and listeners that it’s okay and it’s early days and everyone is still figuring this out and you’re doing the right thing because you’re educating yourself and you’re learning more and that’s all you can do. Um you know we we’re we’re going to help you through it.

But yeah, no sheer panic is is mostly what’s going on and and there are some folks who are experimenting and getting out ahead of it. But it’s it is early days and it’s okay not to have this perfectly figured out today. Yeah, the people that we’re talking to, I think they’re all the trailblazers. So, they tend to know quite a bit about what they want, the strategy, how to test, but there’s a whole bunch of other brands who are just, you know, getting their feet wet and trying to figure out um where they fit, you know, whether they’re the brands that would, you know, that could take better advantage of the LLMs. Um I think we’re going to dive into a lot more of that in the next episode, but um yeah, can you give us some um sort of uh highlights into, you know, what’s to come for these brands? Yeah. So, so things are changing um in the way that shoppers consume information about products and services. uh I want to show you and and talk you through um what we’ve been used to kind of previously and historically versus uh what’s coming now.

So answer engines like Perplexity and Chatgbt and Google Gemini um they are earning more of the product discovery and consideration processes in the shopping funnel, right? So if you think about the shopping funnel as awareness and then consideration and then conversion where awareness is you have to know about the brand or the product before you even can can think about buying it. Consideration is when you decide do I really want it? I’m going to learn more about it. I might figure out if the price works for me compare it to other similar products. And then conversion is is the purchase and and your funnel narrows and folks fall out along the way. Right? Sort of traditionally that’s the way we think about it. So previously you had some awareness happening in search. Diaz was talking about more traditional search engines where uh consumers know we all we’re all consumers. We all know what it means to put in a keyword or a key term and expect that we’re going to get results that matched to the thing that we typed in. Right?

So some of that awareness was happening in search and then we clicked a link and we went to a website and all of the consideration happened there. If if it’s a completely digital journey, all of that consideration was there and the conversion happened right on the site. But as things are changing, we’re seeing a shift. It’s now at least possible that a whole lot, maybe all of the awareness is happening in answer engines and all of the consideration can happen there as well. Right? So in an answer engine, you aren’t just putting in a key term. You’re putting in a phrase. You’re having a conversation. you’re saying like Diaz was was saying, you know, I’m going to an event. The weather’s going to be really warm. What should I wear? You might get questions back or prompts or suggestions for the next thing that you might type in like, um, how formal is this event? What do you expect the weather might be? Is it outdoors or indoors? Right? And as you continue that conversation, you’re going through more of that consideration process.

You might say, “I like this, but it’s too expensive. I like this, but does it come in another color? Show me more things like this. And all of this consideration now is pulled out of the control of the owned environment we were talking about before. Right? Most of the conversion is still today happening almost all of it is still happening on on websites, but not all and we might see that shift more as well. So when I think about the funnel in in digital now, I’m just thinking about the upper parts of the funnel shifting outside of the spheres of control that merchants have. Yeah, the control is, you know, one of the things that DAS talks about very often is um how do you get back the control from these um LLMs. Das, do you want to just give a highlight on um the experience from discovery to experience?

Yeah, just um just to add what Emily to what Emily was saying, I think the obvious um you know uh you know brands that are saying oh we need to sort of be there is the high consideration products right that require a little bit more research and thought uh beauty products which you know is you know you want to the beauty brands want to be on the LMS cuz the text descriptions aren’t quite doing justice to them but I think um you know I just want to pick up on something you said Emily is the difference is conversations right so I think eventually so whether you’re up in the funnel or way at the bottom even very low consideration products even think of uh you know an experience I had go to Amazon I try to find a phone charger I get a thousand of them right and I’m like okay which one what you know and and it’s so hard it sounds easy when you have a lot of choice it’s actually hard because you have to pick the right one and you pick the one that’ll work with your phone and you’re reading through all the descriptions really hard.

I think of that same thing on the LLM where you say, “I have an iPhone 18. Can you find me a charger?” Right? And the LM is doing all the work. So, so I do believe that conversational experiences are going to push all of the funnel up all the way down into the LMS. The urgency right now is more around high consideration products and beauty products and so on. certain categories where they kind of have to. But, you know, I I do feel like it’s it’s much broader than that. It’s conversational versus non-con conversational versus where in the funnel your product uh sits. Good discussion. Okay, I’m going to move on to the next topic and uh let’s go back to an earlier essential research that Chip shared. Let’s see. It’s the relative industry positioning on estimated net new demand and execution risk from AI agents. Here we go. So um the essential model finds that beauty and personal care, travel and health and wellness are seeing the greatest acceleration in net new demand from AI agents.

And it makes sense because these categories represent frequent and complicated decisions that consumers need to make and AI can make decisions easier for them to buy and often leading to incremental new spending. But at the same time, essential simulation finds that up to 60 86% of AI agent mediated transactions are at risk of being abandoned or switched to a competitor when something goes wrong in the purchase uh process. And um the industries that are likely to be impacted the most according to this assimilation are health and wellness, travel, and groceries. I’m going to pause here. Based on what you’re seeing, what are your thoughts? Das, would you like to take that first? Yeah. So, again, just um as I was saying before, there are some obvious industries like the ones you described that’ll probably be impacted the most just because um you know, consumers have kind of decided they just want to use the LMS for that. they don’t they don’t want to or the current way of uh servicing or the experience is so bad that they have found a better way and they’re going to move quickly.

But I I think ultimately the conversational model is what is more natural to consumers. And so I think regardless of what product it is or what category it is, um consumers will prefer to engage with them on on I mean right even right now as we speak I’m speaking with several banks and these are very traditional banks. The last thing I thought would be a bank would be an early adopter of uh of building a presence in LLM. But you know their products are quite nuanced too. Like if you’re trying to apply for a loan, there’s like 20 different loan products with different you know um nuances to it. So I I actually think it is again the conversational model. Now it may be more the early adopters and the risk takers and the brands that sort of jump jump in right away and the others might sort of follow but um and obviously the high propensity industries where they sort of feel the pain a lot more and maybe more immediately but I do think after the early adopters go in there jump in and start seeing the benefits and market share is a big thing right like you know uh LLMs have a lot of Gen Z you know a higher proportion of Gen Z so I I talked brands where they’re like, “Oh, we want new to brand.

We want new to brand.” That’s like what everybody wants. And I say, “Well, guess where new to brand is? It’s on the LMS.” So, if you can figure out how to get there and engage them, you’re going to gain market share very quickly, right? Um, so I think it’s more the the the the brands and companies that are traditionally more risk-taking and willing to sort of take make the bets even though it is early. Emily, you said it’s very early and I agree and there’s a lot of unknowns and experiments and stuff that are happening, but I think the wisdom is for brands to get in there and be part of the experimentation soon because those brands will ultimately be the leaders in their industry because they they jumped in quickly and learned. Yeah. Speaking of Gen Z’s, we actually have the next episode. Uh, I think Emily is going to cover a lot more about the shopping behaviors and how they compare to the demographics that are using um, you know, AI powered selling. So, uh, let’s see.

If there are three things brands can take away from this conversation, what would you say that they are? Emily? Um, I think the first is don’t panic. Just don’t panic. Everything’s going to be okay. Um, it’s a great time to experiment. It’s a great time to learn and figure out uh where you’d like to start. Um, number two is to remember that there are some things you can still control, right? So, uh, Daz, you’re talking about the the conversational expectation that that consumers more and more will expect to be able to just interact that way. That’s true in the owned environment too, right? So, I think that it won’t take long before we all kind of get accustomed to being able to use natural language, not just a search term, but a a longer string, a query, right? And and we’re going to do it on websites, too. And we are going to expect that they can handle it. So, keeping keeping on top of your own environment and making sure that it too is evolving as all this changes. I think that’s really important. Um, number three is to experiment.

This is a time to be wary of the investment. It’s new and it’s unproven, but I wouldn’t I wouldn’t entirely wait. I would start gently experimenting as we move into this kind of new way that folks are going to be shopping. Great. Thanks. And Das, yeah, I think um one of the things that I think is really important to recognize is that it’s, you know, LLMs are not just another channel. uh you know I think sometimes there’s a tendency that oh we have a new channel we’ll we’ll get there eventually but it’s really a new way of uh consumers engaging with brands to buy and and so um I think I think brands have to start thinking about and I I agree that they shouldn’t panic necessarily but at the same time they shouldn’t sit on the sidelines hoping that they can jump in when it’s mature because I think the market share issue is a real issue if you don’t figure out how to play in this new conversational model whether it’s on your website and I I agree Emily it’s doesn’t matter it’s all surfaces consumers want that experience they love it and they they want to see it everywhere so get used to the conversational model figure out how to get your content ready for conversations uh discoverability all of that and I think you’ll you’ll win if you sit on the sidelines you may find um you know you’re losing market share and maybe too late by the time you try to do something experimentation is the phase we’re in you have to learn quickly, learn fast, and adapt to this this new model as quickly as possible.

This podcast is made possible by DaVinci Commerce, the Agentic Commerce Experience platform, enabling global brands to turn conversations into commerce by shaping how shoppers discover, experience, and purchase in the end-to-end AIdriven commerce. It is also hosted in partnership with AI realized, the community for enterprise executives and AI practitioners who are leading AI adoption. I hope you enjoyed today’s episode. I’m always interested in hearing topics that are top of mind for you. So, please drop me a comment with your suggestions. Until next time, innovate responsibly.