Agentic Commerce Arrives — Walmart, OpenAI, and the Future of Retail

Gary and Scott break down Walmart’s groundbreaking partnership with OpenAI — a move that officially launches “AI-first shopping experiences” inside ChatGPT. This is more than a new shopping feature; it’s the dawn of agentic commerce — where AI agents understand intent, plan purchases, and execute transactions autonomously. 

Listeners will learn how Walmart is leveraging this partnership to expand its digital reach, strengthen its retail-media flywheel, and transform from a traditional retailer into a data-driven AI platform. The hosts also unpack what this means for OpenAI’s evolving business model, as commerce becomes a core workload for ChatGPT and a foundation for agent-based ecosystems. 

The conversation covers: 

• 🧭 Strategic Implications: How Walmart gains share-of-basket and new demand surfaces beyond walmart.com 
• 🧠 Technical Breakdown: How AI agents plan, retrieve, rank, and execute orders using retrieval-augmented generation, constraint solving, and real-time checkout orchestration 
• ⚙️ Optimization Insight: Why planning a shopping cart is a “knapsack scheduling problem under uncertainty” — and how that’s reshaping AI logistics 
• ⚖️ Governance & Risk: Hallucinations, ranking fairness, privacy, and accountability in agent-driven transactions 
• 🚀 Future of Retail (2025–2035): From persistent household twins to multimodal perception, agent media, and composable fulfillment 

Gary and Scott explore what this means for CIOs, CFOs, and strategy leaders who need to prepare for AI-driven commerce infrastructure — where assistants become execution engines and supply chains become conversational. 

If you want to understand how Walmart × OpenAI is quietly redefining the economics of retail and why this partnership will shape the next decade of consumer behavior, this is the episode you can’t miss. 

About your AI Guides

Gary Sloper

https://www.linkedin.com/in/gsloper/

Scott Bryan

https://www.linkedin.com/in/scottjbryan/

Macro AI Website:

https://www.macroaipodcast.com/

Macro AI LinkedIn Page:

https://www.linkedin.com/company/macro-ai-podcast/

Gary's Free AI Readiness Assessment:

https://macronetservices.com/events/the-comprehensive-guide-to-ai-readiness

Scott's Content & Blog

https://www.macronomics.ai/blog

Transcript

00:00
Welcome to the Macro AI Podcast,  where your expert guides Gary Sloper and Scott Bryan navigate the ever-evolving world of artificial intelligence.  Step into the future with us  as we uncover how AI is revolutionizing the global business landscape  from nimble startups to Fortune 500 giants.  Whether you're a seasoned executive,  an ambitious entrepreneur,

00:27
or simply eager to harness AI's potential,  we've got you covered.  Expect actionable insights,  conversations with industry trailblazers  and service providers,  and proven strategies to keep you ahead in a world being shaped rapidly by innovation.  Gary and Scott are here to decode the complexities of AI  and to bring forward ideas that can transform cutting-edge technology  into real-world business success.

00:57
So join us,  let's explore, learn  and lead together.

01:06
Welcome to the Macro AI podcast. I'm Gary Sloper. And as always, I'm here with my cohost, Scott Bryan. Great to have you with us. Each week, we explore the intersection of artificial intelligence, enterprise transformation, and the future of business. And in this week, wow, do we have a big one? Yeah, this one is, this is a big one for retail  and for the retail customer experience. recently, October 14th,  Walmart announced a formal partnership with OpenAI.

01:34
And what they're doing is they're aiming to create what they're calling an AI first shopping experience.  phrase sounds like just a marketing title. It isn't. It means you will soon be able to shop Walmart directly inside ChatGBT, plan meals,  restock your pantry, or even checkout  all through conversation powered by OpenAI's new instant checkout technology. Yep. And in this episode, we're going to drill into exactly what does that mean?

02:04
What does it mean for Walmart, for OpenAI, and really for the entire retail landscape over the next decade? We'll hit strategy, economics, technical architecture, risks, and the future of what we're calling agentic commerce, when artificial intelligence doesn't just recommend, but acts on your behalf. Yeah, exactly.  And by the end of this one, you'll see why this partnership could really signal that the way you shop today is really about to be old school.

02:35
ah So let's just kind of back up and start with what actually happened.  So just recently Walmart announced that it's integrated directly into Chat GPT, allowing customers to chat, plan and purchase through OpenAI's uh assistant using instant checkout, like Gary said. Right. What's interesting is users can literally say, I'm hosting a tailgate for 12 people and Chat GPT powered by Walmart's catalog data will essentially

03:05
plan the menu, ah it'll select items,  checks for availability, and then it  executes your payment  at the end. So it's all done uh conversationally, which is pretty interesting. Yeah, and that's really a huge step beyond just product search like we all do every day on the internet. This is more proactive and it's more context-aware shopping. Exactly. It transforms shopping from what do I need to buy to

03:34
Here's what I'm trying to accomplish and it handles it for you. Yeah. If you take a look at the press release, how Walmart framed it is as a way to make shopping more predictive, personal and frictionless. Yeah. What's interesting about all of this, the market really loved it. you own Walmart stock or you watch it, it was one of the top gainers on the Dow that day. So it was hitting a record high.

04:02
which is very impressive for Walmart. Investors immediately recognized what this means though,  and they're really starting to dial in into not just AI companies, but companies powered with some sort of artificial intelligence component in their business that they've publicly mentioned. So Walmart just essentially stepped onto the AI platform stage, not as a retailer, but as a  AI ecosystem partner, if you really think about this announcement and launch.

04:29
Yeah, exactly. And when you, when you look at coverage from Axios, TechCrunch, even Bloomberg, everyone's saying the same thing. This is actually telling us about the arrival of agentic commerce. Yeah, that's right. mean, agentic meaning autonomous agents that handle end-to-end tasks, not just queries. So what that means for  the business here is you give the artificial intelligence a goal and it's

04:58
planning, it's retrieving, validating and executing based on that input. So it's,  I don't know. I could see a large shopping bill at my house.  Yeah, exactly. And it's,  this is kind of a big step, not, just for on the retail side, but on the, uh on the AI platform side as well. So for open AI, this is a pretty big statement. It's, it's saying that chat GPT isn't just a chat interface. It's now a transactional platform.

05:27
where your intent can  turn directly into an action  managed by an agent. Right.  And Walmart's the perfect first mover for this.  If you think about their inventory, you have massive skew diversity,  all different types of  products that they offer, top tier logistics, because they have to get the products out to  all different regions, and retail media scale. So they can deliver on what the agent promises.

05:57
uh massively. So it's definitely going to be a disruptor.  And I think what this means for Walmart is,  know, their strategic angle here. You know,  I don't know what your thoughts are, Scott, but it really could upend the entire retail landscape from smaller organizations or their massive competitors. Yeah, certainly. And for Walmart, uh this really gives them an entirely new demand surface. So shopping in

06:27
shopping intent now starts  outside of Walmart's domains. So not just logging into Walmart.com.  if someone is, you know, meal planning, packing for a trip, you know, setting up their dorm, Walmart can now appear in that conversational context, not just when you type, you know, I need to buy some detergent.  Yeah. Especially that's a good point, you know, moving into a dorm or a new apartment, you know, teaching the agent  on what

06:56
the other things may go into that. ah You know, whether it's skew size and other components that based on that environment,  it could really start to learn and provide you a better output. Yeah. What is the intent? Right. Yeah.  And I think ah it moves Walmart upstream into the intent information layer. They're no longer waiting for search traffic. They're intercepting unstructured goals and converting them into carts  for that shopping experience.

07:27
Yeah. then, and then alongside that there's the share of basket effect. So in  conversational flows, the model is going to curate a handful of options. So if Walmart is in that ecosystem, they can, they can really expand their share of each mission.  rather than having you go to multiple different retailers or online retailers, so you can, it'll, it'll automatically start formulating those lists like groceries, know, household.

07:54
Halloween, back to school, whatever it is, it  will start formulating ah the curating of those options for you. Yeah. And if you think about this, instead of fighting for ad impressions or keyword bids,  Walmart's really competing on the model's policy function. So how it learns to satisfy  customer utility within Walmart's catalog constraints could be very impactful. Yeah. their catalog is obviously massive.

08:24
kind of builds upon a retail media flywheel. So every AI conversation is gonna produce detailed signals and preferences, substitutions, budget limits. all that is data, really is data gold for Walmart Connect, which is their retail media business. Yeah, you're exactly right. It's a good point. mean, retail media margins are often double core retail. If Walmart can use artificial intelligence,

08:53
interactions to really refine targeting and attribution. That's pure profit for them. Yeah. Yeah, exactly. And then, and then kind of finally this, this plays directly into their operational mode. So Walmart's logistics network, you know, inventory precision, same day delivery, pick up drones.  It becomes a real differentiator once agents start optimizing around feasibility as well as the price. Yeah. Yeah, actually right. mean,

09:22
the faster the handoff between the AI planner and Walmart supply chain, the stickier the customer experience will be. So over time, smaller retailers simply won't be able to match that fulfillment efficiency.  it could be  interesting to see what that does down market. Yeah, yeah. A big competitor for Amazon.  So really, just to summarize that  in short,  it'll give Walmart more reach, higher margins, a stronger moat.

09:51
all while positioning Walmart  as a real data-driven AI retailer. So  let's  take look at it from another lens, Gary. What do think it means for OpenAI? Yeah. um Well, I mean, that's  a big question. uh This is really the birth of commerce as a core workload. OpenAI isn't just really answering questions anymore, which most of us are familiar with using their platform.

10:19
Based on  this announcement and go to market, it's really orchestrating transactions. That's high frequency, high value inference.  And they have to get it right because if you think about the mass scale of Walmart customers, ah it could be really impactful  if it's hitting on all cylinders. And I think this is why, you know, we talked about this before in some of our agentic AI discussions, it's not going to be press one for directions or press two to fill a prescription. This is

10:49
the sentiment that's going back and forth here is  it's going to be pretty interesting, I think, from a retail standpoint. Yeah, I think they're really very sticky use cases.  So, know, if chat GPT becomes your household concierge, you know, buying, planning, refilling, those are daily, you know, continuous interactions with the AI platform. Yeah, I agree. Exactly. It gives OpenAI new feedback loops. So

11:18
Think of this, every time an AI plans a meal, gets user corrections, uh completes checkout, it's generating rich training data. the preferences, price, sensitivity, satisfaction, all go into the platform. Yeah. And that's hugely valuable. It really accelerates model improvement in reasoning, uh constraints solving, and the use of tools. And those are skills that generalize far beyond

11:47
just the shopping piece  and the platform just kind of ticks up a level on the intelligence meter and really gets to understand you and  user intentions. Yeah, yeah, you're right. And it also positions OpenAI as a neutral orchestrator. Think of Switzerland for commerce. Amazon Assistant lives inside of Amazon. Google's  inside its own search stack.  OpenAI Assistant, by contrast,

12:16
could be across multiple retailers. Walmart might be the benchmark to start with, but you could see other retailers follow suit. Yeah, so definitely it sparks a lot of change in the retail marketplace. And I don't think that  OpenAI's neutrality will last forever.  Once Walmart, Target, and others start competing for  model bias, OpenAI becomes that uh kind of an economic regulator of sorts.

12:43
deciding who gets surfaced. So some interesting questions there. True. And they'll need transparency, right? So clear economic rules and fairness and ranking. If not, we've talked about, you know, some of the gotchas that have happened with some of the rulings, know, we're going to, yeah, groups like the FTC will come knocking. So you definitely need some sort of governance and the complexities around that for, for open AI. And, and I'm sure they're wrestling with it now.

13:13
because you don't want to get into the penalty box out of the gate and that turns off customers, turns off suppliers, and most importantly, turns off your employees. So that's probably one thing that they'll need to really make sure is locked in. ah On the technical stack, ah we always talk about this on every episode,  what is underneath the hood. So maybe Scott, we kind of...

13:40
pivot a little bit. talked a little about this before we got on the show. ah How is all of this working technically? Yeah, sounds good. think  under the hood, agentic shopping is  certainly a very sophisticated architecture. Yeah, agreed. mean, step one is intent parsing and planning. So the user gives a fuzzy request, say, plan five healthy meals for under $60.

14:08
So then the next step is the LLM parses that into structured sub tasks. ah Think of things like recipes, ingredient lists, skew lookups, uh budget constraints. So there's a lot of information that has to go on there, which you wouldn't necessarily have been able to do that if you just went through a search engine unless somebody had posted something specifically. Right. Yeah. And that takes those sub tasks and then  comes uh retrieval over a commerce graph.

14:37
So a Walmart's catalog, for example, becomes an index graph of products, product attributes, nutrition information, availability. And then the model queries that graph via vector retrieval and structured filters. Right. And then you kind of go into, I'd say step three is, you know, constraint solving. It's not enough to just find the items. It must meet all the constraints put in place. So price.

15:06
dietary concerns, locations, stock, availability. That's an optimization problem, almost like, you know, knapsack scheduling under uncertainty. ah Yeah, knapsack reference.  So  for listeners, the knapsack problem is a classic algorithmic optimization model from computer science, and it  absolutely relates perfectly to constraint solving in this case. um

15:31
So after constraint solving, then comes uh ranking and diversification. So the system has to take, select a handful of items that collectively meet the goal  while maintaining diversity. And it uses a learned re-ranker, which blends relevance, margin, logistics, and then of course, personalization. Right. And then  if you think of,  it step five, guardrails and validation. So

15:58
you know, attribute grounding, safety checks for age restricted items. don't want, um, you know, somebody to nefariously take something, especially if they're a minor, um, allergen filters. That's a big one for a lot of families and individuals and factual verification against the catalog. So is this, is this what is supposed to be there? So, so a lot of things around guardrails and validation that have to be put in place. Yeah.

16:25
And I think we're onto step six. That would be the instant checkout component. So once, once you, the user, accept the list, OpenAI's checkout system,  which is, I believe, powered by Stripe last we heard, that'll then execute the payment. It triggers Walmart's order API and then provides confirmation inside of ChatGPT.  And I would say the, you know, the last one, which is probably near and dear to our hearts.

16:53
based on our careers is latency and caching. So popular intent, so weeknight dinners, school lunch kits,  are they  pre-embedded  and cached for speed? ah Local inventory snapshots are really kept fresh at the edge for accurate availability, but there's probably some component in there of, this user is in a very remote area, ah not just from a bandwidth standpoint, but logistically,  can we fulfill this? m

17:22
Definitely something that I'm sure they put a lot of thought into. Yeah. And I don't think we mentioned privacy. So the link between a chat GPT user and a Walmart account requires explicit consent, know, limited scopes and then also some anonymized telemetry for model improvement. Yeah, that's actually a really good one around privacy. I don't know how we missed that, but glad you picked that one up because that is a good point.

17:50
And that's really the invisible backbone of the partnership.  It's complex. We've talked about agents as orchestrators and this  really is an orchestration of retrieval, know, reasoning and real world execution that,  um, you know, it's going to be interesting to watch from the sidelines. Yeah. So let's, uh, let's just kind of shift the conversation over to, uh, governance risk and, and, competition. And there's, there's definitely a lot of risk in this space. So let's talk a little bit about that.

18:20
Yeah, I mean, I think, you know, somebody that tries to watch ingredients and other things, I mean, you could have hallucinations. So the model claims a product is organic or BPA free and it isn't, that's  a potential liability for for, for the Walmart in this case and probably opening up. Yep. Yep. Yep. As to the complexity. Um, and then right after that would be steering bias. So what if the AI,  uh, systematically promotes  Walmart's

18:48
private label brands because they have a higher margin, is Walmart or OpenAI are both going to be disclosing that?  That's a good point. I think of that one. I was thinking about uh privacy and profiling. So  these assistants will know your diet, your household routines, medications.  The potential for misuse is definitely real. So that is going to be another area that ah

19:16
they'll really need to focus in on. Yep, certainly. um Then there's accountability. So if an agent  misorders something or charges you incorrectly, who's responsible? Is it going to be OpenAI,  Walmart, or  Stripe, the payment processing? So where does that accountability lie? Yeah, outside of accountability, I think you have to also add regulation. um We should probably expect new rules around algorithmic.

19:46
merchandising, disclosure of ranking logic, fairness audits and user controls over recommendation objectives on this platform. ah I don't know if they exist today. I don't think they do, but I'm sure there'll be some consumer groups that will push for those things in the future. Yeah. Yeah. There's definitely a lot to be vetted out here.  And  even especially on the just kind of at a high level on the, competitive front. this, this press release

20:16
this move puts a lot of pressure on Amazon, Google, and even companies like Shopify. Yeah. mean, Amazon's building its own in-house assistant, Rufus, ah but it's really confined within the Amazon ecosystem. I think OpenAI's approach breaks that wall based on everything I've read up on this year. Yeah. They're all doing their own thing. Like Google's got the shopping graph. ah

20:43
but it still struggles with, you know, execution and checkout. So they're working on that and I'm sure they will overcome that. uh But OpenAI just kind of closed that loop. Yeah. I mean, and  to that point, mean, Shopify and Etsy integrations, ah you know, exist via instant checkout. I think that will benefit them,  but they can't match Walmart's,  you know, logistics scale. I mean, they've just had that huge,

21:13
experience for many decades of just being a logistics powerhouse.  So Walmart. The whole retail mode. Yeah. Yeah. Walmart has that mode. So OpenEye has the interface, but I'm not sure there will be a lot of uh family customizable retail agent options that leverage various models in the near future. Could be wrong, ah but we'll see. Yeah.

21:37
Yeah. So I think that's kind of a good transition point. Let's, let's talk about what retail looks like, you know, five to 10 years from now, if this, if this model takes hold.  Yeah. I mean, to be honest, I don't even know what it like, definitely it will look like. feel that five years ago, I wouldn't have expected a lot of things that we have today. You know, if I were to really, really think hard,  um, maybe first shopping missions  will be agent native. So  you won't need.

22:07
to shop item by item, you'll define goals, like we were talking about before, maybe a little bit different, feed my family healthy dinners for $400 a month. And the agent continuously optimizes it. It's identifying the sources, it's finding deals. And the agent is on a 24 by seven, know, preset for you on these options. So they're, constantly looking for those things. I also think the suppliers in these different.

22:37
whether it's ingredients or the actual food, they're going to have uh some catch up to do as well to optimize their environment to match  what these potential uh prompts are asking.  So it's not just, hey, I'm looking for tomato paste. It's going to be, how is that going to impact what is actually being required on the back end from those prompts? Yeah. Yeah, and I was just thinking, think households will have a number of different

23:06
types of shopping agents. Like I might have one for fishing, trying to run up a huge bill, buying me, uh know, fishing lures. But  I think households will also have a, you know, a complete digital twin. you know, a private secure state model of your, know, your pantry, your preferences, your schedules, and then AI and whichever agents you select will probably be automatically managing inventory, exploration, and then coordinating order options.

23:35
across multiple retailers  and  then keeping you apprised  of what they're up to and probably having you validate before they click on the order. Yeah, I love the expiration thing. I'm sure my family will too.  Yeah, I'd say third, there's a multimodal perception here. You'll snap a photo off your fridge and your agent will identify what's inside,  suggest recipes and order what's missing or maybe even identify

24:04
expiration dates on the catch up, we're talking about expiration that needs to be thrown out because it's been there since COVID. Yeah,  exactly.  And then there'll probably be some  on device intelligence. So I think a lot of ranking and  safety checks will run locally for speed and privacy. So on your PC or on smartphones or whatever. And then the heavy reasoning will happen in the cloud. ah And

24:30
And since we'll all soon have our own AI capable PCs and AI capable handhelds,  that'll be, you know, possibly running in your house.  Right. Well, I also think, uh you know, retail media involves  into agent media instead of banners and  ads becoming, you know, those  subtle interventions like switch to private label. It saves $3 and arrives sooner. So I think you're going to see the entire

25:01
media spend and process  be completely different. Yeah. And I think there'll also be a composable fulfillment. So agents will  stitch together the  pickup or micro fulfillment centers and third party couriers all dynamically. So pricing and scheduling will be in real time to get the goods to your house or wherever you're geo located in your scheduler automatically. Yeah. ah

25:29
What about regulation and transparency? ah So  by 2030, we'll have formal AI merchandising disclosure standards. ah Agents  probably be required to instantly explain why they chose certain products and you could probably have a conversation on that. It'd probably be very black and white,  but you'll be able to potentially have a real time conversation on why those things were added into your shopping experience.

25:57
Yeah. And then I think over time, there'll probably be some, some category convergence as well. So, so the same assistance that  handles, you know, groceries will, will also be able to  schedule your oil change or renew prescriptions or buy school supplies. you know, retail healthcare and services will, will start to just become, you know,  an ecosystem and you'll have, you know, master agents and sub agents working together for your household. That's amazing. Wow. uh

26:27
It's gonna look a lot different. So let's start to wrap up the show by posing a few thought experiments. ah So will consumers remain loyal to Walmart or to their agent? Will brand equity matter if agent filters  everything through a best fit lens? I think I want to own my own agent that I train and kind of, you know.

26:56
to my needs, but that's just me. No, I agree with that. Yeah. So what will happen with this in this Walmart model to be seen. ah But I think  what happens when brands start optimizing for the agent,  gaming the retrieval scores instead of search engine optimization. So I think  the new battleground moving forward  in retail will be agent optimization and not web search. Yeah. Yeah. Good point.

27:26
All right. So let's,  let's kind of land the plane and summarize the episode here, Scott, and just kind of go through a couple of final points. Yeah, sure. So in summary,  Walmart's partnership with OpenAI really does, I think, mark the dawn of agentic commerce. uh And I think it expands Walmart's reach. It deepens its data mode and positions OpenAI as the transaction layer for the AI economy,  at least for now. And the others will catch up.

27:55
Yeah. And it's not just about convenience. It's about redefining how intent becomes action and how artificial intelligence integrates with physical supply chains. Yep. Yeah. I think we're, at the point where we're starting to witness the formation of a, a new layer of economic infrastructure. And that would be one where, you know, assistance our AI agents are out there negotiating, optimizing, and transacting on our behalf.

28:22
Yeah. And really the companies that master this intersection of data, trust, fulfillment, they will own the next decade of retail, most likely. Yep. So for any retail executives that are listening, now is the time to really audit your own readiness for agentic commerce. Are your APIs, catalogs, and fulfillment systems ready to talk to AI agents, whether they're yours or another retail partner of yours?

28:51
Yeah, that's the question of the next decade. Yep. Well, thanks for tuning into the Macquarie podcast.  I'm Gary.  Yep. And I'm Scott. And if you like this show, please share it with your network. Appreciate it.