From time to time, Marketecture invites guest authors to weigh in with their unique insights on the media, marketing, and ad tech spaces. Today’s guest author, Andrew Lipsman, an independent analyst and consultant at Media, Ads + Commerce, explains why current grand visions for the future of “agentic commerce” (yes, even ChatGPT’s) are completely misguided.

The recent agentic commerce hype has sent retailers into a frenzy about what it means for the future of shopping, the threat of being commoditized, and the possibility of their retail media businesses getting vaporized.

Consider these recent article headlines: 

These articles envision a future where AI agents become the primary modality for shopping. They discuss the technology that underpins autonomous transaction. They point to Big Tech companies jumping on the agentic commerce bandwagon as evidence of its inevitability.

There’s just one minor detail they fail to properly consider: the consumer.

Before we start calling it a “revolution,” maybe we can find evidence of a single consumer engaging in an agentic purchase?

Nearly all tech prediction misfires commit the same error: They assume a future according to what a technology is (theoretically) able to do vs. how consumers are likely to interact with a technology on a regular basis.

We over-attribute the tech and under-attribute the human in the equation.

Now, inevitably, people right now are challenging me and asking, “But what about ChatGPT’s newly announced Instant Checkout and Agentic Commerce Protocol? Surely that’s a gamechanger?” In full transparency, a lot of what follows this paragraph was written before ChatGPT’s announcement—and I still stand by every word of it. I’ll summarize my reasons at the end of this piece.

Let’s begin by defining agentic commerce, which often gets conflated with various applications of AI along the path to purchase. Here’s an AI-generated definition that aligns with my understanding of the term:

The first sentence captures the key premise: that agents handle the entire buying process.

Under scenarios where the path to purchase is constantly intermediated by a human feedback loop, then it’s not really agentic at all. Those scenarios are merely an evolution of the existing search, comparison shopping, and payment experiences—not the revolution we are being promised.

If we were to use a more lax definition of agentic commerce, then we reduce it to the sum of its component parts. This erodes, if not completely eradicates, the “agentic” value proposition. Plus, all of these capabilities are already addressed in some capacity. 

So, with the definition above in mind, here are eight reasons agentic commerce will prove to be more of a collective hallucination than reality.

Notwithstanding the likelihood of consumer adoption, the very premise of the technology is undermined by the lack of incentive from the largest retailers.

Eric Seufert of MobileDevMemo lays out the argument in his article “Agentic Commerce is a Mirage”:

Amazon and Shopify collectively own more than 50% of the U.S. ecommerce market. How effective would a shopping agent be without access to so much inventory? How much confidence would shoppers put in an agent that excludes half of the ecommerce market from consideration?

There’s also a chicken-and-egg problem where in order for agentic commerce to be maximally useful, retailers will need to overhaul their site experience, product descriptions, and metadata structure for discoverability. But that’s a heavy lift, and one that retailers shouldn’t undertake unless and until agentic commerce represents a meaningful share of purchase activity.

I’ve been in ecommerce for 20 years and watched a dozen supposedly revolutionary trends promising “the future of retail” come and go. I’m not saying the next big innovation isn’t possible, but the default assumption should be that anything being hyped before achieving product-market fit isn’t likely to materialize.

Even ecommerce itself, I would argue, has been wildly overhyped over the years. Many predictions that it would make in-store shopping obsolete sound crazy in retrospect. Nearly 30 years into its ascendance and ecommerce accounts for ~15% of U.S. retail spending.

Here are other absurd trends we’ve been told would revolutionize retail.

Metaverse Commerce (2022) – Remember it was only a couple years ago that we all accepted our futures as avatars in the metaverse, and it would quickly take over for, y’know, living your life in the real world. Why walk down the aisles of a Walmart when you can do it in a virtual store? What a retail revolution!

Livestreaming Commerce (2019) – Analysts were convinced that livestreaming commerce—which by 2019 was amazingly a $180 billion market in China representing 10% of all ecommerce—would follow a similar trajectory in the U.S. One well-known retail analyst pegged the U.S. market to hit $58 billion by 2025. It’s, um, let’s just say a fraction of that. Just because a trend works in one context, doesn’t mean it will in another.

Voice Commerce (2018) – As Amazon Echos became ubiquitous in the late 2010s, predictions abounded that voice commerce was about to disrupt everything. Search marketers were being warned to prepare for a world in which you had to be the first search result on Alexa or you didn’t exist. You could almost cut-and-paste the arguments, from then to now, with agentic commerce. Do you think brands that scrapped their existing SEO in favor of voice search optimization might regret that decision?

Shoppable TV (2016) – This trends pops up anew every few years, going all the way back to the mid-1990s with the promise of being able to “Buy Rachel from Friends’ sweater” through your TV screen. For whatever reason, the media industry continues to be infatuated with the concept and just can’t let it go. Every upfronts season, another company unfurls it’s latest attempt—will it be QR codes, clickable, or voice-activated ads this time?—and the trade pubs dutifully lap it up.

IoT Commerce (2016) – Amid the Internet-of-Things (IoT) boom, we were promised a future where every device in our house would be internet-enabled and designed to anticipate our needs. Milk getting low in your fridge? No worries, you refrigerator will notice and have a new gallon sent to your door! Solution in search of a problem? Perish the thought.

How far have these trends come since their most recent hype cycle? The data on these trends are understandably sparse, but my best back-of-the-napkin calculations based on available data reveal these trends to be inconsequential.

A successful end-to-end agentic commerce experience requires a series of things to be true. Any broken link in the chain results in an unrealized or unsatisfactory purchase. 

In the analysis below, I list as many criteria as I can that “need to be true” in order for a completed transaction to occur. Then I assigned a rough probability of each one being true.

For example, a shopper has to know how to engage with an AI agent, or a transaction will never happen. They have to be OK with giving the agent authority to spend on their behalf. They have to believe the shopping occasion demands the assistance of an agent.

Feel free to assign your own probabilities and play with the math. It’s not about the math so much as the number of things that must be true. Whatever numbers you assign will lead to the same inevitable conclusion.

The probability of a successful agentic commerce transaction is infinitesimal.

How likely is it that a shopper will adopt agentic commerce as a new shopping modality with a low expectation for success under even the best circumstances? Habit formation is a byproduct of a positive feedback loop, and if that feedback is routinely netting a negative result, the behavior won’t catch on.

Agentic commerce means giving purchasing autonomy and authority to a bot as a default. But consumers actually prefer seeing options presented before making a decision because they want to feel confident in the selection.

Remember the early Google.com homepage, which offered users two options for their search query: Google Search or I’m Feeling Lucky. The Google Search option offered the familiar search query result page of 10 or so results offering previews of where you might want to click next. The I’m Feeling Lucky option made this decision for you and automatically sent you to the website for the top listing.

 In a 2006 interview with the Washington Post, Google VP Marissa Mayer revealed that less than 1% of users selected the I’m Feeling Lucky option—and the only downside of a subpar result was having to click the back button.

What percentage of consumers do we think are inclined to take a similar roll of the dice when it involves parting with their hard-earned money?

Apparel has an average ecommerce return rate in the mid-20% range, while other high-consideration categories like shoes, accessories, and consumer electronics are also in the double-digit range.

The economics of ecommerce are famously challenging—with the No. 2 player in the U.S., Walmart, only achieving ecommerce profitability earlier this year. What happens to these economics when return rates jump—and they will—as shopping and buying is outsourced to an agent?

If the economics weren’t problematic enough, there are the unavoidable negative impacts on the consumer. A CivicScience survey from 2020 found that the top pain points for ecommerce purchases all inflicted costs in time, energy, and money on the shopper—where an agent would be little to no help.

Further, consumers have little trust in platforms intermediating their ecommerce transactions. On-platform social checkout has struggled to gain traction because consumers would prefer to interact directly with the retailer, don’t trust products sold on social platforms, and don’t trust platforms with their payment information.

These companies also make speaking with live customer service difficult, if not impossible. Who wants to purchase through a company that doesn’t take accountability for the transaction?

Agentic commerce can only exist if it solves a shopping pain point—saving time, hassle, or money—or delivers a better shopping outcome. But there is an inherent conundrum between the value of the transaction and the usefulness of the agent.

When complexity is high, an AI agent is less likely produce a good result. When complexity is low, the AI agent isn’t addressing enough of a pain point to matter.

I was once shown a demo of how a shopping agent can buy a book off Amazon with a single prompt. I was unimpressed. 

Why do I need an agent to do something for me that takes 1-minute and a couple of clicks on my phone? Also, what version of the book will the agent buy for me — hard cover, paperback, or Kindle? The downside of making a return far outweighs the upside of a few seconds in time-savings.

On the other end of the spectrum, how confident do I feel about giving an agent access to my wallet to spend a couple thousand dollars on a new suit, or couch, or laptop of its choosing?

Examples abound of purchase occasions that agentic commerce would supposedly be great for. But they never consider the potential points of failure.

An oft-cited example is buying groceries, which was referenced by Paypal CEO Alex Chriss in a LinkedIn post:

OK, at least in this instance there’s a real-world problem to be solved. But let’s consider how reality might play out.

Sarah gets a list of 5 healthy dinner meals suitable for children’s tastes. The groceries arrive at her doorstep on Tuesday. The groceries include 10 different ingredients that are already fully stocked in her pantry and fridge, including a new gallon of milk when she already has a near-full gallon. Time to clean out the fridge to make some space!

The agent’s version of “healthy” includes low-fat milk, yogurt, and cheese even though Sarah believes full-fat dairy is healthier. She makes the dinners on the menu for the week, but each of her kids complains and refuses to eat at least a couple of the meals.

Oh yeah, and poor Jake ends up in the emergency room because one of the ingredients wasn’t produced in a nut-free facility.

For AI shopping agents to be any good, they need to know a lot about the shopper. This requires a considerable upfront investment from the consumer to provide user-level access to ecommerce sites, loyalty programs, bank accounts, and/or browsing histories. In addition to data privacy and security concerns, it’s simply a big ask of the consumer.

Even under the most optimal circumstances, when an AI agent knows an incredible amount about your existing purchase patterns, favored brands, household income, etc., how well equipped is it to make a buying decision on your behalf?

The most important variable for many purchases isn’t behavioral, but contextual. That could mean the occasion, physical location, emotional state, sense of urgency, or any other number of factors that make you decide to buy Product A vs. Product B in that moment. 

Maybe a shopper includes that contextual factor in the prompt, but a lot of times its influence is subtle and doesn’t register consciously. Even when it does, the agent may not know how to weigh that variable against others.

If a shopping agent’s job is to “predict” the best purchase for you based on what it knows, how often will it arrive at the best option when it lacks your most important purchase criteria?

Agentic commerce advocates will talk in high-minded terms about all the shopping occasions suddenly made easy. But how well does the theory stand up to reality?

In real life, purchases are often mundane. And judging by my actual recent purchase history, I can’t see a single instance where an AI agent would represent a material improvement in outcome or time-savings.

Here are the last five products I searched for, and what I actually ended up buying:

The instances where an agent might end up in the same place as me—the basketball pump and the Claritin—were by far my easiest transactions. Almost no thought required.

The rest of the instances, I’m certain an agent would end up with a sub-optimal outcome. A single Blue V-Neck Shirt. A pair of OnClouds I’m ambivalent about. A compost bin by any other brand than OXO.

OK, so why don’t I believe ChatGPT’s new features change any of this? Many of the above reasons apply when it comes to what OpenAI is trying to accomplish:

Gamechanger? Hardly.

With all that said, I’d like to offer a challenge. 

If you believe in the power and inevitability of agentic commerce, then use it for your next 5 purchases and let me know how it goes.

Want to raise the stakes? Do it for a $100+ purchase, or for a gift for somebody you care about.

If you’re not willing to do that, ask yourself: Why not?

An earlier version of this article originally appeared on the Media, Ads + Commerce Substack.

Andrew Lipsman is an independent analyst and consultant at Media, Ads + Commerce. His industry coverage specializes in retail media—which he is known for anointing as “digital advertising’s third big wave”—and other areas of the digital media, advertising, and commerce ecosystem. Previously, he was a Vice President & Principal Analyst at eMarketer, focusing on retail and ecommerce. He also served as SVP of Marketing & Insights at comScore, where he oversaw the company’s global marketing insights and thought leadership initiatives.