Susan shopped exactly the way the mall designers intended. The department store anchors were the magnets motivating her to make the trip in the first place. The smaller shops lining the corridors between them turned her walk from point A to point B into a series of serendipitous purchases that kept the whole ecosystem humming, including a stop or two at the food court to grab lunch or dinner.

Fifty years before that, Susan’s grandmom was one of the millions who found the lure of the department store irresistible. A New York Times article published on February 2, 1927 cited Federal Reserve data showing department store sales setting new retail records in 1926. (If you do happen to click on the article link, check out the ad for life insurance on the same page.)

For the first time, curated retail items could be found under one roof for granny to touch, feel and try on. Knowledgeable salespeople demonstrated products and answered questions, turning store browsers into buyers. Stores offered credit to make buying easier, and retail sales took off. And like shopping at the mall, going to the department store was an experience that was part social, part shopping, but mostly lots of fun.

Julie Satow’s book When Women Ran Fifth Avenue documents the role department stores played in shaping commerce and influencing fashion in their heyday. It’s a great read.

Today, Susan’s granddaughter, Ellie, starts her shopping trip with a scroll.

Her smartphone and apps give her access to the equivalent of every mall and every department store ever built with a tap and a swipe. PYMNTS Intelligence data shows that nearly two-thirds of American consumers start their shopping trips that way, making purchases 12 days each month on average and window shopping for another 12. For retailers, this is pretty good news. Mobile window shoppers convert to a purchase at a rate three times higher than the casual mobile phone user. Younger consumers and parents skew that number even higher.

Read More: The 2025 Global Digital Shopping Index: The Rise of the Mobile Window Shopper and What It Means for Payments

The digital world gives Ellie tons of options to buy whatever strikes her fancy without ever visiting a store. She has certainty about product quality and inventory availability even if she decides to make the trip just to see the item for herself. If she doesn’t, the logistics of getting her items delivered are transparent, predictable and efficient.

The latest PYMNTS Intelligence data finds that 48% of clothing and accessories, 61% of electronics purchases and 75% of sporting goods and hobby purchases made online now happen at Amazon. Overall, almost two in every ten retail purchases now starts and ends online.

Read More: Walmart Aims at Closing Amazon Online Sales Gap

But Ellie’s generation may be the last to make even that digital journey themselves.

Do Consumers Still Want to Shop at a Store?

Warren Buffett said in a 1977 Wall Street Journal interview that the best business to own is a toll bridge. His thesis: Once capital is invested to build one, you can keep collecting revenue and raising prices since you control access to the places people want to go.

If you can’t be the destination and monetize it, the next best thing is to own the metaphorical bridge everyone has to cross to get to one. Platforms are a great example of the art and science of being a massively successful toll booth. Or a complete disaster, if you get the platform economics wrong.

Buffett’s aphorism is particularly appropriate to shopping in an age of AI agents.

The retail industry is in the throes of a heated debate about whether to open storefronts to AI models so that consumers (or their agents) who start their product journeys there can find their merchandise and buy. That’s the OpenAI, Stripe, Adyen, Fiserv, Perplexity, Shopify, Google, PayPal and Walmart thesis.

Read More: Department Stores of the Future Are AI Agents

The other side of the argument: if you’re already the destination, what’s the point of the bridge? If consumers already come to you to search, discover, compare and buy, then connecting to someone else’s toll bridge is not in your best interest. As the destination, you’re the bridge and the toll booth all wrapped up into one. That’s the Amazon and eBay thesis. (Amazon, I get. eBay is the ultimate head-scratcher, if you ask me.)

But there’s a more fundamental question at the heart of this issue even before getting to the strategic question of open versus closed.

In a world where agents can buy, do consumers still want to shop at a store?

Will Ellie, her kids or her grandkids need to start at “the store” in order to gather product information, read reviews, evaluate options and decide what, when and whether to buy so that they will have confidence the order will be right and show up on time? If so, consumers won’t be willing to fully delegate to an agent because too much can go wrong.

Or will shopping, as we know it, shift from stores and apps to a collection of hundreds of billions of digital SKUs that agents shop and buy on a consumer’s behalf? In that scenario, consumers say shopping across endless aisles and multiple drives to physical stores is too much of a hassle. Agents can do it smarter and more efficiently.

This turns out to be the $5.5 trillion question for retail in the U.S.

Because if AI agents do the shopping, nobody (or many millions of nobodies) will “go” anywhere. Instead, shopping’s theoretical bridge leads to another bridge and another bridge and another with their own tollbooths.

The destination that was once the store becomes irrelevant because it becomes invisible. The new destination becomes the prompt and the agent dispatched to do the shopping and buying. The bridges and the tollbooths connect to and from this new agentic storefront.

The Shift That’s Already Here, Sort Of

The data says this isn’t so much of a theoretical debate anymore.

PYMNTS Intelligence research shows that more than six in ten U.S. consumers used AI in the past year to do something. More than a third of Gen Z consumers and power users now start their daily tasks on dedicated AI platforms first, including content discovery. And not in addition to Google search, but as a replacement.

As of January 2026, not only have 41% of consumers used dedicated AI platforms for product discovery, but 33% say they have fully replaced their prior methods. They’re not layering AI on top of old habits. They’re shutting the door and leaving them behind.

Read More: Smart Agents Replace Super Apps

This behavior is more predominant among the early adopters who are all in on AI and agents, with 51% having replaced their old methods of product discovery. True to their early adopter roots, they are willing to tolerate untold friction to try something new. Among AI power users, the 24 million Americans who use AI and agents to do everything from building shopping lists to doing research on what stocks to buy, the share who reported replacing their previous search and discovery methods continues to increase since November 2025, when it stood at 46%.

For them, the front door of commerce is already in motion.

But here’s the caveat.

The growth is being driven overwhelmingly by use cases that are not yet letting agents make high-stakes, complex purchasing decisions on their behalf.

In part that’s because the inventory of products and merchants to shop remains nascent. In part it’s because the experience is largely circa the early days of internet commerce: functional, but not exactly one-click amazing. And mostly it’s because consumers still have to trust that their purchase discovery and outcomes are as good as the content discovery and outcomes when the starting point is the physical or virtual store.

For the moment, the interest in doing these things is higher than the reality of actually doing them.

And yet about 82% of these power users, who are the most likely to have replaced their old discovery methods, say they would use AI agents for big, complex purchases where the stakes are high and getting it wrong has financial consequences. These are not impulse or everyday buys. They are the high-consideration, high-research decisions that used to take hours, even days or weeks. And where a lot of spend hangs in the balance.

That’s consumer intent at the very leading edge of AI and agents. And it’s pointed directly at the heart of how retail works today.

Why Shopping is Not a One-Size Fits All Experience

The mistake in the current debate about agents versus stores is treating “shopping” as a one-size fits all activity. It isn’t. There are several distinct reasons for how, why, when and where people buy. And the relevance of AI agents will vary tremendously based on those buying triggers.

Take replenishment, AKA subscriptions.

The dog food. Laundry detergent. Paper towels. Toothpaste. The purchases where the consumer made the real decision once, maybe even years ago, and has been on autopilot ever since. There’s no discovery here. No joy. Just the mild annoyance of remembering to place an order before it runs out. And the catastrophe of running out when they forget something important.

This is where an AI agent doesn’t just help, it can take over entirely and reinvent the subscription experience along the way.

No more boxes of paper towels that pile up in the basement because someone in the household forgot to pause an order. Instead, an agent can notice and nudge.

“It’s been six weeks since you ordered dog food. Time to reorder?” “You haven’t refreshed your white short-sleeve t-shirts for the summer. Want the same ones you bought last year, or take a look at the five most popular styles in your size?” “Time for new flip flops. Same pair as last June, or want to see what’s out there?”

In truth, consumers don’t want to spend their time shopping for these things. They want the buying process to disappear. That’s what the agent can do, with a prompt and one-tap confirmation.

Read More: Why 30 Million US Consumers No Longer Search

Amazon already does a version of this with Subscribe & Save, which I live by. Alexa+ attempts to take it further by adding context, knowing that summer is coming, that the dog food bag lasts roughly this many weeks, that last year’s flip flops ran a half-size too small because of a return and a reorder.

Early access data from Amazon on Alexa+ finds that users tripled their shopping activity and had two to three times more conversations compared to the original Alexa. Amazon made Alexa+ fully available to all U.S. users this month (February 2026), and it’s free for its 250 million Prime members. That’s a lot of people who already live with an agent on their kitchen counter or inside an Amazon app.

Walmart’s play with its One Pay banking, credit, shopping and rewards app tries to capture a piece of this layer by turning the grocery trip into a financial flywheel that expands into replenishment. It remains an aspirational goal. Walmart’s ecommerce business has seen strong growth over the last year (from 16.4% to 19.9%), with much of that growth coming from groceries, which drive nearly 60% of their sales. Its Subscribe and Save service, which launched in 2023, is positioned as a counter to Amazon’s in capturing recurring sales for groceries and essentials.

In an agentic world, whoever owns this layer owns the most frequent, most predictable and most invisible transactions in a consumer’s life.

Then there are the bigger-ticket, once-every-so-often, more considered purchases.

A new camping tent. A stroller. A laptop. A dishwasher. A new car. These are the decisions where people currently spend hours reading reviews, comparing specs, toggling between browser tabs and going back and forth over whether the extra hundred dollars is worth it. And this is exactly the layer where the PYMNTS Intelligence data gets most interesting. It’s precisely these complex, high-stakes decisions where consumers are most eager to hand the tedious task of evaluation those options to AI.

Read More: From Assistive to Agentic AI: Consumers Wade Into Autonomous Commerce

It makes sense. Typing in (or speaking) a detailed prompt is just easier than scrolling through forty-seven open tabs. A consumer can describe what they need in plain language and the agent does in seconds what used to eat up an entire afternoon or more.

Amazon’s Rufus is the most visible example of what this looks like inside a closed ecosystem. The numbers Amazon reports tell you why Amazon is pushing so hard on it.

They report that some 250 million shoppers used Rufus in 2025, with monthly active users growing 140% year over year. Amazon says it’s on pace to drive more than $10 billion in incremental annualized sales with it. Rufus users are 60% more likely to complete a purchase than non-Rufus shoppers. During Black Friday 2025, sessions involving Rufus that ended in a purchase doubled compared to the trailing thirty-day average, while non-AI sessions grew just 20%, they say. That doesn’t feel like a marginal improvement. It suggests that a fundamentally different shopping behavior is happening inside its ecosystem.

Then there are the LLMs such as ChatGPT, Claude, Gemini that want to be the destination where that journey starts and ends, routing consumers to the right merchant with the right product at the right price. It’s also where the strategic tension begins to get, well, a little tense.

Read More: Why the ‘Person’ of the Year in 2025 Should Be the Chatbot

Amazon can end the shopping journey because it owns what I’d call logistics certainty. A consumer knows when the product is arriving: same hour, same day, next day. They know what the shipping costs are: mostly free with Amazon Prime, which is a bonus and eliminates the uncertainty of not knowing the final cost. A consumer knows how to return an item if there’s a problem. And where to do it for free. The entire post-decision experience is part of their destination’s appeal.

Perhaps one of the most underrated variables in the entire agentic commerce debate: What exactly happens once an agent clicks “buy.”

Then there are the highly complex, product/service blended purchases that support some of life’s biggest moments.

The 25th anniversary trip. Having a baby. Sending a kid to college. Buying a first house. Getting a puppy. Planning a wedding. Moving to a new city. Each of these involves dozens of purchases, but none of them is really about filling a cart. They are about making a life passage happen.

It’s also where the question of whether consumers still want to go to stores gets interesting. The answer might be yes, but in a different way than it happens today.

Nobody wants to spend a week researching car seats, strollers, nursery furniture, baby monitors, bottle warmers and the thirty-five other things your friends, relatives and in-laws insist you absolutely must have before the baby arrives. Then there’s the physical infrastructure necessary to support the baby. The diaper service. The pediatrician. The day care. The preschool. It’s exhausting, often contradictory and largely anxiety-producing.

The agent’s role in these moments isn’t to shop for those parents. It’s to be the smart and efficient concierge that helps to simplify the massive complexity around this important life moment.

Today preparing for the new baby (or any of life’s biggest moments) looks like parallel processing: researching across endless tabs, juggling competing recommendations, stitching together a plan from fragments.

Tomorrow it might look like this.

Congratulations! You’re having a baby! Here’s a curated registry across eight retailers based on your budget, your house or apartment size, and what parents with similar lifestyles actually used and loved. Here are the retailers that have most of these items in stock if you want to go in and check them out IRL. Here are the three pediatricians near you accepting new patients with strong reviews. Here’s a timeline of what to buy to avoid the panic-ordering purchase of any car seat in stock at 2 a.m. three days before the due date.

The agent handles the things that take time and create frustration. The hassle of research, comparison and logistics coordination is stripped away, and what’s left is the part that actually matters to people. The choosing, experiencing and satisfaction of making a good decision in the context of something very important about to happen.

Who Plays Where and Why It Matters

So, who owns the toll bridge and who becomes the destination? That depends on which version of shopping you’re talking about. And the four most consequential players in this space, Amazon, Google, Walmart and the LLM platforms, are each building from very different starting positions.

Amazon: The Everything Store wants to become the Everything Concierge.

Amazon pulls in roughly 2.5 billion visits a month to its site, commands roughly 9.1% of all U.S. retail spending according to the latest PYMNTS Intelligence report, serves more than 300 million active customers, with 250 million-plus Prime members locked into an ecosystem that has become the defacto starting point for product purchases. Amazon reported Q4 2025 revenue hit $213 billion, up 14% year over year. These are not the numbers of a company that needs to reinvent itself. These are the numbers of a company that can afford to make big bets from a position of massive retail strength.

That appears to be what Amazon is doing.

Subscribe & Save handles replenishment. Alexa+ is hoping to extend that by contextualizing it, learning the consumer’s purchase velocity, anticipating what they need before they think of it and eventually ordering ahead of time with its auto-buy feature.

For more considered purchases, Amazon has built the perhaps most complete environment in retail: search, reviews, product information, price comparison, and then the killer, logistics certainty, all in a one-stop shop. Consumers start and end the journey on Amazon and reliably know that the product will arrive when promised. Rufus and Help Me Decide don’t replace the shopping journey, but instead compress it.

And at a nearly 10% advertising conversion rate, roughly five times Google Shopping’s rate, the math for brands selling on Amazon is hard to argue with.

Amazon’s bigger bet with Alexa+ is to push beyond shopping and into life. The ambition is not to be just a shopping assistant but a life operating system.

Alexa+ already integrates with Uber, Grubhub, Ticketmaster, Vagaro for spa and fitness, Thumbtack for home services, Square for merchant services, Expedia for travel, Yelp for local discovery, and Amazon Autos for car sales. Amazon’s Panos Panay has described a vision where Alexa becomes the consumer’s personal shopper, butler and home manager. The more she understands about the consumer’s life, the better she can serve the customer.

Add Amazon’s healthcare play through One Medical and pharmacy, its grocery infrastructure through Whole Foods, Fresh, and the Uber Eats delivery partnership, Prime Video for entertainment, and Alexa embedded in hundreds of millions of homes, and you start to see the outlines of a company that could plausibly become the life concierge, not just the destination as the store. What we once called the Super App.

Here’s the catch. Amazon may make more trips to my home in a week than I’d like to admit, but Alexa+ still has a long way to go, at least in my experience, before she can live up to the claim of a personal assistant. She is what most consumers say they’d trust, according to PYMNTS Intelligence data. For me, it’s a crap shoot as to whether she can reliably turn on Bloomberg TV in the morning on my Fire TV, never mind organizing my day-to-day.

The conundrum is that Amazon is trusted today for efficiency, reliability and price. But no one is thinking of Amazon curating their wedding registry. The Everything Store may struggle to become the Everything Concierge precisely because life moments require warmth and judgment that an efficiency machine may not inspire. And Alexa+ hasn’t proven she can deliver.

Then there’s Google, which is playing a fundamentally different game.

Google is a massive advertising machine that generated more $400 billion in revenue in 2025, with advertising driving the lion’s share of those numbers. Google says its Shopping Ads drive 76% of all retail search ad spending. Google is, by a wide margin, the world’s largest digital advertising platform.

But Google’s position in commerce is that it is really nowhere. It’s always been the bridge, never the destination. Consumers search on Google, discover products, and then leave to buy somewhere else. Google gets paid for the referral.

That’s what Google is trying to change.

In January 2026, CEO Sundar Pichai unveiled the Universal Commerce Protocol at NRF, an open standard designed to let AI agents navigate the full shopping journey from discovery through checkout, all within Google’s own ecosystem. Google co-developed UCP with Shopify, Etsy, Wayfair, Target and Walmart, and got endorsements from Visa, Mastercard, Stripe, American Express and Best Buy. The message was clear.

Google wants to stop being the bridge and become the destination.

Read More: The Protocol Power Struggle Reshaping AI-Driven Commerce

This announcement came shortly after Google rolled out agentic checkout in November 2025, letting users set a target price and authorize Google to auto-purchase via Google Pay when the price drops. Its Shopping Graph now indexes more than 50 billion product listings, with 2 billion updated every hour. The new Business Agent feature lets retailers like Lowe’s, Michaels, Poshmark, and Reebok deploy branded AI assistants directly inside Google Search to chat with shoppers and close sales. Direct Offers, a new ad pilot, offers exclusive discounts to high-intent shoppers in AI Mode.

It’s nothing if not ambitious. But Google’s challenge remains closing the gap between intent and conversion by turning itself into the internet’s marketplace.

Google Shopping Ads convert at roughly 1.91%. Amazon’s marketplace converts at nearly 10%. That’s a five-to-one ratio, and it tells you everything about the difference between a platform where people go to browse and a platform where people go to buy.

Open standards and broad retailer partnerships are a compelling pitch, but until more shoppers are completing purchases inside Google rather than clicking away to finish somewhere else, the toll bridge metaphor still holds. And merchants need to consider how much, and when, to put effort into exposing their entire product catalog to Google, without a clear understanding of how it plans to monetize those sales. And who owns the customer relationship. More on that point later.

Walmart is the wildcard with one truly irreplaceable asset: its physical storefront.

Roughly 100 million people walk into Walmart for the most frequent, most habitual, most non-discretionary purchase in retail: their groceries. That foot traffic is massive. But it’s also their greatest Achilles’ Heel.

Few people who go to Walmart for groceries buy anything else. The foot traffic is enormous, but their slice of the retail basket is narrow. PYMNTS Intelligence data shows Walmart’s share of retail declining in nearly every category except food.

Walmart’s AI strategy seems two-fold. With its AI partnerships, Walmart appears comfortable being a destination where the LLM toll bridges send traffic because its physical infrastructure is something no AI platform can replicate. And digital is where they lack meaningful share.

Physically, the One Pay credit and rewards play is an attempt to expand what the in-store shopper buys — to turn a grocery trip into a broader financial relationship. If you are already in the store buying food and the Walmart app knows you need new school supplies for your 10-year old,  it can offer you credit and rewards to buy them right then, and might expand the basket. It’s a theory, for now.

Like Amazon, the challenge for Walmart is in playing the life concierge role.

Walmart is not a lifestyle brand. It is not where a consumer goes to curate their baby registry or furnish their first apartment or plan their wedding. It is not a Super App.  Unless Walmart can leap from “where I buy groceries” to “where my Walmart agent manages my life,” it remains powerful but confined to a single, if highly defensible, position as the world’s biggest grocery store. With a little retail eCommerce on the side.

And then there are the LLM platforms that are building the toll bridges that want to own the road. And become the destination.

Consumers are increasingly starting their discovery journeys on these platforms, and the agents can route them to any merchant. That brings with it enormous disintermediation power. The PYMNTS Intelligence data confirms it. Consumers are replacing traditional search and discovery methods with AI-first approaches, and the replacement rate is accelerating.

Adobe reported that AI-driven traffic to retail sites surged 693% during the 2025 holiday season, and shoppers arriving from AI services were 38% more likely to convert. This sounds amazing. But transaction volume is miniscule; this is still very early days.

OpenAI has already launched its own Instant Checkout feature. Microsoft Copilot is partnering with Shopify for embedded checkout. Perplexity was the first to launch one-click checkout within its app. Everyone wants in on commerce.

But the LLMs have a structural vulnerability that the current hype obscures. They have no logistics. They can send you to a store, but they cannot guarantee when the product arrives, what shipping costs, or how returns work. Every merchant on the other side of their toll bridge is a different experience with a different uncertainty profile. And the selection of those merchants is pretty limited right now.

Being discoverable by an agent does not solve the fulfillment gap. And that is why Amazon’s position is structurally stronger than the LLM toll bridge position, at least for now. Amazon is the one destination where the post-agent experience is already solved.

My sense is that the LLMs’ real aspiration is the life concierge.

Not to sell you things, but to be the agent that manages complexity across your entire life.

Getting a puppy? It finds the vet, orders the food, finds and books the trainer and the dog walker,  schedules the groomer, arranges for doggie daycare and the transportation to and from. The LLM becomes the relationship layer. Merchants, including Amazon, become the inventory.

Their advantage is being platform agnostic, smart and a massive time saver. The disadvantage is that a concierge without logistics and without fulfillment is ultimately dependent on others to deliver. And without access to all of the right products, creates buyer uncertainty.

In a world where the uncertainty tax on fulfillment determines which agent recommendation the consumer actually trusts, that dependency may be the LLMs’ defining limitation.

And  why “just open your storefront to the AI agents” is not the simple answer it appears to be for merchants.

Who Owns the Relationship When No One Goes Shopping Anymore?

Let’s close with how we started. The destination and bridge/toll booth metaphor assumed a world with fixed destinations and fixed paths to get to and from. The destination was valuable because there were a finite number of destinations, and lots of  people wanted to get there. There were only a few ways to  get in and out. The bridge was valuable because it made the trip possible. And people and businesses paid the tolls.

The agentic world makes the destination and the bridges with tollbooths pretty fluid. For the replenishment shopping example, the destination is invisible, handled by an agent on autopilot that noticed a consumer was running low before they did.

For considered purchases, the destination is whoever collapses the research journey fastest while maintaining the certainty that the product will arrive when promised and can be returned if it’s wrong.

For life moments, the destination is wherever the people feel a connection and a sense of trust to start the conversation.

The real strategic question comes down to how consumers view the shopping experience for each of those use cases.

Do they want an agent that makes shopping disappear? Or do they want an agent that makes the shopping experience at a store they know and trust  better?

The answer, almost certainly, is both. The company that figures out how to deliver both will own the most valuable thing in commerce.

Not the product, not the price, not the storefront, and not the toll bridge.

The relationship. The real starting point of any shopping journey.

 

Until NEXT time.

Join the 19,000 subscribers who’ve already said yes to what’s NEXT.

PYMNTS CEO Karen Webster is one of the world’s leading experts in payments innovation and the digital economy, advising multinational companies and sitting on boards of emerging AI, healthtech and real-time payments firms, including a non-executive director on the Sezzle board, a publicly traded BNPL provider.

She founded PYMNTS.com in 2009, a top media platform covering innovation in payments, commerce and the digital economy. Webster is also the author of the NEXT newsletter and a co-founder of Market Platform Dynamics, specializing in driving and monetizing innovation across industries.

When Windows 95 Becomes a History Class

A recent Fast Company story argued that retro tech isn’t just nostalgia merch, it’s becoming curriculum. In 2021, University of Wisconsin–Milwaukee history professor Thomas Haigh began teaching a course on the history of computers after noticing that many classic histories of the 1980s–2000s assume students already know what it was like to live with desktop PCs, early consoles, and floppy disks. His students didn’t.

So Haigh built what amounts to a time machine with power cords: a lab stocked with machines from the 1980s, 1990s and 2000s so students can experience “normal” computing from those eras: saving to disks, booting up creaky operating systems and learning how much patience it used to take just to open a file.

That hands-on approach matters because modern tech is designed to disappear into the background. The cloud is “just there.” Subscriptions renew themselves. Devices update while you sleep. Retro tech forces the opposite: friction you can touch and systems you can understand. It’s technology with visible cause-and-effect, and, for a generation raised inside opaque platforms, that’s basically a superpower.

The impulse is bigger than one campus. The Media Archaeology Lab at the University of Colorado Boulder invites the public to “turn on, open up, play and create” with still-functioning obsolete media, and it hosts events (including repair-focused workshops) that treat old devices as something you can actually tinker with.

And there are plenty of “learn the past” programs for younger kids, too: the Computer History Museum publishes activities and classroom resources for learners of all ages; the National Museum of Computing in the United Kingdom runs learning visits and “Digital Future Days”; and the Vintage Computer Federation’s Commodore Classroom teaches BASIC (and even 6502 assembly) on real Commodore 64 hardware.

A Quick Sweep of the Retro-Tech Market

Of course, retro isn’t only educational, it’s commercial. The same digital economy that made everything instant has also made “slow” feel premium. Consumers are buying limitations on purpose: fewer apps, fewer notifications, fewer ways for a device to phone home (or to accidentally approve a one-click checkout).

Retailers have noticed. Fast Company has chronicled the rise of nostalgia-fueled gadgets and peripherals: new hardware engineered to look like old hardware, but (usually) with fewer mysterious beeps. And businesses like Retrospekt have built serious operations restoring and selling classic instant cameras and expanding into other throwback formats like cassettes and Tamagotchis.

6 Retro-Tech Trends That Are Charming, Weird or Both

1. Landlines, but for kids. A startup wants the home phone back in the kitchen: voice calls only, no texts, no doomscrolling, with parents approving contacts. The most disruptive feature is that it can’t “like” anything.
2. The dumbphone renaissance. Some Gen Zers are ditching smartphones for simpler phones as a digital detox, for less dopamine, more presence and the satisfying clamshell snap of a tiny rebellion.
3. Mechanical keyboards as identity. Retro-styled, loud, clicky keyboards are a booming subculture because, apparently, the future of productivity sounds like a 1992 computer lab.
4. Instant cameras and the luxury of consequences. Retro photography restores scarcity: you get one shot, you wait, you keep the print. In an era of infinite cloud storage, limitation reads as intimacy.
5. Typewriters as anti-surveillance tech. Young people are gravitating toward tech they can see into and understand, and nothing says “data minimization” like a device whose only analytics are ink on paper.
6. Retro gaming as a social ritual. The point isn’t perfect frame rates; it’s gathering in the same room, sharing a controller and arguing about who “really” won, like nature intended.

The Future, With a Little More Friction

Retro tech is having a moment because it offers something our always-on economy rarely does: boundaries. Devices that do fewer things. Media that can’t ping you. Systems you can understand (or at least open up without violating a warranty).

Teaching kids how recent tech used to work won’t turn them into Luddites. It will make them sharper consumers in the cloud era. They learn that “seamless” is a design choice with trade-offs, and that convenience always has a cost, sometimes paid in money, sometimes in attention, sometimes in data.

Also, it finally clears up a major misconception: the floppy disk is not, in fact, “the save emoji.”

Live shopping channels for fashion are growing fast, with over 500,000 hours being viewed per month in the UK

Whatnot

As we scan our social media feeds on our phones, we are constantly being served some version of commerce disguised as entertainment – a “what I ordered vs what I got” reel, a creator unboxing a haul, or a get-ready-with-me video. Fashion retail has already been living inside video for years, and now Whatnot’s live shopping app is poised to grab the majority share.

The classic e‑commerce product page (flat images, rigid sizing charts, templated copy) was never a natural home for something as tactile, social and identity‑laden as clothing. It is an interface built for certainty, applied to an industry built on nuance; now live shopping is the market that aims to address this mismatch.

I view this change as a potential infrastructure shift, not just a clever gimmick. This is why live shopping giant Whatnot’s rise matters to Western fashion right now; not simply because “live shopping is growing” (it is), but because it reveals what the next product page, the next returns strategy, and the next “store” might actually look like. As Grant LaFontaine, co‑founder & CEO of Whatnot states, “live shopping is no longer the future of retail. It’s the present.”

Live Shopping: The New Product Page Is A Person

At a Whatnot live shopping briefing I attended in London, Whatnot’s UK General Manager, Daniel Fisher, used an analogy that resonated because it so clearly captured what fashion has been trying to recreate since the first “add to basket” button: the feeling of being known in a store.

“It’s really about bringing the best of an in-store experience directly to your phone. If you were to head to Soho right now, and walk into a boutique… Imagine that boutique owner closing the store for you, and you’re there with 50 of your friends.”

This frames the store as a relationship, rather than just a square footage metric. This is the part many brands misunderstand when they test livestream shopping like it is a seasonal campaign format. They treat it as a channel, but live shopping acts more like a service layer: it collapses the distance between discovery, education and transaction.

For fashion, this is a big deal because the most expensive problems in the category (anxiety around fit, authenticity, trust, styling confidence) are all communication problems, rather than inventory problems.

A good host is effectively a human “UX layer”: answering questions in real time, showing fabric movement, narrating fit, giving context, building social proof in public. This transforms the live chat from just a comment section into the new fitting room.

Sellers getting this format right does not just lead to more sales, it changes what “conversion” even means. It becomes less like clicking “buy now” and more like joining a habit.

Daniel Fisher, Whatnot UK General Manager

Solo Mio Photography

“Live shopping is a combination of commerce and entertainment, with buyers tuning in for over two million hours weekly and an average Whatnot user spending over 95 minutes a day watching live shopping [Netflix’s average user time is 120 minutes a day].” Fisher went on to say that, “the key to this entertainment factor lies in leveraging the tools available – be it auctions, flash sales or ‘buy it now’s, combined with authenticity (knowing about your product and audience) and consistency. We see sellers who go live daily make on average 166 times more in revenue than sellers who go live once a month.”

Whatnot’s own report positions live commerce as becoming mainstream fast, with Whatnot holding close to 60% market share across North America and Europe, and reporting $8B in live sales GMV in 2025. These are huge numbers, but the sharper fashion implication is that the winner is not just the brand that “does a live,” but the brand (or seller) that builds a repeatable show.

As Fisher described, “consistency is very important. The more you go live, the more success you will see. Daily sellers now average £30,000 a month in sales in the UK and surveyed sellers told us that live selling accounts for two thirds of their total business sales.”

What Live Shopping Means For Fashion Returns

As has been well reported, fashion has a returns problem that it rarely treats like the strategic crisis it is. Returns are not just margin leakage; they can entail reverse logistics, fraud risk, waste, and operational drag, all at enormous scale. In the U.S. alone, the National Retail Federation and Happy Returns estimate total retail returns could hit $890 billion in 2024, with 16.9% of annual sales returned.

Live shopping potentially puts a new spin on this: in the Whatnot ecosystem, returns and end‑of‑line stock do not just get written down, they get re‑contextualised. At the briefing announcing Whatnot’s 2026 State of Live Selling Report, Mike and Annabel Winter of fashion channel Weardeadstock described working directly with brands to take returns and end‑of‑line stock and auctioning items with low starting prices, turning reverse logistics into a format the audience actually wants to watch. This turns live shopping from “QVC for Gen Z” to something more operationally interesting for fashion: returns become programming.

In a traditional brand model, returned inventory is often hidden in warehouses, offloaded through opaque channels, or dumped into off‑price flows that train consumers to wait for discounts. In live shopping, that same inventory can become a time‑boxed event (“returns rail”, “warehouse clearout”, “reverse drop”) or a transparent story (“here’s why this is a return, here’s what’s imperfect, here’s why it’s still great”).

Fashion items being sold on live shopping streams

Whatnot

Although this does not solve overproduction, it turns one of fashion’s most painful cost centres into a relationship moment, all while clearing inventory fast. It also hints at a future where the best live operators do not just sell, but can stabilise the messy middle of fashion’s supply chain.

“The biggest concern from brands was product oversaturation,” Winter told me. “Brands didn’t want products appearing across multiple marketplaces at once, which can dilute perceived value. We address this by offering a controlled, channel-exclusive environment. When items are sold on Whatnot, brands can move stock directly to engaged customers very quickly – often getting hundreds of pieces into real wardrobes within days, not months.”

Winter adds, “that speed and visibility is particularly valuable for smaller or emerging brands. Instead of sitting, their products are worn, shared, and seen almost immediately, helping to build awareness and social proof organically.”

Why China Made Live Shopping Infrastructure

If you want to understand where live shopping goes when it becomes “normal,” you need look no further than China.

Renowned entrepreneur Gary Vaynerchuk (also a seller on Whatnot) writes in the foreword for their report that “China has been the global proof point for years. Livestream commerce there surpassed $700B+ in GMV (gross merchandise value) last year, and top creators sell millions in a single night. In the U.S., we’re now at the same cultural and technological inflection point China hit a decade ago. Community-driven platforms are mainstream, consumers crave authenticity more than polished perfection.”

McKinsey famously pointed to Alibaba’s Singles’ Day presales on Taobao Live, where the first 30 minutes generated $7.5 billion in total transaction value; an almost absurd demonstration of what happens when entertainment, retail and logistics are fused. More importantly, McKinsey’s analysis suggested that, if China is a guide, sales initiated through live commerce could account for 10% to 20% of all e‑commerce by 2026.

China has now shifted live shopping from a feature to an entire layer; live commerce has matured into an ecosystem with specialised roles (hosts, moderators, operators), supply chains built for speed, and platforms designed to convert attention into purchase without friction.

Whatnot’s Live Shopping Treats Trust As The Format

This is where Whatnot deserves more credit than it sometimes gets in surface-level coverage. Yes, the numbers are astonishing: the Whatnot report positions the live shopping market at an estimated $22B across North America and Europe, more than doubling and projected to double again, with Whatnot leading market share.

Live sellers build trust with their audiences

Whatnot

But the more telling signal is behavioural: Whatnot is training consumers to treat shopping as something you attend, not something you click.

At the UK briefing, seller stories described hours‑long streams, intense community rituals, and “event retail” energy, right down to viewers booking time off work to watch Black Friday streams.

This sounds like entertainment, which it is. But it is also a trust mechanism: the more time you spend with a host, the less “anonymous internet risk” you feel. You are not buying from a page; you are buying from a person with receipts, reputation, and a live audience watching.

For fashion, where trust is both the problem and the moat, this matters hugely. The report also notes that Women’s Fashion is among Whatnot’s fastest-growing lifestyle categories year-on-year (UK buyers watch over 500,000 hours of women’s fashion shows on Whatnot each month). This signals that live is not just staying in collectibles, but is moving into the messy, subjective categories where taste and fit dominate.

The Way Ahead For Fashion Brands

Live shopping is not just marketing; it is an operating model that fuses merchandising, media, community, logistics and also the future of search. It rewards items with narrative weight: provenance, scarcity, visible quality, and the kind of styling transformation that would be hard to communicate on a static page. This is why resale, deadstock and “drop” culture translate so naturally; those products arrive pre-loaded with context, and context is the thing a good host can amplify in real time.

Live also switches returns from being a cost centre, where the goal is to make them disappear into the warehouse and off-price channels with as little brand damage as possible, into a front-of-house format; inventory you can explain, show, measure, and move transparently. The most obvious operational benefit of this is velocity, but the more strategic benefit is subtler; you can rebuild trust by making condition, fit and value visible in public, rather than leaving customers to gamble alone.

And crucially, none of this works without the human layer. The host is more than the “talent,” they are the interface. They replace the product page, the fitting room, and the customer service in one fell swoop. Without the key benefits of this role (product knowledge, taste, community management), live streams become more like a stiff advert, and the audience will treat it like one.

Live selling becomes a new “third space” for retail

Whatnot

Live Shopping Is Becoming A “Third Place” Again

For years, fashion has been trying to win on convenience: one-click checkout, next-day delivery, and endless choice. But culture keeps drifting back toward something more familiar: shopping as social life.

Live shopping is about more than just buying, it is about being there when it happens. In a fragmented attention economy, where Deloitte notes social platforms and creator-led video are becoming a new centre of gravity for entertainment, commerce formats that feel like entertainment will keep pulling budget, time and cultural “heat” away from static retail experiences.

Could this be seen as the return of the digital high street? Not the high street as real estate, but as a habit: familiar faces, community rituals, and the feeling that taste is being made live, in public, with other people watching.

China has proved this at scale and this is what Whatnot is building in a Western context: live shopping as an infrastructure layer for trust, community and commerce…one person, one show, and one audience at a time.

Retailers are under constant pressure to protect margins while still investing in growth. From rising costs and economic uncertainty to shifting consumer preferences, there’s very little room for wasted spend.

Payment processing may not be flashy, but it’s a lever worth pulling. Payment processing fees can add up, particularly if you handle a high volume of credit card transactions.

One way to lower payment processing fees is to explore non-traditional pricing models, such as membership-based pricing. Ideal for high-volume retailers, growing omnichannel businesses and brands with thin margins, it offers a more predictable way to manage costs.

Let’s look into it.

What is membership-based pricing for payment processing?

Membership-based pricing replaces percentage markups with a flat monthly fee. Instead of paying a processor a cut of every sale, retailers pay the true interchange and network costs, plus a predictable membership fee.

Here’s how it compares to other pricing modes.

Pricing model	How it works	Impact on retailers
Tiered pricing	Transactions are grouped into broad rate tiers like qualified, mid-qualified, and non-qualified. The processor sets the rates.	Hard to predict costs and easy to overpay. Retailers often don’t know which transactions fall into which tier, leading to higher effective rates.
Flat-rate pricing	A single percentage and per-transaction fee applies to all payments, regardless of card type or risk.	Simple to understand but expensive at scale. Retailers pay the same rate for low-cost and high-cost cards, which eats into margins as volume grows.
Interchange-plus pricing	Retailers pay the actual interchange fees plus a processor markup on each transaction.	More transparent than tiered pricing, but costs still rise as sales increase. The processor earns more as the retailer grows.
Membership-based pricing	Retailers pay a fixed membership fee and cover interchange and network fees without added per-transaction markups.	High-volume retailers can significantly reduce processing costs and gain more predictable monthly expenses.

How membership-style payment processing can save retailers money

Lower effective costs as volume grows

With traditional payment pricing, fees scale directly with revenue. More sales mean more fees, even if nothing about your operation changes. Membership-style pricing, which is offered at Stax, works differently. Retailers pay a flat monthly or annual fee and then process payments at wholesale interchange rates. As transaction volume increases, the effective cost per transaction goes down. For high-volume retailers, that shift alone can unlock meaningful savings.

Fewer hidden markups baked into every transaction

Many pricing models quietly include processor markups in every swipe, tap or online checkout. These markups are often hard to spot and even harder to calculate. When you partner with a provider that uses the membership pricing model, you pay true interchange without an extra percentage added on top. The result is clearer billing and fewer surprises when reviewing statements.

Predictable monthly expenses

Payment fees are one of the most unpredictable line items for retailers. A busy sales month can be great for revenue but painful when fees spike. Membership-style pricing introduces consistency. While interchange still varies slightly by card type, the pricing structure itself stays stable. This makes it easier to forecast costs and budget accurately.

Savings that reward growth instead of penalizing it

Traditional pricing models unintentionally punish success. As sales climb, fees climb right along with them. A membership-based payment pricing model flips that dynamic. The more volume a retailer processes, the more value they get from the flat fee. This makes the model especially attractive for retailers focused on scaling, expanding locations or growing ecommerce and omnichannel sales.

Better alignment with modern retail operations

Retail today is rarely single-channel. Between in-store, online, mobile and subscription-style purchases, payment volume adds up fast. As such, you should opt for a payment solution that can handle that complexity without multiplying costs across channels. Retailers can process more transactions without worrying that each new sales stream will erode margins through higher processing fees.

Clearer insight into where money is going

When pricing is simpler, reporting becomes more useful. Membership-style pricing makes it easier to separate interchange costs from processor fees, helping retailers understand exactly what they’re paying and why. That visibility supports better financial decisions, whether you’re negotiating contracts, comparing providers or evaluating new sales channels.

Types of merchants that benefit most from membership-style payment processing (and who it’s less ideal for)

Membership-style payment processing isn’t a one-size-fits-all solution. Merchants who see the biggest upside include:

• High-volume retailers that process a lot of credit card transactions regularly
• Omnichannel and multi-location businesses that need to keep costs predictable and consistent across sales channels
• Retailers with thin margins

On the flip side, the following types of merchants may not benefit as much from membership-based payment processing:

• Low-volume or early-stage retailers that process a small number of transactions per month
• Businesses with inconsistent processing volume
• Cash-heavy operations

Final words

Membership-style payment processing won’t solve every retail challenge, but it can make a real dent in one of the most persistent costs. For retailers processing steady volume, the model offers a fairer way to pay for payments—one that rewards growth instead of taxing it. The key is understanding your transaction profile and choosing a pricing structure that actually works in your favor.

The company on Tuesday (Jan. 13) announced the debut of the latest iteration of its radio frequency identification (RFID) lanes, designed for things like pop-up shops and festivals.

“This builds on the RFID technology we pioneered in 2023 for merchandise: walk-through lanes that use RFID tags to automatically detect what customers are carrying, so they can simply grab items and walk out by tapping their card to pay,” Amazon said on its blog.

The new lanes feature enhancements designed to speed checkout, such as in-lane screens “with an intuitive user interface guide shoppers through the checkout process while displaying cart totals.”

They also feature motorized gates that automatically open and close to help the flow of traffic, along with “dynamic pre-authorization gives customers greater cart visibility” so they know what they’re spending before finishing their purchase.

Amazon also cites the impact Just Walk Out has had for its corporate users. For example, Lumen Field in Seattle increased total sales per game by 47%, while BayCare’s St. Joseph’s Hospital in Florida shrank wait times from 25 minutes down to 3 minutes.

The technology also helped UC San Diego in California serve 11% more students while reducing retail theft by 83%.

In addition to third-party retail locations such as stadiums, Amazon said it is also adding Just Walk Out technology to its own operations, including more than 40 Just Walk Out-enabled stores at Amazon fulfillment centers, with more slated to go live this year.

“This internal deployment demonstrates our confidence in the technology while creating additional opportunities for innovation and scale,” the company said.

In other Amazon news, PYMNTS wrote on Tuesday about the company’s rivalry with Walmart at a time when “retail is being stretched by two different and increasingly incompatible forces that shape consumer behavior, capital allocation and competitive advantage … Call them essential gravity and discretionary gravity.”

Amazon, that report said, has found its strength is not any one category, but the ability to absorb demand as it appears. Search, recommendations, reviews, Prime membership and fulfillment all come together to ease friction at the moment of intent.

“Still, discretionary gravity is riskier. It is exposed to consumer sentiment, macro cycles and promotional intensity,” that report said. “But it is also where growth lives. When consumers feel confident, discretionary spending expands rapidly. When new categories emerge, platforms, and not stores, can capture the upside first.”

The question before retailers now, PYMNTS added, is not whether they can compete with giants on price or scale. It is whether they grasp which gravity they serve, and whether they are willing to commit fully to it.

Valentine’s Day has become one of the most scalable commercial holidays: a global permission slip to convert feelings into transactions, ideally with a pretty checkout flow. In the U.S., the National Retail Federation said consumers were expected to spend a record $27.5 billion on Valentine’s Day in 2025 — an average of $188.81 — with over half (56%) planning to celebrate, and online ranking as the top shopping destination.

Globally, the holiday shape shifts rather than disappears. In parts of East Asia, for example, the gifting choreography can turn into a two-step: Valentine’s Day followed by White Day on March 14, when gifts are reciprocated, an elegant cultural mechanism that also extends the retail runway. In other words: whether your market favors roses, chocolates or carefully calibrated reciprocity, the digital economy still gets what it wants, another peak moment for commerce with emotion baked in.

Below, in no particular order, are some of the more expensive or just plain out of this world items and experiences available.

Rent a Private Island 

Why book a table when you can book geography? Private-island rental platforms make it disturbingly easy to browse secluded paradises the way you browse sneakers, except the “limited drop” is an actual island and the amenities include “privacy.” Start with marketplaces like Private Islands Online.

Buy a Ticket to the Edge of Space

If your Valentine’s aesthetic is “romantic, but with panoramic curvature of Earth,” Space Perspective’s reservation flow is a masterclass in modern luxury: it’s aspirational, premium, and shockingly straightforward for something that involves the stratosphere. The page lists a $125,000 total cost per seat with a refundable deposit starting at $1,000.

Commission a Drone Light Show

Flowers say, “I care.” A coordinated fleet of drones says, “I care and I have a production budget.” Drone show providers like Sky Elements position the whole thing as turnkey spectacle — perfect for anyone who wants their affection visible from across a river, a highway, and most of their ex’s neighborhood.

Put Your Love on a Billboard

For the performance romantics — and the growth marketers — self-serve digital billboard platforms let you buy attention the way you buy ads: quickly, flexibly, and with analytics energy. Blip Billboards pitches “launch outdoor ads in minutes” with “no contracts.” Your message can be heartfelt, hilarious or lightly terrifying.

Bring the Chef’s Table Home

A private chef experience is peak “I planned this” without actually planning it. Platforms like Take a Chef walk you through the modern ritual: request, compare proposals, customize, and book — turning your kitchen into a stage.  If you want to keep it extravagant but slightly more scalable, marketplaces like Cozymeal also sell private-chef experiences (often framed like events).

Buy a Diamond-Studded Phone Case

Jewelry is traditional. Jewelry for your electronics is postmodern Valentine’s Day. Luxury customization brands like Caviar sell phone cases and phones made from materials like 18K white gold and set with hundreds of diamonds — a gift that says, “I love you,” and also, “I fear scratches.”

Personalize a Fragrance Label

Some brands let you turn scent into a message via customizable labels and packaging. Le Labo’s personalization program lets you add a short message (up to 23 characters) across products, which is basically a love note with a supply chain.

Name a Star 

Is it legally binding cosmic real estate? No. Is it wonderfully extra? Absolutely. International Star Registry sells “name a star” packages complete with a certificate — ideal for anyone who wants romance to feel infinite, framed, and deliverable.

Book a Bespoke, Cinematic Trip

There’s luxury travel and then there’s luxury travel that reads like a mood board. Companies like Black Tomato explicitly sell the idea of tailor-made travel engineered around how you want to feel, not just where you want to go. It’s Valentine’s Day as a curated narrative arc. For a more classic “white-glove operator” approach, firms like Abercrombie & Kent also position themselves squarely in the high-end, highly curated travel lane.

Valentine’s Day, at its best, is a reminder to be deliberate about the people you love. At its most entertaining, it’s a seasonal sandbox where commerce experiments with how far “thoughtful” can be stretched before it becomes “logistically impressive.” If you’re going to lean into the over-the-top, do it with intention: buy the billboard, rent the island, book the chef, launch the drones. Just remember the one luxury no platform can actually fulfill on your behalf: putting your phone down long enough to enjoy the person you just bought the sky for.

As we look toward 2026, the industry isn’t just deploying AI; it is competing for the “orchestration layer” of the digital economy. What began as a quest for efficiency has evolved into a high-stakes contest over agency — specifically, who (or what) controls the decision, the data and the final settlement in an AI-mediated ecosystem.

Agent-Native Infrastructure Becomes Table Stakes

The most significant shift for 2026 is the transition from “AI-enabled” to agent-native infrastructure. Banks and payment networks are no longer just adding artificial intelligence to legacy stacks; they are building with the assumption that autonomous software will initiate transactions, move liquidity and resolve exceptions without a human in the loop.

As PYMNTS CEO Karen Webster wrote on the protocol layer reshaping AI-driven commerce, “This time, the shift is not about making payments invisible or shaving a few seconds off the checkout flow. It is about something much bigger: who or what makes the decision about what to buy and how to pay.” In 2026, agents are not simply accelerating transactions. They are assuming control over choice itself, redefining how value is created and captured across financial networks.

Precision Over Scale: The Move to Specialized Models

Alongside infrastructure change, the AI stack itself is evolving. The era of the general-purpose LLM is giving way to small language models (SLMs) and specialized systems. As reported by PYMNTS, financial institutions are moving toward smaller, more specialized systems designed for discrete tasks such as fraud detection, reconciliation, underwriting and compliance monitoring.

Smaller models are cheaper to run, easier to govern and more predictable in regulated environments where explainability and control matter. In production systems, breadth is giving way to precision. By 2026, specialization will become a prerequisite for scaling AI safely and economically within core financial workflows.

Discovery and the ‘Zero-Click’ Journey

As specialized agents proliferate, the traditional customer journey is being dismantled. The industry is moving from search-based menus to intent-driven discovery layers. In this world, the “wallet” as we know it begins to fade.

In her analysis of AI agents and the declining relevance of traditional wallets, Webster observed, “In a world where agents shop and pay, they will not fill out forms. Consumers will not go to a checkout page. One-Click will become Zero-Click.”

As agents act end to end on behalf of users, the competition for loyalty shifts away from the user interface. Control over discovery increasingly depends on data access, authorization frameworks and protocol-level participation rather than interface design alone that caters to consumers.

ROI Becomes the Gatekeeper for AI Expansion

By 2026, return on investment has become the central gatekeeper for artificial intelligence expansion. According to PYMNTS, CFOs are reallocating budgets away from broad AI experimentation and toward agentic systems that deliver measurable economic outcomes.

Productivity gains, faster cycle times, lower fraud losses and improved working capital performance now define success. AI initiatives that cannot demonstrate clear, repeatable impact struggle to secure continued funding. The result is a more disciplined deployment environment where autonomy advances only when it aligns with financial accountability.

Fraud and Risk Management Become Real-Time

As reported by PYMNTS, AI-powered scams are forcing banks to shift fraud prevention from post-event reviews to real-time defense. Attackers increasingly combine social engineering with stolen credentials, allowing them to pass traditional authentication checks and deceive even well-informed customers. This has pushed banks to deploy AI systems that continuously monitor behavior, device signals and transaction context to detect fraud.

Rather than applying blanket restrictions, institutions are using targeted “smart friction,” such as real-time warnings or step-up verification when risk indicators spike. The growing use of AI-generated voices and impersonation techniques has further blurred the line between legitimate and fraudulent activity, raising the stakes for faster detection, stronger identity verification and adaptive controls that operate during the transaction itself rather than after losses occur.

Across farms, clinics, AI labs and labor platforms, a theme emerged: payments is increasingly the interface, not the moat. The moat is the operating system. Here are eight Monday Conversations from 2025 that captured that shift.

Nelly: Europe’s digital health problem is a process problem (Feb. 3)

Nelly CEO Niklas Radner came to healthtech by way of Klarna, and he brought the same instinct: win by redesigning process. Nelly’s thesis is that digitizing healthcare practices starts with workflow that captures data at the right moment, then turns that data into better patient experiences and better financial products. When paperwork becomes the bottleneck, staffing becomes geopolitics. “We see doctors fleeing [from Germany] to Switzerland, and they call themselves bureaucratic refugees,” Radner said.

Bushel: Tariffs hit the Midwest and software shows up (Apr. 21)

Bushel CEO Jake Joraanstad made tariffs feel less like a policy debate and more like a margin call. Commodity prices, input inflation and higher interest rates collide in the cash flow reality of small and family farms. Bushel’s bet is that digitization changes outcomes by giving farmers timing, transparency and control — especially when the market moves before the office opens. “Over half of the grain offers made through our platform are submitted outside of regular business hours,” Joraanstad said.

Rezolve Ai: eCommerce’s real problem isn’t payments — it’s confusion (May 5)

Rezolve Ai CEO Daniel Wagner reframed cart abandonment as a human-factors failure. Digital shopping still assumes consumers arrive with perfect product knowledge and the patience to filter endlessly. Physical retail works because a salesperson translates intent into a decision. Wagner’s wager is that AI can bring that translation layer online and compress browsing into buying. “The way in which we navigate eCommerce is not good… it is no longer ideal,” Wagner told Webster.

Unlearn: Digital twins could make clinical trials feel less like roulette (June 16)

Unlearn founder Jon Walsh argued that AI-powered “digital twins” can shrink placebo groups, accelerate timelines and make trials more ethical, especially in diseases with small patient populations. The provocation wasn’t just speed. It was a new promise for medicine: fewer cycles of trial-and-error, both in R&D and eventually in treatment. “Our long-term mission is to advance AI to eliminate trial and error in medicine,” Walsh said.

WorkWhile: Underwriting labor is the next underwriting category (June 30)

WorkWhile COO Simon Khalaf (former Marqeta CEO) described the Labor Economy as a prediction market hiding in plain sight. If you can forecast show rates and job fit, you can build a portable stack of instant pay, benefits and financial services around the worker, not the employer. The subversive idea: future wages become collateral, and labor data becomes a credit file. “We’re better at predicting humans than most companies are at predicting whether you’ll pay your credit card,” Khalaf said.

Autonomize AI: America doesn’t do healthcare (July 7)

Autonomize AI CEO Ganesh Padmanabhan aimed at the administrative drag that burns out clinicians and delays care: prior authorization, intake, policy matching and patient communications. Agentic AI matters, in his view, because it can distill messy clinical documentation and attach evidence and provenance to each step. His sharpest point is also a measurement critique: incentives track treatment, not prevention. “We don’t do healthcare in this country. We do sick care,” Padmanabhan said.

Baseten: The AI gold rush isn’t about models — it’s about rails (Sept. 22)

Baseten CEO Tuhin Srivastava put a payments-style frame around AI: training gets headlines, but inference gets adoption. What wins is infrastructure that makes complexity disappear while increasing trust, uptime and security — the same forces that made card networks durable. His edge case is speed: the fastest builders outsource the non-core parts of AI delivery to specialists. “That advantage is speed… you can only move fast if you delegate away stuff that is not core to you,” Srivastava said.

Nova Credit: The next credit bureau is real-time (Oct. 27)

Nova Credit CEO Misha Esipov challenged the core assumption of credit scoring: that liabilities and repayment history are the “truth.” In a gig economy, the missing truth is cash flow — income, expenses and stability visible in bank data. Esipov argued that cash flow underwriting is shifting from experimentation to infrastructure, but only if the industry can standardize messy transaction data into something risk teams trust. “This is not a game of basis points of improvement. This is a step change — hundreds of basis points in approval rates,” Esipov said.

The connective tissue across these conversations is the migration of value from transactions to systems. A grain offer placed at dawn. A clinical trial redesigned around simulation. A shift filled because an algorithm understands skills. A credit decision built on permissioned cash flow. Each is a workflow decision that becomes a financial decision.

For leaders in banking, payments and FinTech, the 2025 Monday Conversation lesson is clarifying: your next competitor may not be “a payments company.” It may be the company that owns the experience and therefore owns the economics above it.

That narrative held water for years, but as commerce and payments innovation accelerates and embedded finance capabilities become democratized, the traditional framing of embedded finance only being a big deal for big companies is shifting.

Findings in the report “Retailers Expand Embedded Finance to Unlock Control and Customization,” a collaboration between PYMNTS Intelligence and Marqeta, reveal that smaller and mid-sized retailers increasingly see embedded finance as a way to close the gap with larger competitors.

About three-quarters of retailers making under $500 million in annual revenue say embedded finance innovation is more important than other innovation areas over the next year.

For smaller retailers in particular, embedded finance can offer leverage. According to the report, 68% of retailers using embedded finance cite gains in operational efficiency, while more than half say it improves customer journeys and reduces checkout friction. Higher conversion rates, faster speed to market for new products and improved access to customer data all follow.

Why Size Shapes Embedded Finance Strategy

One of the report’s more revealing findings is how retailers now define competitive advantage. While embedded finance is associated with revenue growth and efficiency, its strongest perceived benefits relate to trust: improved customer experiences, reduced churn and greater transparency around payments and financing options.

More than half of surveyed retailers say embedded finance bolsters consumer trust, and nearly the same share say it helps prevent churn. These are not marginal gains. In an environment where consumers routinely switch between payment methods—and increasingly strategize how they pay—trust becomes a differentiator.

Smaller retailers, in particular, benefit from this dynamic. Lacking the brand gravity of national chains or marketplaces, they must earn trust through consistency, clarity and seamless experiences. Embedded finance enables that by making payment choice intuitive, financing transparent and rewards integrated rather than bolted on.

For smaller retailers, embedded finance is not expected to generate immediate margin expansion; it is expected to enable scale, resilience and credibility. In that sense, it functions more like core infrastructure than a standalone profit center.

Read the report: Retailers Expand Embedded Finance to Unlock Control and Customization

Smaller Retailers Are Choosing Partners Over Platforms

Strong regulatory and compliance capabilities top the list across all revenue tiers, followed closely by advanced fraud and risk management. Ease of integration and customization remain important, but they no longer dominate decision-making.

Retailers increasingly expect embedded finance providers to act as extensions of their risk, compliance, and payments teams—streamlining KYC checks, reducing AML friction and simplifying data protection across jurisdictions. Per the report, nearly nine in 10 firms face regulatory challenges, making fraud prevention and risk management top vendor selection criteria.

For smaller retailers without large internal compliance departments, this expectation is especially pronounced. The right partner can effectively serve as a risk buffer, allowing firms to innovate without overextending their internal resources.

At the same time, the bar for success has risen. Embedded finance now demands governance, discipline and long-term thinking. Retailers that treat it as a plug-and-play feature risk exposure; those that treat it as strategic infrastructure stand to gain control, credibility and competitive relevance.

After all, embedded finance does not reduce regulatory exposure; it redistributes it. And managing that exposure requires partners with deep compliance expertise, not just technical capabilities.

For smaller and mid-sized retailers, embedded finance offers a rare opportunity: the chance to compete not by matching size, but by matching sophistication. The technology alone is no longer the differentiator. Execution is.

Fraud prevention is no longer a single tool or team; it’s a coordinated ecosystem. As digital transactions scale and fraud tactics evolve, fraud orchestration has emerged as the missing layer connecting risk signals, verification systems and payment gateways. This Tracker explores how fraud orchestration turns fragmented defenses into unified, intelligent protection.

What Fraud Orchestration Is and Why It Matters

Merchants must balance fraud prevention with minimizing payment friction that can stop legitimate customers from buying. Fraud orchestration helps achieve this balance.

Fraud prevention today requires a multilayered approach.

At the same time, merchants must protect not only the transaction itself but also the broader revenue journey. Payment optimization and fraud prevention are deeply interconnected—gaps in one layer can lead to friction, false declines or lost conversions in another. Fraud orchestration helps safeguard revenue by ensuring that risk checks, identity verification and payment routing work in concert rather than in isolation.

In short, fraud has grown too dynamic and sophisticated for single-layer defenses to keep pace. Fraud orchestration has emerged to unify these layers, ensuring that risk decisions evolve as fast as the threats they counter.

Effective fraud fighting cannot come at the expense of customer experience.

Despite these rising threats, merchants are under pressure to strike the right balance between friction and protection. According to a Riskified survey, 85% of merchants say their top challenge is preventing fraud without degrading the customer experience. Nearly half (47%) estimate that up to 5% of legitimate customer orders are wrongly declined as fraudulent—amounting to an estimated $50 billion in lost revenue industrywide.

Spreedly’s 2025 State of Checkout Report confirms that false flags remain a leading cause of checkout failure for some merchants, while 36% have added redundant fraud tools to counter provider outages. With merchants often managing five or more payment integrations, fragmentation itself becomes a source of friction—making orchestration essential.

Orchestration optimizes multiple objectives simultaneously.

Fraud orchestration removes the trade-off between security and customer experience by consolidating risk signals and decisioning into a unified, adaptive workflow. Instead of relying on siloed vendors, orchestration blends identity verification, behavioral analytics, device intelligence and transactional risk scoring into a real-time assessment engine.

Research shows that multilayered, AI-driven fraud controls can reduce false positives and improve decision accuracy, while advanced fraud-management approaches also support higher transaction-approval rates by reducing unnecessary declines. These capabilities offer a critical advantage as instant payments and embedded commerce compress decision windows. By routing transactions through the optimal checks—heightening scrutiny only when risk justifies it—fraud orchestration protects revenue, streamlines checkout and preserves customer trust across every channel.

From Fragmented to Unified Security: Fraud Orchestration in Action

Fraud orchestration is the command-and-control platform that lets organizations integrate multiple components into a single system.

Orchestration removes the need for redundancy in fraud-prevention strategies.

Fraud orchestration thus reframes defense from a patchwork of tools into a coordinated, intelligent system. Spreedly describes it as sequencing risk checks like an air-traffic controller: Each tool contributes its strengths, but orchestration determines the right order and conditions for use. This prevents over-verification of trusted customers while tightening controls on suspicious traffic. Layered defenses incorporating behavioral biometrics, device fingerprinting, rules engines and ML scoring reduce fraud losses and minimize false positives. Operational efficiency also improves: Central orchestration reduces the burden of managing multiple integrations, accelerates iteration of fraud strategies and enables targeted use of cost-effective vendors across use cases.

Implementation of fraud orchestration is rising accordingly.

With fraud escalating across channels, more organizations are turning to orchestration to unify detection, reduce manual overhead and accelerate strategic responsiveness. Datos Insights reports that 53% of United States financial institutions (FIs) already use fraud orchestration, 16% are implementing it and 26% plan to adopt it. It notes that orchestration platforms integrate application programming interfaces (APIs), third-party signals, internal data and ML-based scoring engines into a single decision layer capable of millisecond-level assessments. These systems also enable A/B testing of tools, centralized rule deployment, unified case management and cross-channel visibility—capabilities essential as fraudsters exploit gaps between payment flows. The result is a more agile, data-driven and scalable fraud posture.

A few key examples showcase these solutions.

Spreedly’s acquisition of Dodgeball embeds fraud orchestration directly into its open payments stack, enabling merchants to design and deploy branching fraud workflows visually without custom coding. Each authentication, scoring or authorization step becomes a programmable node, giving teams precise control over friction and risk.

Industry momentum is accelerating. Datos Insights recently profiled both LexisNexis Risk Solutions and ACI Worldwide as leading providers in the fraud orchestration market, delivering real-time risk decisioning and flexible deployment options across large-scale environments. Meanwhile, Zoot Solutions’ life-cycle-wide orchestration model—spanning onboarding, monitoring and decisioning—further demonstrates how orchestration is becoming a unifying layer for adaptive, enterprise risk control.

Why Fraud Orchestration Belongs in an Open Payments Platform

Fraud management today requires an end-to-end solution that touches all parts of the payment journey.

Fraud orchestration within an open payments platform offers end-to-end protection.

The underlying principle is that fraud orchestration does not focus only on the moment of transaction. Rather, it gives merchants the ability to manage all the moments of risk that lead up to the transaction, as well as post-transaction dispute and response management. The process must span the entire payments journey so that both the merchant and its future customers are protected.

Fraud orchestration meets the growing imperative to do more with less.

Merchants face increasing pressure to cut operational costs while managing more complex fraud threats. The Merchant Risk Council (MRC) reports that minimizing fraud-related operating costs has doubled as a top priority, rising from 10% to 20% of merchants year over year, and 51% expect fraud-staff spending to remain flat or decline. Meanwhile, 63% plan to increase investment in fraud-management technologies—driving a structural shift from labor-intensive processes to automated, ML-powered workflows. Fraud orchestration helps bridge this gap: By consolidating data, reducing manual reviews and enabling adaptive controls, it empowers merchants to counter evolving threats with fewer resources while maintaining high fraud-prevention accuracy.

Fraud Orchestration Doesn’t Stop With the Transaction

Fraud orchestration represents the next evolution of intelligent payments. Businesses that unify their payments and fraud strategies can reduce friction, accelerate innovation and preserve trust at scale. In this section, PYMNTS Intelligence will provide actionable insights on how open payments platforms with fraud orchestration capabilities can help organizations stay one step ahead in the fight against digital fraud.

PYMNTS Intelligence offers the following actionable roadmap for companies considering fraud orchestration solutions:

• Be smart. Fraud orchestration is about intelligence as much as prevention. Effective orchestration depends on combining multiple risk signals—such as behavioral patterns, device details and transaction context—so fraud systems can make more accurate, real-time decisions.
• Fight fire with fire. Fraudsters are growing more sophisticated as technology evolves; so must detection and prevention strategies. As fraudsters weaponize automation and generative tools, merchants must counter with adaptive, ML-powered controls capable of identifying new attack vectors in real time.
• Go long. Fraud orchestration doesn’t stop at the transaction. It should touch every step in the payment journey. A modern fraud strategy extends beyond the authorization moment by monitoring risk across onboarding, account changes, transaction flows and post-purchase disputes.
• See both sides. Integrating fraud orchestration with payments routing enables merchants to optimize authorization rates while minimizing unnecessary verification steps that drive cart abandonment.

Merchants today face a more sophisticated and elusive foe than ever before. Rapidly evolving technology tools enable fraudsters to exploit gaps in payment channels in ever-evolving ways. To fight back, merchants need to think about fraud management holistically to coordinate and orchestrate their defenses.