Retail Unwrapped from The Robin Report https://therobinreport.com Retail Unwrapped is a weekly podcast series hosted by our Chief Strategist Shelley E. Kohan. Each week, they share insights and opinions on major topics in the retail and consumer product industries. The shows are a lively conversation on industry-wide issues, trends, and consumer behavior. Thu, 19 Feb 2026 00:04:03 +0000 en-US hourly 1 https://wordpress.org/?v=6.8.2 The Robin Report The Robin Report info@therobinreport.com Retail Unwrapped from The Robin Report https://therobinreport.com/wp-content/uploads/2023/12/RR_RU_Podcast_CTAArtboard-02-copy.jpg https://therobinreport.com Retail Unwrapped from The Robin Report Retail Unwrapped is a weekly podcast series hosted by our Chief Strategist Shelley E. Kohan. Each week, they share insights and opinions on major topics in the retail and consumer product industries. The shows are a lively conversation on industry-wide issues, trends, and consumer behavior. false All content copyright The Robin Report. There’s an AI Encouragement Gap https://therobinreport.com/theres-an-ai-encouragement-gap/ Thu, 19 Feb 2026 05:01:00 +0000 https://therobinreport.com/?p=129626 Theres an AI Encouragement GapEarly data on gender disparities in workforce AI training and encouragement show that the workplace of the future might be even less inclusive. McKinsey reports that fewer entry-level women (21 percent) report that their managers have encouraged them to use AI, compared with 33 percent of entry-level men.]]> Theres an AI Encouragement Gap

It looks like Gen Z, the generation that’s the most politically bifurcated by gender, can now add the “AI encouragement gap” (the significant divide between the high rate at which students and employees are using Artificial Intelligence (AI) tools and the low level of support, guidance, or encouragement they receive from their institutions or employers) to their list of grievances. The chasm between a tech-savvy generation and their less tech-savvy managers is setting up a workplace showdown. As many have predicted, AI’s impact on next gen career prospects is nefarious: AI is not only snatching up entry-level roles, but it is also creating a worker-manager intelligence gap in the workplace.

Is AI changing the workplace culture? And the answer is: The generation gap at work is also causing an AI information gap; older less-tech savvy workers are unable (or unwilling) to encourage and support younger tech-savvy workers to use AI.

Next Gen Against a Wall

The gap adds to the next gen’s lack of motivation, which has led to derision from their predecessors, and they’ve been dubbed “lazy” by those who fail to understand the concept of a generational mental health crisis. Rising costs of housing amid stagnating salaries, bleak professional prospects, a contentious political landscape, and the fact that the world may burn to a crisp due to global warming have the youngest generation in the workforce feeling anxious.  Gen Z is entering a job market where 35 percent of entry-level jobs require 3+ years of experience, and 45 percent of employers post ghost jobs.

McKinsey’s “Women in the Workplace 2025” report shows that gender also plays a role when it comes to seeking career advancement in our dystopian marketplace. While 88 percent of entry-level women say their career is important to them (around the same level as men), only 69 percent of entry-level women say they want a promotion, compared to 80 percent of entry-level men. And, contrary to what our AI overlords once told us, this disparity is only being exacerbated as companies add artificial intelligence to the mix. Companies are prioritizing training and encouraging men to become AI fluent over women. Early data on gender disparities in workforce AI training and encouragement show that the workplace of the future might be gender biased. McKinsey reports that fewer entry-level women (21 percent) report that their managers have encouraged them to use AI, compared with 33 percent of entry-level men. Analysts are calling AI the new “labor market currency.” If that’s true, Gen Z women will have to fight for adequate AI training, sponsorship, and encouragement, or they risk being left behind.

They Can’t Spend What They’ll Never Have

We can’t talk about Generation Z consumers without discussing their financial straits. Gen Z has the highest average personal debt of any generation, at a whopping $94,101 a pop that’s way higher than millennials ($59,181) and Gen X ($53,255). They have fewer economic prospects and are entering a stale job market that economist Diane Swonk told Fortune is “gut-wrenching” for the middle class.  There’s a thin line between optimism and delusion, and next gen consumers are realists. Since they have to be ready for an uncertain future, they consume media critically and research every dollar they spend.

The “AI Encouragement Gap” Creates Generational Disconnects  

While gender is perhaps the most concerning factor impacting AI adoption in the workplace, it doesn’t stand alone: age, confidence, and politics surrounding AI adoption also play a role. Even the gender factor is layered. Employers aren’t encouraging women to learn AI technologies in the same way, but women are also more reluctant to adopt AI into their daily workflow. The key issue is that while a majority of students may use AI, just a few feel their organization encourages its use. This puts the generational digital divide in stark contrast. Next gens may look at their older colleagues as out of touch with technology, which leads to the encouragement gap: You can’t teach what you don’t know.

A Gender Bias Culture

So, how does gender bias come into play? Although only 7 percent of Gen Z consumers identify as non-binary, those who do subscribe to gender norms are more divided than ever in political leanings, policy, and even in the media they consume. Consider that 80 percent of “The Joe Rogan Experience” listeners are men, while 70 percent of progressive-leaning “Call Her Daddy” listeners are women. They’re even using different platforms, with men outnumbering women by two to one on X and Reddit.

Gen Z women entering the workforce today find their optimistic enthusiasm quickly mitigated by reality. While most companies still say they are committed to fostering an inclusive culture, few are equally committed to giving women equal career advancement opportunities as men, particularly at entry and senior levels. As a result, Gen Z women who are entering the workforce are screaming from the rafters that career milestones that felt attainable to their predecessors don’t feel attainable for them. Fortune blames this disparity on “pessimism,” which would imply next gen’s bleak career prospects are just a matter of perspective, but the truth is more complex.

Grim Career Prospects Dampen Next Gen Spend

Gen Z purchasing behavior is characterized by frugality and underconsumption. They aren’t the only ones clutching their wallets. Millennials are scaling back, too, and consumer confidence across the board recently plunged to a 12-year low. Speaking of millennials, Gen Z watched us go through recessions, pandemics, government shutdowns, and the advent of AI. When they see their university degree-holding predecessors struggle to leverage their decades in the workforce to make a liveable wage, it’s hard to believe in their own career prospects. After all, millennials started our careers when the job market was rife with opportunities, whereas all Gen Z knows is an Orwellian present.

You may think that, AI encouragement gap aside, at least Gen Z can look forward to a prosperous future, but future employment prospects are equally grim. Goldman Sachs economists David Mericle and Pierfrancesco Mei say that “jobless growth” will be the new normal. The middle class is eroding, and Gen Z literally cannot afford to spend like their predecessors did at their age. They’ve had to learn to express individuality in new ways: Showing off their taste through vintage finds and books rather than a prestige label. They are running marathons over buying Birkins.

When AI fluency defines our corporate future, unplugging may be the greatest form of luxury. How to individuate in a culture dominated by AI? Next gens are buying to express their individuality rather than conforming to a certain social caste. Their curated individual styles influence everything from how they decorate their homes to the notebooks they buy for class. They are shifting into using clothing to proclaim themselves to the world. Individuation is the antithesis of AI homogenization, and they’ll continue to differentiate themselves through fashion––as long as they can afford it.

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Think You’re in Control Shopping for Groceries? Wrong! https://therobinreport.com/think-youre-in-control-shopping-for-groceries-wrong/ Tue, 03 Feb 2026 05:01:00 +0000 https://therobinreport.com/?p=126768 Think Youre in Control Shopping for Groceries WrongEvery scan of your card, every clipped coupon, every “substitute” you accept when something’s out of stock is recorded. You’re not just earning points; you’re teaching the system how to give you what exactly you want.]]> Think Youre in Control Shopping for Groceries Wrong

You think you’re in control of what you choose in a supermarket? Well, sorry to report, but you’ve been played. You don’t decide what you buy at the grocery store. An algorithm does. Welcome to the brave new world of the Agentic AI shopping experience. Your grocery trip is an experiment—and you’re the test subject. You’re not in control and here’s why.

Pricing and promotions are manipulated just for you. You think the electronic shelf price is the same for everyone?  The offers hitting your phone, your inbox, and your app are tuned into you—your income bracket, your brand loyalties, your preferences and soft spots. And you gave it all permission. That’s the promise of AI, as long as it doesn’t terrify you.

Think about it. You signed up for loyalty programs. But they aren’t just about rewarding you—it’s a brilliant way to deliver exactly what you want based on what the data has recorded. It’s a win-win if you think about it. You provide access to your personal data, and your local store becomes your personal shopper.

Every scan of your card, every clipped coupon, every “substitute” you accept when something’s out of stock is recorded. You’re not just earning points; you’re teaching the system how to give you what exactly you want.

This is not a bad thing if you want a seamless, stress-free shopping experience. The more you let AI know, the more your local shopping experience can make your life easier. We’re just entering this new world on steroids where AI data accelerates the information you give it to deliver an experience that makes you the most important priority.

Is this creeping you out? Don’t panic. You can limit what AI can access and control the world curated just for you. If it does creep you out, be aware, be informed. But when you think about it, we’re entering a social contract with Agentic AI that can make our lives easier. That’s not so bad.

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Intelligent Retail: Mastering Agentic AI https://therobinreport.com/intelligent-retail-mastering-agentic-ai/ Mon, 02 Feb 2026 05:01:00 +0000 https://therobinreport.com/?p=125934 Intelligent Retail Mastering Agentic AIAt best, Agentic AI is a system’s ultimate thinking tool. Enabling a retail metachannel, Agentic learns from itself, tests and evaluates alternatives, executes decisions, and automatically improves. ]]> Intelligent Retail Mastering Agentic AI

Agentic AI is an amorphous catchall that is tricky to define but managed to eclipse any other discourse at the recent 2026 NRF Big Show. Brands including LVMH, Home Depot, Warby Parker, Target, and others discussed their understanding of an Agentic AI future. They were joined by executives from Microsoft and OpenAI. Google’s CEO, Sundar Pichai and new CEO John Furner discussed AI integration with Walmart. Additionally, Pichai announced Google’s Universal Commerce Protocol (a set of global standards to facilitate Agentic AI retail activity worldwide).

There was an abundance of chatter, but retailers and brands seemed unable to deliver a concise, consistent definition of Agentic AI and how to use it. Admittedly, Agentic will change the AI conversation dramatically, and as with any introduction of the next best AI tool, its applications and implications are generally misunderstood.

Will Agentic AI dramatically change the course of retail? And the answer is: If retailers learn what Agentic is and how it really works, it’s a direct path to efficiencies and customer delight.

Chasing Agentic Windmills

With retailers seduced by the lustrous orb of Agentic AI, we thought it would be useful to clear the air with a broad definition of the concept and describe how brands apply (or are building applications for) the technologies. At best, Agentic AI is a system’s ultimate thinking tool and takes on the aptitudes of LLM-powered AI in retail.

  • Customer behavior
  • Inventory flows
  • Supply chain rhythms
  • Pricing strategy
  • Store operations
  • Security oversight
  • Digital interactions
  • Loyalty patterns
  • Customer support
  • Weather activity impacts

Agentic AI Accelerates Retail Operations

Agentic AI upgrades its AI ancestors as it performs tasks autonomously within the retail funnel. New models blend with CRM and POS systems from discovery and checkout to post-purchase support. Agentic AI is still evolving and always improving as it operates at a higher level tackling these complicated tasks.

  • Influencing discovery
  • Optimizing inventory
  • Mitigating supply chain disruptions
  • Applying dynamic pricing
  • Facilitating customer purchase activity capture, checkout, and attribution
  • Leveraging chatbots built from large language models to interpret user input and generate adaptive responses
  • Coordinating staff scheduling
  • Identifying and mitigating dark pattern activity and crime
  • Identifying points of failure
  • Customizing loyalty incentives
  • Resolving support issues
  • Generating catalog, marketing, and advertising content
  • Adapting based on outcomes
  • Mitigating weather disruption costs

Omnichannel Evolution

The omnichannel customer experience stitched together stores, ecommerce, mobile, social, marketplaces, and call centers, but the customer moved among these channels as discrete silos. With Agentic AI, the promise is that the channels will dissolve. This near-future experience is emerging as a novel retail ecosystem that will treat every touchpoint as part of a unified system.

  • The customer journey is continuous and customized
  • Context follows the customer everywhere
  • The brand behaves like a single, coordinated organism, not a set of channels (your call is never transferred to another representative)
  • Data, identity, inventory, and personalization function across devices, whether online, in-store, or both simultaneously
  • A website can be a living store with the thrill of discovery, and a store can be a living website that directs you to what you are searching for
  • The experience adapts to the customer, not the other way around

Metachannel retail (no connection to the Big 7 tech company) is an apt reengineering of omnichannel. Metachannel reflects a quasi-scientific interpretation of systemic metapsychology, which applies concepts of self-examination (of a company, not a personality), interdependence (within the organization and between trusted partners), systems-level behavior, and self-repair or mitigation. It is a retail channel that learns from itself, tests and evaluates alternatives, executes decisions, and automatically improves.

Operations and Aspirations

While the pace and intensity of adoption may vary, an AI transformation is underway across the retail industry. Granted, Agentic AI is the latest hot topic, and there is evidence of early stages of early adoption. Plans and aspirations outweigh practical applications in retail. However, there are a few pioneers.

  • LVMH executives Gonzague de Pirey and Soumia Hadjali have announced an initiative called AI for All, which spans the company’s portfolio of Maisons. The aim of the program is to elevate the user experience across all touchpoints in the system, associates, management, clients, artisans, and operations, through AI. De Pirey emphasizes the importance of an AI that is aligned with the brand’s culture as the company implements what it calls “quiet AI.” He stresses, “The technology should be everywhere, and invisible.” Each Maison at LVMH develops unique AI activations, but the company shares best practices and technology to scale the implementation across the organization. An AI activation at Dior will look very different than one at Sephora, but many of the systems interconnect.
  • At Louis Vuitton, Soumia Hadjali, Global Vice President, Client Development & Digital, applies AI to leverage LV’s many cultural initiatives. “Our digital concierge is both deeply personal and context aware. It will know how our clients shop; not just what they buy, but who they are, and where they live.” She continues, “Louis Vuitton has cafés, restaurants, and exhibitions. We can organize a private table at our restaurant when it is hard to get a table. We can book tickets for an exhibition. We can become part of our client’s life.”
  • Target is on an accelerated trajectory. CIO Prat Vemana describes the retailer’s partnership with OpenAI. He is clear about the retailer’s AI ambitions: “Target has moved from using AI to running on AI.” The new OpenAI integration includes many Agentic AI functions aimed at efficiency both online and in-store. Customer service centers and associates have gained two Agentic AI superpowers via the Agent Assist and Store Companion devices developed with OpenAI. The devices allow price matching and can start returns on the spot in-store. Vemana adds, “Target is not a marketplace; it is a curated retailer. The process of vetting vendors used to take thousands of hours; now we get it done in minutes.”
  • Albertsons’ Agentic AI shopping assistant (which doesn’t seem to have a very catchy name) is jockeying for relevance as grocery options multiply. In a field test AI was challenged with a complicated prompt that required analysis from diverse streams of data and information. It delivered a menu designed to satisfy a group comprising a vegan, lactose-intolerant, peanut-sensitive, and gluten-free group of guests. The bot produced a list of recipes from which to choose and eventually filled the virtual shopping cart with the necessary ingredients, including a few private-label items.
  • Ralph Lauren’s Ask Ralph chatbot is a more primitive version of Agentic AI that shares sophisticated fashion advice from a virtual facsimile of the fashion icon himself. Chief Branding and Innovation Officer, David Lauren, was an early adopter of OpenAI’s ChatGPT through the brand’s tech integration with Microsoft Azure. Understandably, Lauren is an advocate of the shoppable, conversational version of his Dad steering potential clients toward a sale.

Eyes Wide Shut

AI’s stealth infusion into everything has been stunning. User adoption, exploration, and exploitation are fully turbocharged. Both business and society (including consumers) have had little time to consider the implications of these emerging technological shifts as the world races to retool and keep up with the pace of change. The shiny object that is AI, and the even shinier possibilities promised by Agentic, are alluring, but there are vexing implications that can’t be ignored.

Agentic AI reflects engineering advancements that continue to encroach on unique human capabilities. In a capitalist economy, public corporations beholden to shareholders will choose efficiency over the workforce. These will not be layoffs; It is unlikely that jobs lost to AI will ever return. The economic impact of job losses writ large will impact society, culture, governance, and naturally slam into the retail industry.

The computing power needed to support the massive data centers that power AI currently, compounded by the exponentially increasing energy demands of the more complex Agentic AI, will strain aging energy grids in the U.S. and elsewhere. High power demands drive up electricity costs, particularly in the U.S., as renewables stall. Obviously, higher electricity costs reduce discretionary spending for consumers across many income segments.

Agentic AI requires deep, personal data sharing with service providers. For a consumer-facing Agentic agent to be effective, trust is critical. Consumers will be required to share personal and financial information, including personal characteristics (age, weight and size), location data, biometric information for identity verification, routines, habits, pricing sensitivity and logic, and more. In other words, Agentic AI needs to understand who you are, what you want, how you behave, your constraints, and which actions you are comfortable authorizing the agent to perform. It goes without saying that undisclosed data sharing, selling, leaks, and security breaches will shatter the trust between the customer and the brand.

AI Axiom

As retail’s AI transformation marches forward, it should be approached thoughtfully.  Brands and retailers need to anchor every AI decision in their culture, identity, and strategic intent. Ask Ralph, LVMH’s AI for All, and other luxury AI applications should deepen the bespoke, high-touch relationship between client and brand; anything that feels like a generic chatbot breaks the spell. For Target, where speed, scale, and efficiency fulfill the brand’s AI intent, intelligent automation that delivers faster, more personalized service is exactly on‑brand. And when operational AI unlocks cost savings, passing those savings on to shoppers reinforces Target’s value-driven identity. The rule is simple: Innovation only works when it authentically amplifies the brand and delivers meaningful benefit to the one stakeholder who matters most, the customer.

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The Overwhelm Era: Tech-Obsessed Brands Alienate Overstimulated Shoppers https://therobinreport.com/the-overwhelm-era-tech-obsessed-brands-alienate-overstimulated-shoppers/ Tue, 14 Oct 2025 04:01:00 +0000 https://therobinreport.com/?p=98688 The Overwhelm Era Tech Obsessed Brands Alienate Overstimulated ShoppersRetailers say they’re digitally transforming to capture next gen shoppers’ loyalty. That’s because self-serving studies from digital solution providers have conditioned retailers to think that’s what young consumers want.]]> The Overwhelm Era Tech Obsessed Brands Alienate Overstimulated Shoppers

Retailers say they’re digitally transforming to capture next gen shoppers’ loyalty. That’s because self-serving studies from digital solution providers have conditioned retailers to think that’s what young consumers want. Here’s a challenge: Find me someone in their 20s who is begging for another pop-up ad or push notification.

Stop guessing what next gens want and start listening to them. A whopping 78 percent of Gen Z gets overwhelmed when shopping online. They’re telling retailers to reduce friction points along their path-to-purchase, not pile them on in hopes of getting some dreamy ROI.

Gen Z won’t put up with false urgency from retailers. The old “going, going, gone” scarcity narrative will have them “going, going, forever gone” from your email list. Unintentionally frustrating customers isn’t a good business move . . . no matter what the guy selling you the software suite tells you about the magic of digital innovation.

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You’ll Need a Video Game Strategy for Next Gens https://therobinreport.com/youll-need-a-video-game-strategy-for-next-gens/ Wed, 10 Sep 2025 04:01:00 +0000 https://therobinreport.com/?p=98430 Youll Need a Video Game Strategy for Next GensThe key to tapping into gaming communities is authenticity -- the most successful brand activations don’t just show a potential customer a product. They embed the brand into core memories that they’re already creating with their friends.]]> Youll Need a Video Game Strategy for Next Gens

Smart brands see online/video gaming as a shortcut to connect with young (and mercurial) consumers who are otherwise so difficult to reach. To put it into perspective, there will be $100 trillion in wealth transfer to Gen Z. For next gen marketers — and now those targeting Gen Alpha – gaming has become a go-to strategy to tap into those funds. We’re referring to the growing universe of platforms like Roblox which blend interactive gameplay, social connection and user-generated content. Games as a platform are reshaping the cultural definition of ‘play.’ One of the latest hits on Roblox is Steal a Brainrot that revolves around collecting and stealing as many Brainrots as possible. While this may sound bizarre to some, it feels completely normal to millions of young players.

Games and play by association are child’s play, but it might be surprising that video gaming represents a higher share of total media consumption than in any other age group. Video gaming is for children of all ages, and any brand executive can do the math. The Roblox 3D platform alone has more than 380 million monthly active users, growing 19 percent annually from 2021 to 2024. Minecraft grew 12 percent annually, while Fortnite followed with 10 percent. The scale is impossible to ignore.

And this is the edge of the gaming universe; the numbers are impressive. McKinsey & Co. reports that gaming accounts for the largest share of U.S. media consumption at 23 percent, compared with 21 percent for streaming and 20 percent for social media. According to Bain & Co., the global video game market reached $219 billion last year and is projected to grow by 4 percent annually through 2028. What’s more, according to Pew Research Center, 85 percent of U.S. teens report playing video games, and 41 percent say they play them at least once a day. Four-in-ten identify as gamers.

The key to tapping into gaming communities is authenticity -- the most successful brand activations don’t just show a potential customer a product. They embed the brand into core memories that they’re already creating with their friends.

Attention Immersion

The brands that play in the video gaming space know it’s not just about reach but about locking in the user’s attention. On TikTok, engagement is often measured in seconds or even milliseconds. According to Laila Nasr, Strategic Insights & Partnerships Manager at GEEIQ, “Console and PC gaming are the only digital mediums that get close to live-event levels in focus. It’s the difference between scrolling past a social media post and playing a game for hours.” Think about what this means for brands trying to reach next gens in a place they want to be.

McKinsey & Co. measures attention as valuable time spent, driven by focus and intent. Gaming’s advantage is immersion. Leaderboards matter, but the real difference is narrative. As Bain & Co. notes, “Increasingly, gamers and fans are falling in love with universes, stories, and characters rather than the entertainment format itself.”

Gamers invest in creating and co-creating digital identities. A Roblox survey found that 56 percent of Gen Z users agree that styling their avatar is more important to them than styling themselves in the physical world. As Nasr observes, “When you hang out with friends in the real world, you express yourself in specific ways, to show personality, interests, style, and so on. In social gaming environments, like Roblox and Fortnite, players do the same, but here, they’re not constrained by reality.” According to survey data reported in Bain & Co.’s Gaming Report 2025, customization and playing with friends are just as important for gamers on platforms like Fortnite, Roblox, and Minecraft. This relationship immersion leads to the most important currency of any brand: trust.

Trust by Association

According to dentsu’s 2024 State of Gaming Report, 78 percent agree that video games are where they connect with friends and meet new people. For brands, this creates a unique opening to build relationships in gaming communities rooted in authenticity.

“The key to tapping into these communities is authenticity — the most successful brand activations don’t just show a potential customer a product. They embed the brand into core memories that they’re already creating with their friends.” says Nasr.

Brands can build trust and engagement at a community level. For example, e.l.f. Beauty partnered on Love, Your Mind World, a Roblox game supporting teen mental health, and collaborated with Chime to launch Fortune Island: Earn. Learn. Flex, teaching financial literacy, which according to Patrick O’Keefe, chief integrated marketing officer at E.l.f. Beauty aims “to equip our community with the skills and swagger to be their best E.l.f. selves.”

Gaming platforms can be an effective virtual shop window. Vans dropped the Mixxa on Roblox before selling it anywhere else. And a source of valuable advice. Maybelline took over Roblox’s Paradise RP to demonstrate its Sunkisser Blush.

A bigger game-changer, however, is how these platforms are doubling down to create a virtual selling ecosystem. Beauty brands such as e.l.f. Beauty sell real products via Roblox while Fenty launched a shoppable game where players could unlock an exclusive shade of its Gloss Bomb lip gloss.

Gaming platforms are an ideal playground for users to discover and experiment with new products, brands, styles, and influences. For example, L’Oréal Paris lets users play around with the style and color of their avatar’s hair. Skateboarding fans can customize their own Vans shoes for their avatar. It’s a smart move. According to a Roblox survey, 84 percent say their physical style has been inspired by their avatar’s style. However, Nasr warns that success won’t come from brands simply adding a checkout button, “The winners will build experiences where shopping feels like play — where discovery feels earned, products feel native, and purchase is a natural extension of the game.”

A New Game Plan

Gaming is a medium where users commit time, focus, and emotion. As Nasr observes “Social media is saturated, but gaming offers the deeper engagement needed for brand love and loyalty to grow.”  This depth of engagement also translates into conversions. YouGov data report that nearly a third of U.S. sandbox gamers agree with the statement, “I am a sucker for anything branded, even if it’s expensive,” compared with just 22.3 percent of the general population.

Creative content underpinned by strategic reasoning will be critical to successful brand activations, particularly in crafting aspirational experiences. For example, Maybelline’s Roblox game Glamhattan: Colossal Bubble (live from June 15 – October 15, 2025) invites players to explore New York neighborhoods, experiment with virtual makeup looks, unlock exclusive branded rewards,  and purchase products directly in-game.

Savvy C-suite marketers understand that virtual immersion experiences drive a high level of engagement and know how brands can both disrupt and redefine the customer journey. It’s a game that brand executives can’t afford to lose. Kids don’t stop playing games when they become adults. It’s a market for life.

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Electronics Retailers Can Shift the Future of PFAS: Here’s How https://therobinreport.com/electronics-retailers-can-shift-the-future-of-pfas-heres-how/ Tue, 26 Aug 2025 04:01:00 +0000 https://therobinreport.com/?p=98265 Electronics Retailers Can Shift the Future of PFAS Heres HowFor retailers, the message is stark: what begins in chemical plants and semiconductor fabs doesn’t stay there. It flows directly into the products on their shelves — and into the headlines that shape consumer trust. Companies like Target, Best Buy, and Walmart may not manufacture chips, but they market and sell the devices that depend on them. ]]> Electronics Retailers Can Shift the Future of PFAS Heres How

Walk into any major retail store today, from Target to Best Buy, and you’ll see shelves stacked with the latest smartphones, laptops, gaming consoles, and smart home gadgets. These products aren’t just consumer favorites — they are the beating heart of global retail. In 2024 alone, consumer electronics sales topped $1.2 trillion worldwide, making them one of the most important growth engines in the sector.

But behind the sleek glass screen of the latest iPhone or the processing power of a Nvidia graphics card lies a paradox that few shoppers, and not enough retailers, understand: Semiconductors, the chips powering nearly every device on the market, cannot be manufactured without PFAS, the notorious “forever chemicals” now at the center of intensifying public, regulatory, and legal scrutiny.

For retailers, the message is stark: what begins in chemical plants and semiconductor fabs doesn’t stay there. It flows directly into the products on their shelves — and into the headlines that shape consumer trust. Companies like Target, Best Buy, and Walmart may not manufacture chips, but they market and sell the devices that depend on them.

The Semiconductor Paradox

PFAS, shorthand for per- and polyfluoroalkyl substances, are a family of more than 15,000 synthetic chemicals. Their defining feature is the carbon-fluorine bond, one of the strongest in chemistry, which makes them extraordinarily resistant to heat, corrosion, and chemical breakdown. In turn, those traits make them indispensable in semiconductor manufacturing.

As Andrew Chien, a University of Chicago computer scientist and former Intel research leader, recently told Politico: “They’re used in a sequential fashion in the processing of the chips. We can become more efficient about it, but it’s not obvious how we transition away from [PFAS].”

That reality is echoed by Cally Edgren, Vice President of Sustainability and Global Regulatory at Assent, an Ontario-based supply-chain and data platform. She notes: “When most people think about PFAS, they picture water resistance or non-stick coatings. But behind the scenes, ‘forever chemicals’ are foundational to advanced industrial processes — perhaps none more so than semiconductor manufacturing. Their unique chemical properties enable photolithography, plasma processing, wafer cleaning, and even the pristine cleanroom environments essential for chip fabrication. In these settings, PFAS aren’t just convenient—they’re indispensable.”

Translation: without PFAS, there are no semiconductors. And without semiconductors, there are no smartphones, laptops, televisions, ecommerce platforms, or even point-of-sale systems. The chip shortage of 2021, which left retailers scrambling to stock laptops, game consoles, and cars, showed just how vulnerable retail is to disruptions in semiconductor supply. Now, PFAS has become another fault line, raising the stakes even higher.

Why Electronics Retailers Can’t Ignore the PFAS Problem

What makes PFAS so useful in chips is also what makes them dangerous. PFAS compounds don’t naturally degrade, and as a result, they accumulate in water, soil, and bloodstreams, and have been linked to a long list of health issues, including cancers, thyroid disease, infertility, and developmental issues, to name just a few. Major PFAS production facilities in the U.S., Asia and Europe have already left contamination in their wake. Chemours’ Fayetteville Works plant in North Carolina has polluted ten counties with a PFAS called GenX, while its Parkersburg, West Virginia site has repeatedly exceeded wastewater limits, according to the EPA.

For retailers, the stakes aren’t theoretical anymore. PFAS has become a real supply-chain, compliance, and brand risk. UL Solutions, which advises global retailers on chemical safety, points out that rules and reporting requirements are multiplying across states, countries, and regions. At the same time, shoppers are waking up to the issue and increasingly prefer products marketed as PFAS-free. That creates ripple effects: supply chains strained by reformulation or sourcing changes, brands exposed to reputational damage if their products are tied to “forever chemicals,” and mounting costs for compliance, labeling, and even recalls.

In Europe, the issue has already reached a boiling point. It’s not just about regulation—it’s about politics and public pressure. In France, for example, hundreds of activists stormed a PFAS-producing facility near Lyon in March of 2024, staging what they called a “citizens’ inspection” and sparking national headlines about the health risks tied to local contamination. Across the EU, PFAS is no longer a niche concern. It’s a mainstream environmental crisis—and one that consumers, civil society, and retailers are watching closely.

The weight of that public scrutiny has also translated into historic legal accountability. In June 2025, an Italian court delivered a landmark ruling, sentencing eleven former executives — including board members linked to Mitsubishi and other parent companies—to a combined 141 years in prison, with individual terms of up to 17 years. Their crime: decades of mismanagement that left nearly 200 square kilometers of soil and drinking water contaminated with PFAS. It was the first time corporate managers in Europe were held criminally liable for PFAS pollution — a powerful signal that industrial negligence is no longer just a reputational risk, but a path to doing hard time.

In the U.S., the challenges are of an entirely different character. With federal momentum under the Trump Administration moving slowly and often inconsistently, state governments have become the frontline of PFAS regulation. This has produced a patchwork of requirements that vary widely across jurisdictions, forcing retailers and manufacturers to track shifting compliance obligations state by state.

But the biggest risks revolve around litigation. Over the past several years, PFAS lawsuits have led to some of the largest environmental settlements in U.S. history. In 2023, 3M agreed to pay up to $12.5 billion to settle claims related to PFAS contamination of public water systems. That same year, DuPont, Chemours, and Corteva reached a $1.19 billion settlement for similar claims. These cases are only the beginning: municipalities, states, and private plaintiffs continue to file actions against a wide array of companies—including retailers—alleging PFAS contamination or failure to disclose risks.

“For semiconductor companies, the litigation risks are acute, and they should all consider preemptive investment in advanced PFAS treatment infrastructure to demonstrate good faith and reduce damage exposure,” noted Chad Cummings, the CEO of Texas and Florida-based Cummings & Cummings Law, which advises manufacturing companies on mitigating their liability exposure.

For retailers, the message is stark: what begins in chemical plants and semiconductor fabs doesn’t stay there. It flows directly into the products on their shelves — and into the headlines that shape consumer trust. Companies like Target, Best Buy, and Walmart may not manufacture chips, but they market and sell the devices that depend on them. That makes them the public face of PFAS risk, whether through regulatory fines, lawsuits, or reputational damage. In an industry where consumer confidence drives sales, ignoring PFAS is no longer an option; managing it has become a core business imperative.

A Breakthrough That Changes the Equation

For years, the semiconductor–PFAS paradox seemed inescapable: the chemicals were indispensable, but using toxic chemicals with the potential to seep into the environment was almost inevitable.

Now that equation has begun to shift —not in Silicon Valley but in Decatur, Alabama, of all places. There, Daikin America — the U.S. arm of Daikin Industries, a Japanese multinational best known as the world’s largest air-conditioner manufacturer, but is also a global leader in the production of fluorochemicals — agreed to let a small Minneapolis startup try something new. Daikin is not a chipmaker, but it makes the critical PFAS chemicals that chipmakers depend on to make key electronic components. If PFAS can be destroyed at the source, in a plant like Daikin’s, then the manufacturers downstream can easily follow suit.

Enter Claros Technologies, a relatively unknown albeit well-funded environmental technology company that was spun out of the University of Minnesota. Earlier this year, Claros installed its UV-photochemical system at Daikin’s facility and ran it under industrial conditions. Over the course of the pilot, the system processed more than 50,000 gallons of contaminated wastewater and reported 99.99 percent destruction rates. Even more impressive than the percentage destruction was the scale: capable of hundreds of gallons a minute, not the dribble of a contained laboratory experiment.

Claros’ innovation lies in pairing UV with proprietary reagents — a formula that operates at low energy and low cost, while achieving levels of PFAS destruction that far outpace more exotic and expensive approaches like plasma or supercritical water oxidation. That combination — taking a familiar technology like UV and making it do something no one thought possible — is what is turning heads across the industry, prompting one major trade publication in the chemical industry to hail the Daikin trial as a “major breakthrough.

And the implications ripple far beyond Decatur. If chemical plants can destroy PFAS in the wastewater at the point of production, semiconductor fabs, the underlying technology supporting the trillion-dollar consumer-electronics market, can also eliminate PFAS from their production waste streams. At last, one might say, the semiconductor industry may be able to have its cake and eat it too, enabling manufacturers to keep using the PFAS that make modern chips possible, while shedding the risk profile that has made them a global liability.

The Global Arms Race for PFAS Solutions

Although Claros’ UV technology has pulled decisively ahead of its rivals, scores of companies are pursuing an array of promising approaches with different trade-offs in terms of throughput, efficacy, and cost —an arms race in pursuit of the “killer app” for PFAS destruction. The reality, however, is a bit more nuanced; there will not be a single solution for all PFAS destruction. Different settings require different tools: remediating PFAS in farmland soil is not the same as cleaning a contaminated reservoir, which is not the same as treating high-volume wastewater from chip fabs.

The global race to solve PFAS contamination is far from over. Different technologies will likely dominate in different contexts—plasma for certain industrial waste streams, enzymatic degradation for small-scale cleanup, and supercritical water oxidation (SCWO) for specialized niche applications. But for industrial and semiconductor wastewater, the stakes are immediate, and UV-based technology is showing what is possible.

“Semiconductors aren’t going PFAS-free anytime soon,” John Brockgreitens, Ph.D., Vice President of Product Development at Claros, told The Robin Report. “But that doesn’t mean PFAS pollution is inevitable. We’ve proven you can eliminate PFAS at the source, before they ever reach the environment. That’s not just a win for manufacturers — it’s a win for retailers, consumers, and communities that expect supply chains to be sustainable.”

What This All Means for Retail

For retailers, the implications are direct. Electronics sales depend entirely on the steady flow of semiconductors. A disruption in chipmaking — whether caused by regulation, litigation, or reputational fallout — becomes a disruption in retail sales. The 2021 shortage was a warning shot; PFAS represents a potentially longer-term challenge.

But destruction technologies like Claros give retailers a path forward. They provide supply-chain assurance, allowing retailers to say confidently that the products on their shelves are tied to responsible manufacturing. They offer regulatory readiness, helping retailers stay compliant as PFAS rules tighten globally. They protect brand equity by insulating companies from the fallout of PFAS-related headlines. And they strengthen consumer loyalty in an era where shoppers want safer, cleaner, more transparent supply chains.

Replacing PFAS in semiconductor production may take decades, if it can be done at all. In the meantime, the retail sector doesn’t have to stand still. By encouraging suppliers to adopt proven destruction methods, retailers can insulate themselves from regulatory shocks, protect their brands, and give customers the confidence that the products they buy aren’t contributing to PFAS pollution.

For retailers, the message is clear: PFAS may remain essential to semiconductor production, but they no longer have to be a liability. With new destruction technologies now proven at scale, the industry has a way to keep chips flowing, shelves stocked, and consumer trust intact.

Still, voices from inside the supply chain caution against assuming PFAS can be phased out overnight. Mike Bangasser, CEO of Best Technology speaks for many in the industry when he warns: “If PFAS were banned outright, wafer production would collapse. You’d cripple data centers, spike energy use, and stall technologies that underpin modern life — from smartphones to aerospace.” His point echoes a broader frustration: too often, non-scientific policymakers try to legislate away materials that scientists know remain essential, at least until real alternatives exist.

For years, the PFAS debate has been framed as a choice between economic growth and environmental safety. These new technologies suggest that, at least in this case, it doesn’t have to be either-or. By destroying PFAS at the point of production, manufacturers can continue to build the breakthrough chips that underpin the global economy without compounding the environmental damage that has come to define “forever chemicals.”

That, in turn, gives retailers something they have never had before: the ability to break the cycle of liability. But peace of mind only matters if it is backed up by action. The semiconductor industry must show its progress more clearly to the supply chain, and retailers must demand it, pushing suppliers to adopt destruction technologies, requiring transparency, and making PFAS risk management a core part of brand strategy. By doing so, retailers won’t just insulate themselves from regulatory shocks and reputational risk; they will set a new standard for responsible supply chains in the electronics industry. If they seize that role, they can transform PFAS from a looming liability into a competitive advantage. For once, the environment and the economy both stand to win — and the entire electronics ecosystem, from fabs to storefronts, will be stronger for it.

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The AI Agent Survival Guide for Retailers https://therobinreport.com/the-ai-agent-survival-guide-for-retailers/ Thu, 21 Aug 2025 04:01:00 +0000 https://therobinreport.com/?p=98236 The AI Agent Survival Guide for RetailersOnce AI has unfettered access to product data, it becomes much harder to control the terms of engagement. The brands that survive won't be those with the biggest marketing budgets or the most shelf space. They'll be the ones who recognized that in an AI world, controlling the data bridge between digital intelligence and physical products is the ultimate competitive moat.]]> The AI Agent Survival Guide for Retailers

Recently, I sat down with Steve Statler, CEO of AmbAI, expert in Ambient AI technologies, author of “Beacon Technologies,” and host of the Mr. Beacon Ambient IoT Podcast, to discuss the dramatic advances in AI. This report is the distillation of our wide-ranging conversation that we offer as a survival guide for retailers and brands.

The irreversible shift is already happening. ChatGPT is answering 1 billion searches per week. Traffic from AI to retail websites jumped 1,200 percent in a single month. Nearly 40 percent of consumers now use AI as a shopping assistant for researching products or planning purchases.

But research is just the beginning. The next wave of AI will be “agentic,” moving beyond answering questions to taking actions on our behalf, including making purchases. This represents a fundamental disintermediation threat from AI agents acting as intermediaries between brands and customers.  Will this help or harm the brand and retailer connection to the consumer? Will this enhance or impede sales?

Once AI has unfettered access to product data, it becomes much harder to control the terms of engagement. The brands that survive won't be those with the biggest marketing budgets or the most shelf space. They'll be the ones who recognized that in an AI world, controlling the data bridge between digital intelligence and physical products is the ultimate competitive moat.

AI Agent Advantage

Like any procurement professional, this new generation of agents will seek to weaken the position of suppliers by restricting information flow, to get the best possible deal. Imagine a world where your AI agent negotiates directly with a supplier’s AI agent to purchase groceries, select insurance, or replace your T-shirts, jackets, worn-out shoes—all without you ever seeing a brand website, video, or advertisement. The negotiation strips away the positioning information and storytelling, which can bring value to products, by commoditizing the product that the brands are selling.  Agent-to-agent transactions could spell the death of the branded experience, limiting all transactions to the lowest common denominator transactions, with us being none the wiser as to what we are being served. Clearly, this is a problem for brands, and the time is ripe for a proactive solution.

The solution lies in building a strategic alliance of brands, retailers, and technology partners that controls the data flow between consumers using AI to buy and the retailers and brands that supply them. This alliance would ensure brands maintain direct customer relationships while leveraging AI’s power to enhance rather than commoditize the shopping experience and storytelling that makes products valuable.

The Coming Disintermediation

Consider the structural and cultural shift we’re facing. AI is positioning itself between brands and customers, armed with three unprecedented advantages:

  • Intimate customer knowledge: While Amazon knows what you’ve bought, AI knows why you bought it, what you use it for, and whether you really needed it. Through conversations about relationships, health, finance, and daily life, AI platforms are building the most comprehensive customer profiles ever assembled.
  • The power of consumers’ automation bias. As termed by the National Institutes of Health, this bias is the very real and prevalent phenomenon when people, consumers, favor or give greater credence to information supplied by technology like AI agents and ignore contradictory evidence. When agents talk, with uncanny knowledge of our preferences, better mimicking human nuance and empathy and with more authority, we will listen.
  • Complete product intelligence: AI can parse every specification, review, and data point about every product from every competitor, then analyze, compare, and negotiate faster than any human buyer.

This combination of customer knowledge and product intelligence is potent. Users won’t need to navigate websites or deal with limited store staff. AI will understand requirements, shop around, negotiate, and even create personalized content to tell the story of why Product X is perfect for Customer Y.

Traditional merchandising tools—placement, positioning, brand relationships—become irrelevant when a superintelligent purchasing agent is making decisions based purely on data and customer intimacy.

Walmart just announced it will focus its AI efforts on agency, hoping to attract more shoppers away from Amazon with four new super agents, with the goal that AI will drive its ecommerce growth, aiming for online sales to account for 50 percent of its total sales within five years.  Designed to operate with minimal human oversight and execute complex tasks across Walmart’s vast ecosystem, the four agents include:

  • Sparky (customer-facing)
  • Associate (employee support)
  • Marty (supplier automation)
  • Developer (AI testing)

Walmart may be the first to announce such a fully automated decision-making platform for both brands and consumers, but it certainly won’t be the last.

AI: Disruptor in Chief

We can already see the evidence of agents’ disintermediation. Website traffic is falling measurably across the board as AI summaries are presented on the Google home page. These summaries satisfy a user’s question with zero click throughs to brand websites. Existential question: How can you directly influence consumers if they never see your messaging?

The AI powerhouses are actively preparing to take on purchasing tasks on behalf of your customers.  Over one in four of the integrations recently announced by Anthropic was with payment systems PayPal, Square, and Stripe.

OpenAI announced its first services for brands, enabling purchases directly from ChatGPT. There will be no shortage of brands that accept the offer to participate in this pilot, desperate to show shareholders that they have an AI strategy that goes beyond writing marketing copy more efficiently.

The Data Fortress Strategy

The solution lies in controlling something AI desperately needs but currently can’t access at scale: real-world product data. Today, AI’s view of the physical world is surprisingly limited. Show ChatGPT a photo of a product, and it sometimes guesses wrong. AI typically can’t navigate auto-ID systems, struggles with barcodes and QR codes, and has no connection to RFID or emerging ambient IoT data streams. 

But this data represents the largest untapped information pool in the world—trillions of physical items, each with massive datasets about ingredients, provenance, authenticity, location, and lifecycle history. This isn’t just defensive data—it’s the foundation for new business models around transparency, sustainability, and customer engagement.

This isn’t theoretical. The EU is mandating Digital Product Passports (DPPs) for apparel, toys, and furniture within two to three years. Products entering the world’s largest regulated market will need digital IDs with comprehensive provenance data. Like EMV chip-and-pin standards, what starts as regulatory compliance becomes a competitive advantage through reduced fraud, improved efficiency, and enhanced customer trust.

Any brand wanting to sell into Europe will need to develop its DPP systems.  This will eventually be a formidable war chest of data that the AI companies won’t control. Brands already have an amazing cache of product information that they can use to differentiate a direct, brand-controlled, AI-enabled, shopping experience, which can make for a better, more consultative retail experience.  Think of all the instruction manuals, recipes, videos and product information that can be fed into a brand-controlled AI.

Building an Alliance Moat

No single brand can defend against AI disintermediation alone. A single brand app with AI, no matter how good it is, will not stem this tide. We’ve seen most brands fail when they attempt to drive meaningful usage of an app that works with their products exclusively.

An alliance must include three key constituencies working in concert:

  • Leading brands across categories (CPG, fashion, electronics, automotive) that control rich product data
  • Progressive retailers who understand the value of customer relationships over pure efficiency
  • Technology partners who can build and operate the neutral infrastructure required

If we are to offer utility, get frequency of use, and the intimacy that is key to an effective selling experience, a multi-tenant platform will be required that helps consumers manage their pantry, wardrobe, drinks cabinet and tool chest with a one-stop shop. This kind of platform lends itself to being used regularly, having utility, and building trust if it helps customers keep control of their data in a way that the AI giants are not disposed to do.

Timing is one crucial advantage: AI’s connection to the physical world is still being built. Like setting smartphone rules for teenagers, we get one chance to establish ground rules before the AI floodgate opens. Once AI has unfettered access to product data, it becomes much harder to control the terms of engagement.

The brands that survive won’t be those with the biggest marketing budgets or the most shelf space. They’ll be the ones who recognized that in an AI world, controlling the data bridge between digital intelligence and physical products is the ultimate competitive moat.

The Crossroads

Brands face an immediate binary choice: Build an alliance now while you still can or become a commodity product in an AI-driven marketplace where you have no direct customer relationship and compete solely on AI-optimized metrics. Europe is already on the case building a defense that will provide rich data about products that should not be handed over to the AI giants lightly. 

While big tech races to capture consumer data, they’re conveniently overlooking a fundamental issue: giving consumers actual control and portability over their product ownership data, usage habits, and preferences.

The question is whether brands will proactively shape a system that leverages these opportunities in a way that consumers can trust or reactively comply with whatever emerges from Silicon Valley. This Alliance needs founding members now—brands willing to lead this new model of cooperative competition. The window for establishing ground rules is closing rapidly. Every day that passes without coordinated action is a day closer to permanent disintermediation.

Winter is coming. The question is whether retailers will work together to build the alliance moat or find themselves on the wrong side of it when the battle for market dominance begins.

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Amazon’s Showrunner Bet for Retail Media https://therobinreport.com/amazons-showrunner-bet-for-retail-media/ Wed, 20 Aug 2025 04:01:00 +0000 https://therobinreport.com/?p=98228 Why AI Storytelling Could Give Amazon a Retail Media EdgeShowrunner brings new risks. How will Amazon manage IP ownership for user-generated content? Can it maintain quality control while scaling content creation? Will creators embrace the platform or push back, as they have with other generative AI tools? And what guardrails will Amazon apply around moderation, misinformation, and monetization?]]> Why AI Storytelling Could Give Amazon a Retail Media Edge

Amazon’s recent investment in Fable’s Showrunner platform positions the company not just as a retailer or streaming provider but as an emerging player in generative retail media entertainment. While many retailers are still working to scale their retail media networks (RMNs), Amazon is already exploring what may come next: AI-powered, user-generated storytelling. This is a strategic bet on engagement, and a recalibration of what media means in a retail context. In an increasingly fragmented attention economy, where traditional advertising no longer guarantees results, Amazon is looking to reinvent the retail media ecosystem.

Showrunner brings new risks. How will Amazon manage IP ownership for user-generated content? Can it maintain quality control while scaling content creation? Will creators embrace the platform or push back, as they have with other generative AI tools? And what guardrails will Amazon apply around moderation, misinformation, and monetization?

The Rise of Retail Media Networks

Retail media networks have become one of the fastest-growing segments in advertising. Following in Amazon’s footsteps, retailers like Walmart, Target, and Kroger have built their own media groups. Platforms including Walmart Connect, Target Roundel, and Kroger Precision Marketing let brands monetize first-party data through sponsored search, display, and programmatic advertising within closed-loop attribution models.

This shift was sparked by Amazon’s launch of the Amazon Ads Platform (AAP) in 2012. In its first year, the retailer reportedly generated approximately $600 million in ad revenue. Since then, it has seen consistent double-digit growth. Last year, the company reported $56.2 billion in advertising revenue, making it the third-largest digital ad platform in the U.S., behind only Google and Meta. By contrast, Walmart generated $4.4 billion and Target $649 million from their respective RMNs. These networks are growing, but they’re still following the same predictable template: banner ads, search results, and programmatic placements. Amazon, meanwhile, is already moving beyond its own original blueprint.

Amazon’s Generative Media Strategy

Despite building a dominant RMN, Amazon’s investment in Showrunner suggests a new long-term path built on participatory advertising. Showrunner lets users generate animated episodes using AI prompts and then insert themselves into the content. Contributors become influencers and can earn a share of revenue when other creators iterate on their episodes, such as adding new characters, alternate endings, or spin-offs within the Showrunner environment, similar to how user-generated game mods work with games like Roblox and Minecraft. It’s a remixable, creator-first approach.

The platform aligns with Amazon’s broader ecosystem. Content generated in Showrunner is intended to integrate with Alexa, Fire TV, and Prime Video, while also unlocking new pathways for shopping, discovery, and engagement. Rather than simply producing content, Showrunner is an integrated commerce platform. It serves as a tool for product discovery by linking creative content to Amazon’s retail offerings. Imagine a creator producing a fashion show where every outfit links directly to Amazon listings. Or an animated series where a robot chef teaches recipes that sync with cookware and grocery orders. Or a travel documentary where the host visits street markets and every handmade item can be purchased instantly via Amazon.

Amazon’s media ambitions aren’t new. They’ve taken major chances on content before, often at great cost. The company has poured billions into content production through Amazon Studios, including a reported $715 million on the first season of The Lord of the Rings: The Rings of Power, a project that drew sizable audiences but faced creative criticism and questions around return on investment. The Showrunner investment is a departure from these past efforts, aligning more closely with Amazon’s legacy of building scalable transactional platforms over producing top-down content.

Consumer Behavior Has Already Moved On

Amazon’s pivot to participatory content doesn’t come out of the blue. Consumer behavior is shifting, and audiences are choosing creator-led, short-form content, and niche communities over traditional studio-created storytelling. YouTube was recently ranked as the most popular media platform in the U.S. by time spent. Consumers spend over 11 billion minutes on the platform every day. That’s more than Netflix, and more than Facebook and Instagram combined.

In response to this shift, companies are approaching the convergence of media and retail from different angles. Netflix is going physical. In 2025, it plans to launch Netflix House, immersive retail spaces tied to shows like Stranger Things and Squid Game, complete with branded merchandise, themed food, and experiential attractions. While Netflix is embedding content into physical retail, Amazon is embedding retail into user-generated content. Both aim to blur the line between media and commerce, but from entirely opposite directions. Whether starting from retail or media, everyone is chasing the same outcome: more meaningful engagement and more monetizable attention. The future of retail and media lies in who can best merge storytelling with real-time transactions. Amazon’s strategy stands out because it is building content-native commerce from the ground up. Other retailers have experimented with blending media and commerce, but often as collabs rather than fully integrated models. Walmart’s experience offers a telling example.

How Walmart Failed to Do Hollywood

To understand how different Amazon’s media approach is, it’s worth looking at retail leader Walmart. Walmart’s media efforts have spanned multiple formats; in 2010, it acquired Vudu, a direct-to-consumer video platform meant to rival Netflix. But Walmart never fully integrated Vudu into its retail experience and ultimately sold it to Fandango in 2020. In 2023, Walmart partnered with Hallmark to launch a shoppable holiday movie. The campaign embedded clickable Walmart products into the film, blending entertainment and commerce. Clever in execution, but limited in scope, it was a one-off branded campaign, not a platform.

Walmart’s growing partnership with Zepeto, a virtual social platform where users create avatars and explore 3D spaces, and its acquisition of Vizio suggest it isn’t giving up on interactive formats. In fact, it sees the long-term value of owning both the screen and the signal. But where Amazon is betting on participation and creation, Walmart is still chasing distribution and display. Both investments align with social commerce trends and Gen Z behavior. Yet, the contrast is clear. Walmart is retrofitting entertainment with commerce. Amazon is building a new layer of content-native commerce infrastructure.

What It Means for the Future of Retail Media

Retailers have spent the last few years building ways to monetize attention. Amazon is now investing in how customers can create it, unlike the others that remain tethered to traditional marketing tactics. Target leans into curated seasonal drops for attention, Sephora blends commerce with community tools, Nike experiments with gated co-creation via .Swoosh, and LVMH has high-production AR campaigns. All are tightly managed, brand-led ecosystems. Walmart, for its part, continues to invest in acquisitions, but its efforts still focus on distribution and display, not participatory creation.

This shift toward participation isn’t happening only in retail. In the agency world, R/GA’s work with Google’s Veo for luxury brand Moncler shows how AI is transforming storytelling itself. The campaign compressed production to just four weeks, replacing the traditional linear process with a fluid, iterative model where human creative direction blended with AI’s unexpected outputs. R/GA’s first-ever acquisition of AI studio Addition signals a deeper commitment to building proprietary systems for next-generation, participatory storytelling. For brands and retailers alike, it’s a reminder that the creative infrastructure supporting retail media is evolving just as quickly as the platforms themselves.

Amazon, by contrast, is transforming customers from targets into co-creators. Showrunner signals that the next wave of RMNs may not look like media buys or display ads. They may look like customer-created worlds, stories, and tools, crafted not just for watching, but for remixing. And they’ll be built into ecosystems where transactions, content, and data aren’t siloed but synchronized.

As promising as the model is, Showrunner brings new risks. How will Amazon manage IP ownership for user-generated content? Can it maintain quality control while scaling content creation? Will creators embrace the platform or push back, as they have with other generative AI tools? And what guardrails will Amazon apply around moderation, misinformation, and monetization? These are not small concerns. Unlike others testing the waters of content-commerce convergence, Amazon has a decade of media experience to build on, even if some of those efforts missed the mark.

If the future of commerce is about who captures and sustains attention, then building the infrastructure for co-creation may be retail’s most powerful move yet. Retailers can no longer rely solely on data-driven targeting or traditional media placement. The next competitive advantage lies in enabling customers to generate the stories themselves.

Amazon’s bet on Showrunner isn’t just an experiment in generative entertainment. It reflects a broader shift as the boundaries between media, commerce, and technology are collapsing into a single participatory ecosystem. Platforms that effectively support co-creation may better influence how consumers interact with brands and navigate the shopping journey.

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Warnings and Revelations about AI https://therobinreport.com/warnings-and-revelations-about-ai/ Thu, 07 Aug 2025 04:01:00 +0000 https://therobinreport.com/?p=98160 Warnings and Revelations about AIFrom simple stone tools to complex genetic engineering and information technology, the history of technology is the history of human invention. The speed at which the invention of these tools and technologies is being delivered now has become exponential as the application of machine learning and AI becomes the ubiquitous open-source ingredient. ]]> Warnings and Revelations about AI

Editor’s note: We are taking this opportunity to preview an AI-enhanced future that is closer than you think. Although not specifically related to retail, this report is required reading to be forewarned and forearmed about emerging tech breakthroughs that will change all our lives. Knowledge is power, and in this AI Era, the more you know, the better decisions you can make.

We Are All Dreamers…Perfect Dreamers

When it comes to technology, regardless of the consequences, we humans are inexorably drawn to optimism, and we have been consistently proven right to do so. Using our dystopias as guardrails, technology has always delivered outcomes that extend the quantity and quality of human life.

From simple stone tools to complex genetic engineering and information technology, the history of technology is the history of human invention. The speed at which the invention of these tools and technologies is being delivered now has become exponential as the application of machine learning and AI becomes the ubiquitous open-source ingredient.

Tech History as Prelude

Take for example, the cotton gin. Invented in 1793, the cotton gin used a combination of wire teeth on a rotating cylinder and a grate or screen to pull the cleaned cotton fibers through, significantly increasing the speed and efficiency of cotton processing. This had a major impact on the cotton industry, particularly in the Southern states, where cotton was a major, labor-intensive crop and whose commercial use would force huge percentages of the labor force out of work. In the face of this radically disruptive technology, the cotton gin’s inventor, Eli Whitney, wrote this to his father: “One man and a horse will do more than fifty men with the old machines. ‘Tis generally said by those who know anything about it, that I shall make a Fortune by it.”

And indeed, fortunes were made, and the potential catastrophic implications to society were far overshadowed by the entire industry that was born from this simple invention that fueled regional growth in the South for over a century.

And so, it continues into this century. Andrew Ng, founder and lead of Google Brain and currently an Amazon Board member, recently said the same. “Just as the Industrial Revolution freed up a lot of humanity from physical drudgery, I think AI has the potential to free up humanity from a lot of the mental drudgery.”

The Mother of Invention

From simple stone tools to complex genetic engineering and information technology, the history of technology is the history of the human invention of tools and techniques. The speed at which the invention of these tools and technologies is being delivered now has become exponential as the application of machine learning and AI becomes the ubiquitous open-source ingredient layer to everything and is mutually accelerated by the arms race for processing speed. We now measure success in petaflops (a quadrillion floating-point operations per second) and trillions of parameters (the internal, numerical values that LLMs learns during training to process and generate text).

As knowledge-seeking animals, the potential value of these tools to increase our understanding of the world around us and solve some of our most pressing problems around the quality and quantity of life is as tempting as Pandora’s Box, which, while it contained all the evils of the world, it also contained hope. As Marc Andressen said, “Technology is the glory of human ambition and achievement, the spearhead of progress, and the realization of our potential.”

While decades in the making, with this new computational prowess we are continually (seemingly daily now) seeing breathtaking exponential breakthroughs, none more exciting than in the field of Synthetic Biology, where we can truly see the practical application of the positive outcomes of AI. One powerful example of how this is already being used is being pioneered by Andrew Adams at Eli Lilly and Company. In seeking treatment to the debilitating disease for Alzheimer’s, researchers discovered the Christchurch Mutation: just one copy of the Christchurch variant conferred protection against Alzheimer’s disease, even in individuals with genetic predispositions to the disease. Being able to apply Synthetic Biology to enhance and deliver this modification would transform the field of Alzheimer’s from treatment to prevention.

Add to this the recent open-source release of Google’s Alphafold, their free AI Model to predict the structure of all of life’s molecules and we start to see what’s now possible. The fact that Google just gave away access to over 200 million proteins and provided a free AI tool for scientists to experiment with is in itself exponential.

Admittedly, to the non-scientific community, this seems interesting but arcane until we start to see the practical application of the new technology toolsets being built. Enter Colossal founder Ben Lamm, a protégé of George Church. A self-described ‘serial entrepreneur,’ he started Colossal with $15M in 2019, now worth $10.2B, with the sole purpose of advancing the cause of de-extinction, using advanced gene editing technology to rebuild the DNA of lost megafauna and other creatures. With Earth on track to lose between 30 to 50 percent of its biodiversity by 2050, maintaining this integrity is vital to life on Earth; his work is mission-critical. His most recent accomplishment, the birth of three dire wolves (Romulus, Remus, and Khaleesi) is considered “the world’s first successfully de-extincted animal,” the first of their kind to be alive in over 10,000 years. While Woolly Mammoths and Dodo Birds are also on their roadmap, the work at Colossal is not simply to create novel creatures for 21st-century Jurassic Parks; instead, it is about building the technological capabilities to stop the current waves of extinction in their tracks. Colossal also seeks to use Synthetic Biology in other useful ways, successfully editing the genes of an Amazonian microbe they call ‘X-32’, from a microbe that enjoys eating plastic to a microbe that is voracious for them, digesting polymers in weeks instead of decades or centuries and leaving behind carbon dioxide, water, and biomass. This novel solution could swiftly help us address the problem of plastic pollution on our planet and microplastics in our bodies, all with the enhanced use of data and computational power.

A Synthetic Future

With synthetic data and synthetic biology naturally comes ‘synthetic everything’. Synthetic Humans (Robots), Synthetic Media (Google VEO, Midjourney), Synthetic News and even Synthetic Truth. That there are bad actors and bad intent, we are clear. And the need for us to be diligent and leery, especially in this current era, of dystopias of our own making, is real. The need for the ethical human in the loop couldn’t be more dire and we must all remain diligent to these poor outcomes. We must, and will be, diligent, as these are the human decisions put before us as we build this awesome new AI toolset whose promises far outweigh the perils.

At this year’s World Economic Forum in Davos, Andrew Ng, ever the tech optimist, was asked directly about the perils of AI and Artificial General Intelligence (AGI), and he replied, “Do we think the world is better off with more intelligence? We use, primarily, human intelligence; now we have artificial intelligence. I think that intelligence, net-net, tends to make societies wealthier, make people better off…intelligence can, in some cases, be used for nefarious purposes, but on average, I think it actually makes us all much better off.” But is this a false equivalency? More intelligence may be better intelligence, but is more AI better AI? The answer to this depends wholly on how we use it.

From our daily businesses to our daily feeds, the exponential pace of the practical use cases for the application layers of machine learning, AI, and even Agency is indisputable. It has already become a known-known that AI is the ubiquitous open-source business ingredient for speed, agility, efficiency and profitability. To paraphrase Eli Whitney, ‘From this technology, one can make fortunes.’  However, only by fully understanding the implications beyond the opportunities and using the processes of applied innovation to look at technology breakthroughs outside our industry, we can see more clearly a wider view, ensuring we drive the most desirable outcomes.

As leaders, we must always be deliberate about what we set in motion. In Pandora’s fable, when we are open to every inevitability there can be unintended consequences. But with the right insights, we also know that Hope never left the box.

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Janice and Jason Wang Are Creating the AI RetailTech Future https://therobinreport.com/janice-and-jason-wang-are-creating-the-ai-retailtech-future/ Tue, 05 Aug 2025 04:01:00 +0000 https://therobinreport.com/?p=98133 Janice and Jason Wang Are Creating the AI RetailTech Future“The supply chain for mass-produced garments is a very lengthy one—we can predict weather better than we can predict what fashions will sell.” Janice Wang]]> Janice and Jason Wang Are Creating the AI RetailTech Future

What does it take to be a pioneer in uncharted retail industry waters? The global fashion industry is driven by innovation and creativity, but defined by more tangible assets: fabric, form, warehouses and stores. Technology has played a central role in production, less so in the front office. Alvanon, a Hong Kong-based fashion tech firm co-founded by siblings Janice and Jason Wang, has strived to harness data and leverage technology over the past 25 years. As forerunners, they have led the way to maximize the impact of innovation while minimizing the friction and constraints across solutions that impact every stage of the fashion supply chain.  

AI-Relevant High Tech

The Wangs focused on a core problem in the industry, responsible for customer frustration and a cascade of returns and a frustration for retailers: sizing. Alvanon has worked with hundreds of the world’s leading brands, from Chanel, Walmart, Lululemon, and Gap, to Target, Stitch Fix, Polo Ralph Lauren, and more to help them optimize the ways they approach fit and sizing to design processes and reduce waste and inventory costs.

This is much more complex than it sounds and has advanced exponentially with AI. The fashiontech innovator has been enhancing its solutions with artificial intelligence (AI) to infuse further precision and accuracy in the fit and design process and turn product development cycles into perpetual learning and innovation engines. 

Founded in 2001 in Hong Kong, Alvanon currently has headquarters in New York, London, Germany, Shanghai, Shen Zhen, and Australia. Its global team of 200 creates data-driven physical and digital sizing and fit tools and provides consulting services to help clients address challenges in apparel development, production, and retail.

“The supply chain for mass-produced garments is a very lengthy one—we can predict weather better than we can predict what fashions will sell.” Janice Wang

The Wang Way

Founders (and siblings) Janice and Jason Wong grew up in a Hong Kong garment manufacturing family, where they developed a holistic understanding of the apparel industry, from the rigor of precise design, through the complex logistics of globally dispersed supply chains, to the ever-evolving expectations of consumers. Janice is CEO and Jason is COO; together they guide Alvanon with a pragmatic understanding of their industry’s challenges and a desire to balance innovation with execution. 

Alvanon’s strategic outlook is holistic and begins with an essential understanding of the critical importance of data, and how it flows between each link of the apparel value chain. “The supply chain for mass-produced garments is a very lengthy one—we can predict weather better than we can predict what fashions will sell,” observes Janice. “The 18 months it typically takes to bring a piece from concept to floor is typical for producers of evergreen items like basic T-shirts or sweatpants, but for a hot neon pink shirt, trendiness cannot be predicted that far out,” she explains. Janice believes most processes are currently insufficiently agile to fulfil fast-changing consumer trends and tastes. “And then when you factor in sizes across a global consumer population, the problem becomes even more complex!” 

The Fit-Tech Revolution

The Wangs understood that sizing was a key unlock to brand success. Alvanon’s journey began with a prescient realization: Precise sizing is not only key to consumer satisfaction, but also the fundamental underpinning of the profitability of every apparel brand. Janice explains, “We’ve built a ‘fit standard’—a series of mannequins that work as an industrial benchmark, covering the global spectrum of human bodies.” Alvanon has created a consistent sizing and fit language, AlvaForms. Their innovation is a poster child for the practical application of AI technologies. These physical and digital fit models are crafted based on extensive anthropometric data from millions of body scans and are designed to reflect a broad spectrum of human body shapes and sizes. 

AlvaForms are used in product development, grading, and quality control processes by hundreds of apparel brands and manufacturers and are integrated within digital design workflows, accessible via Alvanon’s Body Platform (ABP), a software-as-a-service solution it launched nearly a decade ago. The ABP enables apparel designers, manufacturers, and retailers to create consistent sizing for prototyping, sampling, and fit validation, which in turn allows tighter coordination across globally dispersed supply chains. By converting vast amounts of anatomical data into granular and precise fit categories, Alvanon helps global brands improve design accuracy and, in return, reduce expensive product returns.

AI Transformation 

The Alvanon Body Platform was a breakthrough for stakeholders—whether high-fashion couturiers or fast-fashion manufacturers—to work with one universal, trusted fit standard.  “As 3D design gained more industry traction, ABP allowed 3D design software users to use virtual AlvaForm that was exactly the same as their physical AlvaForm,” says Janice. 

As visionaries, Alvanon is looking to harness AI to ride a further wave of fashion tech innovation. Janice observes that as brands continue to build ever-massive libraries of digital assets, “there needs to be some discipline, and they need search capabilities. Alvanon’s AI journey was built on top of 20 years of building libraries of bodies, examining outliers, categorizing ethnicities and points of measurements in 3D.” AI now forms an integral component of Alvanon’s sizing intelligence ecosystem, integrating all the data and analytical processes the company has generated along that journey. AI tools have been layered onto this foundation to address and reduce the challenges created by the data silos that emerge within the legacy systems of fashion companies. As Janice describes: “Silos emerge as more humans try to do their jobs with limited amounts of data or try to draw holistic insight from the wrong datasets.” 

Alvanon’s AI-driven system enables faster, more accurate demand forecasting and fit analyses, in part because it is purpose-built to cut through these silos in an increasingly digitally native fashion world. Eric Lee, Alvanon’s Executive Director for the Americas, explains, “The truth is, we know what an effective sizing system looks like — it really hasn’t changed that much since Alvanon started 25 years ago.” That said, “Most sizing tools on ecommerce sites are built to drive conversion, not to capture accurate shopper body and shape data. As a result, brands are often left with an incomplete—or misleading—picture of their customers’ bodies, which limits their ability to design better-fitting garments.” 

Alvanon is working to deepen AI integration to build end-to-end sizing solutions that continuously adapt and learn from real-time data across the fashion supply chain. The company envisions AI not just as a fit and demand prediction tool, but as an enabler of data-driven collaboration between designers, manufacturers, and retailers to break down existing data silos and achieve a single sizing standard across digital and physical product workflows. 

Transformative Agentive AI Platform 

The transformation Alvanon is working to achieve is being accelerated by AI’s own iterative journey, as the technology moves beyond basic generative functions (creating images or designs based on prompts) towards agentive AI, in which models can act autonomously to optimize and manage workflows. Jason highlights this pivotal transition: “AI agents are increasingly more interesting for the apparel industry. AI is all about machine learning; more and better ‘ground truth’ data you can feed the machine, the better.” Agentive capability allows AI to make decisions proactively and improve operational efficiency, rather than requiring constant human input. Such autonomous intelligence is particularly relevant for the complex and multifaceted apparel industry, where multiple stakeholders need to collaborate on fit, sizing, and design in fast-moving environments.

Lee explains BodyAI was developed as “a data translation tool that helps apparel teams interpret ecommerce feedback and other data sources to drive smarter sizing and design choices.” Lee believes this will help brands “create smarter products, better fit, and loyal customers who keep coming back.”

BodyAI represents a key step in moving toward autonomous intelligence: “AI can enhance many tasks today in the apparel industry, but only if there is enough reliable data and the systems are in place,” says Jason, “ I can see a future where AI is helping in real time to determine the exact sizing allocation going into each store, and from that, determining the production lot. The key is to solve the issue of reliable consumer data.” 

BodyAI’s suite of services uses AI to capture and create avatars of consumers and provide each with sizing and fit advice alongside other AI tools that are in the market today. Other tools on the market, like Google’s Doppl app, offer a virtual representation of how clothes might look, but there is a critical difference between visual try-on and accurate fit. “Virtual try-ons make everyone look good, but if the digital asset doesn’t match the physical garment, customers will be disappointed,” says Jason Wang. That’s where BodyAI comes in; not to replace existing tools, but to sit alongside them, ensuring that the visual experience is grounded in physical reality. BodyAI acts as a “bridge between the ecommerce team and the product teams,” enabling both commercial and product stakeholders to extract greater value from the data already in their possession. 

From AI to Beyond

Looking forward, Alvanon is significantly expanding its investments in AI and data-driven solutions. The company envisions a future where fashion is shaped by entities capable of converting complexity into clarity and speed at scale. Beyond delivering reliable sizing and fit, Alvanon seeks to harness consumer trust to help fashion evolve into an industry where digital precision, sustainability, and customer satisfaction are no longer trade-offs but synergistic goals. As Janice puts it, “The issue is not just about getting the right size, but building systems that can adapt, learn, and serve both the industry and the consumer—faster, smarter, better.” In this AI-powered era, Alvanon’s continued focus on innovation, collaboration, and human-centric design is its foundation to remain indispensable in the ever-evolving fashion landscape.

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