Retailgentic: Agentic Commerce meets Retail and Brands

Scot Wingo
  • 5.0 (7)
  • TECHNOLOGY

Retailgentic is the podcast where Agentic Commerce meets retail innovation. We help retailers and brands prepare for the future of agent-driven shopping with actionable news, expert insights, deep analysis, and forward-looking predictions.

  1. Ashish Gupta, VP/GM of Merchant Shopping at Google: UCP Deep Dive, Nerding out on Product Data Feeds, the importance of Product-Level Context PLUS Google's Vision for Agentic Commerce

    2D AGO

    Ashish Gupta, VP/GM of Merchant Shopping at Google: UCP Deep Dive, Nerding out on Product Data Feeds, the importance of Product-Level Context PLUS Google's Vision for Agentic Commerce

    This episode explores the shift from traditional search and ecommerce flows into a new agentic commerce environment where shoppers are using AI surfaces to discover, compare, and increasingly delegate parts of the buying journey. Ashish explains what Google was seeing internally that led to the development of UCP, why the protocol was designed to be open and ecosystem-wide, and why the ambition goes far beyond checkout. He also shares how Google is thinking about discovery, conversational product data, merchant readiness, and the long-term role of AI across the shopping journey. For retailers, brands, marketplaces, and commerce tech teams, this conversation is a helpful window into what Google believes is changing now, and what foundations businesses should be investing in before the market fully shifts. Highlights  How Google’s large-scale ad and data systems shaped his approach to commerceWhy UCP emerged now, and the two major trends that inspired itWhy Google believes agentic commerce needs an open, ecosystem-wide standardWhy the future of UCP extends far beyond checkoutHow discovery is starting to take shape within the protocolWhy richer, more conversational product data matters in AI shopping experiencesWhat retailers need to do now to improve visibility on AI surfacesHow Google is thinking about the relationship between agentic commerce and advertisingWhy agentic commerce is still early, but already moving from concept to realityAgentic commerce is still early, but this conversation makes one thing clear: the infrastructure decisions being made now will shape who gets discovered, considered, and chosen in the next era of shopping. Timestamps2:32 — Welcome and introduction to Ashish Gupta 5:01 — Building Google’s data infrastructure and declarative querying at scale 9:43 — AI at Google before the current wave 11:32 — What it means to be an Engineering Fellow at Google 14:00 — Balancing technical leadership and operational leadership 16:10 — Why Ashish moved into merchant shopping 17:41 — The origin story behind UCP 24:58 — Why Google chose an open protocol approach 27:50 — Responding to skepticism around Google’s commerce efforts 32:30 — Discovery, catalog search, and where UCP expands next 35:39 — Multi-item and multi-merchant cart support 37:43 — New protocol capabilities and partner onboarding 38:42 — Why product data quality matters more in AI shopping 43:22 — How shoppers are using AI surfaces in more complex ways 47:47 — Agentic commerce and advertising 50:10 — Where agentic commerce may go from here 51:46 — Closing thoughts and where to follow Ashish 👉 Connect with Ashish: https://www.linkedin.com/in/ashishgupta98/ 👉 Check out UCP announcement: https://www.retailgentic.com/p/flash-googlenrf-announces-universal 🧠 Want to stay ahead in AI commerce? Subscribe and follow along:📰 Subscribe to the free Substack: retailgentic.ai📺 Watch episodes on YouTube & Subscribe for updates: https://www.youtube.com/@Retailgentic

    47 min
  2. Inside Vendee Labs: Darryl Carlton and Ross Gardiner on Building Buyer-First Agentic Commerce

    MAR 12

    Inside Vendee Labs: Darryl Carlton and Ross Gardiner on Building Buyer-First Agentic Commerce

    In this episode, we take a deep dive into what buyer-side agentic commerce could actually look like. The conversation explores the origins of the company, why Darryl and Ross focused on reducing friction for buyers, and how that unexpectedly opened up solutions for sellers, payment providers, and enterprise procurement teams as well. The episode also features a live demo of Vendee Labs’ platform, showing conversational discovery, real-time product retrieval, multi-vendor carting, and a multi-item ACP checkout flow.  Highlights Why Vendee Labs is approaching agentic commerce from the buyer’s perspectiveThe founding story behind the company and the friction that inspired itHow ChatGPT and Claude changed the direction of the productA live demo of conversational commerce across real merchantsWhat a multi-vendor, multi-item ACP checkout could mean for online shoppingWhy autonomous commerce needs legal and governance frameworks, not just AIThe vision for a Universal Protocol Bridge across ACP, UCP, and future standardsHow strong permissions and audit trails could reduce chargebacks and disputesWhy poor product data creates broken outcomes in agentic shoppingWhere Vendee Labs sees opportunity across consumer, B2B, procurement, and white-label use casesVendee Labs is betting that the future of commerce won’t just be agent-powered—it will be buyer-centered, trust-driven, and built to work across whatever protocols come next. Timestamps: 00:06:09 — Ross shares his background in global technology planning and delivery 00:07:23 — Darryl shares his background in retail IT, telecom, AI, and governance 00:08:53 — Darryl reflects on AI before and after the ChatGPT moment 00:10:03 — Discussion on LLMs, explainability, and true intelligence 00:11:26 — The founding story behind Vendee Labs 00:13:13 — How the product evolved into its current form 00:16:06 — The Vendee Labs pitch: changing how the world buys 00:17:06 — Why solving buyer friction also solves seller-side pain points 00:20:18 — Live demo begins 00:21:10 — Running shoes search and conversational discovery demo 00:25:42 — Multi-vendor cart and checkout walkthrough 00:31:06 — Why richer product data is critical for agentic commerce 00:35:46 — Consumer, B2B, procurement, and white-label distribution paths 00:38:46 — Team size, bootstrapping, and current company stage 00:40:39 — Ross outlines roadmap, buyer taxonomy, and MVP plans 00:42:15 — Scot and Darryl discuss adoption speed in agentic commerce 00:44:18 — Darryl’s theory on trust events and adoption 00:45:34 — Governance-by-design versus fixing broken outputs later 00:47:46 — Where to learn more and try the demo 👉 Connect with Darryl: https://www.linkedin.com/in/darrylcarlton/👉 Connect with Ross: https://www.linkedin.com/in/rossgardiner/👉 Check out the demo: https://vendeelabs.com/ 🧠 Want to stay ahead in AI commerce? Subscribe and follow along:📰 Subscribe to the free Substack: retailgentic.ai📺 Watch episodes on YouTube & Subscribe for updates: https://www.youtube.com/@Retailgentic

    50 min
  3. Exploring the Intersection of OpenClaw and Agentic Commerce:lobster: - the Retailgentic Podcast OpenClaw Deep Dive

    MAR 5

    Exploring the Intersection of OpenClaw and Agentic Commerce:lobster: - the Retailgentic Podcast OpenClaw Deep Dive

    In this episode of the top Agentic Commerce Podcast we explore the powerful shopping powers of the OpenClaw open-source agent. Can the Claw shop on Amazon, shop locally and use the VisionClaw system with META Ray-Ban’s to buy a very hard to search for dog treat? Tune in to find out! Highlights: What OpenClaw is (and why “persistent” changes everything)The real difference between OpenClaw vs. ChatGPT/Claude as toolsHow OpenClaw runs (Mac Mini vs. cloud VPS like DigitalOcean)Why “no guardrails” is both the innovation and the riskRisk mitigation: limiting blast radius with single-use virtual cardsWhy browser-driven commerce is riskier than server-to-server protocols (ACP/UCP)The “skills” layer: how OpenClaw becomes extensible like Lego bricksWhy SERP-style APIs beat slow webpage crawling for shopping tasksLive demos: product search, local inventory, and frictionless checkoutUsing Slack as the agent interface (channels for shopping, health, etc.)The sci-fi moment: Meta Ray-Ban glasses + VisionClaw + Gemini for visual shoppingOpenClaw isn’t the final answer for agentic commerce, security and architecture matter, but it is an incredible preview of where the UX is heading. If you want a glimpse of the “always-on shopping agent” future (and how people are hacking it together right now), this one’s for you. Happy agentic commerce.🦞 Timestamps: 01:38 — OpenClaw takeover begins: why Scot called Ryan as a lifeline 05:26 — What OpenClaw is: persistent agent, open source, “unhinged,” and why that matters 08:21 — The “gigantic loop”: always-on agent behavior (old-school “cron jobs,” new-school autonomy) 09:26 — The killer feature: OpenClaw keeps working after you close your laptop 12:33 — Read-only Gmail as an assistant: catching missed emails + reducing cognitive load 14:35 — The trap: spending time building automation to “save time” (catch-22) 15:33 — Why OpenClaw-style commerce is riskier than ACP/UCP: browser manipulation 18:02 — Gateway Dashboard tour: where OpenClaw is configured (channels, skills, cron jobs) 20:30 — Skill spotlight: Rye for agentic Amazon-friendly purchasing 22:39 — Skill spotlight: SERP API for faster product search + ratings without crawling 24:30 — Skill spotlight: Buy Anything for context-filled checkout (address, identity, card) 28:19 — Demo: “Find me the 5 best-rated 65-inch TVs” (online + local) 35:20 — Live purchase demo: finding USB-C cables, choosing Anker, and the agent checks out 37:05 — “Most frictionless checkout”: no login, agent already knows everything 37:31 — What this means for Alexa: why “available 24/7” changes habits 39:07 — Meta Glasses demo setup: first-person vision commerce  40:24 — Vision commerce in action: identifies product + searches best price automatically 41:34 — Multi-store results: Amazon + Chewy + Walmart links dropped into Slack 👉 Connect with Ryan: https://www.linkedin.com/in/ryaneade/ 🧠 Want to stay ahead in AI commerce? Subscribe and follow along:📰 Subscribe to the free Substack: retailgentic.ai📺 Watch episodes on YouTube & Subscribe for updates: https://www.youtube.com/@Retailgentic

    44 min
  4. Kiri Master's Round 2: The Ad Wars Come to Agentic Commerce

    FEB 26

    Kiri Master's Round 2: The Ad Wars Come to Agentic Commerce

    Retail media has been a profit engine for retailers, especially onsite sponsored product ads with massive margins. But what happens when shopping shifts from browsing and searching to AI agents that “decide the SKU” before a shopper ever hits a retailer site? In this episode, Scot and Kiri map the collision course between retail media networks and agentic commerce, walk through emerging ad formats from Google, Amazon (Rufus), and LLMs, and dig into the hardest problem of all: monetizing AI attention without breaking trust. What’s Covered: Why agentic shopping compresses the journey, and shrinks onsite ad inventoryThe “two threats” to onsite retail mediaHow offsite retail media depends on audience signals that may dry up as browsing declinesWhy in-store media may be the most resilient channel Google’s “Direct Offers,” the rise of an agentic storefront, and what it unlocksThe emerging idea of “Agentic PLAs” and retailers bidding at the SKU level (Buy Box vibes)Kiri’s wishlist: multimodal ads (video/try-ons), offsite audience extension, and contextual targeting over “creepy” behavioral retargetingAgentic commerce won’t kill advertising, but it will force it to evolve fast. The winners will be the platforms that can monetize attention without sacrificing trust, and the brands/retailers that learn to show up in these new surfaces early. Timestamps 00:05:04 — Meet Kiri Masters + Retail Media Breakfast Club00:08:01 — The three buckets: onsite, offsite, in-store retail media00:10:01 — Why onsite is the money machine (and most vulnerable)00:11:11 — Offsite retail media + closed-loop attribution00:14:23 — In-store media: small today, resilient tomorrow00:16:11 — Are retailers already seeing traffic shifts? Category matters00:19:27 — ChatGPT ads: early signals and why it’s still rudimentary00:21:22 — Scott’s framework: ad formats + Instant Checkout incentives00:23:06 — Google’s “Direct Offers” and the agentic storefront idea00:25:10 — Collaborative bidding: retailer + brand split the spend00:28:11 — Google testing new units: “Agentic PLA” / paid retailer placement00:33:14 — Trust vs monetization: don’t break the golden goose00:34:04 — Amazon Rufus: sponsored prompts as a new surface00:39:08 — Instacart’s ad playbook + trade dollars as inspiration00:40:38 — Why it’s not a race to the bottom: service layers + loyalty00:43:24 — The big hope: context-based targeting over creepy retargetingk00:46:52 — If Kiri ran ChatGPT ads: offsite + multimodal + new formats00:48:04 — Virtual try-ons + “throw away the sponsored product textbook”00:50:00 — Closing + follow Retailgentic👉 Connect with Kiri: https://www.linkedin.com/in/kiri-masters/👉 Learn more about Retail Media Breakfast Club: https://www.retailmediabreakfastclub.com 🧠 Want to stay ahead in AI commerce? Subscribe and follow along:📰 Subscribe to the free Substack: retailgentic.ai 📺 Watch episodes on YouTube & Subscribe for updates: https://www.youtube.com/@Retailgentic

    50 min
  5. True Fit Announces Agentic Commerce Agent To Solve the Fit/Sizing-Driven $850B Returns Crisis Facing Fashion Online Retailers

    FEB 17

    True Fit Announces Agentic Commerce Agent To Solve the Fit/Sizing-Driven $850B Returns Crisis Facing Fashion Online Retailers

    True Fit is evolving from a static “what size should I buy?” widget into a conversational agent that can handle the nuanced questions shoppers actually ask: comfort, flattering fit, fabric behavior, and edge cases like petite proportions. We also dig into how vertical agents (like True Fit) can accelerate horizontal super-agents via Model Context Protocol (MCP), and why the future of agentic shopping will be built on clean, structured, prioritized proprietary data, not scraped internet sentiment. Highlights True Fit’s specialized size + fit agent (and why it matters now)Why 70% of fashion agent questions are about size/fitThe “Fit Passport”: from form-filling to natural conversation profilingWhat generic agents miss: real-time sales + returns behavior, not just PDPs/reviewsVertical vs. horizontal agents, and how True Fit uses MCP as an accelerantThe unglamorous moat: data cleaning, normalization, canonicalizationTrue Fit scale: 80M active users, hundreds of millions of profiles, ~100K brands, ~500 retailersIf agentic commerce is collapsing the funnel, fit is one of the biggest friction points left, and True Fit is making it a first-class agent powered by the kind of data most models will never see. Timestamps 01:44 — Breaking news episode + guest intro (Jessica Murphy, True Fit) 03:12 — True Fit announces a specialized size + fit agent 04:20 — From static widget to agentic shopping assistant 05:47 — Why fit-related returns are so brutal in apparel 07:02 — What the agent experience looks like 08:05 — “Fit Passport” and conversational profiling 09:07 — Where checkout happens (and what’s coming later) 10:17 — Why generic agents break: stale info + limited context 11:35 — The moat: structuring + cleaning sizing data 12:30 — Vertical vs. horizontal agents 13:29 — MCP as an accelerant for super-agents 15:18 — Top-of-funnel value: narrowing choices to “most likely kept” 16:10 — Who might use TrueFit’s MCP (LLMs + agent builders) 16:37 — Availability: March partners, April target GA 18:01 — Founder story: why Jessica started True Fit 19:41 — Fundraising reality + “it’s a data problem” 21:16 — True Fit scale + global complexity of sizing 👉 Connect with Jessica: https://www.linkedin.com/in/jessica-murphy-68a8b8/👉 Learn more about True Fit: https://www.truefit.com/ 🧠 Want to stay ahead in AI commerce? Subscribe and follow along:📰 Subscribe to the free Substack: retailgentic.ai 📺 Watch episodes on YouTube & Subscribe for updates: https://www.youtube.com/@Retailgentic

    24 min
  6. Saurabh Vijayvergia & Brian McCarthy from Deloitte on Trust, Catalogs, and the Real Agentic Commerce Stack

    FEB 12

    Saurabh Vijayvergia & Brian McCarthy from Deloitte on Trust, Catalogs, and the Real Agentic Commerce Stack

    There’s a fundamental difference between adding AI to today’s ecommerce workflows and re-architecting commerce for an agent-driven world. In this episode, we start with Deloitte’s Agentic Commerce paper and quickly fan out into what’s changed since its release. If you’re trying to separate signal from noise in the rush toward AI-powered shopping, this conversation grounds Agentic Commerce in real systems, real economics, and real decisions retailers need to make now. Highlights  Why Agentic Commerce is a paradigm shift, not a bundle of AI featuresThe evolution from SEO → GEO → ACO, and why GEO is just a waypointThe two biggest misconceptions Deloitte is hearing from retailers and brandsWhy structured product + data catalogs are the no-regret investmentThe real question execs keep asking: Where do we start? (and what’s measurable)The “Acommerce ecosystem”: orchestrators + specialized “nano agents”Trust, security, returns, customer service, and why this can’t be a side projectForecasts for how big agentic commerce gets, and why the point is: it moves the needleAgentic commerce is becoming a new channel with new unit economics, and the brands and retailers that get their product truth, governance, and trust foundations right now will be the ones that win when agents become the default interface. Timestamps:01:54 — Meet Deloitte 02:10 — The paper: Agentic Commerce: Redefining Retail Economics 03:55 — ACO + the SEO/GEO conversation 04:11 — VJ’s background: SAP → Deloitte, retail AI intersection 05:50 — Brian’s background: supply chain → strategy → consulting 07:49 — “Traditional AI” vs GenAI in retail 09:38 — Why Deloitte wrote the paper (and why GEO isn’t the endpoint) 11:49 — Deloitte’s definition: why it’s a journey, not a switch 13:33 — NRF vibe check + what’s changed since December 14:27 — Common misconceptions (and what leaders miss end-to-end) 16:14 — The questions execs are asking: where to start + ROI 18:03 — Why this could be a golden age of storytelling + loyalty 21:06 — The no-regret starting point: catalogs + structured data 21:34 — Org design + governance + democratizing AI usage 23:15 — CFO-ready thinking: measuring value by channel 26:12 — Zero-click pressure + “what are you doing about it?” 28:31 — Balanced portfolio: fast wins vs complex upside 30:32 — The core distinction, again: AI add-ons vs agentic redesign 31:18 — Do we still need websites? (channels vs replacement) 33:17 — Deloitte’s role: advise, build, operate 37:29 — “Acommerce” + ecosystems of nano agents 41:31 — Protocols + UCP + what changes next 42:50 — Meta, OpenAI, Google: where this is headed 46:58 — 2030 forecasts: conservative vs aggressive cases 50:02 — Where to follow Saurabh's podcast: The Retail Tales 👉 Connect with Saurabh: https://www.linkedin.com/in/svijayvergia/👉 Connect with Brian: https://www.linkedin.com/in/briancmccarthy/👉 Learn more about Deloitte: https://www.deloitte.com/us/en.html Check out the materials we discuss: 🔗 Agentic Commerce: Redefining Retail Economic 🧠 Want to stay ahead in AI commerce? Subscribe and follow along:📰 Subscribe to the free Substack: retailgentic.ai 📺 Watch episodes on YouTube & Subscribe for updates: https://www.youtube.com/@Retailgentic

    51 min
  7. Sensor Tower SVP Ian Simpson breaks down Holiday ’25 funnel data, conversion lift, and what brands should do next.

    FEB 5

    Sensor Tower SVP Ian Simpson breaks down Holiday ’25 funnel data, conversion lift, and what brands should do next.

    In this episode, Scot digs into a question he keeps getting from readers and listeners: What’s actually going on inside Amazon’s Rufus, and what should brands do about it? Ian brings fresh analysis from Sensor Tower’s panel-based methodology (privacy-compliant, double opt-in), walking through Holiday ’25 shopping sessions to show where Rufus shows up in the funnel, how usage spikes during peak moments, and why it appears to correlate with dramatically higher conversion. Along the way, they zoom out to the bigger shift: as more people learn to “talk to AI” (thanks to ChatGPT-style habits), conversational shopping becomes increasingly normal, and increasingly hard to “optimize” using old keyword-era tactics. Highlights: “The consumer is trained.” A year of daily conversational AI use has taught people how to prompt, so when they see Amazon Rufus, they already know how to use it.Rufus sessions show a major conversion lift. In Ian’s read of the report: ~3.5× lift vs. non-Rufus sessions, with Rufus-touch sessions far more likely to end in purchase.Rufus had outsized influence during Holiday ’25. A large share of purchases included Rufus interaction, even if not every session did.Their team mapped ten distinct Rufus-assisted shopping paths, including the standout “Research Conversationalist” profile.Correlation vs causation is real. Ian flags measurement caveats: not every “non-Rufus session” is a shopping mission; intent bias exists; so the takeaway is directional, but meaningful.Brands should shift from “keyword jail” to “product truth.” Better attributes, clearer specs, stronger review signals, and real storytelling matter more in conversational shopping.AEO anxiety + the brand-level rebound. Ian argues the future isn’t just “optimize for prompts”, it may reward brands with stronger reputation and social proof signals (think forums and communities).AI can talk consumers out of premium. They’ve seen examples where AI steers price-sensitive users away from expensive brands, an early warning system for brand teams.Retail media won’t vanish, but it will mutate. In a lower-click world, retailers will experiment heavily to preserve value, without turning the experience into ad soup.If you’ve been treating Rufus like a curiosity, this data makes it hard to ignore: conversational commerce isn’t “coming”, it’s already shaping how high-intent shoppers decide. Timestamps: 00:00 – The Consumer Is Now Trained 02:09 – Why This Episode Focuses on Rufus 05:49 – Ian Simpson’s Background 06:47 – Founding a Bottled Tea Startup 09:14 – Pathmatics → Sensor Tower Acquisition 10:11 – How Retail Media Intelligence Was Born 13:50 – How Sensor Tower Delivers Its Data 15:36 – Why Sensor Tower Started Tracking Agentic Commerce 21:08 – How the Rufus Analysis Was Done 22:48 – The 3.5× Conversion Lift Explained 24:18 – Amazon’s $10B Rufus Claim vs. Independent Data 28:16 – Correlation vs. Causation in Rufus Usage 31:23 – Rufus as a Research Companion 32:20 – The Cup Holder Story (Problem-Based Shopping) 39:55 – Why Rufus Usage Sticks After the Holidays 40:19 – The 10 Rufus Shopping Profiles 41:35 – The “Research Conversationalist” Funnel 45:00 – Why “AEO” Makes Ian Nervous 46:47 – Brand Matters Again in Agentic Commerce 48:47 – When AI Talks Consumers Out of Premium Products 58:21 – Retail Media’s Future in a Low-Click World 01:01:31 – Avoiding the Minority Report Ad Nightmare 01:06:21 – Instacart: The Wild West of Retail Media 01:07:15 – Where to Follow Ian 👉 Connect with Ian: https://www.linkedin.com/in/iansimpson/👉 Learn more about Sensor Tower: https://sensortower.com Check out the materials we discuss: 🔗 Sensor Tower Black Friday AI Trend Update  🔗 How Amazon’s Rufus Shaped Holiday Shopping 🧠 Want to stay ahead in AI commerce? Subscribe and follow along:📰 Subscribe to the free Substack: retailgentic.ai 📺 Watch episodes on YouTube & Subscribe for updates: https://www.youtube.com/@Retailgentic

    1h 8m
  8. Ken Moore, Mastercard Chief Innovation Officer, on the Blueprint for Agentic Commerce: Trust, Tokens & “Know Your Agent”

    JAN 29

    Ken Moore, Mastercard Chief Innovation Officer, on the Blueprint for Agentic Commerce: Trust, Tokens & “Know Your Agent”

    In this episode of Retailgentic, Scot and Ken map out how Mastercard saw agentic commerce coming early, and what they built in 2025 to prepare the ecosystem, especially around trust, identity, consent, and tokenization. We dig into:  How Mastercard Foundry takes ideas from experiments → production-grade products → global scale“Know Your Agent”: registering legitimate agents (agentic equivalent of KYC/KYB) to reduce malicious bot risk“Order Intent”: adding richer context so that with consent, agents/merchants can fulfill the right order (not just process a payment)Why consumer consent is non-negotiable (passkeys/biometrics + tokenized credentials)Mastercard Insight Tokens: a secure and governed way for agents to access and apply permissioned insights from Mastercard, which will enable consumers to receive, with their consent, more personalized and useful experiencesAgentic Toolkit and why Mastercard leaned into services to support customers move from strategy → execution fastMastercard’s Agent Pay Acceptance Framework: helps merchants totransact with trusted agents with a minimal liftStandards: why Mastercard will support ACP + AP2 and expects interoperability (or convergence) over timeAgentic commerce won’t be won by whoever moves fastest, it’ll be won by whoever earns trust at scale. Key timestamps 05:14 — Ken’s background: technologist, global banking work, startups, Accenture, Citi → Mastercard Foundry07:44 — How Foundry works: experiment, build, then “graduate” products into core teams10:32 — The pace-of-change thesis: why organizations must be built to adapt continuously13:07 — How Mastercard saw agentic commerce early (signal-spotting in 2024)14:23 — The 3 converging forces: AI reasoning, compute, and foundations (tokens/passkeys/consent)19:01 — AgentPay launch + what it includes (Know Your Agent, Order Intent)21:05 — Consumer consent, passkeys/biometrics, and tokenizing payment credentials22:25 — First agentic transaction (partner example)23:19 — Agentic Toolkit + Insight Tokens + consulting expansion26:00 — Merchant Acceptance Framework + scaling agentic readiness for the “long tail” of merchants27:13 — Tokenization explained simply (cocktail-party version)29:37 — Passkeys explained (biometric identity replacing passwords)33:37 — Returns problem + how agentic workflows could reduce “buy 3, return 2”40:19 — Standards wars: ACP vs AP2 + why Mastercard stays agnostic44:03 — Crystal ball: adoption, trust, and why B2B may go autonomous faster47:43 — The travel agent analogy: why some flows stay assisted by choice👉 Connect with Ken: https://www.linkedin.com/in/ken-moore-cio/👉 Learn more about Mastercard: https://www.mastercard.com/us/en.html 🔗 Agentic Toolkit: https://www.mastercard.com/us/en/news-and-trends/press/2025/september/mastercard-unveils-new-tools-and-collaborations-to-power-smarter,-safer-agentic-commerce.html🔗Agentic Commerce Rules, Mastercard Joins Google: https://www.mastercard.com/us/en/news-and-trends/stories/2026/agentic-commerce-rules-of-the-road.html🔗Agent Suite: https://www.mastercard.com/us/en/news-and-trends/press/2026/january/mastercard-launches-agent-suite-to-ready-enterprises-for-a-new-e.html 🧠 Want to stay ahead in AI commerce? Subscribe and follow along:📰 Subscribe to the free Substack: retailgentic.ai 📺 Watch episodes on YouTube & Subscribe for updates 🎧 Listen wherever you get your podcasts: Spotify, Apple, etc: https://retailgentic.transistor.fm

    49 min
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5
out of 5
7 Ratings

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Retailgentic is the podcast where Agentic Commerce meets retail innovation. We help retailers and brands prepare for the future of agent-driven shopping with actionable news, expert insights, deep analysis, and forward-looking predictions.

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