In this episode, Scot sits down with Debra to unpack what might be the most important shift in digital advertising since social media.

This isn’t theoretical. It’s happening right now, and brands that don’t understand it risk getting left out of the new chain of commerce.

Highlights 

• Why ChatGPT’s ad rollout is just the beginning, not an experiment
• The tension between trust vs. monetization in AI interfaces
• How retailers are both excited and terrified of AI shopping agents
• The emergence of “AI Media” as a new category (like social + retail media before it)
• Why current ad formats are “boring”… and what comes next
• How companies should actually prepare (hint: it’s not just media buying)
• The shift from advertising to agent influence, and what that means for the future

We’re still early, but not that early. The rules of digital advertising are being rewritten in real time, and for the first time in decades, the winners aren’t obvious. The question isn’t whether AI will reshape commerce. It’s whether your products, and your data, are ready to compete when agents decide what gets bought.

Timestamps:

 02:19 – Meet Debra Aho Williamson 

 05:00 – From social media to AI: spotting the next shift 

 09:00 – What “AI Ad Economy” actually means 

 11:00 – Are we at a social media–level inflection point? 

 13:00 – ChatGPT ads: early signals and what matters 

 16:00 – Why current AI ads look like search ads 

 18:00 – Trust vs. monetization: the line platforms can’t cross 

 23:00 – Why retailers are leading AI ad adoption 

 25:00 – Google’s AI ad strategy vs. ChatGPT 

 29:00 – Perplexity, Copilot, and the fragmented landscape 

 33:00 – Where Meta fits (and why it’s surprising) 

 35:00 – New ad formats: sponsored prompts + conversational ads 

 38:00 – Reddit, TikTok, and emerging players 

 40:00 – How brands should prepare for AI media 

 43:00 – Why structured product data is critical 

 45:00 – The future: ads for agents, not humans

👉 Connect with Debra: https://www.linkedin.com/in/debrawilliamson/
👉 Learn more about Sonata Insights: https://www.sonatainsights.com/

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Today we’re dropping a surprise podcast that is different than anything we’ve done before and a first of it’s kind! Scot Wingo was invited by Ben Miller, VP of Content and Strategy to participate in the first ever shoptalk debate format talk. The topic - Agentic Commerce Will AI agents transform retail?

On the pro agentic side we had Ekta Chopin, CDO at ELF Beauty and myself.  If you’re not familiar with Ekta, she’s a thought leading CDO and has a great substack for other CDOs.

On the ‘anti agentic side’ we had Sarah Marzano, Principal Analyst, Retail Ecommerce and Retail Media at Emarketer and Andrew Lipsman - independent analyst and consultant for media, ads and commerce.

Before the show, Scot asked and received permission from Shoptalk and all the participants to turn the raw audio into a podcast. In the AI era, speed matters so we are getting this in your hands only 2 days after it happened.

This debate took place at 12pm PDT on Tuesday March 24th at Shoptalk’s AI Stage.

Timestamps
00:01 – Why this episode is different from anything Retailgentic has done before
01:28 – The Shoptalk debate topic: Will AI Agents Transform Retail?
02:04 – Meet the debaters: Ekta Chopra, Andrew Lipsman, and Sarah Marzano
07:48 – The first big battle: how should agentic commerce be defined?
10:25 – Scot’s argument: consumers are already changing behavior faster than many retailers realize
13:16 – Sarah’s pushback: brands need clarity before making big bets
15:18 – Consumer adoption: how much automation will shoppers really accept?
17:16 – Why product data and offer-card visibility matter now
19:05 – Andrew’s argument: shopping still requires human decision-making
23:05 – Ekta on brand visibility, content readiness, and why this matters for beauty
24:49 – 2030 predictions: will 10% of e-commerce be bot-to-bot?
27:03 – Does agentic commerce threaten retail media?
29:11 – Sarah’s case for why AI referrals may actually help retailers
32:22 – Ekta on why rich product data matters more than media for e.l.f.
33:06 – Scot’s case that traffic decline is already starting in some categories
37:16 – What brands and retailers should do over the next 6–18 months
40:25 – Why Sarah says brands should test, but not overreact
42:11 – Scot’s closing case for why this shift is fundamentally different
43:22 – Andrew’s closing warning against fear-based decision-making

🧠 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

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 commerce
• Why UCP emerged now, and the two major trends that inspired it
• Why Google believes agentic commerce needs an open, ecosystem-wide standard
• Why the future of UCP extends far beyond checkout
• How discovery is starting to take shape within the protocol
• Why richer, more conversational product data matters in AI shopping experiences
• What retailers need to do now to improve visibility on AI surfaces
• How Google is thinking about the relationship between agentic commerce and advertising
• Why agentic commerce is still early, but already moving from concept to reality

Agentic 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.

Timestamps
2:32 — 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:
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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 perspective
• The founding story behind the company and the friction that inspired it
• How ChatGPT and Claude changed the direction of the product
• A live demo of conversational commerce across real merchants
• What a multi-vendor, multi-item ACP checkout could mean for online shopping
• Why autonomous commerce needs legal and governance frameworks, not just AI
• The vision for a Universal Protocol Bridge across ACP, UCP, and future standards
• How strong permissions and audit trails could reduce chargebacks and disputes
• Why poor product data creates broken outcomes in agentic shopping
• Where Vendee Labs sees opportunity across consumer, B2B, procurement, and white-label use cases

Vendee 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:
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📺 Watch episodes on YouTube & Subscribe for updates: https://www.youtube.com/@Retailgentic

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 tools
• How OpenClaw runs (Mac Mini vs. cloud VPS like DigitalOcean)
• Why “no guardrails” is both the innovation and the risk
• Risk mitigation: limiting blast radius with single-use virtual cards
• Why browser-driven commerce is riskier than server-to-server protocols (ACP/UCP)
• The “skills” layer: how OpenClaw becomes extensible like Lego bricks
• Why SERP-style APIs beat slow webpage crawling for shopping tasks
• Live demos: product search, local inventory, and frictionless checkout
• Using Slack as the agent interface (channels for shopping, health, etc.)
• The sci-fi moment: Meta Ray-Ban glasses + VisionClaw + Gemini for visual shopping

OpenClaw 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/

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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 inventory
• The “two threats” to onsite retail media
• How offsite retail media depends on audience signals that may dry up as browsing declines
• Why in-store media may be the most resilient channel 
• Google’s “Direct Offers,” the rise of an agentic storefront, and what it unlocks
• The 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 retargeting

Agentic 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 Club
• 00:08:01 — The three buckets: onsite, offsite, in-store retail media
• 00:10:01 — Why onsite is the money machine (and most vulnerable)
• 00:11:11 — Offsite retail media + closed-loop attribution
• 00:14:23 — In-store media: small today, resilient tomorrow
• 00:16:11 — Are retailers already seeing traffic shifts? Category matters
• 00:19:27 — ChatGPT ads: early signals and why it’s still rudimentary
• 00:21:22 — Scott’s framework: ad formats + Instant Checkout incentives
• 00:23:06 — Google’s “Direct Offers” and the agentic storefront idea
• 00:25:10 — Collaborative bidding: retailer + brand split the spend
• 00:28:11 — Google testing new units: “Agentic PLA” / paid retailer placement
• 00:33:14 — Trust vs monetization: don’t break the golden goose
• 00:34:04 — Amazon Rufus: sponsored prompts as a new surface
• 00:39:08 — Instacart’s ad playbook + trade dollars as inspiration
• 00:40:38 — Why it’s not a race to the bottom: service layers + loyalty
• 00:43:24 — The big hope: context-based targeting over creepy retargeting
• k00:46:52 — If Kiri ran ChatGPT ads: offsite + multimodal + new formats
• 00:48:04 — 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:
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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/fit
• The “Fit Passport”: from form-filling to natural conversation profiling
• What generic agents miss: real-time sales + returns behavior, not just PDPs/reviews
• Vertical vs. horizontal agents, and how True Fit uses MCP as an accelerant
• The unglamorous moat: data cleaning, normalization, canonicalization
• True Fit scale: 80M active users, hundreds of millions of profiles, ~100K brands, ~500 retailers

If 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/

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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 features
• The evolution from SEO → GEO → ACO, and why GEO is just a waypoint
• The two biggest misconceptions Deloitte is hearing from retailers and brands
• Why structured product + data catalogs are the no-regret investment
• The 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 project
• Forecasts for how big agentic commerce gets, and why the point is: it moves the needle

Agentic 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

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

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 experiences
• Agentic Toolkit and why Mastercard leaned into services to support customers move from strategy → execution fast
• Mastercard’s Agent Pay Acceptance Framework: helps merchants to
• transact with trusted agents with a minimal lift
• Standards: why Mastercard will support ACP + AP2 and expects interoperability (or convergence) over time

Agentic 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 Foundry
• 07:44 — How Foundry works: experiment, build, then “graduate” products into core teams
• 10:32 — The pace-of-change thesis: why organizations must be built to adapt continuously
• 13:07 — 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 credentials
• 22:25 — First agentic transaction (partner example)
• 23:19 — Agentic Toolkit + Insight Tokens + consulting expansion
• 26:00 — Merchant Acceptance Framework + scaling agentic readiness for the “long tail” of merchants
• 27:13 — 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 agnostic
• 44:03 — Crystal ball: adoption, trust, and why B2B may go autonomous faster
• 47:43 — 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

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