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

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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

🧠 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

Consumer behavior is already shifting, people are asking LLMs what to buy, building shopping lists in chat, and moving through commerce in new ways. In this episode of Retailgenic, Scot sits down with Maia to unpack what “agentic commerce” actually means, why Stripe is moving fast, and what merchants can do now to get ready for checkout inside AI experiences. 

They discuss:

• Why agentic commerce is a spectrum: fully autonomous agents vs. AI-assisted buying inside chat interfaces
• Stripe’s four AI focus areas (and why agentic commerce is only one bucket)
• The big initiatives driving Stripe’s agentic push
• What Copilot Checkout looks like in practice: Stripe-powered checkout embedded natively in chat
• How Stripe is approaching merchant control and merchant-of-record requirements
• How product discoverability works today (feeds + syndicator integrations) vs. the longer-term self-serve vision
• What merchants are asking for most: fraud, trust, identity, and governance in an agent-led world
• The “why now” moment: traffic shifts, zero-click pressure, and board-level attention accelerating experiments

Agentic commerce is no longer theoretical, it’s becoming a real channel. The winners will be the merchants who make their catalogs discoverable, keep control of checkout, and build trust and fraud defenses for an AI-led future.

Notable Timestamps
02:06 – Scot introduces Maia, AI CRO at Stripe
04:07 – Maia’s background: e-commerce founder → LivingSocial → Stripe
06:54 – Stripe’s 4 AI buckets (infrastructure, AI across payments, dev tools, agentic commerce)
09:22 – The “agentic commerce is a mirage” debate + definition confusion
10:43 – Maia’s spectrum definition: autonomous vs. chat-native buying
14:40 – Copilot Checkout: what it is, how Stripe fits, and where to sign up (waitlist)
18:15 – Agentic Commerce Suite: discoverability, checkout/fraud, choosing agents in dashboard
20:04 – How products become discoverable: direct feed vs. syndicators + onboarding reality today
21:15 – Shared Payment Tokens (SPTs): secure handoff + merchant-of-record control
24:05 – Merchant sentiment shift: from skepticism → exec sponsors + resources dedicated
29:37 – Fraud + trust layer: Radar expansion, Link wallet, and SPT fraud signals
31:58 – 2030 sizing: Stripe won’t pick a %, but “this is happening”
33:07 – Where to follow Maia/Stripe + NRF context

👉 Connect with Maia: https://www.linkedin.com/in/maiaj/
👉 Connect with Scot: https://www.linkedin.com/in/thescotwingo/
👉 Learn more about Stripe: https://stripe.com/payments/ai

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This week on the retailgentic podcast, we have an experiment for you. NRF concluded Tuesday Jan 13th and Scot's good friend and podcast partner over at the Jason and Scot show, Jason Goldberg (Chief Digital Commerce Officer at Publicis) was invited to ‘tie the bow’ on the conference in the last keynote: Commerce Disrupted: Rise of the AI Native Consumer.

This episode is the audio from that presentation on 1/13/26. Jason covers:

• Agentic commerce, defined clearly: not “AI efficiencies,” but new consumer behaviors (and the full “iceberg” of influence, not just robot-takes-card transactions).
• Is it hype or historic? Jason frames the debate (skeptics vs believers) and uses live audience polling to set the stakes.
• A disruption of discovery: the decline of “saw in store,” then “search,” then “social”, and now the robot becomes the front door.
• The cautionary tale (Tudor Ice): why incumbents often miss the next business model, even when they dominated the last one.
• Retail growth is concentrated: a few giants capture a huge share of growth, while challengers (Shein/Temu/TikTok Shop) rewrite the playbook.
• AI shopping ramps fast: from research → to product tiles → to direct purchase inside AI experiences, plus retailer catalogs moving upstream.
• 0-click commerce: the next leap isn’t fewer clicks, it’s no clicks (automation, replenishment, “never let me run out”).
• Onsite vs offsite agents: retailers’ on-site assistants (ex: Amazon) vs consumers using neutral offsite agents that choose the retailer for them.
• Winning the robots: why optimization shifts toward what models care about (criteria, sources, “GEO/AEO/ACO”), and why this changes constantly.
• Change management wins: Doug McMillon’s “How did you use AI to prepare?” as a culture lever—and why org adoption matters as much as tech.

If AI changes the way people discover, it changes everything downstream. Brands, retailers, and platforms all have to learn to win the robot’s shelf.

Notable timestamps 

• 00:00 — The real disruption: new consumer behavior, not efficiency gains
• 01:43 — Scott sets up the “special episode” + NRF context
• 03:17 — The experiment: “put you in the audience” (keynote replay)
• 06:29 — The big questions: how big is agentic commerce + who wins?
• 08:07 — Skeptics vs believers: “hallucination” vs “overhyped” vs transformational
• 11:05 — Defining agentic commerce + the “influence vs transaction” iceberg
• 15:07 — Tudor Ice story: disruption, incumbents, and missing the next model
• 19:14 — $5.3T retail + who captured the growth (concentration)
• 22:16 — “Disruption of discovery”: saw-in-store → search → social
• 25:04 — Viral demand shock example (whipped coffee)
• 26:53 — Sunscreen example + TikTok → then “ask the robot”
• 29:08 — “How fast this changed” (recent launches + ecosystem momentum)
• 30:19 — From “order” to “never let me run out” (automation framing)
• 31:11 — Clicks: 22 → 4 → “one-click” → 0-click
• 32:40 — Proof points: agent assistants and rising adoption
• 33:49 — Offsite agents: buying without choosing a retailer first
• 34:03 — In-store: pointing ChatGPT at the shelf (real-world agent use)
• 36:29 — Scale math: small % of prompts can still be massive volume
• 38:34 — Robots optimize differently + why brands need new processes/tools
• 39:36 — GEO/AEO vs the bigger strategic layer (Agentic Commerce Optimization)
• 40:33 — Doug McMillon’s culture lever: “How did you use AI to prepare?”
• 42:12 — Final message: change management to avoid being the “ice harvesters”

👉 Connect with Jason: https://www.linkedin.com/in/jasongoldberg/
👉 Connect with Scot: https://www.linkedin.com/in/thescotwingo/
👉 See the slides: https://open.substack.com/pub/scotwingorefibuy/p/jason-goldbergs-full-nrf-keynote

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Today we have a special FLASH episode - no fancy intros, just the news as it's breaking at NRF.

Consumer behavior doesn’t change overnight, even when the technology is obvious. In this episode of Retailgentic, Scot sits down with Hamish Gunasekara to unpack why agentic commerce is inevitable, why it’s moving slower than the hype suggests, and why product data infrastructure, not checkout, is the real unlock.

We cover:

• Why “fully autonomous shopping” is the wrong definition of agentic commerce
• Why consumer habits change slower than technology
• Why global mega-catalogs don’t work (and never really have)
• How vertical AI shopping experiences can thrive alongside ChatGPT
• The hidden trust and governance problem no one is talking about
• Why product catalogs are the hardest unsolved problem in commerce

If you’re a retailer, brand, agent builder, or investor trying to understand what actually matters in the agentic commerce stack, this episode is foundational.

Timestamps:
02:39 Meet Hamish & the origin of Catalog
04:55 From Afterpay to Cash App Commerce
11:30 The Naya experiment & lessons learned
14:24 How AI is changing discovery
16:08 Why catalog data is broken
18:30 Fundraising & early traction
20:48 Who Catalog is built for
23:20 Why global catalogs don’t work
28:30 The agentic commerce stack
33:40 Defining agentic commerce (correctly)
37:30 Why vertical agents will win
43:45 Trust, governance, and adoption
44:51 Where to learn more

👉 Connect with Hamish: https://www.linkedin.com/in/hamish-gunasekara/
👉 Learn more about Catalog: https://getcatalog.ai/

🧠 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

Matt Nichols is back, and a lot has changed since his first appearance on Retailgentic. Scot and Matt revisit the predictions he made six months ago, look at what came true far faster than expected, and dig into the infrastructure challenges that still stand between us and frictionless agentic transactions. From SKU mapping and API-first checkout to the economics of feeds and the future of retailer traffic, this episode is a full-stack view of where Agentic Commerce stands at the end of 2025, and what’s coming in 2026.

If you want more of Matt’s backstory and Commerce Ventures’ thesis, listen to Episode 4! It pairs perfectly with this deep dive. In this episode, they cover: 

• Why VC predictions used to take 5–10 years to play out… and now take 5–10 weeks
• What Commerce Ventures is hearing from both startups and their LP base (top retailers + PSPs)
• Why ACP isn’t “the solution”—and what infrastructure still needs to be built
• The “API vs. fake-it-til-you-make-it” debate in agentic transactions
• How retailers should think about feeds, reviews, and blocking scrapers
• Why “AI magic on your own site” is step one for most brands
• Predictions for 2026: traffic shifts, wallet battles, Apple’s eventual entry, and more
• Where Matt thinks the industry is overly optimistic, and where the real upside is

If this year taught us anything, it’s that the next six months will change more than the last six years. Stay tuned.

Timestamps
05:00 — Welcome back, Matt Nichols
05:10 — Six months later, the world looks different
05:35 — Commerce Ventures in 60 seconds
06:30 — What changed in 2025?
08:00 — Standards vs. infrastructure
10:00 — Retailers’ three priorities right now
12:40 — Static feeds → AI-centric feeds
15:00 — Reviews, Q&A, and proprietary data
17:30 — SKU-level identifiers
20:00 — API-first checkout vs. agentic scraping
22:30 — Fraud, agent authentication & whitelisting
24:00 — Payments are further ahead than commerce infrastructure
27:00 — What retailers are actually worried about
30:00 — Google’s role in accelerating the shift
32:00 — Vertical agents vs. horizontal giants
34:00 — Predictions for 2026 & beyond
38:00 — Final reflections

👉 Connect with Matt: https://www.linkedin.com/in/matthewnichols/
👉 Learn more about Commerce Ventures: https://commerce.vc/

🧠 Want to stay ahead in AI commerce? Subscribe and follow along:
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📺 Watch episodes on YouTube & Subscribe for updates 
🎧 Listen wherever you get your podcasts: Spotify, Apple, etc: https://retailgentic.transistor.fm

In this episode of Retailgentic, Scot sits down with Luca to unpack a research paper that blends academic rigor with real-world implications:
“LLMs Reproduce Human Purchase Intent via Semantic Similarity licitation of Likert Ratings.”

The paper, co-authored with Colgate-Palmolive researchers, explores whether AI can accurately simulate human reactions to product concepts, enough to replace or accelerate traditional consumer panels, which are slow, expensive, and hard to scale.

This one goes deep, but in ways that any retail or AI leader should care about. Scot and Luca discuss:

• Colgate’s Challenge: How to test product concepts faster and at scale.
• Synthetic Consumers: AI models that react to products like human panels.
• Accuracy Breakthrough: Reaching ~73–74% agreement with real consumers.
• Fixing LLM Failure Modes: Why naive prompts don’t work, and what does.
• Bayesian Reasoning: Adding uncertainty so AI stops being confidently wrong.
• Smarter A/B Testing: Using AI to pre-screen ideas before running live experiments.
• Digital Clones: Future consumers earning money by sharing preference data safely.
• Simulated Populations: Matching real audiences for testing and predictions.

AI isn’t just helping brands write copy or generate images, it’s beginning to think like their customers. If synthetic consumers continue to evolve at this pace, product development, A/B testing, and personalization may look completely different in just a few years.

Timestamps:
03:00 — Luca’s background: Rocket Internet, HelloFresh, Lazada, Stitch Fix
08:00 — How PyMC Labs was founded & why Bayesian modeling matters
16:00 — Bayesian thinking explained in simple terms
19:00 — High-stakes decisions & why probabilistic reasoning matters
24:00 — Colgate’s challenge: testing product concepts at scale
26:00 — How synthetic consumer panels work
30:00 — Accuracy results: humans vs. AI (~73–74%)
32:00 — Why naive LLM prompting fails (“mode collapse”)
35:00 — How reasoning → scoring solves accuracy issues
38:00 — Example: synthetic consumers evaluating PyMC’s own website redesign
44:00 — How AI can pre-screen ideas for smarter A/B testing
48:00 — Where AI cannot replace causal testing
49:00 — Digital clones & monetizable consumer preferences
52:00 — Future benchmarks, new LLMs & evaluation methods

👉 Connect with Luca: https://www.linkedin.com/in/lfiaschi/
👉 Learn more about PyMC Labs: https://www.pymc-labs.com
👉 Check out the paper: https://arxiv.org/pdf/2510.08338

🧠 Want to stay ahead in AI commerce? Subscribe and follow along:
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#Retailgentic #AgenticCommerce #SyntheticConsumers #AIShopping #ProductTesting #CPGInnovation #GenerativeAI #BayesianModeling #Ecommerce #FutureOfRetail #DataScience #LLMs #AIResearch

In this episode of Retailgentic, host Scot sits down with Mike Edmonds, PayPal’s VP of Agentic Commerce & Commercial Growth, to unpack the massive pivot PayPal has made into the Agentic Commerce era, and what it means for retailers, brands, platforms, and developers.

Mike goes deep on:

• PayPal’s Agentic Bet: Why PayPal is going all-in on Agentic Commerce
• Merchant Anxiety, Explained: The real reason so many merchants are anxious about LLMs
• Instant Checkout 2.0: Where PayPal sees Instant Checkout heading next
• Wallets as Identity: Why wallet identity will matter more than ever
• 2030 Predictions: Mike’s bold predictions for shopping agents in 2030
• Two-Track Future: A world split between autonomous commerce and luxury human-led experiences
• Protocol Chaos Simplified: How PayPal plans to tame and unify an explosion of competing protocols
• Merchant of Record Relief: The surprising emotional fear merchants have about disintermediation

As AI agents reshape discovery, checkout, and trust, PayPal is building the rails for the future of digital commerce.

Key Timestamps:
02:15 — Mike introduces his background.
04:45 — How Mike’s career path led directly into PayPal’s Agentic Commerce leadership role.
06:20 — What “VP of Agentic Commerce & Commercial Growth” really means at PayPal.
07:48 — The biggest lessons Mike learned leading AI strategy at Microsoft.
10:35 — What merchants are actually thinking about Agentic Commerce (the real pulse).
12:18 — Mike explains the off-surface vs on-surface Agentic Commerce model.
13:10 — Why merchants feel overwhelmed by LLMs, APIs, and protocol sprawl.
14:47 — PayPal’s role as the one-to-many connector across LLMs and platforms.
16:06 — What technical pieces merchants need in place to integrate Agentic checkout.
17:45 — How on-surface conversational agents can finally boost conversion rates.
19:30 — Why conversational checkout is the missing piece in Agentic shopping.
20:55 — What the Perplexity partnership enables for checkout, payments, and reach.
23:30 — How PayPal is powering ChatGPT Instant Checkout and expanding ACP.
26:12 — Why Agentic protocols are diverging, and how PayPal navigates the chaos.
28:30 — The emotional fear merchants have of LLMs.
30:05 — Mike’s 2030 prediction
31:40 — Why some categories will automate, while luxury experiences stay human.
33:10 — Multimodal will reshape shopping through voice, gestures, and identity.
35:00 — The top concerns merchants raise in every PayPal Agentic conversation.
37:05 — Where to find Mike and what PayPal has coming next.

Announcements & press releases related to the conversations:

• Perplexity: https://newsroom.paypal-corp.com/2025-05-14-Perplexity-Selects-PayPal-to-Power-Agentic-Commerce
• Google (commerce agent for merchants: https://cloud.google.com/blog/topics/financial-services/introducing-an-agentic-commerce-solution-for-merchants-from-paypal-and-google-cloud
• OpenAI: https://newsroom.paypal-corp.com/2025-10-28-OpenAI-and-PayPal-Team-Up-to-Power-Instant-Checkout-and-Agentic-Commerce-in-ChatGPT
• AP2: https://developer.paypal.com/community/blog/PayPal-Agent-Payments-Protocol/ and https://cloud.google.com/blog/products/ai-machine-learning/announcing-agents-to-payments-ap2-protocol
• PayPal’s Agentic Commerce Services: https://newsroom.paypal-corp.com/2025-10-28-PayPal-Launches-Agentic-Commerce-Services-to-Power-AI-Driven-Shopping

👉 Connect with Mike: https://www.linkedin.com/in/michaeledmonds/
👉 Learn more about PayPal: https://www.paypal.com/us/home

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In this episode of the Retailgentic Podcast, Scot talks with Stu Solomon, CEO of HUMAN Security, the company analyzing 20+ trillion digital interactions every week to detect bots, fraud, and now agentic AI behavior. Stu breaks down:

• Why bots now exceed human traffic
• The 1300% growth in agentic activity
• How HUMAN identifies good vs. bad bots
• The rise of agentic logins, navigation, and even checkouts
• Why spoofing of ChatGPT and Perplexity traffic is exploding
• What retailers need to know about letting AI agents crawl their sites
• The coming world of agent-to-agent commerce

If you’re preparing for the future of retail, ad tech, AI commerce, or online security, this is essential listening.

Timestamps
02:20 — What HUMAN actually measures (bot vs human vs agentic)
03:40 — Stu’s background (military → Amazon → banking → VC → CEO)
06:40 — The logistics + retail connection
09:00 — How HUMAN works: media + enterprise security
11:00 — The digital journey from ad → login → checkout
12:11 — HUMAN at 20 trillion interactions/week
16:55 — Why HUMAN started publishing agentic data
17:50 — 1300% growth in agentic activity
18:30 — Machine traffic surpasses human traffic
19:40 — The diversification of generative AI traffic
20:30 — Agentic login + website navigation behavior
24:00 — How HUMAN distinguishes bot vs agent vs human
33:00 — The bad side: spoofed ChatGPT & Perplexity traffic
38:30 — Retailers blocking bots without realizing it
47:00 — The inevitability of agentic adoption
48:40 — The future: agent-to-agent transactions
49:30 — The end of 2FA hell?

👉 Connect with Stu: https://www.linkedin.com/in/stu-solomon-733a217/
👉 Learn more about HUMAN: https://www.humansecurity.com/

🧠 Want to stay ahead in AI commerce? Subscribe and follow along:
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