Marketecture Podcast Episode 161: The State of AI with eMarketer’s Nate Elliott

Date: February 20, 2026
Host: Ari Paparo (A), with Eric Franchi (C)
Guest: Nate Elliott (D), Principal Analyst and Head of AI Research at eMarketer

Overview

In this episode, Ari Paparo and Eric Franchi dive deep with Nate Elliott, eMarketer’s head of AI research, on the rapidly evolving role of AI in marketing, advertising, and commerce. Drawing from 20+ years of digital marketing experience, including stints at DoubleClick and Forrester, Nate provides nuanced, sometimes skeptical, and always data-conscious perspectives on how AI is shaping both consumer behavior and enterprise marketing strategies. The conversation covers consumer adoption curves, the confusion in AI terminology, how AI is (and isn't) influencing buying decisions, the threats and opportunities for publishers, the state of “AEO” (AI Engine Optimization), and the real risks/realities for martech and ad tech.

Key Discussion Points & Insights

[05:17] Getting to Know Nate Elliott and His Perspective

• Nate joined eMarketer six months ago, after a long career in digital research and consulting.
• Leads eMarketer’s coverage on how “AI is changing marketing, advertising, and commerce.”
• Jokingly described his job as “trying to sort through all the confusing data on AI” (07:02).
  • Quote: “There is so much bad data that leads to bad insight and bad recommendations... If you guessed a number between 0 and 100 in terms of how many people use AI, I could find a study to back you up.” – Nate Elliott [08:47]

[10:31] AI Taxonomy: Why the Term ‘AI’ Is Increasingly Meaningless

• The hosts and guest agree that “AI” encompasses a vast range of technologies and use cases, leading to constant crossed wires in industry conversations.
• Nate’s Take: It’s his job now to play “taxonomy cop” to help bring seriousness and specificity to discussions.
  • Distinctions include “AI for productivity” (employee tools), enterprise-level AI (efficiency/effectiveness), and AI-powered products.
  • Quote: “We use these two letters [AI] as a monolith... In practice, these are worlds apart.” – Nate Elliott [11:27]
• Joking that “asking the AI to create the taxonomy” might soon be the industry’s solution.

[12:22] Consumer Adoption: Are We All AI Users Now?

• Passive vs. Active Use: The distinction between involuntarily using AI (everyone, via Google/Netflix/feeds) versus seeking it out (like ChatGPT).
  • Only a minority are “active” users—roughly 15-20% of US online users engage weekly with tools like ChatGPT (15:03).
  • “100% of people use AI whether they know it or not” (15:44); but fundamental behavior change is more limited.

[14:10] Google’s Messy AI Branding and Measurement Issues

• Google’s “branding mess” with overlapping products and unclear statistics creates further confusion about real adoption and value.
• Microsoft’s “Copilot” brand praised as more coherent.

[16:13] Agentic AI and Shopping: Is Anyone Really Buying?

• True agentic transactions (“buying via ChatGPT”) are minuscule—forecasted to be << 1% of e-commerce even by 2026.
• Influence is much broader, but hard to measure: if you count every AI-powered recommendation, you can claim 100% of online shopping is “influenced by AI.”
• eMarketer’s approach: Measures only direct prompt-to-purchase in the same session for clarity.

[19:47] AI-Driven Discovery, “AEO,” and the Marketer’s Dilemma

• Marketers are extremely concerned about being included in chatbot/AI answers (“AI Engine Optimization”/AEO).
• The parallel with SEO in the late ‘90s: “It was a disaster, because we didn’t know anything... The reckoning that happened in SEO is going to come to AEO, too.” – Nate Elliott [20:37]
• Wild West tactics abound, reminiscent of early SEO “gaming the engines.”
• Quote: “We still don’t know if we can accurately measure how often these things are mentioning different products.” – Nate Elliott [21:26]

[22:01] Paid Media, Measurement, and the Hope for Better Data

• The promise of ad platforms for AI engines: not because of ads per se, but for the keyword tools and campaign planning data that would benefit both paid and organic optimization.
• Quote: “I’m really excited about ads in AI engines...hoping that the AI platforms that sell ads will start to offer the same kind of keyword planning tools that search engines have offered for decades.” – Nate Elliott [22:16]

[23:20] What Are CMOs and Agencies Actually Doing with AI?

• CMOs focus on basic AEO and increasing team productivity rather than much else.
• Agencies are fixated on AI as both threat and tool; incentive to automate what they do before clients or competitors do for them.
• Huge tension: Real adoption is slowly incremental, despite bombastic headlines about “the SaaS apocalypse” or “95% of marketing” being automated.
• Machine learning already underpins martech and adtech tools; what’s new is language, not fundamental capability—“more evolution than revolution” (24:48).
• Quote: “Saying that 95% of marketing will be AI is just nonsensical to me.” – Nate Elliott [29:06]

[27:26] AI's Impact on Workforce and Tools

• Many managers and CEOs hope for cost savings from AI tools, but will likely face significant “upheaval” before realizing actual business change.
  • “You need people to tell the tools what to do. At least at this point.”

[31:07] Labelling and Disclosure in Advertising

• Skepticism about looming regulatory and industry frameworks for labelling AI-generated content.
• Quote: “I don’t know why we need to label AI generated content and advertising, especially given that 100% of what’s coming out of agencies...will have used AI at some point.” – Nate Elliott [31:07]

[36:22] The Content Marketplace Debate

• Industry wrangling over whether large AI companies will be “forced” to pay publishers for data and content used in LLM training and answer generation.
• Amazon and Microsoft are creating content marketplaces to ensure publishers get paid (and to assure enterprise cloud clients).
  • Microsoft reportedly has already spent ~$10 million.
• Google’s claim that scraping for AI is equivalent to web search is meeting increasing skepticism.
• Quote: “AI overviews in particular seem less likely than other LLM services to offer people a chance to actually click through and go find the source of the content.” – Nate Elliott [36:49]
• Google and Microsoft have a business incentive to maintain publisher health, unlike fast-moving AI startups.

[41:54] Existential Questions for Publishers (and AI Platforms)

• If content quality/value erodes, both search and AI engines lose value.
• “If this content goes away, then both search and AI die. That’s the bottom line for Google.” – Nate Elliott [40:56]
• Google is “somewhat trustable as the adult in the room,” but if OpenAI “wins the race,” industry norms may further erode.

[43:37] The Rise of “REO” (Reddit Engine Optimization) and Content Floods

• With Reddit’s newfound status as favored LLM input (and due to paywalls blocking other major sources), brands are flooding Reddit with content.
• Reddit benefits with better ad sales, but struggles to package this for advertisers.
• LLMs are easily “influenced” by a single page or manipulated content (echoes of “Google bombing”).
  • Experiment: Publish a listicle or opinionated article, and—thanks to the lack of established inputs—the LLM might confidently repeat its claims as fact.
• Quote: "The ability to get a really confident sounding answer from an AI based on a single, willfully incorrect webpage seems a little bit startling right now.“ – Nate Elliott [45:38]

[47:38] WebMCP and Designing the Web for Bots

• Chrome’s proposed WebMCP standard would let sites embed content “for agents, not humans”—enabling companies to optimize for chatbot and agentic access directly.
• Still, data shows enormous divergence between top SEO results and top chatbot responses (as low as 8% overlap!).
• Quote: “If you’re a top 10 [Google] link...and you only have an 8% chance of showing up in LLM responses...that doesn’t sound like good SEO is good GEO.” – Nate Elliott [48:34]

[49:30] Out-of-Home Advertising and Silicon Valley Buzz

• Discussion of Vibe’s “targeted” billboard campaigns in San Francisco and the history/impact of strategic real-world advertising for tech brands.

[54:30] Agency Rebates and Opacity in Media Buying

• Indie agency Acadia launches insureRebate.com, calling out opaque rebate practices at holding company agencies.
• Jared Belsky claims rebates and non-transparent incentives represent 3–10% of the $600B market and as much as 30% of agency profits.
• General agreement: It’s a recurring scandal the industry seems unable/unwilling to fix, but transparency/earned media may help.

[56:40] Amazon Becomes #1 Fortune 100 Company

• Amazon surpasses Walmart to top the Fortune 100 by revenue ($717B).

Notable Quotes & Memorable Moments

• “[With AI], If you guess a number between 0 and 100 on usage, I can find a study to back you up.” – Nate Elliott [08:47]
• “We use these two letters [AI] as a monolith… but in practice, you’ve got… worlds apart.” – Nate Elliott [11:27]
• “It really is the fastest technology adoption curve we’ve ever seen.” – Nate Elliott [15:44]
• “If this is search, we’re in 1998. Think about what SEO looked like in 1998. It was a disaster!” – Nate Elliott [20:06]
• “Saying 95% of marketing will be AI is just nonsensical to me.” – Nate Elliott [29:06]
• “100% of what comes out of the agency at some point will be AI powered in some way.” – Nate Elliott [29:06]
• “The reckoning that happened in SEO in the early 2000s is going to happen in the AI engines in the next couple of years.” – Nate Elliott [20:37]
• “You need people to tell the tools what to do. At least at this point.” – Nate Elliott [27:39]
• “If this content goes away, then both search and AI die. That’s the bottom line for Google.” – Nate Elliott [40:56]

Timestamps for Key Segments

• [05:17] – Nate Elliott’s background and role at eMarketer
• [08:47] – Problematic AI data and industry confusion
• [10:31] – Taxonomy confusion around “AI”
• [12:22] – Consumer adoption: passive vs. active usage
• [14:10] – Google’s AI branding and usage stats
• [15:03] – Real numbers on active AI users
• [16:13] – Buying things with AI: reality vs. hype
• [19:47] – AEO (“AI Engine Optimization”): Marketer fears and opportunities
• [22:01] – Paid ads and keyword data for AI answers
• [23:20] – CMO/agency reality on AI adoption
• [31:07] – Disclosure requirements and labeling AI content
• [36:22] – Content marketplaces and publisher compensation
• [41:54] – Existential threats for web publishers
• [43:37] – The “Reddit effect” on LLMs and “REO”
• [47:38] – WebMCP and agent-specific web content
• [49:30] – Out-of-home advertising and Silicon Valley
• [54:30] – Agency rebates and transparency debates
• [56:40] – Amazon becomes #1 Fortune 100 company

Conclusion

This episode provides an insightful, data-driven, and occasionally skeptical overview of the state of AI’s impact on marketing, commerce, and media. Nate Elliott reveals the deep confusion and hype in the current landscape (“taxonomy cop required”—[11:27]), guides listeners through the actual numbers on AI adoption and shopping (“15–20% weekly users”) and highlights both the practical and philosophical challenges marketers, publishers, and agencies face as AI increasingly permeates every layer of the digital economy.

For more from Nate Elliott, check out eMarketer’s “Behind the Numbers” podcast and research at eMarketer.com.