Latest / Retail Media Breakfast Club / Will Ads Ruin AI? Why Agentic Advertising Might Save the Internet
Transcript
- Maybe Ads in AI don't have to suck? === [00:00:00] Kiri Masters: It seems almost inevitable that we'll end up with ads inside LMS in the near future. The math is simple. OpenAI and its competitors have invested over $200 billion in the AI [00:00:15] infrastructure and our $20 subscriptions alone won't deliver returns at that scale, neither will taking a cut of retail revenue through instant checkout or Atlas [00:00:30] Advertising represents trillions in addressable market opportunity. [00:00:34] It's not quite free money, but it's pretty damn close. [00:00:38] The fear for many is that advertising when introduced to a surface that has become the [00:00:45] most intimate digital confidant for many people, is that the experience will be bad, creepy, intrusive, and overwhelming. Call me idealistic. But I don't think that ads within AI interfaces [00:01:00] necessarily have to suck. [00:01:02] This episode is based on an op-ed that was originally published for my column at the drum on November 6th. [00:01:08] [00:01:10] Kiri Masters: As someone who spent years tracking the retail media industry, perhaps I should be concerned [00:01:15] about this shift. After all, someone searching for the best laptop for video editing under $1,500. [00:01:23] Used to start that search on a retailer's website surrounded by product ads [00:01:30] generating a healthy 70 to 80% profit margin for that retailer. But AI answer engines are now increasingly fielding these questions and intercepting the intent that currently flows through [00:01:45] retail media platforms. as an aside, This is without any agent inter integration as well. [00:01:51] This behavior, doing this research upfront in an LLM is already happening. Now retailers should be [00:02:00] tracking these developments closely as a possible threat to their lucrative retail media business. But for the general public, I don't think that the introduction of ads in AI answer engines automatically means instant in [00:02:15] ification. [00:02:16] That's a technical term. By the way. The advertising technology being built today is designed specifically to avoid repeating the mistakes that degraded search results and turned [00:02:30] Amazon into a pay to play marketplace. [00:02:32] History says the fear is justified. The anxiety around ads in AI stems from watching two decades or more of platforms and tify themselves [00:02:45] in pursuit of advertising revenue. First, there's the corruption of recommendations. If OpenAI, for example, monetizes chat, GBT with ads, will it eventually recommend the TV whose manufacturer paid the [00:03:00] most rather than the one that's genuinely best for my needs. [00:03:04] The platform's entire value proposition rests on providing trustworthy, unbiased guidance, introducing financial incentives to [00:03:15] skew recommendations, breaks that trust, and then there's the privacy factor. We are entrusting our AI companions with our most intimate information, health concerns. Relationship struggles, financial [00:03:30] anxieties, personal insecurities. [00:03:32] Using that data for hyper targeting advertising could feel like a profound violation. [00:03:39] History suggests that these fears aren't hypothetical. Google search results became increasingly [00:03:45] difficult to distinguish from ads. Facebook's feed prioritized engagement over accuracy, fueling misinformation, and Amazon search experience is dominated by sponsored placements that are based primarily on who paid for [00:04:00] placement as Brian O'Kelly, the founder of AppNexus and a pioneer Of the Internet's ad economy admits the system is breaking down in real time, more cluttered, harder to navigate. Introducing that broken system into AI [00:04:15] seems like it would accelerate whatever diminishing Trust remains. [00:04:19] Who funds the world ads? Digital advertising is the economic foundation, keeping the internet freely accessible as [00:04:30] ads industry analyst Eric Sert argued in a recent post on x. Digital advertising is the most positive sum economically expansionary technology summoned by humanity. No other technology [00:04:45] has created more consumer surplus or stimulated more long-term economic activity without advertising revenue. [00:04:54] He notes the internet itself would cease to exist as a freely accessible [00:05:00] commodity and would instead be a luxury good reserve for moguls and dust beds. AI platforms face identical economic pressure. The infrastructure required to run. These systems cost [00:05:15] billions of dollars beyond subscription revenue. [00:05:17] Advertising and commerce represent the most viable paths to monetization at scale. Miracle Ads is [00:05:30] the Ad Tech solution trusted by Rakuten and over 50 global enterprise retailers. That's because Miracle Ads was built with both three P Marketplace sellers and one P suppliers in mind. Both advertiser [00:05:45] audiences demand a seamless advertising journey from onboarding to reporting. [00:05:50] You can offer everything from sponsored products to video ads all in one solution. Learn more@miracle.com. That's [00:06:00] M-I-R-A-K l.com. [00:06:01] [00:06:02] Kiri Masters: Now let's talk about Ag Agentic advertising a different foundation. The advertising technology being developed specifically for AI environments operates on different [00:06:15] principles than the surveillance based targeting that broke consumer trust. It's called agentic Advertising, and its core innovation is that it targets content and context. [00:06:27] Rather than people and data, [00:06:30] traditional digital advertising built its infrastructure around tracking individuals through cookies, browsing history, demographic profiles, and purchase behavior. The goal was to know as much as possible about you [00:06:45] personally and then show ads based on this data collection. [00:06:50] This created the privacy nightmares and data breaches defining the current moment. The new model of Ag agentic advertising flips that model. [00:07:00] Instead of profiling users, AI agents analyze the content and context of the conversation itself, matching ads to themes and topics rather than personal attributes. [00:07:14] [00:07:15] Someone asking about sustainable hiking gear. Triggers recognition of content, themes, outdoor recreation, environmental values, product research without needing to know who that person is, what they've purchased before, or what [00:07:30] websites they've visited. Brian O. Kelly, who now runs ad Tech firm Scope Three and is championing an agentic advertising framework called Ad Context Protocol, or ad. [00:07:41] CP describes the shift in a recent op-ed [00:07:45] for Fast Company. Here's a quote from him. If the attention economy monetize distraction, the agentic AI economy has the chance to monetize trust. We can use AI to filter noise instead of creating it, he [00:08:00] suggests a simple exercise to validate this concept. Copy a page that you've browsed and paste it into chat GBT. [00:08:07] Then ask it to produce an add and compare the result to what's actually on the page. More likely than not chat BT [00:08:15] gave a better ad without even needing your brow history or data. This makes content. The product again, not you. AD CP isn't confined to ads in AI answer engines. [00:08:28] It's being built as an open standard [00:08:30] to support media buying across a wide range of digital contexts from the Open Web and CTV to conversational and AI driven environments. But some ad tech companies like Thread. [00:08:42] That's [00:08:45] T-H-R-A-D-A, building infrastructure for this model to run specifically within AI answer engines, what they call conversational advertising. The company says it is bringing the internet era advertising model to AI applications, subsidizing AI [00:09:00] accessibility through ads, including the ability to insert native ads into AI chat conversations. [00:09:05] If a user is asking, what's the best way to get around the city? They might see a sponsored Uber recommendation and thread itself follows the [00:09:15] ad CP Design Choice. Their bidding system prioritizes user experience over the highest payer that could prove to be a guardrail against the pay-to-play dynamics that degraded search and e-commerce a [00:09:30] chance for a fresh start. [00:09:31] High intent conversational advertising has the potential to be more relevant. And helpful than anything currently available. Users provide far more context to their AI companions than to a search box, [00:09:45] so the signals are stronger and the user is actively engaged rather than passively scrolling. That's valuable to advertisers, but to be effective rather than creepy, ~need different creative approach.~ [00:09:56] ~We will ~We will need different creative approaches, different measurement frameworks, [00:10:00] and different expectations about how advertising functions for retail media networks Specifically, and I'll explore this more deeply in a future column, the implications are more fraught when AI intercepts. [00:10:15] Purchase intent before a shopper ever reaches a retailer's website. [00:10:20] The entire business model generating those onsite ads is threatened. And while the offsite audience extension capabilities from retailers can offer [00:10:30] strong signals to advertisers, those may pale in comparison. To what an AI model could offer advertisers, but for the broader marketing ecosystem, the arrival of advertising in AI may not be the [00:10:45] catastrophe that many fear. [00:10:47] Perhaps it's an opportunity to rebuild advertising infrastructure on better principles, assuming that the industry is willing to learn from its mistakes. [00:10:57]