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‘It’s Google’s Game to Lose’: Why AI Chatbots Can’t Match Google Search’s Advertising Model

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‘It’s Google’s Game to Lose’: Why AI Chatbots Can’t Match Google Search’s Advertising Model

Quick Read

  • A single sentence about Italian restaurants exposes why AI chatbots can't replicate Google's most valuable business, and the reason has nothing to do with search quality.
  • One of the podcast hosts admitted he drastically cut his own Google usage, yet he still ended up bullish on Alphabet. The reason why is the real story.
  • ChatGPT launched without something so obvious that it stunned a seasoned investor, even though Google had quietly solved that problem years ago.
  • Many financial professionals are salespeople paid on what they push, not whether you end up wealthier. A fiduciary is the opposite. The SEC legally requires them to put your interests first. Advisor.com's free matching tool pairs you with vetted fiduciaries from major national firms, all in under three minutes. See who you match with today.

A recent episode of We Study Billionaires makes a case that cuts against the loudest bear argument on Alphabet (NASDAQ:GOOGL | GOOGL Price Prediction): that AI chatbots will eat Google Search. Hosts Shawn O’Malley and Kyle Grieve argue the opposite, and the reasoning has less to do with model quality than with how advertising actually works.

Their argument matters right now because the stock has already re-rated. Alphabet traded at $347.33 as of 7:59 p.m. ET on September 17, 2026, up 1.30% on the session, 11.18% year to date, and 39.56% over the past year. The one-year figure is the relevant one, because the fear the hosts are dissecting is a fear that did not materialize.

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Why a Chatbot Conversation Is Worth Less Than a Search Query

O’Malley’s core point is that not every query carries the same commercial value, and that is why large language models struggle to compete with Google’s ad model. Conversations with AI tools, Shawn O’Malley said, tend to be “very technical and niche” and do not directly relate to a purchase or spending decision. An advertiser could theoretically pay to put a billboard inside an LLM conversation, O’Malley said, but that is “really just not a great model compared to Google Search because you don’t have the same targeting at scale”.

The concrete version, from O’Malley on The Investor’s Podcast Network: “An Italian restaurant can pay to be the very first result that shows up in your town when you Google restaurants near me. And that’s very valuable digital real estate.”

That is the whole argument in one sentence. A search query often carries purchase intent, while a chatbot conversation rarely does. Intent is what advertisers pay for.

Grieve on Distribution and the Ads Google Already Built

Kyle Grieve extended the point to distribution and monetization. When ChatGPT launched, Kyle Grieve said he “was just kind of amazed that they just weren’t showing ads of some sort”, crediting Google for having solved a problem the new entrants had not. Google places ads above, below, and inside AI Overviews, meeting users at multiple points in a single search.

On reach, Grieve said Google “could immediately just roll out AI mode to over a billion monthly active users, allowing them to collect even more data on how consumers are using AI for things like shopping”. On The Investor’s Podcast Network, Grieve called the resulting data advantage “sort of their game to lose”, which is the phrasing our headline tightens.

What Makes the Episode Credible

The hosts concede the fear was reasonable. The Investor’s Podcast Network noted ChatGPT created genuine uncertainty about search especially in 2024 and early 2025, and that clarity only came later that AI Overviews could be monetized similarly to traditional search. More striking: one host on The Investor’s Podcast Network account said he was a heavy ChatGPT user at the time and cut his Google usage “very significantly”, and that this concerned him about the business. An analyst describing his own behavior working against his thesis is worth more than confident assertion.

Valuation Backdrop, Then vs. Now

The opportunity Shawn O’Malley describes came when Alphabet traded at what he called a historic discount of 17x earnings due to AI fears. That is a past reference point tied to when the thesis was placed, and it describes valuation at that moment rather than today’s shares. You can find the full discussion on the episode page for TIP847: Alphabet (GOOGL): The Megacap That Still Might Be Underrated, and Alphabet’s own Q2 FY2026 results are in its 8-K filing with the SEC.

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The tension worth keeping is in the headline itself. Calling it Google’s game to lose is a bull case that also concedes the game can be lost. The hosts are arguing about advertising economics and distribution while acknowledging AI still poses risk. For the opposite view, our reporting today on the investor arguing AI companies have no competitive moats takes the same question from the other end: whether the durable advantage lives in incumbency or in model quality.

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