Some Thoughts on GOOG: An 'Emperor Has No Clothes' Moment

A melting moat, and no cavalry in sight

Polymath Investor. (2025). “Google Search In Trouble"

I worked at Google from before the Global Financial Crisis until 2010.

I still regret not keeping those RSUs (or GSUs as they call them). It’s been a 10x since then.

Yet, on Wednesday, the stock plunged 7% after Eddy Cue, Apple’s services chief, said AI search engines will replace traditional search engines¹ (ie. Google).

The problem with Google isn’t that its other businesses—YouTube, Cloud, Quantum, Gemini to name a few—aren’t good. On the contrary, each of those could be world-class companies on their own². The issue here is that Google Search is just too darn good—as a massive cash-generating machine with a operating margins at scale that I have yet to see on a S&P 500 company.

Google has been trying for years to diversify and reduce its dependence on Search ads. Lately, they’ve had some success, but the company still fundamentally relies on Search as the bedrock of its profitability.

Let’s put some numbers to it: 1) In 2024, Google generated $350 billion in revenue. 2) Of that, $305 billion came from Google Services (which includes Search Ads, YouTube, Google Network, subscriptions, and other products). 3) The other major segment was Google Cloud, with $43 billion.

Now, let’s look at operating margins: 1) Google Services ran at ~40% operating margin. 2) Google Cloud’s margin was ~14%.

While Google never disclosed specific margins for Search Ads, it was widely believed they operated at over 75%³ —an almost unheard-of figure for an S&P 500 company. Today, that margin is likely in the 45–60% range. Still, pretty darn good.

Google does report revenue for individual subsegments though—Search, YouTube, and Google Network—and there, you’ll see that Search alone accounts for ~65% of the Google Services revenue.

If Services as a whole has a 40% operating margin and Search represents 65% of that, running at ~45-60% margin, then it’s clear that YouTube, Google Network, and Subscriptions are way less profitable.

I can confirm this from the advertiser side. Take travel insurance, financial services, or some verticals on e-commerce—advertisers can pay $10+ per click on some keywords. The cost of serving that ad? Practically zero.

By contrast, YouTube is a great platform, but CPCs and CPVs are nowhere near Search, and YouTube has to split revenue with content creators. Same with Google Network.

Could Cloud make up the difference?

Doubtful.

The margins are far lower, and Google would need to triple AWS's revenues just to match Google Services in size. That seems unrealistic.

So, the hope shifts to Gemini.

Again, not even close to Search, why? 1) There are many strong contenders in the LLM race—Google doesn’t have a monopoly here like it did in Search for many, many years. 2) The cost of serving a single LLM chat response is at least an order of magnitude higher than a traditional search result⁴. And 3) It’s not clear whether or how Gemini will even be monetized through search ads, if at all.⁵

That’s why I don’t think Gemini can “replace” Search. More competition, higher costs, and unclear monetization.

Which brings us back to the beginning: Google’s issue isn’t that its other products are bad. It’s that Search is superlatively good at generating cash. And now, it’s under attack—by well-funded, hungry competitors going straight for its core business.

One final argument I often hear in the media is that "valuable" searches—travel, finance, e-commerce—still happen on Google, not on LLM interfaces. That may be true for now. But I think we’re about to see a “gradually, then suddenly” moment.

Why? Because we haven’t yet seen mass adoption of web search inside Grok, GPT, or Perplexity.

I honestly can’t remember the last time I used Google. For planning my last trip, I used Perplexity, and for buying my most recent tablet, I used Grok. Those would’ve been pretty valuable clicks—clicks that didn’t go to Google. (By the way, the experience was far better than today’s cluttered search pages.) Multiply that by millions, and you start to see the erosion of Google Search’s moat.

The world of Search is a world governed by Pareto dynamics—you have long tails everywhere. You don’t need mass adoption of LLMs worldwide to make a dent in Google’s Search business. By targeting the "head"—a relatively small number of high-value searches in areas like financial services, travel, and e-commerce—you can inflict significant damage at the very heart of Google’s profit machine.

It really comes down to two questions:

1. How quickly will adoption grow for these new LLM interfaces—specifically among users who perform high-value searches?

2. How long can Google "extend and pretend" that Search remains unshaken?

I can tell you this though: Google has many levers to pull to squeeze more out of Search. If you check their 10-K, you’ll see two key metrics for Search Ads: Paid Clicks and Cost-Per-Click. They can influence both—by increasing ad density on SERPs, tweaking the Quality Score algorithm, making ads blend more with organic results or integrate them more with other products, etc.

So I expect a few more solid quarters of Search traction—unless a sharp recession provides cover for a quicker drop—before we start seeing stabilization, then a mild decline on Search ad revenue. And once that happens, earnings call questions will get harder to dodge.

That’s when the narrative turns.

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1. https://www.cnbc.com/2025/05/07/alphabet-shares-sink-on-report-apple-may-add-ai-search-to-its-browser.html

2. Well, at least YouTube and Cloud for sure as they are actually generating profits.

3. https://www.informationweek.com/it-leadership/google-s-search-business-runs-on-75-profit-margin

4. According to an analysis by Azeem Azhar, each interaction with ChatGPT can consume up to 2.9 watt-hours (Wh) of energy, which is nearly ten times the 0.3 Wh energy cost of a standard Google search. SemiAnalysis further estimates that if Google replaced its current search algorithms with LLMs, each search request could cost up to 8.9 Wh-potentially 30 times more than current search costs. (SemiAnalysis. (2023). The inference cost of search disruption – Large language model cost analysis. https://www.semianalysis.com/p/the-inference-cost-of-search-disruption)

A 2025 AI industry cost guide from Businessware Technologies explains that while LLM costs have dropped with new models like GPT-4o, the expense per request remains significant, especially at scale. Even with cost-optimized models, the total cost of deploying LLM-powered systems-including API usage, infrastructure, and document intelligence-remains much higher than traditional search, especially for high-volume applications.
(Businessware Technologies. (2025, April 21). What does it cost to build an AI system in 2025? A practical look at LLM pricing. https://www.businesswaretech.com/blog/what-does-it-cost-to-build-an-ai-system-in-2025-a-practical-look-at-llm-pricing)

5. During Q1 2025 earnings call, Sundar Pichai was really bullish on how “AI Overview” was being rolled out and had “roughly similar monetization rates” to plain Google Search. “Google AI Overviews are a search feature that utilizes generative AI to provide users with a concise, AI-generated summary of a topic based on a variety of sources, including the web and Google's Knowledge Graph.” Think on that for a moment, let’s suppose you were doing research to buy a laptop, you would click in 1, 2, 3, or 4 ads trying to find information on different models. Now, If you have everything you need in the Google Search Results Page, then no need to click on all those ads and the overall CTR (click-through-rate) for that query should start trending lower.