# VC10X Pulse - Google I/O - Is Google the underdog in the AI race?

An episode of [VC10X - Investing, Venture Capital, Asset Management, Family Office, Wealth Management](https://invisiblenetwork.ai/podcast/1632806986), 21 May 2026, 7:53.

Audio: https://anchor.fm/s/a453ddd4/podcast/play/120326606/https%3A%2F%2Fd3ctxlq1ktw2nl.cloudfront.net%2Fstaging%2F2026-4-21%2F424604619-44100-2-837a075ba87be.mp3

Google I/O may have changed the way investors should look at the AI race. For the last two years, Google has often been framed as the incumbent under threat — especially as ChatGPT, OpenAI, and Anthropic captured attention in consumer and enterprise AI. But Google’s advantage is different. It is not just competing through a standalone chatbot. It has distribution across: Search Android YouTube Gmail Chrome Workspace Google Cloud TPUs Gemini In this episode, we break down why Google may be the “underdog” in market narrative — but one of the most strategically positioned companies in AI. Key questions we explore: – What did Google I/O reveal about Google’s AI strategy? – Why is distribution such a powerful moat in AI? – Can Google defend Search while transforming it into an AI-native interface? – How do Android, YouTube, Gmail, Workspace, and Chrome strengthen Gemini’s reach? – Why could TPUs become an important infrastructure advantage? – What should investors watch: model quality, monetization, capex, or platform control? The core investor question: Can Google convert its massive distribution into durable AI monetization? If it can, Google may not be behind in the AI race. It may be one of the most important companies to watch. Subscribe to VC10X for fact-based, investor-first analysis on AI, venture capital, and global markets. LINKS Prashant Choubey - https://www.linkedin.com/in/choubeysahab Subscribe to VC10X newsletter - https://vc10x.beehiiv.com Subscribe on YouTube - https://youtube.com/@VC10X Subscribe on Apple Podcasts - https://podcasts.apple.com/us/podcast/vc10x-investing-venture-capital-asset-management-private/id1632806986 Subscribe on Spotify - https://open.spotify.com/show/7F7KEhXNhTx1bKTBFgzv3k?si=WgQ4ozMiQJ-6nowj6wBgqQ VC10X website - https://vc10x.com For sponsorship queries reach out to prashantchoubey3@gmail.com This channel is for asset managers, allocators, and investors who want analysis that holds up — not headlines dressed as insight. Subscribe for weekly data-driven breakdowns of the forces reshaping capital markets. Disclaimer:This content is for informational purposes only and does not constitute investment advice.

## Transcript

[0:00] For the last two years, the AI race has been framed as Open AI
[0:03] versus Anthropic. Open AI had the consumer
[0:07] mindshare, Anthropic had the safety and enterprise narrative,
[0:10] Meta had the open source developer strategy, NVIDIA had
[0:13] the infrastructure choke point. And Google.
[0:16] Google was often treated as the incumbent that missed the
[0:19] moment. But after Google IO, that
[0:22] framing may be too simplistic because Google's advantage is
[0:26] not just models, it is distribution.
[0:28] Search, Android, YouTube, Gmail, Chrome, Workspace, Cloud, Dpus.
[0:34] Google may not be the loudest AI company in the market, but it
[0:37] may have one of the deepest platform modes in the entire AI
[0:40] race. Google IO was not just a model
[0:44] launch event, it was a distribution event.
[0:47] Google announced deeper AI integration across Search,
[0:50] Gemini, Android Workspace, YouTube, Hotos, Developer Tools
[0:54] and variables. The company described AI mode as
[0:57] the biggest upgrade to search in more than 25 years and said it
[1:01] is bringing agentic AI abilities directly into search.
[1:04] It also announced Gemini models including Gemini Omni and Gemini
[1:08] 3.5 Flash and Gemini Omni focused on multimodal input and
[1:14] output starting with video. The important point for
[1:16] investors is this. Google is not trying to win AI
[1:19] through 1 stand alone chatbot. Google is embedding AI into
[1:23] products that already have massive global usage.
[1:27] This is very different go to market strategy from most AI
[1:30] labs. Why does Google look like the
[1:33] underdog in the AI race? Google has been under pressure
[1:36] because the market's initial AI framework was simple.
[1:39] ChatGPT became the new interface.
[1:41] Search looked vulnerable. Google looked defensive.
[1:45] That concern was not yet rational.
[1:48] If users shift from search links to AI answers, Google's score
[1:51] advertising business could be disrupted.
[1:53] This is the beer case. But the latest data complicates
[1:57] that story. In Q12026, Alphabet reported
[2:01] revenue of $109.9 billion, up 22% year over year.
[2:06] Google services revenue grew 16% to over $89.6 billion and
[2:11] Search, another advertising revenue grew 19%.
[2:14] So for now, the search business is not collapsing.
[2:17] It is still growing. That does not eliminate the long
[2:20] term risk, but it suggests Google has more room to adapt
[2:23] than the market initially assumed.
[2:25] Distribution is Google's hidden AI advantage.
[2:28] Most AI companies need to acquire users.
[2:31] Google already has them. This is the key difference.
[2:34] Google can push AI into search where intent is already
[2:37] captured. YouTube where video discovery
[2:40] and creation can become AI native.
[2:42] Android where AI can become the operating system layer.
[2:45] Gmail and Calendar where agents can act on personal context.
[2:49] Workspace, where enterprise productivity already happens.
[2:53] Chrome where browsing behavior can become agentic.
[2:55] Cloud where enterprises by infrastructure and AI tooling.
[2:59] This matters because distribution reduces customer
[3:01] acquisition cost. If Google can make Gemini useful
[3:04] inside products people already use daily, it does not need to
[3:08] fight the entire AI race. Through a separate chatbot app,
[3:11] it can turn existing surfaces into AI interfaces.
[3:14] That is the platform mode. Now let's talk about search.
[3:17] Search is both the risk and the opportunity.
[3:20] Search is Google's biggest vulnerability, but it is also
[3:23] it's biggest advantage. Google said AI Overviews now has
[3:27] more than 2.5 billion monthly active users, and AI Mode has
[3:30] already passed 1 billion monthly active users within a year.
[3:34] That scale is important. Open AI may have the strongest
[3:36] consumer AI brand, but Google has the most important consumer
[3:40] intent layer on the Internet. If AI changes search behaviour,
[3:43] Google has to manage a difficult transition from links to
[3:46] answers, from queries to tasks, from search results to agents.
[3:51] The investor question is whether Google can protect monetization
[3:55] while changing the interface. If it can, Google becomes one of
[3:58] the biggest winners of AI. If it cannot, AI compresses one
[4:01] of the most profitable business models in technology.
[4:04] That is why Alphabet is so interesting right now.
[4:07] It is both the risk and the asset.
[4:10] Google Cloud is becoming a serious AI business.
[4:12] The second major signal is cloud.
[4:15] Alphabet said Google Cloud revenue grew 63% in Q12026,
[4:20] exceeding 20 billion for the first time, while backlog nearly
[4:23] double quarter over quarter to more than 460 billion.
[4:27] That matters because AI is not only a consumer product, it is
[4:30] also an enterprise infrastructure market.
[4:32] Google has three assets. First, frontier models through
[4:35] Gemini and DeepMind. Second, cloud distribution
[4:38] through Google Cloud. 3rd, proprietary infrastructure
[4:41] through Tpus. This gives Google a vertically
[4:44] integrated AI stack. Models, infrastructure developer
[4:48] tools, enterprise distribution, consumer services.
[4:51] Very few companies have all of those at once.
[4:55] The TPU angle. Google's quiet infrastructure
[4:57] mode. Most investors talk about NVIDIA
[5:00] when they talk about infrastructure correctly so, but
[5:04] Google has been investing in GPUs for years.
[5:06] That gives Google an important strategic advantage.
[5:09] It is not fully dependent on external GPU supply in the same
[5:12] way as many AI companies are. This does not mean GPUs replace
[5:17] NVIDIA overnight, but it does mean Google has more control
[5:20] over its AI cost structure than a company that has to buy
[5:23] compute entirely from outside vendors.
[5:25] It is an AI race where interface cost matter.
[5:28] Infrastructure efficiency becomes a comparative advantage.
[5:31] The winner may not simply be the company with the best model, it
[5:34] may be the company that can serve intelligence at the lowest
[5:37] cost across the last distribution base.
[5:39] That is where Google's position becomes very interesting.
[5:42] Why investors may still be enterprising Google.
[5:45] The market often values Google like an advertising incumbent,
[5:49] but after IO, the better framing.
[5:51] Maybe Google is an AI platform company with an advertising cash
[5:55] engine. That distinction matters because
[5:58] Google has massive free cash flow, global distribution, a
[6:01] leading research lab, cloud growth, custom AI chips,
[6:06] consumer services, Enterprise Products developer reach.
[6:10] The beer case is that AI disrupt search.
[6:13] The bull case is that Google uses AI to expand search into a
[6:16] broader agentic interface while monetizing across ads,
[6:20] subscriptions, enterprise software and cloud.
[6:22] Investors need to underwrite both.
[6:24] What could still go wrong? This is not a one sided story.
[6:28] There are real risks here. First, source monetization could
[6:31] compress if AI answers reduce ad clicks.
[6:35] Second, AI CapEx is rising across the industry and
[6:38] investors will increasingly demand proof of return on
[6:40] invested capital. Third, Open AI and Anthropic
[6:43] remain extremely strong in developer mindshare and
[6:46] enterprise AI perception. 4th Google's product execution has
[6:50] historically been uneven across messaging, assistance and
[6:53] consumer apps. So the thesis is not Google has
[6:56] already won. The thesis is Google may be more
[6:58] comparative than the market narrative suggests.
[7:01] Google Are you sure that Google's AI strategy is not just
[7:04] about releasing a better chat bot?
[7:06] It is about embedding AI into every major distribution service
[7:10] the company owns Search, Android, YouTube, Workspace,
[7:14] Chrome Cloud. That is why Google may be the
[7:17] underdog with the strongest platform mode.
[7:20] The AI race may not be 1 only by the company with the best model
[7:24] demo. It may be 1 by the company that
[7:26] can distribute AI to billions of users, monetize it across
[7:30] multiple services, and grant it efficiently at a global scale.
[7:34] And on that basis, Google is not behind.
[7:37] It may be one of the most important companies to watch in
[7:39] the entire AI race. That's all for this week.
[7:42] We'll be back next week with another story from the front
[7:45] lines of global investing VC10X.

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