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How AI Transformed Google Cloud from an Also-Ran into Alphabet’s Powerhouse
Personal Anecdote
I still remember the first time I sat down with a CEO and asked, “Why are we drifting toward cloud services when our legacy product still works?” It was 2019, and the company had clung to on-premise servers out of habit. At that moment I realized: inertia in tech doesn’t mean safety—it often means missed opportunity. Fast forward six years working in enterprise AI and cloud strategy, and I see the exact same pattern playing out across major players right now.
Expert Analysis: What Happened with Google Cloud & Alphabet
Here’s the crux: Alphabet’s cloud business, once considered a laggard, has pivoted sharply. According to a recent report, Google Cloud’s revenue in Q3-2025 topped $15 billion, marking a 34% year-over-year increase, driven by demand for AI infrastructure (including its own “Gemini” model).
Let’s pick this apart:
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Strategic shift: When Thomas Kurian took over the cloud business, he didn’t just tweak the culture—he changed the game. The unit moved away from trying to piggyback off ad-business goodwill and instead targeted enterprise customers, segmented by industry rather than geography.
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Infrastructure bet: Alphabet invested heavily in datacenters, custom chips (TPUs), networking gear—things that take scale and patience. And yet, that bet is paying off because generative AI workloads demand exactly that.
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Competitive repositioning: Historically, Google Cloud trailed behind the cloud titans Microsoft Azure and Amazon Web Services (AWS). Now, with the TPU push and AI-model support, it’s fighting for parity—or at least credibility.
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Profitability & resilience: This isn’t just growth for growth’s sake. Google Cloud turned its first profit recently, and Alphabet’s leadership is signalling that they expect resilience even in a potential AI-bubble correction.
From where I sit, this is a textbook case of how a technology unit transforms from “also-ran” to “growth driver”.
My Take: The Bigger Picture & What It Means for You
I don’t see this simply as “Google Cloud is doing well”. I see three macro themes:
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AI infrastructure is now a differentiator, not a nice-to-have
Many businesses treated cloud computing as commoditized. But when the workload shifts to generative AI, custom chips and optimized infrastructure become strategic barriers—not just cost centres. -
Enterprise sales and specialization win over “one-size-fits-all”
The pivot to industry-specific sales teams (vs generic reps) indicates that complex buyers demand domain expertise. If you don’t structure your organisation that way, you’ll leave money on the table. -
Time & scale matter more than chasing hype
Alphabet didn’t overnight become Cloud-champion by releasing one feature. They invested years in hardware + partnerships + operational discipline. That means sustainable growth, not flash-in-the-pan.
For businesses and strategists reading this: if you’re chasing “AI” but skipping investment in infrastructure, partner model, or go-to-market, you’re setting yourself up for either cost overruns or competitive obsolescence.
Prediction: What’s Next for Google Cloud & Cloud + AI
From my vantage, here’s where things are headed:
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Google Cloud will pivot into “AI platform + services” niche: Rather than generic IaaS, expect it to push high-value capabilities—pre-trained models, verticalised AI services, etc. This will raise switching costs for customers.
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Smaller players will get squeezed: As Google, Microsoft, Amazon roll everything into cloud + AI stacks, companies that only offer compute or just software will find margins compressing.
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Capital intensity will increase—but expect efficiency gains: Alphabet’s 2025 cap-ex is projected at US $91-93 billion. But that also means infrastructure becomes a moat, which fewer firms can replicate.
Actionable Takeaways: What You Must Do Now
If you’re reading this as a business leader, tech strategist, or investor, here are three immediate steps you must take:
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Audit your AI-infrastructure readiness
Ask: Do you have the hardware, cloud partnerships, and internal expertise to support real AI workloads (not just experiments)? If the answer is “no” or “sort of”, it’s time to budget and plan. -
Segment your go-to-market around industry verticals
Generic sales and marketing work less well now. Build teams or units that specialise (e.g., healthcare-AI, manufacturing-AI). That matches what Google Cloud has done and signals credibility. -
Focus on tying AI outcomes to business value—not just features
Rather than “we’re using AI”, shift to “we’re using AI to reduce X cost, increase Y revenue, or improve Z customer experience”. That mindset separates strategic bets from vanity projects.
Disclaimer
All opinions in this blog post are mine (based on my 5+ years of experience in cloud and AI strategy) and do not constitute financial or professional advice.
Original news source: “AI turned Google Cloud from also-ran into Alphabet’s growth driver” published by The Indian Express.
Copyright
© 2025 FlowandFind. All rights reserved by the original publisher. The summary above is original work by this blog author, with attribution and link to the source.