Nvidia didn’t just ride the AI wave, it built the surfboard thanks to the graphics processing unit that evolved from powering video games to becoming the computational engine of the AI revolution.
Today, roughly 92% of all AI data center processing runs on Nvidia chips, according to IoT Analytics. That kind of market share is virtually unheard of in hardware.
Key Points
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It controls about 92% of data center GPUs, with its CUDA software creating a near-impenetrable moat.
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AI demand keeps fueling massive revenue and profit growth.
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Competition and market swings pose threats, yet Nvidia’s innovation, margins, and Jensen Huang’s foresight make it a strong long-term bet.
The Relentless March of AI
Even as growth cools from two years of triple-digit surges, Nvidia’s financials remain astounding. In fiscal Q2 2026, revenue jumped to $46.7 billion, while earnings per share climbed 61%. The data center segment which acts as the backbone of AI training and inference now accounts for over 85% of total sales.
According to PwC, the global AI economy could reach a staggering $15 trillion and change by the turn of the decade, more than China’s entire GDP today. If Nvidia captures even a small fraction of that growth, its trajectory could still astonish skeptics.
CUDA is The Secret Weapon
Nvidia’s free cash flow per share has already exploded 15-fold since 2020. Few companies in history have ever sustained that kind of compounding power for this long, and fewer still have done it with such strategic control over both hardware and software.
One detail that often escapes investors is Nvidia’s software ecosystem, CUDA, has become the “operating system” of AI. It’s used by virtually every AI researcher, startup, and hyperscaler.
This gives Nvidia a switching moat that looks more like Microsoft in the 1990s than a typical chipmaker today.
The Roadblocks (nd Why They Might Not Matter
Of course, no forecast this bold comes without caveats. Nvidia faces growing competition from AMD, Intel, and custom chips developed in-house by Amazon, Google, and Meta.
Demand for AI infrastructure could also cool if global tech spending slows or if AI adoption underdelivers on commercial results.
Even so, Nvidia’s long-term thesis doesn’t hinge on perfection. In other words the hype may ebb and flow, but the structural demand for accelerated computing is here to stay.
Valuation Is Still Not as Wild as It Looks
At first glance, Nvidia’s valuation, about 50x trailing earnings, looks rich. But relative to its 10-year earnings power, it’s arguably reasonable. The stock trades for less than 30 times next year’s expected profits, a level investors once paid for far slower-growth companies like Cisco or Oracle during their prime.
It’s also worth remembering that Nvidia’s profit margins hover above 55%, higher than Apple’s, and the company’s balance sheet is pristine.
Unlike many past tech darlings, Nvidia doesn’t need to raise capital to grow but is generating more cash each quarter than Intel earns in a year.
And then there’s Jensen Huang. Nvidia’s visionary founder-CEO has repeatedly spotted the next computing paradigm before anyone else, from parallel processing to deep learning to generative AI. If history is any guide, betting against Huang has been one of the worst trades an investor could make.
The Bottom Line
Nvidia is no longer just a semiconductor company, it’s the infrastructure layer of the AI economy.
Whether or not it mushrooms from here, it’s positioned to capture a disproportionate share of one of the largest technological transformations in history.
For long-term investors willing to ride the volatility, Nvidia could still be one of the most important wealth-building stories of the next decade.