@PositiveMindsGlobalResults | @Binance Square Official I #AIStocks
September 24, 2026
The AI investment story is evolving.
The first phase was dominated by GPUs and foundation models. The next phase is increasingly about the infrastructure required to run AI at enormous scale — memory, storage, CPUs, networking and data-center systems.
And the numbers are getting difficult to ignore.
💾 1. AI Infrastructure Is Expanding Beyond GPUs
Companies such as Dell, Micron and Western Digital have benefited from the enormous buildout of AI infrastructure.
Western Digital says AI is creating a structural increase in data-storage requirements. Its recent IDC-backed research found that 61% of surveyed organizations experienced at least 25% data growth over the past year because of AI, while 74% expect similar growth over the next three years.
That matters because AI does not simply consume computing power — it creates enormous quantities of data that must be stored, retrieved and processed.
📈 2. NVIDIA: Record Growth, But a Different Valuation Story
NVIDIA remains central to the AI infrastructure cycle.
Its latest quarterly results showed $96.2 billion in revenue, up 106% year over year, with Data Center revenue reaching $89 billion, up 117%. Gross margin was approximately 75%.
Even more striking, NVIDIA management said it expects approximately 70% revenue growth in fiscal 2028, while describing demand as supply-constrained.
Yet the stock’s valuation has compressed sharply. Recent reporting puts NVIDIA below 17× forward earnings, close to its lowest valuation level in more than a decade.
This creates an unusual market debate:
Can AI earnings continue accelerating faster than investors reduce the valuation multiple?
🤖 3. The Agentic AI Revolution Changes the Hardware Equation
This may be the most important development.
Traditional generative AI primarily focused on answering prompts. Agentic AI is designed to perform multi-step tasks autonomously — planning, executing, checking results and interacting with software.
That changes infrastructure requirements.
AMD itself argues that agentic AI can create demand for additional CPU infrastructure alongside GPU systems.
Meta’s Muse has provided a real-world example of this shift. Its rapid adoption has helped revive investor attention around CPUs and AI inference infrastructure, with AMD eventually crossing the $1 trillion market-capitalization milestone on September 21.
⚡ 4. AMD’s $1 Trillion Milestone Is More Than a Number
AMD’s rise reflects a broader market question:
What happens when AI moves from training models to continuously operating agents?
The answer could involve substantially more demand for CPUs, memory, networking, storage and power — not simply more GPUs.
AMD’s market capitalization reached approximately $1 trillion in September 2026, while its shares had gained roughly 185% during the year at the time of the milestone.
Meanwhile, Micron’s next major test arrives on September 30, when it is scheduled to report fiscal Q4 results.
🔎 THE BIGGER PICTURE
The AI trade is becoming an entire infrastructure ecosystem:
GPU → CPU → Memory → Storage → Networking → Power → Data Centers → AI Agents
The most important question for investors may no longer be simply:
“Who builds the best AI model?”
It may increasingly become:
“Who supplies everything required to keep billions of AI operations running?”
That is where the next phase of the AI infrastructure story could become especially important.
⚠️ Market Note: Strong historical performance does not guarantee future returns. AI infrastructure companies also face valuation risk, cyclical demand, capital-spending fluctuations, competition, supply constraints and macroeconomic pressure.
Do your own research (DYOR). This is educational content, not financial advice.
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