Top 7 AI Storage Stocks to Watch Right Now!

AI storage stocks are getting attention as artificial intelligence pushes demand for more efficient and powerful data infrastructure. Traders focused on opportunity, volatility, and timing should pay close attention to this niche, because the need for computing power, storage, and scalable platforms isn’t slowing down. 

Check out my complete AI stock watchlist here!

Here are seven stocks worth watching now based on current data trends, business expansion, and sector momentum.

7 AI Storage Stocks to Watch

Ticker	Company Name	Sector	Focus Area
NYSE: VRT	Vertiv Holdings Co.	Industrial Tech	Data Center Infrastructure
NYSE: AMT	American Tower Corp.	REIT	Data Centers / Wireless Infrastructure
NASDAQ: MU	Micron Technology	Semiconductors	High-Bandwidth Memory / AI Storage
NASDAQ: NTAP	NetApp	Computer Hardware	Enterprise Data Storage Solutions
NYSE: SNOW	Snowflake	Cloud Software	Data Warehousing / Analytics
NYSE: DLR	Digital Realty Trust Inc.	REIT	Colocation / Data Center Operations
NASDAQ: GSIT	GSI Technology Inc.	Semiconductors	Custom AI Processing / Memory

Before you send in your orders, take note: I have NO plans to trade these stocks unless they fit my preferred setups. This is only a watchlist.

The best traders watch more than they trade. That’s what I’m trying to model here. Pay attention to the work that goes in, not the picks that come out.

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Vertiv Holdings Co. (NYSE: VRT)

Vertiv is one of the most direct plays on the explosion in AI data center spending. The company makes infrastructure equipment like cooling systems, racks, and power management hardware—critical for supporting the high-performance servers that run artificial intelligence applications. In July 2025, Vertiv announced the acquisition of Great Lakes Data Racks & Cabinets for $200 million, showing aggressive expansion in the data storage solutions space.

The demand for advanced computing power continues to rise, and so does the need for supporting infrastructure. VRT has been gaining momentum as traders bet on higher capital expenditure from cloud service providers like Amazon, Microsoft, and Alphabet. Citi analysts recently raised the stock’s price target to $149, projecting continued revenue growth and performance improvements through 2026.

From my experience trading and teaching AI-related stocks, companies like Vertiv stand out because they sell the picks and shovels—the hardware needed to build the future. VRT’s broad portfolio and role in the global data center ecosystem make it a strong candidate for those looking to trade around this multi-year AI megatrend.

American Tower Corp. (NYSE: AMT)

American Tower is better known for wireless infrastructure, but the company has been expanding steadily into the data center market. With over 148,000 communication sites globally, AMT provides the kind of infrastructure needed to support both edge computing and AI workloads. Its ROBiN AI-powered material handling platform, launched in 2024, reflects its growing push into automation and machine learning for logistics and cloud storage.

This is a REIT with a predictable cash flow structure, but don’t assume it’s slow-moving. Mizuho recently raised its price target to $217, citing growth in tenant billing and a strong outlook in global markets. American Tower is building data storage capabilities to handle growing traffic from 5G, IoT, and AI-enabled devices.

I teach traders not to ignore REITs in the tech space, especially when they tie directly into AI infrastructure. AMT is one of the few companies combining long-term contracts, global reach, and AI-specific innovation. It’s a stock to watch for traders interested in lower volatility setups with sector exposure.

Micron Technology (NASDAQ: MU)

Micron has quietly become one of the strongest AI infrastructure plays this year. Its transformation from a cyclical memory producer to a key player in high-bandwidth memory (HBM) makes it a must-watch AI stock. In Q3 2025 (fiscal year, March–May), Micron delivered $9.3 billion in revenue, with over $6 billion coming from HBM, which is now central to powering AI models.

Read more: Micron Shines with Strong Earnings Forecast 

Bloomberg Intelligence projects HBM to grow from $4 billion in 2023 to $130 billion by 2033, and Micron is positioned to take significant market share. The company’s HBM4 chips are reportedly performing better than peers, and its customers include top-tier AI chipmakers like Nvidia and AMD. Despite a recent pullback in the share price, analysts like Mizuho reaffirmed a $150 price target based on long-term margin expansion and platform adoption.

From my trading experience, I look for companies that are shifting their business model to align with major sector trends. Micron is doing exactly that. The shift from commodity DRAM to AI-optimized chips could mean a rerating of the entire stock if execution holds.

NetApp (NASDAQ: NTAP)

NetApp offers enterprise-level data storage and cloud computing solutions. While it isn’t flashy, this company provides the storage systems that help run large AI models and applications. The stock trades at a forward P/E around 13.5, with projected full-year earnings of $7.72 per share and revenues near $6.74 billion.

Analysts are forecasting modest revenue growth, but a bigger focus is on NetApp’s ability to support hybrid cloud infrastructure. That’s increasingly important as businesses manage AI workloads across private servers and public cloud platforms. NTAP recently became a Zacks Rank #3 stock, meaning it’s showing signs of stable earnings and neutral sentiment—good conditions for trading breakouts or earnings catalysts.

In my teaching, I emphasize that traders shouldn’t chase hype every time. NTAP is a business with strong fundamentals and a foothold in a growing industry. When the rest of the market turns back to quality, stocks like this can quickly catch a bid.

Snowflake (NYSE: SNOW)

Snowflake isn’t a hardware company. It’s a platform for data storage, analytics, and machine learning applications, with a strong foothold in enterprise AI. The company posted 27.71% EPS growth and 24.57% revenue growth in the past year, driven by the continued demand for large-scale data processing and AI integration.

Under its new partnership with WNS Holdings, SNOW will have even more to offer. 

Traders should note that SNOW trades at a high multiple (Forward P/E over 190), so it’s priced for perfection. But this kind of volatility also creates opportunities. Whether you’re playing short-term options setups or looking for price-action trades around earnings, the consistent data growth trend gives SNOW recurring catalysts.

I don’t teach people to blindly hold high-P/E stocks. But if you’re trading high-momentum setups or looking for institutional movement around earnings or news events, Snowflake remains one of the strongest software names in the AI data center segment.

Digital Realty Trust Inc. (NYSE: DLR)

Digital Realty is a global REIT operating over 300 data centers across six continents. The company’s data center leasing and colocation services are key to cloud computing and enterprise AI expansion. With a $1.3 billion lease backlog and ongoing land purchases, DLR is gearing up for continued growth as data demand rises.

Analysts revised DLR’s FFO per share to $7.04 for 2025 and praised the company’s solid balance sheet. Zacks recently ranked it as a Buy, and the company is investing up to $3.5 billion into development activity this year alone. Despite rising competition, DLR’s diversified customer base and global footprint help secure consistent revenue.

Trading REITs requires a different strategy than growth tech stocks, but I include names like DLR when teaching students how to balance sector exposure with volatility. DLR’s high-quality tenants and expansion strategy give it room for upside, especially when cloud infrastructure demand surges.

GSI Technology Inc (NASDAQ: GSIT)

GSI Technology is a small-cap semiconductor company with a focus on AI workloads and custom memory solutions. The stock has soared over 60% in the last 30 days, driven more by sentiment than fundamentals. Revenue has been declining, and the company trades at a lofty 7x price-to-sales ratio—well above industry norms.

Right now, GSI’s financials don’t support the hype. But traders with experience in small-cap volatility will recognize these setups: huge price swings, news-driven momentum, and liquidity risk. If you’re day trading or swing trading and know how to handle fast movers, GSIT is a watchlist candidate—but it’s not for everyone.

I teach traders to understand the story behind the price. GSI may have long-term potential, but right now it’s a sentiment stock. Be fast, be smart, and manage risk tightly.

How to Evaluate AI Storage Stocks

Evaluating AI storage stocks starts with understanding what kind of storage they offer—hardware like SSDs and HDDs, or cloud-based data warehousing platforms. The second layer is market positioning: who are their customers, and how are they serving the AI workload boom? Are they selling to hyperscalers like Amazon and Microsoft, or targeting enterprise clients with smaller-scale infrastructure needs?

Look at metrics like revenue growth, gross margins, and sales momentum—especially from AI-related business units. Also examine forward guidance and capital expenditures. These numbers tell you whether the company is reinvesting in innovation or relying on legacy contracts. In my experience, traders who understand the business behind the ticker make better decisions with clearer risk/reward setups.

Focus on the fundamentals, but always stay flexible for momentum shifts.

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How is AI Shaping the Future of Cloud Storage?

AI is pushing cloud storage beyond simple data archiving and into dynamic, on-demand computing platforms. Workloads are getting larger and more complex. That requires higher throughput, lower latency, and more intelligent data management systems. Companies are scaling infrastructure not just for volume, but for speed and AI-specific applications.

This is where innovation matters. Technologies like HBM, liquid cooling, and AI-optimized SSDs are creating a new layer of competition. Companies that build infrastructure with machine learning in mind are winning contracts and growing their share. Traders should watch for signs of adoption—big client wins, new product rollouts, and increasing capex.

From a trading perspective, that means focusing on who’s enabling AI—not just who’s talking about it.

Risks and Challenges in Trading AI Storage Stocks

AI storage stocks can be volatile, speculative, and dependent on large customer deals. Valuations often run ahead of fundamentals, and small shifts in sentiment can lead to double-digit price moves. For traders, this means you have to be disciplined. Set stop losses. Don’t overleverage. And always respect market signals.

Another risk is supply chain and manufacturing delays, especially in hardware and semiconductors. AI demand might be rising, but if a company can’t fulfill orders, revenue stalls. Keep an eye on earnings calls, backlog data, and product rollouts. In my experience, the best setups come when you combine news, volume, and technicals.

You don’t need to chase every stock in this space. Wait for the setup, know your exit, and let the trade come to you.

Key Takeaways

• AI storage stocks are benefiting from the growth in cloud computing, machine learning, and data-heavy workloads.
• Vertiv, Micron, and Digital Realty stand out for their infrastructure-focused offerings and strong market positioning.
• Not all stocks in this category are equal—some are built on hype rather than performance. Know the difference.
• Use fundamentals, catalysts, and technical setups together. Don’t rely on one data point.

This is a market tailor-made for traders who are prepared. AI stocks thrive on volatility, but it’s up to you to capitalize on it. Stick to your plan, manage your risk, and don’t let FOMO drive your decisions.

These opportunities are fast and unpredictable, but with the right strategy, you can make them work for you.

If you want to know what I’m looking for—check out my free webinar here!

Frequently Asked Questions

What role do tech companies play in shaping the AI data storage market?

Tech companies are the main drivers of innovation in the data storage market, investing heavily in infrastructure to support artificial intelligence and machine learning workloads. Companies like MSFT, AMZN, and Google are building scalable platforms that depend on high-speed data access and cloud-native storage architecture. These investments create trading opportunities in both software and hardware providers aligned with next-generation AI requirements.

How should traders use analysis to evaluate profitability and growth potential in AI storage stocks?

Strong analysis involves looking at revenue trends, cost structure, and how efficiently a business converts capital into profitability. You want to identify stocks with consistent results that exceed market expectations, especially in high-demand segments like GPUs and cloud services. I teach traders to focus on measurable growth potential—if a stock can’t show improving margins or demand visibility, it’s usually a pass.

Are cloud services still a strong area of investment for AI-related returns?

Yes, cloud services continue to be a central area of investment due to rising demand for AI model training, storage, and deployment. Companies offering scalable infrastructure benefit from recurring revenue and long-term customer relationships, improving equity value and return potential. Traders should watch how cloud-native providers adapt to rising data usage and how that translates into improved financials.

How are assets and securities in the AI storage sector being priced today?

Assets tied to AI infrastructure, including data centers, chips, and software platforms, are seeing premium valuations relative to traditional tech securities. This is partly due to higher expected earnings, but also because of speculative capital flowing into high-growth sectors. I always tell traders to look at valuation against actual results—not just the story—especially when finance-driven bubbles start to form.

What influence does NVDA have on gpus and other AI infrastructure stocks?

NVDA remains the leader in GPUs designed for artificial intelligence, and its hardware sets the standard for processing power in AI environments. When NVDA reports strong results or offers bullish guidance, it often lifts related stocks with exposure to GPU-dependent applications. For traders, NVDA acts as a benchmark for AI hardware sentiment across the broader market.

How do investment strategy and capital allocation affect expected results in AI-focused stocks?

 Capital allocation reveals a lot—companies reinvesting into AI platforms, expanding storage capabilities, or acquiring infrastructure assets often signal confidence in future demand. The quality of an investment comes down to whether it can generate positive results, beat expectations, and show efficient use of capital over time. I’ve seen plenty of businesses burn cash chasing hype—solid returns come from disciplined execution.