10 AI Stocks I'd Buy Without Hesitation
Artificial intelligence (AI) is creating the greatest investment opportunity of our generation.
These 10 stocks dominate critical segments of the AI value chain.
Each company has defensible market positions and accelerating revenue growth.
10 stocks we like better than Nvidia ›
Artificial intelligence (AI) has reached an inflection point where early leaders are separating from the pack, creating exceptional investment opportunities across the AI value chain. From semiconductor giants to software innovators, the winners in this space offer compelling multiyear growth stories as AI transforms from experimental technology to business necessity. Smart positioning in quality AI stocks today could deliver strong returns as this technology reshapes every industry over the next decade.
The AI revolution is accelerating beyond even optimistic forecasts. Companies successfully harnessing AI are seeing dramatic improvements in productivity and customer outcomes, while those ignoring it risk obsolescence. The total addressable market reaches into the trillions, yet adoption remains early. This creates a rare window for investors to position themselves before the masses recognize AI's full potential.
I've analyzed dozens of AI-related companies to identify those with sustainable competitive advantages and clear monetization paths. These 10 stocks offer diversified exposure across infrastructure, software, and applications. Each brings unique strengths to the AI ecosystem, and I'd confidently buy any at current level for long-term holdings.
Nvidia (NASDAQ: NVDA) controls between 70% to 90% of the data center graphics processing unit (GPU) market, making its GPUs the industry standard for training large language models. The investment case rests on CUDA's decade-long ecosystem advantage, creating high switching costs.
In Q1 of fiscal 2026, Nvidia reported record revenue of $44.1 billion, with data center revenue reaching $39.1 billion, a 73% increase year over year. Despite a $4.5 billion charge related to unsellable H20 GPUs due to U.S. export restrictions to China, Nvidia's dominance in AI infrastructure remains unchallenged.
ASML Holding (NASDAQ: ASML) manufactures the only extreme ultraviolet lithography machines capable of producing cutting-edge semiconductors, giving it the lion's share of the market for this critical technology. The company's substantial backlog provides multiyear revenue visibility, while research and development spending of around 4.3 billion euros annually maintains its technological moat. As AI drives demand for more advanced chips, ASML benefits, regardless of which chipmaker wins, making it a defensive play on AI infrastructure growth.
Microsoft (NASDAQ: MSFT) monetizes AI through proven channels, with Copilot subscriptions already generating billions in annualized revenue just months after launch. The company's advantage lies in distribution: 1.5 billion Office users worldwide and a dominant Azure cloud position enable rapid AI deployment at scale. Microsoft's track record of successfully monetizing new technologies through existing customer relationships reduces execution risk, while AI integration across all products drives pricing power.
Lemonade (NYSE: LMND) uses AI throughout insurance operations to slash costs and improve customer experience, with 70% of claims processed instantly without human intervention. The company's loss ratios have improved dramatically as its algorithms learn from expanding data sets, while operational expenses remain a fraction of traditional insurers.
As Lemonade scales into auto insurance and other verticals, its AI-first approach creates structural advantages that legacy carriers cannot replicate without rebuilding from scratch.
SoundHound AI (NASDAQ: SOUN) provides voice AI technology to major automotive and restaurant brands, with revenue growing over 80% annually and gross margins expanding toward software-industry standards. The company's edge-computing approach processes voice on-device, addressing privacy concerns while reducing latency. Recent customer wins include multiple top 10 automakers and expanding restaurant chains, validating the technology as voice interfaces become standard across industries.
Palantir Technologies (NASDAQ: PLTR) leverages two decades of classified government work to build AI platforms now driving over 70% annual commercial revenue growth. The company's Artificial Intelligence Platform (AIP) enables enterprises to deploy large language models on private data, addressing the security concerns limiting corporate AI adoption. With government contracts providing a stable base of revenue and commercial acceleration, Palantir offers both growth and stability in the emerging AI landscape.
Applied Digital (NASDAQ: APLD) operates purpose-built data centers for high-performance computing, with facilities designed specifically for AI workload requirements, including advanced cooling and power density. The company has secured long-term contracts with Tier-1 customers for its entire 400MW capacity, providing predictable revenue growth. As AI compute demand outstrips supply, Applied Digital's specialized facilities command premium pricing, while its 2GW-plus development pipeline positions it for sustained growth.
Oklo (NYSE: OKLO) develops small modular reactors addressing AI data centers' massive energy requirements, with each reactor designed to provide 15MW to 50MW of clean baseload power. Recent regulatory streamlining and partnerships with data center operators validate the business model as tech companies seek carbon-free energy sources. The company's recycled fuel approach and compact design offer economic advantages over traditional nuclear energy, positioning it to benefit from AI's growing energy demands.
CoreWeave (NASDAQ: CRWV) specializes in GPU-accelerated cloud computing, offering AI-optimized infrastructure that major AI companies use for training and inference. The company is projected to generate $5 billion in revenue for 2025, with analysts expecting revenue to more than double to $11.6 billion in 2026 -- a 130% growth rate that validates its AI-first strategy. With established relationships serving leading AI labs and better GPU availability than most hyperscalers, CoreWeave has carved out a defensible niche in the fast-growing AI infrastructure market.
BigBear.ai (NYSE: BBAI) applies AI to defense and commercial analytics, with expertise in computer vision and predictive modeling for mission-critical applications. The company reported Q1 2025 revenue of $34.8 million with 5% year-over-year growth and maintains a $385 million backlog, providing long-term revenue visibility. Recent contract wins in supply chain optimization and defense analytics demonstrate the value of specialized AI applications in regulated industries where accuracy and explainability matter most.
These 10 stocks represent different layers of the AI ecosystem, from essential infrastructure to specialized applications. While AI investments are inherently volatile, each company demonstrates strong fundamentals, defensible market positions, and clear paths to sustainable growth. The convergence of technological capability, enterprise adoption, and massive addressable markets creates a compelling long-term opportunity for patient investors.
Before you buy stock in Nvidia, consider this:
The Motley Fool Stock Advisor analyst team just identified what they believe are the for investors to buy now… and Nvidia wasn't one of them. The 10 stocks that made the cut could produce monster returns in the coming years.
Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you'd have $656,825!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you'd have $865,550!*
Now, it's worth noting Stock Advisor's total average return is 994% — a market-crushing outperformance compared to 172% for the S&P 500. Don't miss out on the latest top 10 list, available when you join .
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*Stock Advisor returns as of June 2, 2025
George Budwell has positions in Lemonade, Microsoft, Nvidia, and Palantir Technologies. The Motley Fool has positions in and recommends ASML, Lemonade, Microsoft, Nvidia, and Palantir Technologies. The Motley Fool recommends the following options: long January 2026 $395 calls on Microsoft and short January 2026 $405 calls on Microsoft. The Motley Fool has a disclosure policy.
10 AI Stocks I'd Buy Without Hesitation was originally published by The Motley Fool
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They operate probabilistically. They interpret nuance. They guess what you meant. They decide how to respond based on what they know about you, about the world, and about the constraints you've given them. In other words, they operate in context, and the quality of that context determines the quality of every outcome. That's the revolution. Not faster chips. Not smarter models. Context as compute. Of course, context isn't a panacea. Bad context leads to brittle systems that overfit or misfire. And without transparency, it's nearly impossible to audit why a model made the decision it did. Precision must be earned—and constantly recalibrated. Brain-computer interfaces are no longer science fiction. The distance between intent and action is shrinking fast, and we're nearing a moment when you won't need to type, tap, or even speak. You'll think. The machine will act. In that world, there is no interface. No menus. No 'are you sure?' confirmation screen. Your brain becomes the input layer. And the system, if not fully aligned, becomes dangerous in its fluency. What disappears with conversation is not just UX—it's friction, correction, negotiation. When your mind sends a signal, there's no time to clarify. No chance to restate. No contextual cues, such as facial expressions or tone. The system must already know your preferences, values, limitations, and goals before executing anything on your behalf. This isn't just a shift in interaction; it's a fundamental change. It presents a profound challenge to accountability, regulation, and trust. If something goes wrong—if the system misunderstands your intent or violates your consent—what will we audit? There is no transcript. No written instructions. Only context. In healthcare, the stakes couldn't be higher. Imagine a BCI-enabled system monitoring your neurological signals to adjust a medication or initiate treatment. There's no margin for guesswork. The model must operate within a context grounded in clinical rules, patient history, and real-time consent. That's not just context—it's compliance by design. Commercially, this shifts how choices are made. You won't comparison-shop. You won't click. You'll express a need, and the system will fulfill it. If your brand isn't context-aware, it won't even be part of the decision. Marketing becomes metadata. Preference becomes architecture. This is why Model Context Protocol isn't just a technical spec, it's a governance framework. A way to encode not just what a machine can do, but what it should do, under the terms set by the human it serves. When conversation disappears, context becomes everything. And MCP is what keeps that context aligned, auditable, and human-centered. Today, OpenAI owns your context inside ChatGPT. Apple is building a closed-loop context layer around Siri. Google is doing the same with Gemini. Meta? They're still trying to get back in the room. 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The future will depend on whether MCP becomes open, auditable, and user-governed, or whether context becomes the new extraction layer, just hidden behind predictive convenience. Because whoever controls that layer will influence: Context, not code. That's the new dividing line. Code tells machines what to do. Context tells them who they are. And when the machine acts on your behalf, only one of those matters. This is the new terrain for design, ethics, infrastructure, and sovereignty. Not smarter prompts. Not flashier apps. Contextual scaffolding for autonomous execution. In a world where consumers no longer tap, scroll, or search, brand visibility doesn't disappear—but it evolves. When decisions are made by AI systems interpreting context rather than by users navigating menus, brands must shift their focus from front-end design to contextual presence. That means designing for discovery within the system. If the AI is selecting the best option based on your price sensitivity, behavior, or preferences, then the question becomes: Are you structured to be chosen? The brand battle won't happen on screens. It will occur in context layers that determine what is relevant, helpful, and aligned. To win, brands need to think like structured data and act like trusted proxies. HTTP created the Web. MCP for AI will make the next layer: A world where intent flows invisibly through invisible systems. Where cognition, not clicks, defines our digital lives. And where proximity to context, not placement on a screen, determines which ideas, brands, and actions win. If you're still designing for the app economy, you're already behind the curve—design for context. Or disappear into someone else's. The future of AI won't be written in screens, apps, or even prompts. It will be written in the invisible thread of context—what systems remember, how they align, and who they serve. If you're not designing for context, you're not designing for the future of AI; you're defaulting to someone else's.
