저자: JamieDimon · 외국인
요약 보기
디몬은 AI가 자신의 커리어에서 가장 중요한 기술 변화라고 주장하며, 2026년에는 순수 AI 기업이나 과대평가된 테마주보다 AI 관련 매출을 입증한 기존 대기업이 유리할 것이라고 말합니다. 그는 매출 성장, 현금 흐름, 밸류에이션 배수(MSFT 약 28배, NVDA 약 35배, GOOGL 약 22배, TSMC 약 18배)를 근거로 마이크로소프트(Microsoft), 엔비디아(Nvidia), 알파벳(Alphabet), 아마존(Amazon), TSMC 등 다섯 개의 AI 주식을 추천합니다. 또한 기술 변화, 규제, 높은 밸류에이션 등 AI 관련 고유의 위험을 언급하면서, 기술 보유분의 10~15%를 이들 종목에 배분할 것을 제안합니다.
다듬은 글
You know, in my 40-plus years in banking, I've watched countless technology revolutions transform entire industries. From personal computers in the 1980s to the internet boom of the 1990s to mobile computing in the 2000s, each wave of innovation created both extraordinary opportunities and spectacular failures for investors.
Artificial intelligence represents the most significant technological shift I've witnessed in my career. At JP Morgan Chase, we're not just observers of the AI revolution, we're active participants. We spend over $15 billion annually on technology, employ thousands of engineers and data scientists, and use AI throughout our operations for everything from fraud detection to trading algorithms to customer service.
This experience gives us unique insight into which AI investments represent real business transformation versus which ones represent speculative hype. We work directly with every major technology company, finance AI infrastructure projects, and see firsthand which AI applications generate actual revenue versus which ones remain experimental concepts.
The AI investment landscape in 2026 is fundamentally different from the speculative environment of 2023 and 2024. The initial AI hype cycle has ended. Companies that promised AI transformation without delivering measurable results have been punished by markets. Investors now demand proof of AI revenue, not just AI promises.
This environment favors established technology companies with proven AI capabilities, substantial research and development resources, and existing customer relationships that can monetize AI services. It punishes pure-play AI companies with no revenue, startups dependent on venture funding, and companies that rebranded existing products as AI solutions.
Today, I want to share with you my five top AI stock picks for 2026. These aren't speculative bets on emerging AI technologies or attempts to pick the next open AI. These are investments in established companies that are successfully monetizing artificial intelligence while maintaining the financial discipline and competitive advantages that create long-term shareholder value.
These companies have survived AI hype cycle, demonstrated real AI revenue growth, and positioned themselves to benefit from the next phase of AI adoption without depending on unsust ainable valuations or speculative investor enthusiasm. My first AI stock pick for 2026 is Microsoft. Microsoft represents the perfect combination of AI innovation and business execution that separates real AI leaders from AI pretenders.
The company's partnership with open AI, integration of AI throughout their product portfolio, and Azure cloud platform position them to capture AI value across multiple revenue streams. At JP Morgan, we use Microsoft's AI services extensively, and we've observed how their AI integration creates real value for enterprise customers rather than just generating marketing headlines.
Microsoft Copilot embedded in Office applications genuinely improves productivity for knowledge workers in ways that justify subscription premium pricing. Microsoft's AI strategy is built around enhancing existing products rather than creating entirely new AI businesses. This approach provides immediate revenue from current customers while reducing the risk associated with unproven AI market segments.
Azure AI services generate substantial revenue from enterprise customers who need cloud-based AI capabilities without building their own infrastructure. Microsoft benefits from the massive capital requirements for AI infrastructure that favor established cloud providers over smaller competitors. The company's financial performance demonstrates successful AI monetization.
Microsoft's commercial revenue growth has accelerated since implementing AI features with customers paying premium prices for AI-enhanced productivity tools and cloud services. Microsoft generates over $65 billion in annual free cash flow, providing substantial resources for AI research and development while maintaining shareholder returns through dividends and share repurchases.
This financial strength allows aggressive AI investment without compromising financial stability. The current valuation of approximately 28 times earnings reflects the market's recognition of Microsoft's AI leadership while remaining reasonable for a company with such strong competitive positioning and cash flow generation.
Microsoft's AI capabilities extend beyond consumer applications into enterprise solutions that create sticky customer relationships and recurring revenue streams. Azure AI, Dynamics AI, and security AI services provide multiple growth vectors that reduce dependence on any single AI application. My second AI stock pick for 2026 is Nvidia.
Nvidia has established itself as the essential infrastructure provider for artificial intelligence, controlling over 80% of the AI chip market, and generating extraordinary returns from the AI boom. The company's graphics processing units have become the foundation for training and deploying AI models across every industry.
At JPMorgan, our quantitative trading and risk management systems rely on Nvidia hardware for machine learning applications. We've observed how Nvidia's CUDA software ecosystem creates switching costs that protect their market share even as competitors develop alternative AI chips. Nvidia's competitive advantage comes from their integrated hardware and software approach that makes their GPUs particularly efficient for AI workloads.
While competitors focus on individual components, Nvidia provides complete AI infrastructure solutions that are easier for customers to implement and scale. The company's data center business has experienced explosive growth with revenue increasing from $3 billion in 2020 to over $47 billion in 2024.
This growth reflects genuine demand for AI infrastructure rather than speculative investment in unproven technologies. Nvidia's financial performance has been exceptional with gross margins exceeding 70% and free cash flow growing from under $5 billion to over $35 billion annually. These metrics demonstrate pricing power and operational leverage that creates substantial shareholder value.
The company maintains substantial investment research and development spending over $8 billion annually on next generation AI technologies. This investment creates the innovation pipeline necessary to maintain technology leadership as AI markets evolve. Nvidia's expansion into software and services provides higher margin revenue streams that complement hardware sales.
AI enterprise software, Omniverse collaboration tools, and automotive AI solutions diversify revenue beyond pure chip manufacturing. The current valuation of approximately 35 times earnings reflects expectations for continued AI growth while providing reasonable value for investors who believe in sustained AI infrastructure demand over the next decade.
Nvidia also benefits from AI model training requirements that continue increasing in scale and complexity. Larger AI models require more computational power creating sustained demand for Nvidia's most advanced and profitable products. My third AI stock pick for 2026 is Alphabet Google. Alphabet represents the deepest AI research capabilities in the technology industry combined with multiple platforms for monetizing AI innovations.
Google search business provides massive data sets and revenue streams that fund AI development while creating barriers to entry for potential competitors. At JP Morgan, we use Google Cloud AI services for various applications and have observed how Google's AI capabilities extend far beyond search into cloud computing, advertising optimization, and productivity applications.
Google's AI strategy leverages their core competencies in data processing, machine learning, and algorithmic optimization across their entire business ecosystem. Search, advertising, cloud computing, and consumer applications all benefit from shared AI research and development. Google Cloud AI services compete directly with Microsoft and Amazon for enterprise customers who need AI capabilities without internal development resources.
Google's technical expertise and competitive pricing have gained market share in this rapidly growing segment. The company's Bard AI assistant and AI-enhanced search features provide new revenue opportunities while protecting their core search business from AI-powered competitors. Google's integration of AI into search maintains their dominant market position while improving user experience.
Alphabet generates over $70 billion in annual free cash flow, providing enormous resources for AI research and development. The company's other bets division includes AI-related investments in autonomous vehicles, healthcare, and other emerging technologies that provide optionality for future growth.
Google's advertising business benefits from AI-powered optimization that improves targeting and conversion rates for advertisers. This creates value for customers while increasing Google's revenue per advertisement, demonstrating how AI enhances existing business models. The current valuation of approximately 22 times earnings provides attractive value for a company with such dominant market positions and AI capabilities.
Alphabet trades at a discount to other major technology companies despite superior AI research and development resources. Alphabet's AI investments span the entire technology stack from custom AI chips to large language models to consumer applications, providing multiple opportunities for monetization as AI markets develop.
My fourth AI stock pick for 2026 is Amazon. Amazon's AI capabilities extend across their entire business ecosystem from AWS cloud services to consumer applications to logistics and supply chain optimization. The company's massive scale and data resources create competitive advantages in developing and deploying AI solutions.
At JP Morgan, we use Amazon web services for various applications and have observed how AWS AI services provide enterprise customers with sophisticated capabilities at competitive prices. Amazon's cloud infrastructure supports much of the AI development occurring across the technology industry. AWS AI services generate substantial revenue from customers who need AI capabilities without building their own infrastructure.
Amazon benefits from the massive capital requirements and technical complexity of AI development that favor established cloud providers. Amazon's consumer AI applications including Alexa voice assistants and recommendation algorithms generate value through improved customer experience and increased purchase frequency.
These applications demonstrate practical AI benefits for mainstream consumers rather than technical demonstrations for early adopters. The company's logistics and supply chain operations use AI extensively for inventory management, demand forecasting, and delivery optimization. These internal AI applications provide competitive advantages in e-commerce while demonstrating real-world AI value creation.
Amazon's advertising business increasingly relies on AI-powered targeting and optimization that improves results for advertisers while increasing Amazon's revenue per customer. This shows how AI enhances existing business models rather than requiring entirely new revenue streams. The company generates substantial free cash flow that funds both AI development and other growth initiatives.
Amazon's financial strength allows sustained investment in AI capabilities without compromising other business priorities. Amazon's expansion into AI-powered healthcare, automotive technology, and other industries provides multiple growth opportunities that leverage their core AI capabilities across different market segments.
The current valuation reflects expectations for continued growth across Amazon's various business lines while providing reasonable value for investors who believe in the company's ability to monetize AI innovations. My fifth AI stock pick for 2026 is Taiwan Semiconductor Manufacturing Company TSMC. TSMC represents the essential manufacturing infrastructure that enables all AI innovation.
The company produces the advanced semiconductors required for AI applications, creating a strategic bottleneck that generates pricing power and sustainable competitive advantages. At JP Morgan, our semiconductor analysts consider TSMC the most strategically important company in the global AI ecosystem.
The company's manufacturing capabilities are so advanced that they're essentially irreplaceable for producing the most sophisticated AI chips used by Nvidia, Apple, AMD, and other AI leaders. TSMC's competitive advantages come from their massive investments in manufacturing equipment and process technology.
The company spends over 35 billion annually on capital expenditures, creating barriers to entry that are virtually insurmountable for potential competitors. AI applications require the most advanced semiconductor manufacturing processes available, which currently only TSMC can produce at scale. This creates pricing power and customer dependence that generates consistent revenue growth even during semiconductor market downturns.
The company's customer relationships are extraordinarily strong because switching semiconductor manufacturers is extremely difficult and risky for technology companies. Long-term contracts and technical collaboration create predictable revenue streams that support consistent profitability. TSMC benefits from multiple AI trends simultaneously, increased AI chip demand, larger and more complex AI processors, and growing adoption of AI applications across consumer and enterprise markets.
The company's geographic expansion into the United States and other locations reduces concentration risk while maintaining manufacturing advantages that support long-term competitive positioning. From a financial perspective, TSMC generates substantial free cash flows and maintains conservative balance sheet management.
The company regularly returns capital to shareholders through dividends while investing in capacity expansion and technology development. TSMC trades at approximately 18 times earnings, which provides reasonable value for a company with such strategic importance and limited competition in advanced semiconductor manufacturing.
Now, let me explain how these five AI stocks work together to create comprehensive of exposure to AI opportunities while managing sector-specific risks. These companies provide exposure to different aspects of AI value creation: software applications, Microsoft; hardware infrastructure, Nvidia; cloud services, Alphabet, Amazon; and manufacturing, TSMC.
This diversification captures AI growth across multiple market segments while reducing dependence on any single AI technology or application. The portfolio also balances different AI investment approaches. Established companies with existing AI revenue, Microsoft, Alphabet, Amazon, and infrastructure providers that enable AI development, Nvidia, TSMC.
This combination provides current AI profitability with exposure to continued AI infrastructure growth. Geographic diversification through TSMC provides exposure to Asian technology leadership while maintaining focus on companies with global market reach and competitive advantages that transcend regional economic conditions.
These companies also have complementary relationships that strengthen each other's competitive positions. Microsoft and Amazon compete in cloud services, but are both customers of Nvidia and TSMC. Google competes with Microsoft in productivity applications, but relies on similar semiconductor infrastructure.
At JP Morgan, when we construct AI portfolios for institutional clients, we emphasize exactly these characteristics: diverse AI exposure, proven revenue generation, relative to growth prospects. I also want to address the risks involved in AI investing because this sector remains volatile and subject to significant technological and competitive uncertainties.
AI technology evolution could render current approaches obsolete or reduce the competitive advantages of established companies. New AI architectures, quantum computing, or other technological developments might disrupt existing AI leaders. Regulatory risks are increasing as governments worldwide consider AI safety regulations, antitrust enforcement, and technology export restrictions that could affect AI company operations and profitability.
Competition in AI markets is intensifying as more companies develop AI capabilities and seek to capture AI value. Maintaining competitive advantages requires continuous innovation and substantial investment with uncertain returns. Economic downturns could reduce enterprise AI spending and delay AI adoption timelines, creating temporary headwinds for AI investments even if long-term trends remain positive.
AI market valuations remain elevated compared to traditional technology companies, creating risks if AI adoption occurs more slowly than currently anticipated by investors. Despite these risks, I believe AI investing is essential for technology-focused portfolios because artificial intelligence is transforming every industry and creating new sources of competitive advantage that will persist for decades.
The companies I've recommended have demonstrated their ability to generate real AI revenue rather than just AI promises. They've survived the initial AI hype cycle and proven they can monetize AI innovation through established business models and customer relationships. For investors building AI exposure for 2026, I recommend allocating 10% to 15% of technology holdings to these five companies with weightings based on individual risk tolerance and investment objectives.
The AI revolution is still in its early stages, but the companies that will capture most of the value are already identifiable. They're the established technology leaders with the resources, capabilities, and customer relationships necessary to translate AI innovation into sustainable profitability.
These five AI stocks, Microsoft, Nvidia, Alphabet, Amazon, and TSMC represent my highest conviction ideas for investors who want meaningful AI exposure without excessive speculation or risk. The next phase of AI development will favor companies that can execute AI strategies profitably rather than companies that simply promise AI transformation.
The five companies I've recommended today have already demonstrated this execution capability while positioning for continued AI growth.
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