An Investor's Guide to the Artificial Intelligence (AI) Value Chain

The artificial intelligence (AI) revolution extends far beyond chatbots and automation to fundamentally restructure information processing, decision-making, and infrastructure development. According to International Data Corporation, total global spending on AI could reach $500 billion in 2024. However, capturing this potentially once-in-a-lifetime investment opportunity requires understanding how each segment of the AI value chain enables and amplifies the next.

This comprehensive view of the AI value chain, from the foundational computing power to the transformative applications, provides important context for investors to assess the broader impact and strategic implications of the AI revolution. The story is no longer just speculation-real-world deployments are already under way, as evidenced by Japan's recently announced partnership between Nvidia (NASDAQ:NVDA) and its third largest telecom, SoftBank. This initiative is designed to accelerate the build of AI infrastructure across the nation's robotics, automotive, healthcare, and telecom industries, representing an early test case of this complete value chain in action.

Image Source: Getty Images.

While the Japan example offers an interesting glimpse into how the AI value chain can be deployed at scale, the broader story is one of interdependence and synergy, where advancements in one area unlock new possibilities in the next. Understanding this interconnected landscape is essential for investors to identify opportunities and mitigate risks as artificial intelligence unfolds across industries in the years ahead.

So let's dive deeper into the foundational elements of the AI revolution, from processing power to algorithm development to real-world applications. Identifying the innovators and leaders within each layer of the value chain will equip investors with the insights needed to capitalize on this technological transformation. And for those seeking broader exposure, we'll also explore the 10-leading AI-themed exchange-traded funds (ETFs) that could provide diverse and efficient ways to invest in this burgeoning space.

Computing foundations

The AI revolution starts with raw computing power. Nvidia dominates the AI chip market with an estimated 80% to 95% share in AI accelerators, according to multiple analysts. The company's H100 Graphics Processing Unit (GPU), which sells for up to $40,000 per unit, has become the de facto standard for training large language models. Through the first three quarters of fiscal 2025, Nvidia's data center revenue reached nearly $80 billion, with Q3 alone generating $30.8 billion, underscoring the enormous demand for the chipmaker's AI-capable GPUs.

Advanced Micro Devices (AMD) (NASDAQ:AMD) has emerged as a credible challenger with its MI300 accelerators, which combine CPU and GPU capabilities in a single chip. Early benchmarks suggest performance competitive with Nvidia's offerings at potentially lower power consumption. While AMD currently holds less than 10% market share, major cloud providers including Microsoft (NASDAQ:MSFT) and Meta Platforms have announced plans to deploy MI300 chips.

Intel (NASDAQ:INTC) pursues a multipronged AI strategy. Its Gaudi 3 AI accelerators target cost-sensitive customers, while its next-generation Meteor Lake CPUs incorporate neural processing units for on-device AI. The company's Intel Foundry Services division aims to capture part of the AI chip manufacturing market, backed by tends of billions in new facility investments over the past few years.However, Intel has struggled to execute on this plan quickly enough, leading to disappointing quarterly results and the recent departure of former CEO Pat Gelsinger.

Taiwan Semiconductor Manufacturing Company (NYSE:TSM) manufactures most of these advanced processors, including Nvidia's H100 and AMD's MI300. Its planned transition to 2nm manufacturing in 2025 signals continued advancement in processing capabilities and manufacturing expertise.

The broader AI chip market extends beyond traditional processors. Broadcom (NASDAQ:AVGO) specializes in networking chips crucial for connecting AI systems, while Marvell (NASDAQ:MRVL) develops custom AI accelerators for specific applications such as automotive and 5G infrastructure.

Lam Research (NASDAQ:LRCX) provides critical semiconductor manufacturing equipment, specifically for etching and deposition processes essential to producing advanced AI chips.

Nebius Group (NASDAQ:NBIS), formerly known as Yandex, has transformed into a full-stack AI infrastructure company located in Europe. Its AI-centric cloud platform is designed for intensive workloads, while also providing data services through Toloka AI and autonomous driving technology through Avride. The company's GPU clusters and developer tools, combined with R&D hubs across Europe, North America and Israel, position it as a significant player in the AI infrastructure landscape, particularly in Europe.

Here's a look at the 2024 stock performance in the computing foundations segment.

Performance data covers Jan. 1 to Dec. 6, 2024.

Power infrastructure demands

The exponential growth in AI computing creates unprecedented energy challenges. According to current estimates, data centers currently consume approximately 2% of U.S. electricity, and this figure is projected to balloon to 4% by 2026, with AI workloads demanding significantly more power than traditional computing tasks. This surge in power consumption has reignited interest in nuclear energy solutions, particularly the advanced reactor designs being developed by companies such as Oklo (NYSE:OKLO) and NuScale Power (NYSE:NU).

Constellation Energy (NASDAQ:CEG) leads the traditional nuclear market with its existing fleet of high-capacity reactors, positioning it well for near-term AI power demands. Meanwhile, Oklo's compact fast reactor design and NuScale's small modular reactor technology target the distributed power needs of future data centers. The International Atomic Energy Agency projects first commercial small modular reactor operations could begin around 2030, when companies like NuScale and Oklo expect to achieve commercial deployment.

Image Source: Getty Images.

The AI power challenge creates opportunities for investors across nuclear energy companies. Constellation Energy offers stable returns with AI-driven growth potential through its established nuclear fleet, while next-generation providers like Oklo and NuScale present higher-risk opportunities in potentially transformative technologies. The critical nature of power infrastructure for AI deployment suggests sustained demand for reliable, carbon-free nuclear power solutions.

Here's a look at the 2024 stock performance in the AI energy and infrastructure segment.

Performance data covers Jan. 1 to Dec. 6, 2024.

Software development and cloud infrastructure

The AI revolution has transformed how software is built and deployed. GitLab (NASDAQ:GTLB) and JFrog (NASDAQ:FROG) provide the foundational tools developers use to create AI applications, while companies such as SoundHound AI (NASDAQ:SOUN) build specialized AI solutions on top of this infrastructure. This creates a two-tiered investment opportunity: the tools that enable AI development and the specialized AI applications themselves.

The cloud giants demonstrate how this plays out at scale. Microsoft's Azure OpenAI integration has driven significant revenue growth, while Amazon (NASDAQ:AMZN) leverages Amazon Web Services to power both internal AI development and external customer solutions. Alphabet's (NASDAQ:GOOGL) Google Cloud differentiates through its AI research division DeepMind, creating unique enterprise solutions.

Data infrastructure companies represent another crucial link in the AI value chain. Snowflake (NYSE:SNOW) has evolved from data warehousing to become a crucial AI development platform, with its latest Data Cloud innovations enabling enterprises to build and deploy AI models directly on their data. MongoDB (NASDAQ:MDB) provides a flexible document database architecture that matches how AI applications process information, with its Atlas platform becoming the preferred choice for many top companies building AI applications.

Here's a look at the 2024 stock performance in the AI software and cloud computing segment.

Performance data covers Jan. 1 to Dec. 6, 2024.

Enterprise solutions

The enterprise AI market represents one of the clearest paths to monetization in the entire AI value chain. Palantir Technologies (NASDAQ:PLTR) demonstrates this through its AIP platform, where customers pay for concrete business outcomes rather than experimental AI implementations.

While early AI adopters focused on research and development, companies now demand solutions directly affecting their bottom line. This shift benefits companies such as C3.ai (NYSE:AI) and UiPath (NYSE:PATH), which focus on industry-specific solutions and measurable business results.

Here's a look at the 2024 stock performance in the AI-enterprise solutions segment.

Performance data covers Jan. 1 to Dec. 6, 2024.

Quantum computing

Think of quantum computing as a long-term call option on the future of AI processing. While classical computers struggle with certain types of calculations crucial for AI, quantum computers might solve them exponentially faster.

D-Wave Systems (NYSE:QBTS), IonQ (NYSE:IONQ), and Rigetti (NASDAQ:RGTI) offer different approaches to this future. The risk-reward proposition here mirrors early semiconductor investments -- high uncertainty but massive potential upside if the technology achieves its promised breakthroughs.

Here's a look at the 2024 stock performance in the quantum computing segment.

Performance data covers Jan. 1 to Dec. 6, 2024.

Healthcare transformation

Healthcare represents a trillion-dollar industry ripe for AI disruption, with clear regulatory pathways to monetization. Recursion Pharmaceuticals (NASDAQ:RXRX) shows how AI can transform the economics of drug discovery: Instead of betting on single molecules, investors gain exposure to a platform that could accelerate the entire drug development process. Butterfly Network (NYSE:BFLY) takes a different approach, using AI to make medical imaging more accessible and affordable.

Here's a look at the 2024 stock performance in the healthcare AI specialist segment.

Performance data covers Jan. 1 to Dec. 6, 2024.

Autonomous systems and robotics

The robotics industry demonstrates AI's real-world impact through multiple approaches. Tesla (NASDAQ:TSLA) leads in consumer autonomous-driving data collection, with over a billion miles of data on its Full Self-Driving beta feature. Aurora Innovation (NASDAQ:AUR) focuses on autonomous trucking, targeting commercial routes with its Aurora Driver platform.

In the robotics space, Symbotic (NASDAQ:SYM) transforms warehouse operations through AI-powered automation, securing contracts with major retailers including Walmart. Serve Robotics (NASDAQ:SERV) specializes in autonomous last-mile delivery, while Kraken Robotics (OTC:KRKN.F) applies AI to underwater robotics for defense and commercial applications.

Here's a look at the 2024 stock performance in the autonomous systems and robotics segment.

Performance data covers Jan. 1 to Dec. 6, 2024.

Defense and security

The escalating AI arms race between the U.S. and China has created a new paradigm in defense spending. China's stated goal of AI military supremacy by 2030 has triggered increased Western investment in AI defense capabilities. Lockheed Martin (NYSE:LMT) sits at the forefront of this response, with the F-35 program increasingly incorporating AI for autonomous operations and threat detection.

Smaller defense contractors offer targeted exposure to this technological competition. Kratos Defense & Security Solutions (NASDAQ:KTOS) specializes in autonomous systems and AI-enabled drones, positioning it to benefit from the military's push toward unmanned platforms. BlackSky (NYSE:BKSY) provides another crucial capability in this AI arms race, using machine learning to analyze satellite imagery for military and intelligence applications.

For investors, the U.S.-China AI rivalry creates a unique opportunity. The Pentagon's newly announced Advancing AI Multiple Award Contract, potentially worth $15 billion over the next decade, demonstrates the scale of military AI adoption. This contract aims to expand the Department of Defense's Advana data analytics platform while providing AI capabilities across all DoD organizations.

Here's a look at the 2024 stock performance in the AI-defense and security segment.

Performance data covers Jan. 1 to Dec. 6, 2024.

AI-theme ETF opportunities

ETFs provide multiple options for investors seeking a broader exposure to the AI value chain with reduced single-company risk. These funds offer diversification across companies and segments while requiring less active management than individual stock selection. These funds also typically provide exposure to most of the elements comprising the AI value chain, giving investors a straightforward and cost-effective way to participate in this powerful trend.

Following is a list of 10 of the best-performing AI-themed ETFs in 2024 with net assets exceeding $200 million at the time of this writing, along with their corresponding expense ratios.

Performance data covers Jan. 1 to Dec. 6, 2024

Key takeaways and performance analysis

The AI revolution has reshaped traditional market dynamics through three transformative themes in 2024: the fierce competition for compute infrastructure dominance, the accelerating drive to monetize enterprise AI, and the widespread adoption of AI-powered automation. Market performance reflects these themes, with infrastructure leader Nvidia gaining 187.6% and enterprise pioneer Palantir soaring 344.6% so far this year.

The battle for AI computing extends far beyond semiconductors, creating unexpected winners in adjacent industries such as nuclear power generation, where companies such as Constellation Energy and Oklo have captured gains exceeding 100% amid surging data center power demands. Enterprise AI solutions demonstrate the clearest path to commercialization, as businesses rapidly adopt tools that deliver measurable operational improvements.

AI-powered automation represents perhaps the broadest opportunity, transforming industries from manufacturing to healthcare. This transformation spans everything from Symbotic's warehouse robots to Recursion's AI-driven drug discovery platforms, showing how AI reshapes traditional operations across every major industry vertical.

AI-themed ETFs have also delivered exceptionally strong performance, gaining 27.2% on average this year, though still trailing the outsize returns of leading individual stocks such as Nvidia, Palantir, and SoundHound AI. This enormous performance gap highlights a crucial dynamic: While ETFs offer safer broad-based exposure to the AI revolution, the most significant opportunities undoubtedly lie in individual companies operating at the leading edge of this technological and societal transformation.

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John Mackey, former CEO of Whole Foods Market, an Amazon subsidiary, is a member of The Motley Fool's board of directors. Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool's board of directors. Randi Zuckerberg, a former director of market development and spokeswoman for Facebook and sister to Meta Platforms CEO Mark Zuckerberg, is a member of The Motley Fool's board of directors. George Budwell has positions in IonQ, Kratos Defense & Security Solutions, Lockheed Martin, Microsoft, Nvidia, Palantir Technologies, SoundHound AI, Taiwan Semiconductor Manufacturing, Vanguard World Fund-Vanguard Information Technology ETF, and Walmart. The Motley Fool has positions in and recommends Advanced Micro Devices, Alphabet, Amazon, GitLab, Intel, Kraken Robotics, Lam Research, Meta Platforms, Microsoft, MongoDB, Nebius Group, Nvidia, Palantir Technologies, Serve Robotics, Snowflake, Taiwan Semiconductor Manufacturing, Tesla, UiPath, Walmart, and iShares Trust-iShares Semiconductor ETF. The Motley Fool recommends Broadcom, C3.ai, Constellation Energy, JFrog, Lockheed Martin, Marvell Technology, and Nu Holdings and recommends the following options: long January 2026 $395 calls on Microsoft, short February 2025 $27 calls on Intel, and short January 2026 $405 calls on Microsoft. The Motley Fool has a disclosure policy.