What Are the AI Stocks? How to Identify Top Companies

Artificial intelligence (AI) represents technologies enabling machines to perform functions typically associated with human intelligence, such as learning, reasoning, and problem-solving. This includes understanding language, analyzing data, and making recommendations. AI is deeply integrated into various industries, transforming operations and creating new possibilities. Investing in companies at the forefront of this technological shift has become a significant area of interest. This article explores what constitutes an AI stock, how to identify companies contributing to the AI landscape, and different approaches to gaining exposure to these businesses.

Understanding AI Stocks

An “AI stock” refers to a company whose core business, products, or services are fundamentally driven by or directly contribute to the development of artificial intelligence. This distinguishes them from companies that merely use AI as a tool. For example, a bank using AI for fraud detection is not primarily an AI stock; a company creating AI algorithms or specialized hardware for AI computation is.

AI stocks can be categorized based on their primary contribution to the AI ecosystem.

AI Hardware and Infrastructure

This category includes companies developing specialized chips, such as Graphics Processing Units (GPUs) and Tensor Processing Units (TPUs), essential for processing AI workloads. These companies also provide the underlying cloud infrastructure that supports AI development and deployment.

AI Software and Platforms

This segment encompasses businesses that create AI development tools, machine learning platforms, large language models (LLMs), or operating systems designed specifically for AI applications.

AI Applications and Services

This category comprises companies integrating AI directly into their core products or providing AI-powered solutions to other businesses. This can include AI-driven analytics, computer vision systems, or natural language processing applications.

Data Providers and Aggregators

These companies collect, process, and supply the extensive datasets necessary to train and validate AI models. These datasets are crucial for the learning capabilities of advanced AI systems.

Key Sectors and Companies

AI is making a notable impact across various industries. In AI hardware and infrastructure, NVIDIA leads in GPU development, essential for training complex AI models. Taiwan Semiconductor Manufacturing Company (TSMC) manufactures chips for major AI players. Intel and Advanced Micro Devices (AMD) also develop processors with AI acceleration features.

Within AI software and platforms, Alphabet (Google’s parent company) develops AI models and offers cloud platforms like Google Cloud, which provide AI services and custom-designed TPUs. Microsoft’s Azure cloud platform offers extensive AI capabilities and tools. IBM has also developed specialized AI chips and platforms.

For AI applications and services, Amazon integrates AI into its e-commerce operations and cloud services through Amazon Web Services (AWS). Adobe utilizes AI within its creative software suite, enhancing functionalities like content creation.

AI’s influence extends across numerous broader industry sectors. In healthcare, AI transforms diagnostics, personalizes patient care, and optimizes operations. The financial services sector uses AI for risk modeling, fraud detection, and algorithmic trading. The automotive industry applies AI in autonomous vehicles, while manufacturing uses AI for automation and predictive maintenance.

Identifying AI-Driven Companies

Identifying companies with a substantive focus on artificial intelligence requires a methodical approach. One way to begin is by examining a company’s public filings and reports. Annual reports, such as the Form 10-K filed with the Securities and Exchange Commission (SEC), often contain discussions of a company’s strategic initiatives and research and development (R&D) spending. These documents can be accessed through the SEC’s EDGAR database or the investor relations section of a company’s website.

Within these filings, look for mentions of AI, machine learning, deep learning, or related terms in the “Business” section. The “Risk Factors” section can highlight dependencies on AI technologies. The “Management Discussion and Analysis” (MD&A) often details investments in new technologies like AI. Analyzing earnings call transcripts and investor presentations can also reveal management’s strategic priorities and AI-related investments.

Assessing a company’s product and service focus is another important step. Determine if AI is central to its main offerings rather than a peripheral feature. Look for products explicitly marketed as “AI-powered” or services that rely heavily on AI algorithms.

The composition of a company’s leadership and talent pool can also indicate its commitment to AI. The presence of AI experts, data scientists, and machine learning engineers suggests a strategic emphasis on AI development. Hiring trends, particularly an increase in AI-related job postings, can signal expansion. Strategic partnerships with AI leaders or acquisitions of AI startups demonstrate a company’s intent to expand AI capabilities. Finally, analyzing revenue streams to determine if a significant portion is directly generated from AI products or services provides a tangible measure of a company’s AI focus.

Approaches to Investing in AI

Several practical investment approaches are available for individuals seeking exposure to AI stocks.

Individual Stock Ownership

This direct method involves purchasing shares of specific companies with a strong AI focus. This typically involves opening a brokerage account online. To open an account, individuals generally need to provide personal information. Many online brokers offer commission-free trading and may not require a significant minimum initial deposit.

ETFs and Mutual Funds

Another common approach is investing in Exchange-Traded Funds (ETFs) or mutual funds that focus on artificial intelligence. ETFs hold a diversified basket of securities and trade on stock exchanges like individual stocks. Many ETFs track indices or sectors, including AI, providing diversified exposure to multiple AI-related companies in a single investment. Mutual funds pool money from many investors to purchase a portfolio of securities; they are typically managed by professionals and trade once a day. Both offer diversification and professional management, potentially reducing the risk associated with investing in single stocks.

Robo-Advisors

Robo-advisors offer an automated approach to investing in AI-themed portfolios. These digital platforms use algorithms to provide financial planning and investment management services. After an investor answers questions about their financial situation and goals, the robo-advisor constructs and manages a diversified portfolio, often consisting of low-cost ETFs. Robo-advisors typically offer lower fees compared to traditional financial advisors and often have low or no minimum balance requirements. When choosing an investment platform, consider factors such as fees, investment selection, and customer service.