August 7, 2025
Artificial intelligence (AI) has rapidly evolved from a niche technology to a foundational force shaping nearly every major industry in the U.S. economy. Given the scale of investment, breadth of adoption, and the distinct economics of AI business models, there is a compelling case for creating a standalone AI sector within widely used classification systems such as the Global Industry Classification Standard (GICS). Doing so would not only improve transparency for investors and policymakers, but also better reflect the economic reality of a technology reshaping global value chains.
According to the 2025 AI Index Report from Stanford’s Institute for Human-Centered Artificial Intelligence, global corporate investment in AI reached $252.3 billion in 2024, up more than 13-fold from 2014 levels. This massive increase in capital deployment reflects not just the growth of AI-native firms, but also widespread adoption across sectors traditionally considered outside the tech domain. For instance, the McKinsey & Company “State of AI in 2024” survey found that over 60% of companies in technology, financial services, and healthcare are now using AI in core operations. Adoption is growing steadily in retail, logistics, manufacturing, and professional services as well.
Spending by the largest U.S. firms further underscores the outsized role AI now plays in corporate strategy. The Washington Post reports that Microsoft, Amazon, Meta, and Alphabet are expected to spend more than $400 billion between 2024 and 2026 on AI-related infrastructure, including chips, model development, and cloud capacity. IOT Analytics estimated that AI-related data center capital expenditure reached $125 billion in 2024 alone, with Nvidia controlling over 90% of the GPU market enabling these systems. These figures not only dwarf prior IT investment cycles but also highlight how the nature of AI’s cost structure—requiring massive compute and data infrastructure—sets it apart from traditional software and IT services.
While many of these AI investments are currently embedded within broader GICS sectors like Information Technology, Communication Services, and Health Care, the business models and capital dynamics of AI companies are fundamentally different. As noted in the 2023 article The New Business of AI, AI firms often rely on vertically integrated stacks, model-as-a-service revenue, and a dependence on foundational model infrastructure, distinguishing them from traditional SaaS or platform companies. These differences affect how revenues scale, how margins behave, and how risk is distributed across the value chain.
In practical terms, classifying AI as its own sector would create several benefits. For investors, it would enable cleaner benchmarking and more targeted portfolio construction. For policymakers and regulators, it would improve tracking of systemic risk and concentration in a domain increasingly central to national security, labor productivity, and information control. From an economic statistics perspective, having AI as its own sector could better inform GDP measurement, labor reallocation, and capital formation trends.
Importantly, the number of companies focused primarily on AI is growing rapidly. According to a list maintained on Wikipedia, dozens of major firms—including Anthropic, OpenAI, Cohere, Hugging Face, Scale AI, and Inflection AI—operate with AI as their core business. Many of these companies are either unicorns or backed by major tech conglomerates, and a recent analysis by Ascendix Tech found that over 50% of tech startups with billion-dollar valuations in 2024 were AI-first companies.
In summary, the scale of AI spending, its cross-sector penetration, and its unique operating model all support the argument that AI should be classified as a distinct sector of the U.S. economy. As AI continues to reshape everything from labor markets to geopolitics, giving it proper structural recognition is not just a matter of taxonomy—it’s a reflection of the future of economic organization.
Data sourced from:
- Stanford Institute for Human-Centered AI – 2025 AI Index Report
Global corporate AI investment data ($252.3B in 2024)
🔗 https://hai.stanford.edu/ai-index/2025-ai-index-report/economy - McKinsey & Company – The State of AI in 2024
AI adoption rates across industries
🔗 https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2024 - Washington Post – The AI Spending Boom Could Have Real Consequences for the U.S. Economy
Projected $400B AI infrastructure spend by Big Tech (2024–2026)
🔗 https://www.washingtonpost.com/technology/2025/08/04/big-tech-ai-spending-economy/ - IOT Analytics – Top Generative AI Companies & AI Infrastructure Spending
$125B data center capex, Nvidia market share in AI GPUs
🔗 https://iot-analytics.com/leading-generative-ai-companies/ - Casado & Bornstein – The New Business of AI and How It’s Different from Traditional Software
Explains AI business models vs. SaaS
🔗 https://a16z.com/the-new-business-of-ai-and-how-its-different-from-traditional-software/ - Ascendix Tech – How Many AI Companies Are There?
Over 50% of tech unicorns are AI-related in 2024
🔗 https://ascendixtech.com/how-many-ai-companies-are-there/ - Wikipedia – List of Artificial Intelligence Companies
Directory of major AI-native firms like OpenAI, Anthropic, Hugging Face
🔗 https://en.wikipedia.org/wiki/List_of_artificial_intelligence_companies
