Investing in AI: Assessing the investment opportunities

Artificial Intelligence (AI) has moved beyond speculation and now actively reshapes technology industry economics. Analysts credit recent technology stock gains to surging AI investments, which drive sector growth through increased earnings, and expanding capital investment. The evidence points to AI’s operational reality and its profound business performance impact.  

Sources: U.S. Bank Asset Management Group Research, Bloomberg, November 7, 2025.

What is Artificial Intelligence?

Scientists define AI as simulating human-like intelligence in machines/computers. The field encompasses multiple disciplines, including machine learning, deep learning, generative AI, and agentic AI.

• Machine learning empowers practitioners to train machines in performing specific tasks by leveraging data and algorithms to analyze vast information pools. These systems often uncover trends that remain hidden to human analysts, making machine learning a powerful tool for data-driven insights 
• Deep learning utilizes multiple neural network layers to replicate tasks related to voice, hearing, and vision. For instance, devices like Amazon’s Alexa and Apple’s Siri respond to voice commands and questions, while adaptive cruise control in vehicles “sees” the road ahead and automatically adjusts speed to maintain safe distances.¹
• Generative AI (GenAI) advances beyond linear decision-making by mastering language and creating new content. Building on the foundations of machine learning and deep learning, GenAI employs algorithms trained on large datasets to generate text, code, audio, and video. This capability is reshaping industries and skill sets, introducing both new opportunities and challenges.
• Agentic AI extends GenAI by introducing systems that plan, reason, and act to complete complex, multi-step tasks with minimal human oversight. These proactive systems use reasoning, tools, and iterative processes to achieve goals, continuously learning and adapting over time.

AI’s rapid evolution is transforming how we live, learn, work, and conduct business, outpacing previous technological innovations. Modern era technological innovations include personal computers (1980s), Internet of things (1990s), mobility/smartphones (2000s), cloud storage/computing (2010s), and now AI (2020s). While all these innovations impact how we live, work and play, AI embodies unprecedented adoption, potentially driving an even more profound impact on our lives relative to other technologies.

"AI will likely become the biggest, the best, and most important of technology revolutions," according to Sam Altman, CEO, OpenAI.² Artificial intelligence "is one of the most profound technologies we are working on, as important or more than fire and electricity," notes Sundar Pichai, CEO, Alphabet.³ "You're not going to lose your job to AI, but you're going to lose your job to somebody who uses AI" says Jensen Huang, CEO, NVIDIA.⁴ Compared to past  innovations, AI's rapid evolution requires significant capital investment in AI companies in addition to retooling processes and retraining workers, which creates new investment opportunities.

Sources: U.S. Bank Asset Management Group Research, Bloomberg, November 7, 2025.

What is driving AI spending growth and adoption?

AI is driving both top-line growth and bottom-line efficiency. As a disruptive technology, AI creates opportunities for investors seeking opportunities to invest in cutting-edge innovation. Below are key factors fueling AI’s rapid adoption and expansion.

• Industry leaders assert that adopting AI early and effectively sets businesses apart in the market. Organizations across nearly every sector are investing in AI to unlock new revenue streams, streamline or automate processes and workflows, address talent shortages, and cut operational costs throughout their departments. For example, Andy Jassy, CEO of Amazon.com, recently emphasized that the company will reduce its corporate workforce as it integrates more generative AI tools and agents. Jassy encouraged employees to learn, experiment, and discover how to accomplish more with leaner teams.⁵
• Technological breakthroughs and fundamental business needs are fueling an AI spending surge. GenAI breakthroughs are delivering tangible value and driving business demand. Additionally, continuous Graphics Processing Unit (GPU) advancements and widespread data availability make AI accessible to more organizations.⁶ Cloud computing services from providers such as Amazon Web Services, Microsoft Azure, Google Cloud, Oracle, and Meta are supporting this expansion. Although deploying AI technology remains costly, increasing efficiency is making it more economically viable for both businesses and consumers.
• Semiconductor chip manufacturers and software developers are working to overcome significant limitations in current AI models:
  • AI engines do not possess human-like comprehension, consciousness, or common sense. They rely on statistical patterns and lack physical experience, which restricts their understanding of the tangible world and the nuances of abstract reasoning, complex ethics, and subtle human emotions.
  • AI models may confidently produce false information, so users must verify A.I. outputs.
  • AI systems can inherit and perpetuate biases present in their training data, making performance highly dependent on the quality and quantity of that data.
  • Training and operating advanced AI models require substantial computational and energy resources.
  • AI raises concerns about intellectual property, copyright, and potential job displacement.

What is the scope of investment opportunities and risks?

The growth and innovation of AI requires development across a variety of industries.  AI model development requires data, software, security and distribution with energy development and data centers required to run it all.  Below are key AI investment sub-sectors and key risks.

• AI empowers businesses to boost efficiency, deepen customer understanding, improve decision-making, and accelerate innovation, contributing to enhanced growth. These advancements create investment opportunities for companies building AI infrastructure and those leveraging AI to secure and maintain competitive advantages. For example, AI relies on data, so companies specializing in data capture, cloud storage, processing, software analytics, security, distribution, and data center electrification stand to benefit from long-term growth.
• AI’s total addressable market (TAM) continues to expand as emerging technologies and applications reshape the landscape. By most measures, the AI evolution remains in its early stages, yet its vast potential to automate tasks and create new markets justifies ongoing business investment. Over the past two quarters, nearly every major tech company—from hyperscalers  (large cloud service providers that operate massive data centers and offer on-demand, highly scalable computing resources) like Microsoft, Amazon, and Google to enterprise leaders such as IBM, ServiceNow, and Oracle—has emphasized a transformative theme: AI is fueling both revenue growth and operational efficiency. The consistent narrative from these earnings calls shows that companies and investors now view AI not as an experiment or R&D expense, but as a margin-accretive technology that enhances customer engagement, shortens development cycles, and reduces labor and infrastructure costs.
• Progress in foundational models is lowering AI model training costs, which in turn expands the available application range within the technology stack - the suite of tools firms use to build and run applications, websites, and projects. This trend creates new business opportunities for software companies focused on data storage, security, analytics, productivity, and semiconductor design.
• Investors will closely watch how businesses integrate AI into workflows in 2026 and beyond. Healthcare organizations are using AI to improve patient care and achieve better outcomes. The industry applies AI to disease diagnosis, treatment planning, drug discovery and development, medical imaging analysis, and patient monitoring. By saving physicians time, AI ultimately enables more patient-centered care.
• Elevated equity market valuations pose a near-term challenge. Many AI company valuations reflect optimistic expectations that may not align with current profitability. Not all AI applications offer clear, sustainable paths to profit, so investors increasingly demand tangible evidence of returns on AI investments. If promised revolutionary changes fail to materialize in the coming months, investor sentiment across the AI ecosystem could decline. However, modest market corrections and industry consolidation are normal market dynamics. For now, AI and its related infrastructure maintain a strong growth outlook.

Sources: U.S. Bank Asset Management Group Research, Bloomberg, November 7, 2025.

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