The "AI bubble" debate centers on the massive investments - hundreds of billions of dollars - flowing into data centers and large-language model training. These investments are projected to surpass a trillion dollars over the next decade. For comparison, the Apollo moon program cost about $260 billion (in today's dollars) [1], less than what's being spent on AI this year, while the U.S. interstate highway system tallied around $600 billion [2], equivalent to just two years of current AI spending.
For these huge sums to be worthwhile, the profits generated by this AI infrastructure must exceed the investment. It's likely that industry plans will shift as business leaders better understand AI demand. Just three years ago, OpenAI launched ChatGPT publicly, and since then, generative AI ("Gen AI") use has skyrocketed. As of August 2025, the Federal Reserve Bank of St. Louis reported that 54.6% of U.S. adults had used Gen AI - up from 44.6% the previous year. In contrast, early adoption rates for the Internet and personal computers were much lower [3].
Companies are embracing Gen AI quickly, mainly because it boosts productivity and fosters innovation. Surveys from The Wharton School, MIT, and McKinsey show that between 72% and 88% of managers have begun using Gen AI and plan to expand its use throughout their organizations [4].
This rapid uptake is driving exponential growth in AI model applications, from entertainment and research to productivity tasks - a trend consistent with the Diffusion of Innovations Theory, which posits that innovations spread rapidly if they offer clear benefits, compatibility with existing systems, ease of trial, and measurable results. Gen AI meets all these criteria. It's relatively free to access compared to the significant productivity gains it delivers. Gen AI automates routine activities like data analysis and reporting, allowing employees to concentrate on strategy and creative problem-solving.
A major advantage of AI is that it lets employees automate repetitive work without needing coding skills, freeing up time for higher-value tasks. With the arrival of agentic AI, which automates these steps even further, this benefit will become increasingly evident. According to Wharton, the top uses for Gen AI are:
Other notable business uses include internal support, customer service, market research, generating emails, supplying evidence for decision-making, and programming code production. Gen AI's versatility means it's found across all corporate departments, including HR, legal, and IT. The chart below shows that businesses are increasingly using Gen AI in more and more functions.
McKinsey reports that the need to adopt Gen AI touches every business function and employee. Not embracing this technology isn't seen as an option, as it can make everyone more effective. An MIT survey found that 73% of respondents believe AI helps their organization stand out, and 76% think it enables individuals to distinguish themselves professionally [5].
Yet Gen AI isn't only about saving time and money; it's also helping businesses grow revenues. One manager in the Wharton survey described how Gen AI accelerated product design by generating fresh ideas and visual concepts driven by real customer preferences, resulting in quicker and more market-aligned launches.
This dual benefit of efficiency and revenue growth motivates companies to invest heavily in tailoring Gen AI to their needs and integrating their own data. The returns on these investments appear promising. As the chart below shows, 74% of managers see positive returns on their AI investments.
While businesses are still in the early stages of implementing and refining Gen AI, positive experiences are leading to bigger budgets - 88% of surveyed leaders plan to increase Gen AI spending over the next five years.
Fear is another motivator: many expect Gen AI to disrupt entire industries. Seventy percent of Wharton survey participants believe AI will revolutionize their sector. For instance, future travel planning might rely entirely on AI tools like ChatGPT, making services like Expedia obsolete. This sense of threat pushes companies to honestly evaluate their strengths and weaknesses and innovate to avoid being left behind.
Conclusion
This discussion highlights corporate Gen AI adoption, where financial resources and value potential are highest, but non-corporate users - such as consumers and students - are also adopting it quickly. Consumer monetization of AI is just beginning, and within a year, buying products and services via AI will likely become common.
From an investment standpoint, surging demand for Gen AI could justify the enormous expenditure by tech giants. Recent declines in AI stock prices present buying opportunities for disciplined investors. Demand for AI remains robust, and the underlying fundamentals point toward continued strong growth.
Disclosures
LIM is an Investment Advisor based in Dallas, Texas and registered with the Securities and Exchange Commission. Registration does not imply a certain level of skills or training. LIM is a company with purpose, dedicated to creative and unique thinking. We focus on portfolio valuation and research, along with superior client experience. We seek to identify investment opportunities by looking at economic factors, security valuation and human behavior. We start with the fundamentals of portfolio management and valuation. Then we build on these fundamentals with unique thinking and creative intelligence gathering to form a viable investment thesis. We believe this approach leads to dynamic global portfolios with increased return and managed risk. LIM utilizes Charles Schwab & Co. Inc. (“Schwab”), a FINRA-registered broker-dealer, member SIPC, as its custodian of assets. LIM is independently owned and operated and not affiliated with Schwab.
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