A comprehensive financial analysis by investment platform Fundrise suggests the artificial intelligence wave could generate approximately $20 trillion in market value, following a consistent pattern observed across four decades of technological evolution. CEO Ben Miller and his team analyzed over 40 years of data from 250 tech companies with at least $1 billion in market capitalization, including giants like Adobe, Amazon, Nvidia, AMD, Meta, and Microsoft.
The research uncovered a striking “rule of three” pattern: each major technology wave generated roughly three times the value of its predecessor. The internet era created 3.5 times the value of the PC wave, mobile technology generated 3.4 times the internet wave’s value, and cloud computing produced three times mobile’s value. Applying this consistent growth pattern to AI suggests the current wave will reach approximately $20 trillion in total market capitalization.
The analysis broke down company revenues by technology wave—PC, internet, mobile, and cloud—and by their position in the technology stack: applications, hardware, and platforms. Hardware companies typically capture value earliest in each wave, but the application layer closest to consumers ultimately claims the largest share. Amazon dominated the internet application layer, Instagram led mobile, and Salesforce topped cloud computing.
Miller compared the current AI moment to the mobile wave circa 2009, when the iPhone had few applications. He argues it’s premature to worry about AI’s return on investment, noting that “the lag is super consistent” across technology waves. The firm estimates Nvidia’s market capitalization could reach $4 trillion by 2030, which independently validates the $20 trillion total wave valuation.
Research firm IDC reached similar conclusions using a completely different methodology—an input-output model examining AI’s supply chain and end-user economics across geographies—arriving at $19.9 trillion in global economic impact. Miller suggests these estimates may be conservative, given that GPU computing power is advancing faster than Moore’s law, potentially driving even greater economic growth than historical patterns predict.
Key Quotes
Everybody’s constantly talking about the waves. And I was wondering, does the financial data match the waves?
Ben Miller, CEO of Fundrise, explaining the motivation behind his team’s comprehensive analysis of technology waves. This question led to the discovery of the consistent “rule of three” pattern across four decades of tech evolution.
The thing that I found shocking is the growth rates are fairly consistent.
Miller describing his surprise at discovering that each technology wave—from PC through cloud computing—generated approximately three times the value of its predecessor, a pattern that held remarkably steady across 40 years of data.
The lag is super consistent. It’s shortsighted to assume that the return on investment in AI isn’t coming because it’s not here yet.
Miller addressing investor concerns about AI profitability, comparing the current moment to 2009’s mobile wave when the iPhone had few applications. He argues historical patterns show returns consistently arrive after infrastructure buildout.
If compute is the primary underlying driver of economic activity, economic growth, economic opportunity, then there’s an argument that it’s actually bigger.
Miller suggesting the $20 trillion estimate may be conservative, noting that GPU computing power is advancing faster than Moore’s law, potentially accelerating AI’s economic impact beyond historical technology wave patterns.
Our Take
This research offers a refreshing counterpoint to both AI hype and skepticism by grounding projections in historical data rather than speculation. The convergence of Fundrise’s market capitalization analysis and IDC’s economic impact modeling around $20 trillion significantly strengthens the credibility of this figure. What’s particularly insightful is the application-layer thesis—while Nvidia and infrastructure players dominate headlines today, history suggests the real winners haven’t emerged yet. The 2009 mobile comparison is apt: Instagram, Uber, and other mobile-defining companies didn’t exist when the iPhone launched. Similarly, AI’s killer applications likely haven’t been built. For investors, this suggests a barbell strategy: own infrastructure plays now while watching for application-layer innovators. The “rule of three” pattern also implies AI isn’t as unprecedented as it feels—it’s following a well-worn path of technological disruption, just at unprecedented scale.
Why This Matters
This analysis provides crucial perspective for investors and business leaders navigating AI’s uncertain landscape. While concerns mount about when AI investments will generate returns, historical patterns suggest patience is warranted—application-layer winners typically emerge years after infrastructure buildout begins. The “rule of three” pattern offers a data-driven framework for understanding AI’s potential scale, suggesting current valuations and investments may be justified despite limited near-term profitability.
The research has significant implications for investment strategy and corporate planning. Companies building AI infrastructure today—particularly hardware providers like Nvidia—are positioned for early gains, but the ultimate value will accrue to application-layer companies that successfully reach consumers. This mirrors how Amazon, Instagram, and Salesforce captured disproportionate value in previous waves. For businesses, the message is clear: the AI opportunity is real and massive, but competitive advantages will shift from infrastructure to applications over the coming decade. The convergence of two independent analyses around $20 trillion strengthens confidence in AI’s transformative economic potential.
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Source: https://www.businessinsider.com/ai-value-estimate-20-trillion-tech-wave