AI boom or bubble? Assessing the Risks Behind US Growth

The global narrative around artificial intelligence has changed in recent years from positive to something far more risky. An AI boom sweeping capital markets, corporate strategies and business forecasts. While this boom has changed market valuations and tech budgets to unpredictable levels, it has also raised critical questions if this growth is sustainable or are we surrounded by an economic bubble? This could change markets and unbalance corporate balance sheets. An analysis on this explored the dual nature of AI, its innovations to growth and risks in an invest cycle causes business implications. Let's explore this in this article.

The United States economy has become increasingly dependent on AI-investment and financial performance. According to economist Ruchir Sharma, about 60% of US economic growth in FY2025 was due to AI-driven spending and market gains, signaling how deeply rooted the technology has become in the macroeconomic environment.

1. Capital Spendings: Enterprises have poured a significant amount of capital into building AI infrastructure, from data centres to personal computers creating a new investment cycle in various sectors.

2. Market Valuation: AI-associated stocks have increased a major proportion of market gains, concentrating wealth and investor attention around shrinking companies.

AI’s contribution to growth is not simple but dynamic, having effects on investment returns, employment in tech sectors and consumer spending. Yet, many economic indicators such as productivity growth in non-tech sectors, wage expansions and large scale adoption of AI remains unevenly distributed.

Despite significant economic contribution, TEI warns that the AI boom or bubble is not rhetorical. It is based on classic financial risk indicators. Business economist identified such bubble highlighting four critical factors:

- Overinvestment: large scale expenditure on AI capital, particularly in infrastructure reflects patterns seen in prior bubbles.

- Overvaluation: Equity Valuation for AI leaders often outpace traditional valuation such as free cash flow or long-term earnings potential.

- Over-Ownership: Institutional investors hold an unusual amount of share in equity related to AI companies.

- Over-Leverage: Companies issue debt to fund AI initiatives, potentially highlighting financial risk without future returns.

These indicators are present across both public and private markets, suggesting that many described as boom could exhibit characteristics of bubbles. Boom highlights transformative potential of AO, bubble captures speculative behaviour and extended valuations that often preceded market corrections.

The debate of whether AI represents a boom or bubble is far from settled even among experts:

- Bubble Concern of Finance Leaders: Veteran investor Jeremy Grantham has publicly stated that AI appears like a bubble, comparing it where valuations outpaced fundamental earnings.

- Industry Acknowledges Risk: Leaders such as DeepMind’s Demis Hassabis agreed that parts of the AI investment cycle has become a bubble, especially during early-stage funding where valuations may not correspond to real-product maturity.

- Optimistic Approach: Some tech executives like Nvidia’s CEO Jensen Huang, view the current environment as a foundational shift rather than short-term spike.

- Broader View: Surveys show that more than half of major market respondents identify the AI bubble as the biggest risk to economic growth in 2026.

This mix of perspectives highlights a central idea that economic benefits of AI are real but the speed of investment can expose market risks.

Understanding when and how a looming correction could occur is critical for executive decision-making. Multiple factors trigger this:

- Monetary Policy Shifts: Historically, bubbles are not due to technology failure but rising interest rates. With inflation pressure and central banks tightening policy, the cost of capital will rise making equity less sustainable.

- Market Sentiment Shocks: sudden shift in investor confidence driven by lesser earnings or macroeconomic stress could lead to rapid repricing.

- Narrow Adoption of AI: due to high investment levels. Broad corporate adoption and measurable productivity gains remain less pervasive.

The World Economic Forum suggests that even if a bubble bursts resulting in fallout of previous cycles, speculative firms and lenders will be at high exposure though financial markets would still face volatility and risks.

For CXOs and CTOs, navigating through this complex environment, the focus is on strategic defensibility and value creation. Key strategic imperatives are:

- Align AI with Outcomes: Prioritize AI initiatives with measurable ROI, revenue growth, cost and customer engagement.

- Manage Financial Exposure: Evaluate capital structure and stress test where correct valuations are necessary.

- Bridge Adoption and Productivity: Ensure AI adoption from pilot to operational execution, critical between speculative and sustainable growth.

- Monitor Market: Internal and external indicators multiply the cost of capital and competitive benchmarks about real-time strategic pivots.

Evaluating the AI boom or bubble through this lens reveals the risk management and growth needs to be mutually exclusive.

The question of an AI boom or bubble is a strategic imperative that demands impartial judgement from leaders. On one hand, AI has accelerated growth, transformed markets and redefined competitive advantage. On the other hand, rapid expansion of capital flows, valuations and debt into AI assets has introduced fragilities of past market bubbles.

At TEI, we help enterprise leaders translate complex technological and economic shifts with analysis and actionable insights. Is your organization harnessing the power of AI while mitigating systemic risks?