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US$19tn worth of projected AI earnings already factored into the current stock market: report

By DigiconAsia Editors | Sunday, November 23, 2025, 8:23 AM Asia/Singapore

UStn worth of projected AI earnings already factored into the current stock market: report

Two key risks in current AI valuation bubble are: overestimating total sector profits, and assuming short-term gains persist long-term.

Global investment banking and securities firm Goldman Sachs has issued a cautionary note on the current AI boom bubble, emphasizing technological and infrastructural challenges despite the surge in market enthusiasm.

While AI-related stocks led by major players have soared, the firm has highlighted that much of the valuation increase already factors-in expected AI-driven economic growth. Their research suggests a risk of over-investment in AI infrastructure, particularly in capital expenditures on data centers and energy, which may not yield proportional returns, posing correction risks to the market.

The firm draws parallels to previous technology bubbles, such as the dot-com era, yet stresses key differences: today’s leading AI firms report solid earnings and sustainable growth, not just speculative hype. This fundamental strength tempers fears of a classic financial bubble, although the sector remains vulnerable to shocks such as disappointing earnings or loss of investor confidence.

Understanding the backlog paradox
A critical technology aspect underscored by experts including Goldman Sachs and AI analysts is the supply-side bottleneck in the AI ecosystem:

  • Demand for AI computing power and infrastructure increasingly outpaces the capacity to supply it, especially due to constraints on energy, data centers, and physical infrastructure.
  • This “backlog paradox” means many AI firms hold substantial contracts and capital but face delays building sufficient infrastructure to capitalize on opportunities, creating a structural challenge in the AI sector’s scaling phase.
  • The next phase in AI development will therefore hinge not merely on investment volume but on effective execution amid these constraints. Control over energy resources, power grid access, and data center capacity is emerging as a competitive moat alongside traditional technological capabilities, according to Goldman analysts.

In short, while the AI boom is underpinned by genuine technological progress and substantial market opportunity, it is also marked by significant infrastructural challenges and risks of investment misallocation.

These factors shape a more complex picture than simple bubble speculation, pointing to a transformative yet potentially volatile growth phase for AI technology.

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