Nvidia’s $100B AI Power Play: Rocket Fuel or Ticking Time Bomb?

The recent investment of Nvidia is considered as fuelling the AI money machine, so what is the most likely result and what are the risks behind that move.  What is the implication to AI stocks investors in reaction to this ?

Nvidia's Recent Investment: Fueling the AI Ecosystem

Nvidia's most prominent recent investment, announced in September 2025, is a landmark strategic partnership with OpenAI to deploy at least 10 gigawatts of Nvidia-powered AI data centers—equivalent to millions of GPUs for training next-generation models. To support this, Nvidia committed up to $100 billion in progressive investments into OpenAI (starting with an initial $10 billion), tied to each gigawatt deployed, with the first phase launching in late 2026 using Nvidia's Vera Rubin platform.

This deal, described by Nvidia CEO Jensen Huang as "monumental," builds on Nvidia's broader spree of AI investments, including $5 billion in Intel for AI chip collaboration, up to $1 billion in AI coding startup Poolside, and stakes in over 50 AI ventures in 2025 alone (e.g., Perplexity, Figure AI).

These moves position Nvidia not just as a chip supplier but as a financier in the AI supply chain, creating a self-reinforcing "money machine" where its capital flows back as GPU purchases.

Most Likely Result: Accelerated AI Infrastructure Buildout and Ecosystem Lock-In

The most probable outcome is a rapid scaling of AI compute capacity, solidifying Nvidia's dominance while boosting the sector's growth trajectory.

This investment directly enables OpenAI's path to "superintelligence" by addressing the massive energy and hardware demands of advanced models—Huang noted the deal could involve 4-5 million GPUs, potentially powering AI applications in drug discovery, robotics, and enterprise tools.

By funding customers like OpenAI (and indirectly others via stakes in CoreWeave and Oracle), Nvidia creates a flywheel: investments → GPU sales → revenue growth → more investments.

Analysts project this could add $100-200 billion to Nvidia's revenue by 2030, as AI infrastructure spending hits $2 trillion annually to meet demand.

Broader ripple effects include faster AI adoption across industries (e.g., pharma reducing drug development from 12 to 1 year) and Nvidia's market share holding at 80-95% for AI accelerators, thanks to ecosystem lock-in via NVLink and CUDA software.

Key Risks Behind the Move 

While promising, this strategy carries significant vulnerabilities, echoing past tech booms like the dot-com era's vendor financing excesses (e.g., Cisco lending to buy its own gear). Here's a breakdown:

These risks are heightened by the sector's $1T+ in circular deals, where progress stalls could leave $2T in stranded assets.

Implications for AI Stocks Investors

This investment signals robust short-term tailwinds for AI stocks but heightens volatility for long-term holders, as it amplifies both growth and bubble concerns.

Nvidia's stock surged ~4% ($170B market cap gain) post-announcement, reflecting investor bets on the flywheel, but recent pullbacks (e.g., Nasdaq's worst week in months) show anxiety over capex sustainability.

Bulls like Berkshire Hathaway (buying 17.8M Google shares at $2-2.8T valuation) see it as validation of AI's "positive-sum" potential, with Nvidia as the "picks-and-shovels" play.

Bears, including Michael Burry's $1.2B short on Nvidia/Palantir, warn of overvaluation—Nvidia trades at 76x forward earnings amid doubts on hyperscaler ROE.

Bullish Reaction:

Expect 10-20% upside in Nvidia and peers (AMD up on OpenAI tie-up; Arm/CoreWeave via Nvidia's $4.3B portfolio) if Q4 earnings (Nov 2025) confirm demand. Broader AI ETFs (e.g., BOTZ, AIQ) could rally on infrastructure wins, with 30% CAGR through 2030.

Bearish Reaction:

A miss on guidance could trigger 15-25% sector sell-off, hitting high-beta names like SoundHound AI (up 271% on Nvidia's stake but at 37.5x sales).

 Investors should diversify—e.g., into enterprise AI (PLTR) or infra (APLD)—and monitor ROI metrics.

 Investor Strategy:

 View this as a high-conviction bet on AI's multi-year buildout, but hedge with 10-20% cash allocation.

 Long-term, it could redefine categories (e.g., AI coding >$1B ARR via GitHub Copilot), but near-term reactions hinge on earnings and adoption proof points.

 If you're in AI stocks, trim Nvidia exposure above $1,000/share and rotate to undervalued plays like AMD for diversification.