NVIDIA’s stock is positioned for continued growth as demand for its GPU chips remains robust, according to a comprehensive analysis from Morgan Stanley following three days of meetings with NVIDIA’s executive team in New York City. The investment bank met with CEO Jensen Huang, CFO Colette Kress, and other senior management to assess the company’s trajectory in the AI chip market.
Morgan Stanley analyst Joseph Moore emphasized that “every indication from management is that we are still early in a long term AI investment cycle.” The firm maintained its “Overweight” and “Top Pick” ratings with a $150 price target, suggesting potential upside of 12% from current levels.
A critical highlight from the meetings is that NVIDIA’s next-generation Blackwell GPU chip production is progressing on schedule and is completely sold out for the next 12 months. Any new Blackwell orders placed now won’t ship until late next year, creating a backlog that continues to drive strong demand for NVIDIA’s previous generation Hopper chips, which will remain a significant revenue factor throughout the year.
The Hopper chips are being sold in clusters to major cloud “hyperscalers” including Amazon, Microsoft, and Meta Platforms, demonstrating NVIDIA’s dominance in the enterprise AI infrastructure market.
Moore identified a new growth driver for NVIDIA: inference computing is evolving to solve increasingly complex problems, requiring a richer hardware mix. This development plays directly into NVIDIA’s strengths. “The longer term vision is that deep thinking will allow every company in the world to hire large numbers of ‘digital AI employees’ that can execute challenging tasks,” Moore explained.
The analyst noted that task-oriented inference could cause an exponential jump in inference complexity, representing “an important new avenue for growth.” NVIDIA’s full-stack approach to solving these problems further solidifies the company’s competitive advantage in the AI chip market.
CEO Jensen Huang indicated to Morgan Stanley that the company expects meaningful growth in 2025 extending into 2026, though specific figures were not disclosed. NVIDIA’s stock performance reflects this optimism, with shares rising approximately 10% since early October and an impressive 172% gain year-to-date.
Key Quotes
Every indication from management is that we are still early in a long term AI investment cycle.
Morgan Stanley analyst Joseph Moore made this assessment after three days of meetings with NVIDIA’s executive team, signaling that the current AI boom has substantial room for continued growth rather than approaching saturation.
Any new Blackwell orders now that aren’t already in queue will be shipped late next year, as they are booked out 12 months, which continues to drive strong short term demand for Hopper which will still be a major factor through the year.
Moore explained the supply-demand dynamics showing NVIDIA’s next-generation chips are completely sold out, creating a cascading effect that maintains strong sales of current-generation products.
The longer term vision is that deep thinking will allow every company in the world to hire large numbers of ‘digital AI employees’ that can execute challenging tasks.
This statement from Moore captures NVIDIA’s strategic vision for AI’s evolution, moving beyond current applications to a future where AI agents perform complex work across all business sectors.
The notion that a more thoughtful, task oriented inference would cause an exponential jump in inference complexity strikes us an important new avenue for growth, and another clear area where NVIDIA’s full stack approach to solving these problems adds to the company’s considerable lead.
Moore identified inference computing as an emerging growth driver that plays to NVIDIA’s strengths, suggesting the company’s competitive moat is widening rather than narrowing as the AI market matures.
Our Take
NVIDIA’s position appears increasingly unassailable as the AI infrastructure arms race intensifies. The 12-month backlog for Blackwell chips is extraordinary and suggests that even with massive production capacity, demand is outpacing supply by a significant margin. What’s particularly noteworthy is the shift toward inference workloads requiring sophisticated hardware—this counters the narrative that inference would commoditize and erode NVIDIA’s margins. The concept of “digital AI employees” isn’t just marketing speak; it represents a fundamental reimagining of enterprise operations where AI agents handle complex tasks autonomously. If this vision materializes even partially, the addressable market for AI chips expands exponentially beyond current training and simple inference workloads. NVIDIA’s full-stack approach—combining hardware, software, and ecosystem—creates switching costs that will be difficult for competitors to overcome, even as alternatives emerge.
Why This Matters
This analysis is significant because it confirms that the AI infrastructure boom shows no signs of slowing, with NVIDIA positioned at the epicenter of this transformation. The 12-month sellout of Blackwell chips demonstrates that enterprise demand for AI computing power far exceeds current supply, validating the massive capital investments being made by tech giants in AI infrastructure.
The emergence of complex inference computing as a new growth driver is particularly important, as it suggests AI workloads are evolving beyond simple training tasks to more sophisticated, real-world applications. The concept of “digital AI employees” executing challenging tasks represents a fundamental shift in how businesses will operate, potentially creating a multi-trillion dollar market for AI infrastructure.
For investors and industry observers, NVIDIA’s continued dominance despite competition from AMD, Intel, and custom chips from hyperscalers indicates the company has built sustainable competitive advantages through its full-stack approach. This positions NVIDIA not just as a chip supplier, but as the foundational infrastructure provider for the AI economy, with implications for enterprise software, cloud computing, and workforce transformation across all industries.
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