• In the past, NVIDIA capitalized on its GPU supremacy to spearhead generative AI innovation. However, it started to face intensifying competition and the looming risk of market saturation, as enterprises remain uncertain about the ROI of large-scale AI infrastructure investments.
• The ambitious $500-billion “Stargate Project” – championed by Trump and OpenAI – initially seemed like a windfall for NVIDIA’s high-end GPUs. Yet, breakthroughs from DeepSeek challenge this trajectory, proving that cutting-edge AI models can thrive under compute-constrained conditions. NVIDIA now needs a compelling new vision beyond simply pushing the envelope on GPU performance.
• This is where Agentic AI comes in – not just as the next stage of AI evolution, but as NVIDIA’s answer to long-term scalability and differentiation. By investing in AI agents that can reason, plan, and execute autonomously, expanding into consumer-level edge computing, and laying the foundation for physical AI in robotics, NVIDIA wants to remain at the heart of AI economy, which represents a “multi-trillion dollar opportunity”.

Exhibit 1: NVIDIA’s Next Focus: Agentic AI

Source: CES 2025

• As the AI landscape transitions from training scaling to test-time scaling, merely offering cutting-edge GPUs is no longer a sufficient competitive advantage. NVIDIA’s introduction of Blackwell GPUs, Cosmos world model, Project Digits, and AI Blueprints is far more than a series of product releases – it represents a deliberate, ecosystem-first strategy to solidify its position as the backbone of AI infrastructure.
• Consequently, NVIDIA is building an integrated AI platform that combines compute power, foundational models, and enterprise-ready AI orchestration. This ensures that organizations don’t just buy NVIDIA’s chips, but architect their AI capabilities around its ecosystem, embedding NVIDIA’s solutions into every layer of the AI value chain. By expanding beyond hardware and into the full agentic AI workflow, NVIDIA is trying to future-proof its leadership in AI.
• DeepSeek’s breakthrough carries dual implications for NVIDIA. On the one hand, it heightens competition in the AI hardware space, as more cost-efficient alternatives challenge NVIDIA’s dominance. On the other, it serves as a catalyst for
• NVIDIA’s Agentic AI ecosystem building, driving down inference costs and accelerating adoption.
  Sensing the potential edge, NVIDIA, along with Microsoft and AWS, rapidly integrated DeepSeek’s R1 opensource frontier model into their platforms, leveraging its efficiency to expand adoption and enhance its AI ecosystem.
• DeepSeek’s success highlights the power of better cost structure as a competitive moat, fueling mass adoption in an increasingly commoditized and open AI landscape. To stay ahead, NVIDIA needs to sharpen its enterprise-level agentic AI pricing models, ensuring both clarity and cost competitiveness to gain market traction.

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