NVIDIA (NVDA) investor relations material

AI infrastructure and industry transformation

• AI infrastructure spending is accelerating toward $3–4 trillion by 2030, driven by the need for generative computing that enables users to know and ask anything, not just retrieve information.

• The shift from retrieval-based to generative AI requires a new layer of computing, with large, context-driven models and complex recommendation engines for each user.

• The end of Moore's law necessitates co-design, chip interconnects like NVLink, and scaling up chip production, leading to a rapidly expanding semiconductor industry.

• AI models are growing in complexity and demand, pushing the industry to innovate in both hardware and software to maintain rapid progress.

• The overall market for AI is expanding beyond cloud service providers to enterprises, regional clouds, and neoclouds, with significant growth in model companies and applications.

Key applications and business opportunities

• Coding is identified as the foundational application for AI, with derivatives in bug finding and cybersecurity, which is expected to be the next major use case.

• Partnerships with companies like CrowdStrike, Cisco, and Palantir are enabling new AI factory platforms and cybersecurity solutions globally.

• AI is becoming central to business processes, supply chains, and communication, with every technology company expected to become high CapEx or OpEx due to compute needs.

• The company is positioning its compute systems as investable, durable assets, enabling new financing models and supporting the growth of AI-native startups.

• Physical AI, starting with self-driving cars and expanding to robotics and telecommunications, is expected to see significant adoption and market growth by 2030.

Supply chain, market reach, and financial strategy

• The company leverages its scale and long-term supply chain relationships to secure both upstream components and downstream land, power, and shell for data centers.

• Its full-stack AI factory platform allows rapid deployment and productivity, with a diverse go-to-market strategy through CSPs, OEMs, and neoclouds.

• Asset-backed compute systems are enabling new financing structures, with significant contracted demand and offtake supporting investments in AI infrastructure.

• Regionalization of AI is emphasized, with hubs and partnerships worldwide to address local needs and regulatory environments.

• The company is confident in sustaining high growth rates, projecting 70% year-over-year revenue growth and continued expansion of its market share.