Summary of "Conversation with Jensen Huang, President and CEO of NVIDIA | WEF Annual Meeting 2026"

Summary of Business-Specific Content from the Conversation with Jensen Huang, President and CEO of NVIDIA | WEF Annual Meeting 2026

Company Strategy & Leadership

NVIDIA’s leadership under Jensen Huang has delivered extraordinary shareholder returns since its IPO in 1999, with a compounded annual return of 37%, significantly outperforming major financial firms like BlackRock (21%).
Huang emphasizes long-term vision and infrastructure investment as key to NVIDIA’s success and future growth.
NVIDIA positions itself at the core infrastructure layer of AI, supplying chips and computing power to hyperscalers and AI companies worldwide.
He highlights the importance of broadening the global economy through AI, ensuring benefits reach diverse geographies and sectors.

AI as a Platform Shift: Framework & Industry Impact

AI represents a fundamental platform shift comparable to the PC, internet, and mobile cloud revolutions.

The AI computing stack is described as a five-layer “cake”:

Energy Base layer powering AI’s real-time processing.
Chips and computing infrastructure NVIDIA’s core business.
Cloud infrastructure and services
AI models Language models, reasoning models.
Application layer Industry-specific AI applications in healthcare, finance, manufacturing, etc.

The largest infrastructure buildout in human history is underway, with hundreds of billions invested in chip fabs, cloud data centers, AI supercomputers, and related energy infrastructure.

Examples of infrastructure investments:

TSMC building 20 new chip plants
Micron investing $200 billion in US memory fabs
Foxconn, Wistron, Quanta building 30 new computer factories

AI Models & Innovation Highlights (2025)

Major breakthroughs in AI models include:

Agentic AI systems: Capable of reasoning, planning, and performing tasks beyond simple queries.
Open models: e.g., DeepSeek, enabling companies and researchers to build domain-specific AI solutions.
Physical intelligence AI: AI understanding complex scientific domains such as protein folding, chemistry, physics, and quantum mechanics.

Case study: Partnership with Lilly using AI to understand protein structures, accelerating drug discovery.

Labor, Jobs & Organizational Impact

Contrary to fears of AI job displacement, Huang argues AI is creating labor shortages in skilled trades (plumbers, electricians, technicians) due to massive infrastructure buildout.

Salaries in these sectors have nearly doubled, with six-figure incomes common for workers building chip and AI factories.
AI augments jobs rather than replaces them:
- Radiologists use AI for image analysis, enabling them to focus more on patient care; the number of radiologists has increased, hospital revenues rose, and more staff were hired.
- Nurses benefit from AI-assisted charting and transcription, freeing time for patient interaction, improving throughput and hospital performance, leading to more hiring.

Framework to assess AI impact on jobs:

Differentiate between the purpose of a job (e.g., patient care) and the tasks (e.g., image reading, charting) that can be automated.

Huang emphasizes AI as a productivity enhancer, leading to more jobs and better outcomes.

Global & Emerging Markets Strategy

AI should be treated as critical national infrastructure alongside electricity and roads.
Developing countries can leverage open AI models combined with local expertise (language, culture) to build domain-specific AI.
AI’s ease of use (prompting, natural language interaction) enables rapid adoption even without advanced technical skills, potentially closing the global technology divide.
Encourages emerging markets to build AI ecosystems and invest in AI infrastructure to accelerate economic growth.
Highlights AI’s potential to democratize programming and innovation by allowing users to instruct AI to generate code and applications without deep technical knowledge.

Europe’s Role & NVIDIA’s Market Position

Europe’s strong industrial and manufacturing base positions it well to lead in physical AI and robotics, a once-in-a-generation opportunity.
European countries should invest in energy and AI infrastructure to support AI ecosystems.
NVIDIA works with every AI company globally, powering AI applications across languages, sciences, and industries.
Huang advocates for Europe to leapfrog traditional software eras by integrating AI deeply into manufacturing and industrial sectors.
Europe’s strong scientific research base can leverage AI to accelerate discovery in deep sciences.

Investment & Market Insights

Despite talk of an AI bubble, Huang argues the demand for NVIDIA GPUs is outstripping supply, with rental prices rising even for older generation GPUs.
2025 saw record VC funding (~$100 billion globally), mostly into AI-native companies building applications across industries.
The AI infrastructure buildout requires trillions of dollars in investment over coming years.
Huang encourages pension funds and institutional investors to participate in AI infrastructure investments to share in long-term growth.
Infrastructure investments in energy, manufacturing, and skilled trades are critical and represent attractive, sustainable investment opportunities.

Key Frameworks and Recommendations

AI Computing Stack (Five Layers): Energy → Chips → Cloud → Models → Applications
Job Impact Framework: Distinguish between job purpose vs. task automation to understand AI’s effect on employment.
Platform Shift Concept: AI as a new computing platform enabling new applications and industries.
Global AI Strategy: Build AI infrastructure nationally, leverage open models, and use local knowledge to create domain-specific AI.
Investment Playbook: Focus on infrastructure buildout, support AI-native startups, and promote broad participation in AI-driven growth.

Key Metrics & KPIs

NVIDIA’s 37% compounded annual shareholder return since 1999 IPO.
VC funding in AI-native companies in 2025: over $100 billion globally.
Chip and memory investments:
- TSMC building 20 new plants
- Micron investing $200 billion in US fabs
Labor market: Nearly doubling of salaries in AI infrastructure-related trades.
GPU rental spot prices increasing, indicating strong demand and supply tightness.

Presenters & Sources

Jensen Huang – President and CEO, NVIDIA (primary speaker)
Moderator (unnamed in transcript)
Mentioned companies: NVIDIA, TSMC, Micron, Foxconn, Wistron, Quanta, Lilly, DeepSeek, Anthropic (Claude), ChatGPT (OpenAI)

This summary captures the core business, strategic, operational, and leadership insights shared by Jensen Huang at the WEF Annual Meeting 2026.