NVIDIA CEO Urges Employees to Automate Every Task with AI

Introduction

NVIDIA CEO Jensen Huang has issued a clear directive to employees: automate every task possible with artificial intelligence. In a recent all-hands meeting following NVIDIA's record-breaking $57 billion revenue quarter, Huang responded forcefully to reports that some managers were discouraging employees from relying too heavily on AI tools, asking "Are you insane?" and stating unequivocally: "I want every task that is possible to be automated with artificial intelligence to be automated with artificial intelligence."

This directive represents a significant shift in how NVIDIA approaches artificial intelligence adoption within its own organization. Rather than treating AI as an optional productivity enhancer, Huang is positioning automation as a core requirement for all employees, reinforcing NVIDIA's position as both a leader in AI hardware and one of the technology's most aggressive internal adopters.

The announcement comes at a pivotal moment for the AI industry, as major technology companies increasingly mandate AI use in their workflows. Huang's comments also addressed a critical concern for many workers: whether AI automation will eliminate jobs. His response, backed by NVIDIA's rapid expansion from 29,600 to 36,000 employees, suggests that automation and job growth can coexist in the current AI boom.

Huang's Directive: Automate Everything Possible

The "Are You Insane?" Moment

According to an audio recording obtained by Business Insider, Huang's comments came during an all-hands meeting where he addressed reports that some NVIDIA managers were discouraging employees from relying too much on AI. His response was characteristically direct and emphatic.

Key Points from Huang's Statement:

Clear mandate: Every automatable task should be automated with AI—no exceptions
Manager pushback addressed: Direct response to reports of managers discouraging AI use
Cultural shift: Moving from optional to required AI adoption across all departments
Tool refinement: Encouraging engineers to improve tools when full automation isn't yet possible
Continuous improvement: Focus on iterative enhancement rather than waiting for perfect solutions

This directive reflects NVIDIA's broader internal pivot toward making AI tools a standard part of its workflow, not just an experimental addition. The company is using its commanding market position to showcase how deeply an AI-driven company can embed automation into its own structure—right down to daily workflows.

Specific Tools and Platforms

Huang reportedly urged engineers to continue using tools such as Cursor, an AI-assisted coding platform that NVIDIA's own developers rely on extensively. The platform represents a shift toward AI-assisted development, where artificial intelligence augments human coding capabilities rather than replacing them. He also encouraged engineers to keep refining these tools when tasks fall short of full automation, suggesting that the goal is continuous improvement rather than immediate perfection.

AI Tools Mentioned:

Cursor: AI-assisted coding platform used by NVIDIA developers
Generative AI systems: For coding and development work
Automation tools: For various workflow tasks across the organization

This focus on specific tools demonstrates that NVIDIA isn't just talking about AI adoption in abstract terms—the company is actively using and improving AI tools in its daily operations, setting an example for how AI can transform workplace productivity. By mandating the use of tools like Cursor, NVIDIA is creating a culture where AI proficiency becomes as fundamental as traditional software development skills.

Industry-Wide AI Mandates

Tech Giants Embrace Required AI Use

NVIDIA's directive is part of a broader industry trend where major technology companies are moving from optional to required AI adoption:

Microsoft and Meta:

Have tied AI use to employee performance evaluations

Google:

Has instructed engineering teams to incorporate generative AI systems into coding work

Amazon:

Has explored deploying Cursor in response to employee demand

These internal mandates mark a notable shift from AI as an optional productivity enhancer to a required professional tool. Across the technology sector, managers increasingly expect engineers to integrate automation and generative AI not just for speed, but also to ensure familiarity with the systems driving their companies' next-generation products. This trend reflects a broader movement toward human-AI collaboration in the workplace, where AI tools become integral to daily workflows rather than supplementary aids.

The Strategic Imperative

This shift reflects several strategic considerations:

Competitive Necessity:

Companies need employees familiar with AI systems that power their products
AI proficiency becomes a competitive advantage
Early adoption creates expertise that competitors may lack

Product Development:

Employees using AI tools understand their capabilities and limitations
Direct experience informs product development decisions
Internal use cases drive innovation
Building products that solve real problems encountered in daily work

Cultural Transformation:

Moving from AI as external technology to AI as integrated workflow
Creating an AI-native workforce
Building organizational capabilities around AI

Addressing Job Security Concerns

Rapid Growth Despite Automation

Huang directly addressed a recurring anxiety within the workforce: whether AI automation tools could eventually eliminate some roles. His response was both confident and data-driven, pointing to NVIDIA's rapid expansion as evidence that automation and job growth can coexist.

NVIDIA's Growth Metrics:

Fiscal 2024: 29,600 employees
Fiscal 2025: 36,000 employees
Growth: Addition of 6,400 employees in one year
Current status: "Probably still about 10,000 short" of staffing needs

This growth trajectory suggests that rather than eliminating jobs, AI automation is enabling NVIDIA to scale operations more efficiently, creating new opportunities even as existing tasks become automated. The company's expansion demonstrates that automation and hiring can occur simultaneously, challenging the common narrative that AI adoption necessarily leads to workforce reduction.

Expansion Plans

Huang cited specific expansion initiatives that demonstrate continued hiring needs:

Geographic Expansion:

Taipei: New facilities requiring additional staff
Shanghai: Expansion into Chinese market
Multiple US sites: Continued domestic growth

These expansion plans indicate that NVIDIA's automation strategy isn't about reducing headcount—it's about enabling the company to grow faster and more efficiently while maintaining quality and innovation.

"I Promise You, You Will Have Work to Do"

Huang's direct assurance to employees—"I promise you, you will have work to do"—reflects a broader perspective on how AI automation changes rather than eliminates work. This perspective aligns with research showing that AI adoption often creates new categories of jobs even as it transforms existing ones. This perspective suggests:

Work Transformation:

Automation handles routine, repetitive tasks, freeing human workers for complex problem-solving
Employees focus on higher-value, creative, and strategic work that requires human judgment
New roles emerge as AI capabilities expand, creating demand for AI specialists and hybrid roles
Traditional job functions evolve to incorporate AI collaboration rather than being replaced

Growth Enablement:

Automation allows companies to scale without proportional headcount increases
Efficiency gains enable expansion into new markets and products
Technology creates new categories of work

Skill Evolution:

Employees develop new skills working alongside AI
AI proficiency becomes a core competency
Workforce adapts to AI-enhanced workflows

The Context: Record-Breaking Quarter

$57 Billion Revenue Quarter

Huang's directive came during an all-hands meeting following NVIDIA's strongest quarter on record, with $57 billion in revenue—a figure that underscores the company's dominant position in the AI hardware market. This context is important because:

Financial Success:

Record revenue demonstrates market demand for NVIDIA's AI products
Success validates the company's AI strategy
Growth creates resources for expansion and hiring

Market Position:

NVIDIA's dominance in AI hardware gives it unique insights into AI adoption patterns
Company can serve as a model for AI-driven operations, demonstrating best practices
Leadership position enables bold internal initiatives that other companies may follow
First-hand experience with AI tools informs product development and customer guidance

Strategic Confidence:

Strong financial performance provides confidence for aggressive AI adoption
Success enables investment in AI tools and training
Market position supports cultural transformation

This financial context suggests that NVIDIA's AI automation mandate isn't a cost-cutting measure—it's a strategic initiative enabled by success and designed to maintain competitive advantage.

Implications for the AI Industry

Setting the Standard

NVIDIA's aggressive internal AI adoption sets a standard for how AI-native companies should operate. As a leader in AI hardware, NVIDIA's approach to internal AI use demonstrates:

Leading by Example:

Using the technology you create builds credibility
Internal experience informs product development
Demonstrating value to customers through own use

Cultural Transformation:

Moving from AI as product to AI as infrastructure
Creating AI-native organizational culture
Building competitive advantage through internal expertise

Industry Influence:

Other companies look to NVIDIA for AI adoption strategies
Setting trends in workplace AI integration
Influencing broader industry practices

The Automation Paradox

Huang's comments highlight an important paradox in the current AI boom: companies are simultaneously automating tasks and hiring aggressively. This suggests:

Automation Enables Growth:

Efficiency gains allow companies to scale operations
Automation handles routine work, freeing humans for complex tasks
Technology creates capacity for expansion

New Categories of Work:

AI creates new types of jobs and roles
Automation generates demand for AI expertise
Technology enables new business models and markets

Complementary Relationship:

AI and human workers complement rather than replace each other
Automation increases productivity per employee
Higher productivity enables more hiring, not less

Technical Implementation: Tools and Platforms

Cursor and AI-Assisted Development

Huang's specific mention of Cursor highlights the importance of AI-assisted coding platforms in modern software development. Cursor represents a category of tools that enable AI-assisted development, transforming how engineers write code and solve problems. These platforms:

Development Acceleration:

Speed up coding tasks through AI assistance
Reduce time spent on routine programming work
Enable developers to focus on architecture and problem-solving

Quality Improvement:

AI can suggest better code patterns
Catch errors and suggest fixes
Maintain coding standards automatically

Learning and Adaptation:

Developers learn from AI suggestions
Tools improve through use and feedback
Continuous refinement of capabilities

Beyond Coding: Comprehensive Automation

While Huang mentioned Cursor specifically, his directive to "automate every task possible" suggests a broader scope that extends beyond coding to encompass various forms of workplace automation:

Workflow Automation:

Document processing and analysis
Communication and scheduling
Data analysis and reporting

Decision Support:

AI-assisted decision making using machine learning models
Pattern recognition and insights from data analysis
Predictive analytics for business intelligence

Creative and Strategic Work:

Content generation and editing
Research and analysis
Strategic planning support

This comprehensive approach suggests that NVIDIA sees AI automation as applicable across all functions, not just technical roles.

Challenges and Considerations

Managing the Transition

While Huang's directive is clear, implementing comprehensive AI automation presents challenges:

Training and Adoption:

Employees need training on AI tools
Change management for new workflows
Overcoming resistance to new technologies

Tool Selection and Integration:

Choosing appropriate tools for different tasks
Integrating AI tools into existing workflows
Managing multiple AI platforms and services

Quality and Oversight:

Ensuring AI outputs meet quality standards
Maintaining human oversight where needed
Balancing automation with control

Cultural Change:

Shifting from manual to AI-assisted work
Building trust in AI systems
Creating new norms and practices

Addressing Skepticism

Huang's forceful response to managers discouraging AI use suggests that skepticism remains a challenge, even within a company that creates AI technology. This skepticism may stem from:

Uncertainty About Quality:

Concerns about AI accuracy and reliability
Fear of errors or mistakes
Preference for proven manual processes

Job Security Fears:

Worry that AI will replace human workers
Uncertainty about future roles
Resistance to change

Lack of Understanding:

Insufficient knowledge about AI capabilities
Unfamiliarity with available tools
Difficulty seeing automation opportunities

Huang's directive addresses these concerns by making AI adoption mandatory and providing reassurance about job security through growth data.

Future Outlook

Continued Expansion

Huang's statement that NVIDIA is "probably still about 10,000 short" of staffing needs suggests continued aggressive hiring, which implies:

Sustained Growth:

Expansion into new markets and products
Increased demand for NVIDIA's AI solutions
Continued investment in research and development

Diverse Hiring Needs:

Not just technical roles, but across all functions
New roles created by AI capabilities
Support for expanded operations

Global Presence:

Expansion in Taipei, Shanghai, and US locations
Building global AI infrastructure
Serving international markets

Industry-Wide Transformation

NVIDIA's approach reflects and influences broader industry trends:

Mandatory AI Adoption:

More companies will require AI use
AI proficiency becomes standard job requirement
Industry-wide cultural shift

Work Transformation:

Routine tasks increasingly automated
Human workers focus on complex, creative, strategic work
New categories of jobs emerge

Competitive Dynamics:

Companies without AI adoption risk falling behind
AI-native companies gain advantages
Market leaders set adoption standards

Conclusion

Jensen Huang's directive to NVIDIA employees represents a defining moment in workplace AI adoption. By mandating that "every task that is possible to be automated with artificial intelligence" should be automated, Huang is positioning NVIDIA as not just a creator of AI technology, but as a model for how AI-native companies should operate.

Key Takeaways:

Clear mandate: AI automation is required, not optional, at NVIDIA
Tool focus: Specific platforms like Cursor are integral to workflows
Job security: Rapid growth from 29,600 to 36,000 employees demonstrates automation and hiring can coexist
Industry trend: NVIDIA joins Microsoft, Meta, Google, and Amazon in mandating AI use
Strategic imperative: AI adoption is about competitive advantage, not just efficiency
Future growth: Company plans to hire 10,000 more employees despite automation

The directive comes at a time when NVIDIA is experiencing unprecedented success—a $57 billion revenue quarter—demonstrating that aggressive AI adoption is a strategy for maintaining leadership, not a response to challenges. Huang's assurance that employees "will have work to do" reflects a vision where AI automation enables growth and creates new opportunities, rather than eliminating existing ones. This approach positions NVIDIA as both a creator and a practitioner of AI technology, using its own tools to drive internal transformation.

As the AI industry continues to evolve, NVIDIA's approach to internal AI adoption will likely influence how other companies think about integrating AI into their workflows. The message is clear: in an AI-driven world, companies that don't aggressively adopt AI internally risk being left behind, while those that embrace automation can scale faster, innovate more effectively, and create more opportunities for their workforce. This represents a fundamental shift in how organizations approach workplace AI, moving from experimental adoption to strategic integration.

The future of work in the AI era isn't about humans versus machines—it's about humans working alongside AI to achieve more than either could alone. NVIDIA's directive and its continued growth demonstrate that this future is already here.

Sources

Want to learn more about AI tools and automation? Explore our AI tools catalog to discover platforms like Cursor and other AI-assisted development tools, check out our AI fundamentals courses to understand how AI automation works, or browse our glossary for key terms like artificial intelligence, generative AI, and machine learning. Learn more about NVIDIA's role in AI hardware and how AI agents are transforming the workplace.