Jensen Huang: We are worried that AI replacing jobs might be heading in the wrong direction

Source: World Economic Forum Annual Meeting

Content organized by: Peter_Techub News

As artificial intelligence (AI) technology advances rapidly, discussions about whether “AI will replace human jobs” continue to intensify. From the tech industry to traditional sectors, from corporate management to frontline workers, anxiety is spreading worldwide.

At the recent World Economic Forum, Jensen Huang, founder and CEO of NVIDIA, offered a perspective different from the mainstream narrative on this issue. He pointed out that the common concerns about AI may be misfocused. In Huang’s view, AI is not just a simple efficiency tool but a “platform-level leap” that is reshaping computing methods, industrial structures, and economic systems.

AI is the Next-Generation General-Purpose Computing Platform

Huang Huang compares AI to PCs, the internet, and cloud computing, believing it shares the attribute of a “general-purpose platform.” In the past, software relied on humans pre-writing rules, and computers could only operate in highly structured environments; now, AI enables computers to understand natural language, images, and complex semantics for the first time, allowing reasoning and decision-making in real-time environments.

He notes that the large models and intelligent applications currently attracting attention are just the initial forms of this platform. In the future, many new applications will be built directly on AI capabilities, driving a shift in software paradigms from “instruction-based” to “intent-based.”

AI Changes Tasks, Not the Purpose of Work

Regarding the core question of “Will AI replace jobs,” Huang Huang suggests distinguishing between a “task” and a “purpose” of a job.

Using the healthcare industry as an example, he pointed out that when AI made breakthroughs in medical image recognition, some believed radiologists would be quickly replaced. However, the reality was quite the opposite: AI automated repetitive tasks like image analysis, enabling doctors to focus more on diagnostic decisions, patient communication, and interdisciplinary collaboration. The overall efficiency of the healthcare system improved, leading to increased service demand and job growth.

Similar changes are occurring in nursing. AI applications in medical record organization and data entry have reduced nurses’ administrative workload, allowing them to focus on patient-centered responsibilities.

Huang Huang believes that AI automates “how to do” rather than “why to do.” When work goals are amplified and efficiency is improved, employment structures tend to change but not necessarily decrease.

AI Is Triggering a New Wave of Infrastructure Development

At the industry level, Huang Huang emphasizes that AI is not just a competition of algorithms or models but a global infrastructure-building effort.

He breaks down the AI industry into several layers: energy, chips and computing power, data centers, models, and applications, noting that these layers are expanding simultaneously. Worldwide, the construction of “AI factories” is accelerating, with investments reaching hundreds of billions of dollars and expected to move toward a trillion-dollar scale.

This process is also creating numerous new industry jobs, including high-skilled engineering positions and manufacturing, installation, and maintenance roles related to computing infrastructure. In some regions, these roles are even experiencing significant salary increases.

The Technical Barriers Are Rapidly Being Lowered

Huang Huang also points out that another important impact of AI is the significant reduction of technical barriers. As natural language becomes the primary mode of human-computer interaction, more people without technical backgrounds can directly participate in software development and product creation.

He believes this change will broaden participation in technological innovation, allowing more regions and populations to enter the digital economy.

On a global scale, Huang Huang introduces the concept of “National Intelligence,” suggesting that language and culture are becoming vital resources in the AI era. Through localized training and applications, countries can build intelligent systems tailored to their needs rather than relying solely on external technologies.

Conclusion

In Huang Huang’s view, AI is not a cold “replacement machine” but a general-purpose technology that amplifies human capabilities and reshapes productivity structures.

The real question may not be “Will AI replace human work,” but rather: Are society, industries, and individuals prepared to adapt to this deep technological transformation?