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Home » Nvidia CEO Jensen Huang says AI won’t be the job killer that everyone fears. The reason is as follows
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Nvidia CEO Jensen Huang says AI won’t be the job killer that everyone fears. The reason is as follows

Editor-In-ChiefBy Editor-In-ChiefJanuary 21, 2026No Comments6 Mins Read
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Nvidia CEO Jensen Huang said Wednesday that artificial intelligence will lead to more jobs, not fewer. In an interview with BlackRock CEO Larry Fink at the World Economic Forum in Davos, Switzerland, Jensen systematically explained how AI is different from other technological innovations of the past and how it could be an incredible driver of economic growth and prosperity. Jensen’s meeting with WEF co-chair Fink led to a high-level conversation about what AI is, what it is not, what kind of investment is needed, why, and how much investment is needed. At the heart of the exchange, the CEO of club name Nvidia said that AI is a platform change. Examples of platforms include private businesses, the Internet, smartphones, and the cloud. These are both physical and digital infrastructures on which the applications we all use in our daily lives are built. Just as these platforms have laid the foundation for significant economic growth, so too will AI. ChatGPT and other large language models may technically be applications in their own right, but the difference is that new AI-oriented applications will be built on top of these LLMs. Jensen believes there are five layers to building an AI platform. (1) Enough energy to run everything. (2) Nvidia-proprietary chip/computing infrastructure; (3) Cloud Infrastructure/Services. (4) AI model. (5) Application layer. This is the key layer where the economic benefits of AI are realized. Allaying the world’s not-so-irrational fears about AI replacing human workers, Jensen offered a more optimistic view. Beyond the jobs created by the physical construction of AI infrastructure, such as electricians, plumbers, and construction workers, Jensen said the implementation of AI will increase demand for goods and services, which will lead to increased employment. Although the number of employees per customer may not be as large, it is still possible that more customers will demand more employees as the company becomes more efficient. For example, the number of radiologists has increased as hospitals are able to handle more patients thanks to AI, Jensen said. While AI reads the scan, a human is still needed to review and confirm the diagnosis. More patients means more scans to examine, and more human radiologists are needed. The benefit is that with AI performing the scans, radiologists have more time to spend with patients and discuss results with fellow clinicians. Jevons paradox? As radiologists become more capable and efficient at their jobs, it becomes easier to see radiologists, resulting in an overall increase in demand from patients to see radiologists. Radiology was a timely analogy, as Bristol-Myers Squibb, the club’s name, announced Tuesday that it will collaborate with Microsoft’s AI-powered radiology platform to develop and launch an image processing algorithm aimed at accelerating early detection of lung cancer. These new tools, which can be used to analyze X-rays and CT scans, can help clinicians see hard-to-see lung nodules and identify patients in the early stages of the disease. This partnership is the latest way in which healthcare and artificial intelligence are rapidly intersecting. On stage with Fink on Wednesday, Jensen pointed out that there is a movement in nursing similar to what is happening in radiology. Nurses spend about half of their time preparing medical records. But Jensen said AI allows nurses to spend more time visiting patients and providing the human touch that is often lacking when hospitals are understaffed. By reducing nursing bottlenecks, hospitals can see more patients faster. As a result, increased demand for hospitals improves their financial situation, which in turn allows them to hire more nurses. In Jensen’s view, the key to understanding how AI will impact a particular job is to first distinguish between purpose and task. Returning to the radiology example, he said the purpose of radiologists is to diagnose patients, and the job of radiologists and nurses is ultimately to care for people. Reading and scanning charts is very important for that purpose, but it is a task that needs to be performed to achieve the end goal of the job. By automating certain tasks, you can improve people’s ability to actually do their jobs. Therefore, Jensen argued that AI should not result in fewer doctors and nurses in the medical field, but should allow more doctors and nurses to spend more time with patients and provide better outcomes. Asked about investing in AI, Jensen largely put aside thoughts about spending bubbles. So when asked if investment levels are too low, he offered a simple way to think about spending: is there a bubble or is more spending needed? He attributed this to the fact that even though there are millions of Nvidia GPUs (graphics processing units) currently available in the cloud, spot prices for GPU rentals are rising, not just for the latest generation, but even for chips from two generations ago that are in the rearview mirror. He believes this is due to the large number of AI companies being founded. If rental prices for GPUs from two generations ago are increasing, it’s clear that supply (as a whole, not just related to the latest chips) is significantly lower than demand. Conclusion There may be bubble-like areas in the market, but the word has no place in the conversation when discussing names like Nvidia and mega-cloud infrastructure players that generate real revenues and trade at reasonable valuations. We are still in the early stages of building our AI infrastructure, before we start thinking seriously about the application layer of the stack that touches every aspect of our daily lives. (Jim Cramer’s Charitable Trust is long NVDA, BMY, and BLK. See here for a complete list of stocks.) As a subscriber to Jim Cramer’s CNBC Investment Club, you will receive trade alerts before Jim makes a trade. After Jim sends a trade alert, he waits 45 minutes before buying or selling stocks in his charitable trust’s portfolio. If Jim talks about a stock on CNBC TV, he will issue a trade alert and then wait 72 hours before executing the trade. The above investment club information is subject to our Terms of Use and Privacy Policy, along with our disclaimer. No fiduciary duties or obligations exist or arise from your receipt of information provided in connection with the Investment Club. No specific results or benefits are guaranteed.



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