Top Market Strategist Tom Lee Weighs In On Nvidia And AI Boom: 'Doesn't Seem Like A Bubble'

Renowned market strategist Tom Lee predicts a sustained AI boom, spotlighting NVIDIA Corp‘s (NASDAQ:NVDA) role in the trend.

What Happened: On Monday, Lee, a partner at Fundstrat Global Advisors, expressed his optimism about the ongoing AI surge in an interview with CNBC’s Last Call. “It doesn’t seem like a bubble. There’s real demand there,” he asserted, referring to Nvidia and the wider AI industry.

“In the past two years, there has been a lot of transformation. I think critical mass has been reached for AI. If there is a shortage of workers, over time we know we have to replace salaried workers with Silicon…,” he said regarding the skilled workers shortage in the tech industry.

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His comments came in response to the recent bullish sentiments surrounding the AI sector. This includes a prediction by Nvidia’s CEO Jensen Huang about the rise in global demand for AI infrastructure as nations prioritize the construction of independent systems.

Why It Matters: This development aligns with recent predictions and trends in the AI industry. Nvidia CEO Jensen Huang had forecasted a surge in global demand for AI infrastructure as countries prioritize building and controlling their AI systems. This prediction was made in light of the growing emphasis on “sovereign AI capabilities” in countries like India, Japan, France, and Canada.

Moreover, the AI story has driven remarkable growth in companies such as Nvidia and Microsoft Corp. Analyst Marc Chaikin of Chaikin Analytics suggested an outside-the-box way to invest in and profit from the AI boom, emphasizing the potential of IT technology stocks as consulting firms help companies transition into using more AI in their operations.

Meanwhile, Nvidia is leveraging AI tools to expedite chip design amid growing demand. The company, along with other industry players, has introduced AI tools to automate tasks like writing hardware code, verifying it, and summarizing notes and status updates, significantly reducing the time and complexity involved in creating advanced chips.

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