Beyond the Chatbot: Veteran Analyst Pivots AI Investment Thesis to Physical World, Backs Tesla and Nvidia

For three years, the financial world's conversation on artificial intelligence has been dominated by chatbots and large language models. But according to one closely-watched Wall Street voice, that focus is about to shift—dramatically.

Dan Ives, veteran tech analyst at Wedbush Securities, is steering the investment narrative toward what he calls "physical AI": intelligent systems that interact with and manipulate the physical world. In a recent client note and media appearances, Ives positioned Tesla (TSLA) and Nvidia (NVDA) not merely as beneficiaries, but as foundational pillars of this emerging epoch.

"The real economic value of AI isn't confined to a chat window or a data center," Ives told CNBC. "It's when AI gets legs, wheels, and eyes—when it starts driving cars, running factories, and managing infrastructure. That's the next industrial revolution, and it's already underway."

This marks a significant pivot from the prevailing AI investment playbook. While hyperscalers and software firms have captured headlines, Ives contends the tangible, revenue-generating phase of AI will be built on machines that perform physical labor and decision-making.

Tesla's Business Model Pivot

At the core of Ives' thesis for Tesla is a fundamental rebranding: from electric vehicle manufacturer to a vertically-integrated AI and robotics platform. The key driver is Tesla's Full Self-Driving (FSD) software suite, now offered at $99 per month. According to data from Inside EVs, Tesla reported 1.1 million active FSD subscriptions in its last quarter—a 38% year-over-year surge.

"We are witnessing a business model transformation in real time," Ives noted. He projects FSD adoption could leap from roughly 12% today to 50% by 2026, a "golden year" he believes will be catalyzed by the convergence of FSD, the anticipated Cybercab network, and the Optimus humanoid robot. Ives maintains an Outperform rating on Tesla with a $600 price target and an $800 bull-case scenario.

Nvidia: The Invisible Operating Layer

If Tesla is building the agents, Nvidia is building the nervous system. Ives frames Nvidia CEO Jensen Huang as the "godfather of AI," whose company provides the essential silicon and software layer for physical AI. Beyond its data center dominance—evidenced by $51.2 billion in Q3 data center revenue, up 66%—Nvidia is deepening its push into "embodied AI."

Through its Isaac Sim platform for robotic simulation and projects like the GR00T foundation model for humanoid robots, Nvidia is aiming to be the standard for training and deploying intelligent machines. Its automotive segment, though smaller, is growing rapidly, with quarterly revenue of $592 million (up 32% year-over-year) driven by the DRIVE platform and a recently announced partnership with Uber.

"Nvidia isn't just selling chips; it's selling the entire stack for the physical economy's automation," Ives argued, suggesting the company holds a four-to-five-year lead over potential rivals.

Analyst Commentary

"Ives is spot-on about the direction, but dangerously early on the timeline," says Michael Chen, a portfolio manager at Horizon Capital. "The infrastructure is being laid now, but mass-scale profitability in physical AI is a 2030s story, not a 2026 one. The market's patience will be tested."

"Finally, someone is talking sense!" exclaims Sarah Gibson, an engineer and tech investor. "The hype around generating poems and images is absurd when the real problem is our crumbling physical infrastructure and labor shortages. Tesla and Nvidia are the only companies building the full stack. This isn't just an investment trend; it's a societal imperative."

"This feels like a narrative crafted to revive interest in Tesla's story," offers David Park, a skeptical independent analyst. "FSD is still a Level 2 system with glaring limitations, and humanoid robots are a decade away from commercial viability. Calling this a 'new industrial revolution' now is hyperbolic and ignores the immense, unsolved challenges in real-world robotics."

"The data supports the shift," notes Dr. Anya Sharma, a professor of robotics at Stanford. "Investment in industrial automation and embodied AI research has tripled in two years. Nvidia's tools are becoming the de facto standard in labs worldwide. The flywheel effect Ives describes is real, even if the public manifestation is gradual."

This analysis was inspired by reporting from TheStreet. It has been expanded with additional context, commentary, and forward-looking implications.