Despite an approximate 9% year-over-year decline in vehicle deliveries in 2025, marking the second consecutive year of negative growth, Tesla’s (TSLA) stock price has been surging in the capital markets. Its share price rose over 60% in 2024 and has continued to climb about 10% into 2025. Against the backdrop of challenges in its electric vehicle business, this strong stock performance has drawn widespread attention. Behind this, a core market expectation is that the company is transitioning from an automaker to an artificial intelligence enterprise. This doesn’t mean abandoning its EV business, but rather that Tesla’s future will increasingly depend on its investments and breakthroughs in artificial intelligence. It is the immense potential of AI technology that supports its high valuation, with a price-to-sales ratio nearing 15 times.
Morgan Stanley released a research report indicating that the successful deployment of Tesla’s robotaxi business is a key catalyst underestimated by the market. Analyst Andrew Percoco believes the firm is optimistic about Tesla’s Cybercab model and its related businesses, predicting it will generate a powerful “flywheel effect” for its entire ecosystem. He explains that each additional mile of safe, unsupervised driving by a robotaxi provides an optimization opportunity for the underlying autonomous driving model, thereby accelerating the path to full self-driving capability for personal vehicles. This progress can not only drive the adoption of the FSD suite, boost vehicle demand, and enhance cash flow, but it can also fund Tesla’s long-term layout in the field of physical AI. Although Tesla’s deployment process in Austin is cautious, it helps refine its rollout strategy, paving the way for rapid scaling in seven new cities planned for entry in the first half of this year. It is expected that the transition time from supervised to fully autonomous driving will be significantly shortened in the future.
The Morgan Stanley team specifically emphasized that, leveraging its vertical integration advantages from vehicle manufacturing to fleet operations, Tesla’s robotaxis possess a significant cost structure advantage. Taking the Model Y as an example, they estimate its comprehensive cost to be approximately $0.81 per mile, significantly lower than the ride-hailing industry’s $1.71 and Waymo’s $1.43. With the mass production of the Cybercab, they project the cost per mile could potentially drop further to $0.37 by 2035.
Another electric vehicle company, Rivian (RIVN), is also investing heavily in artificial intelligence, but its market situation is markedly different. Rivian’s price-to-sales ratio is only 3.3 times, with a market capitalization below $20 billion, a far cry from Tesla’s valuation of approximately $1.2 trillion. Wall Street still seems skeptical about this emerging AI-focused stock, but this could also present a potential opportunity for investors. Firstly, Rivian is going all-in on AI. With institutions like McKinsey predicting autonomous vehicles will become a reality within the next few years, Rivian recognizes that full self-driving capability will be central to future competition. Consequently, it is investing heavily in AI research and development, even planning to produce its own AI chips to control core technology and reduce reliance on external suppliers.
Secondly, Rivian’s new R2 SUV is poised to be a key driver of its AI strategy. The evolution of AI models relies on massive amounts of data, and Tesla’s leading edge stems from the real-world data collected by its millions of vehicles on the road. Next month, Rivian is expected to begin deliveries of its R2 model, its first vehicle with a starting price below $50,000, which will make its products accessible to tens of millions of new buyers. As sales volume increases, Rivian will gain more data to train and optimize its autonomous driving models.
