Tesla robotaxi is a multi-trillion dollar opportunity - ARK
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Investing.com -- According to ARK Invest, Tesla (NASDAQ: TSLA)'s upcoming robotaxi service represents a transformative, multi-trillion-dollar opportunity in the mobility industry.
Following Tesla's third-quarter earnings report, the company confirmed plans to launch a ride-hailing service next year in Texas and California, potentially unlocking a market far larger than the traditional ride-hailing sector.
"Elon Musk confirmed that next year Tesla will launch a ride-hail service—in our view, unlocking a multi-trillion-dollar robotaxi opportunity—in Texas and California," said ARK.
In ARK's view, Tesla is poised to benefit from this new service by leveraging electric vehicles' cost advantages over gas-powered cars.
"The operating costs associated with electric vehicles are roughly one-third those of their gas-powered counterparts," ARK analysts explained.
Tesla estimates that, at scale, robotaxi rides could cost consumers only $0.30-0.40 per mile, which ARK says is well below the $2 per mile typical of ride-hailing services and the $0.70 per mile cost of personal car ownership.
Tesla employees have already been testing the service in California, and while some states will require a safety driver during the early phases, ARK believes Tesla's large fleet will help the company meet regulatory thresholds swiftly.
Even if regulators delay the full rollout, ARK sees strategic benefits in Tesla starting with a human-driven service.
The opportunity is said to extend far beyond just operational savings. "Lower price points could unlock ~$11 trillion in revenue potential, ~80 times larger than the addressable market that Uber (NYSE: UBER) and Lyft (NASDAQ: LYFT) target today," ARK stated.
The firm explains that it believes the enormous potential comes from Tesla's ability to provide lower-cost rides that could attract far more users than traditional services.
ARK emphasized that Tesla's "multi-trillion-dollar opportunity" hinges on scaling quickly and deploying vehicles without safety drivers to achieve optimal efficiency.
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