Tesla’s Autonomy Push Meets Rising Industry Momentum, as New Data Signal a Bigger Market Taking Shape

Tesla is widening its self-driving ambitions while fresh industry research points to a larger commercial opportunity for autonomous vehicles (AVs). The company began rolling out FSD (Supervised) v14.1, adding “Arrival Options” that let drivers choose where the system should park at trip’s end and introducing an additional speed profile alongside updates to emergency-vehicle behavior and other driving scenarios, according to the company’s statement on X.

The software update lands as Tesla reported record third-quarter deliveries and energy-storage deployments. The company said it produced 447,450 vehicles and delivered 497,099 in the period, including 481,166 Model 3/Y deliveries, and deployed 12.5 GWh of energy-storage products. Tesla plans to post third-quarter financial results on Oct. 22, 2025 and hold a results webcast that afternoon.

Rival Lucid Group also detailed quarterly operations , saying it produced 3,891 vehicles in the third quarter and delivered 4,078, with nine-month totals of 9,966 produced and 10,496 delivered. Lucid scheduled its earnings call for Nov. 5, 2025 and opened a shareholder Q&A portal in partnership with Say Technologies ahead of the event.

Beyond individual company updates, a new report from the Bank of America Institute sketches an expanding economic canvas for autonomy. The think tank estimates the AV opportunity could reach $1.2 trillion by 2040 as adoption spreads beyond passenger cars to trucks, public transport and industrial uses. The report cites more than 120 robotaxi and shuttle deployments worldwide from 32 companies, with seven already fully commercial.

Costs remain pivotal. According to the report, removing the human driver can cut per-mile costs by 52%, and hardware costs for Chinese robotaxi platforms have fallen more than 50% compared with prior AV models—trends that could unlock new addressable markets as operators scale. At the same time, the shift to end-to-end AI “AV2.0” architectures is driving sizable infrastructure needs: a small test fleet could require 100 petabytes of data storage after three years, and training/running models may demand 10× more GPUs than current L2 driver-assistance systems.

Safety and liability remain central to commercialization. The Institute notes that human error accounts for 94% of crashes and argues AVs could deliver a step-change in roadway safety, even as insurance responsibility tilts from individual motorists toward manufacturers and software providers. Public confidence is still evolving: only 13% of U.S. adults report they are prepared to trust AV technology, with 53% citing safety as the leading concern, according to survey data cited in the report.

Taken together, Tesla’s continued software iteration and record vehicle delivery pace, Lucid’s production ramp, and Bank of America’s projection of a broadening economic prize suggest autonomy is moving from pilot projects to early commercialization. The winners are likely to be firms that can pair steadily improving driver-assistance stacks—such as Tesla’s latest additions around arrival choices and emergency-vehicle handling—with the balance-sheet capacity and data-center infrastructure required to operate fleets at scale.