According to a statement from a senior Tesla executive obtained by Chasing Cars, Tesla plans to pull back on its current pricing strategy - which includes regular vehicle price changes. The change will take effect in Australia, at least, but potentially in the wider Asia-Pacific market.
This new pricing strategy is a big change to Tesla’s existing philosophy, which has been to adjust pricing based on market conditions. This meant regular vehicle price changes - sometimes multiple changes for the same vehicle within the same month.
This new “stable pricing” scheme will begin once the regular version of Tesla’s Refreshed Model Y begins shipping in Australia, which is expected to be sometime this summer.
One possible reason for these changes is consumer sentiment. It’s hard to commit to a big purchase—especially a vehicle—when prices can drop or rise by $5,000 or more overnight. That uncertainty was on full display in December 2022, when Tesla slashed Model Y prices after the pandemic-driven supply chain issues.
While most price adjustments have been smaller, typically between $1,000 and $2,000, they still create stress for buyers trying to secure the best deal.
Another potential reason for getting rid of evolving prices is rising competition from China’s low-cost EVs. Tesla may be avoiding a race to the bottom, where Tesla and Chinese competitors get into an intense price war, and margins become razor thin.
Chinese vehicles offer premium features at lower prices, thanks to heavy government subsidies. Markets like Australia, where Chinese EVs are gaining traction, are seeing increased interest in these more affordable vehicles.
Rest of the World
For now, this new price policy seems to be limited to Australia. It’s unclear whether Tesla plans to expand them across the Asia-Pacific market—let alone globally.
Tesla often discusses pricing strategies during financial events, so there’s a chance this topic could come up in the Q1 2025 Earnings Call—though that’s still some time away. Many customers would welcome more stable pricing, as it would make committing to a Tesla purchase easier. It would also prevent owners from getting upset when the price goes down shortly after they’ve purchased the vehicle.
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Tesla's Robotaxi network pilot is slated to launch in Austin in just a few weeks with Model Y vehicles running FSD Unsupervised. However, beyond the technological hurdles of implementing FSD, there’s a crucial question.
How Will Driverless Vehicles Be Insured
Will there be an insurer that steps up to cover Tesla’s taxi network, or will Tesla be on its own? The question becomes even more complicated once customers add their vehicles to Tesla’s Robotaxi network and start receiving and using FSD Unsupervised themselves.
Robotaxi Insurance
Actuarial science (the math behind insurance rates) requires vast amounts of data, and there is little data on autonomous fleets today. However, Waymo, Google's self-driving car division, has already launched in several markets and is insured by a third-party insurance company, so there is some history.
However, it wouldn’t be surprising if Tesla decided to insure their own fleet. While Tesla Insurance has relied on third-party insurance behind the scenes, Tesla recently started underwriting their own insurance earlier this year.
FSD Unsupervised to Include Insurance?
The fundamental difference between FSD Supervised and FSD Unsupervised lies in responsibility. With today’s FSD Supervised, the liability lies with the driver - they must remain attentive and legally responsible for the vehicle’s actions at all times. On the other hand, with Unsupervised FSD, they may not necessarily have to, as the vehicle is handling the entire driving task without needing human oversight or intervention.
Today’s insurance policies would argue that the owner of the vehicle is entirely liable for what happens with their vehicle. They also typically don’t allow ride-hailing services and will likely not permit autonomous use when FSD Unsupervised finally starts rolling out.
Tesla will likely need to offer insurance to drivers while their vehicles are driving on FSD Unsupervised. This could be through Tesla Insurance or some future means that they haven’t disclosed yet, but Tesla’s venture into insurance is starting to make a lot more sense now with robotaxis.
Tesla could include the cost of insurance for FSD Unsupervised right into the FSD subscription fee. If traditional insurance companies aren’t willing to take on the additional liability, then Tesla will likely have to. This would increase the cost of FSD Unsupervised, which would now include insurance.
Tesla Insurance is currently limited to just a few states, which would limit Tesla’s expansion of FSD Unsupervised. It seems that Tesla Insurance would need to expand quickly, or traditional insurance companies would need to start offering insurance for customer vehicles operating autonomously. Given how slow traditional companies move compared to Tesla, this could become an issue, as Tesla needs to get their insurance product approved on a state-by-state basis.
Insurance is a complicated issue that could slow down the expansion of autonomy for customer-owned vehicles, but it’s only one of the many hurdles Tesla needs to solve on its way to offering FSD Unsupervised.
Whichever path Tesla takes could be one that will define the rest of the Robotaxi industry.
Tesla’s ambitions extend far beyond electric vehicles, with the company recently saying its goal is sustainable abundance. However, solving vehicle autonomy and deploying a large-scale Robotaxi network are key steps toward that goal.
Today, FSD Supervised offers a glimpse into what an autonomous vehicle will be capable of, but the journey to truly autonomous vehicles involves several interconnected pillars that are in development.
The FSD Journey
The foundation of Tesla’s ambitions is in FSD, which has been on a long, iterative journey. The end goal for FSD is to power both autonomous vehicles, as well as Optimus, Tesla’s humanoid robot.
FSD’s journey began with FSD Beta, an initial phase of real-world testing and extensive data gathering with real users. The first batch of users were influencers on Twitter and YouTube. Tesla eventually opened up FSD Beta to more owners with their Safety Scores in the United States, and then the program rolled out to Canada. Shortly afterward, the Safety Score requirement was removed, and Tesla offered FSD Beta to anyone who purchased FSD or subscribed to FSD. This process took place over several years.
In Spring of 2024, Tesla removed the Beta label and formally introduced FSD (Supervised). FSD Supervised dropped the vast majority of Tesla’s hand-written code and adopted an approach that relied on end-to-end AI networks. This was an important architectural shift, where AI took over most input and output, meaning that AI was controlling the brake and accelerator for the first time.
With the launch of FSD v12.5, FSD also became a hands-free experience with vehicles with a cabin camera. The steering wheel nag was finally gone.
Tesla has also been testing FSD Unsupervised in California and Texas, albeit with safety drivers - ahead of the upcoming launch of the Robotaxi Network in Austin. While some reports from analysts like Adam Jonas have mentioned that Tesla intends to remotely supervise the fleet with teleoperators, we expect that the teleoperation will be limited to getting vehicles out of precarious situations and evaluating fleet performance.
FSD’s entire evolutionary process is fuelled by the vast amounts of data gathered from millions of Tesla vehicles on the road, enabling the AI to continuously learn and improve from an unparalleled diversity of real-world encounters. Tesla takes massive swathes of data and then automatically annotates them with key labeling parameters to prioritize for its learning suite.
Training and executing these increasingly sophisticated AI models demands immense computing power, both within the vehicles themselves and within Tesla’s growing data centers. In the car, FSD hardware has jumped from HW3 to the current AI4.
However, with V13 already pushing AI4 to its limits due to the increasingly intensive demands of larger and more complex AI models, the upcoming AI5 hardware is expected to further improve in-vehicle processing by increasing memory and compute power. That’s not to say AI4 won’t be able to achieve autonomy, but AI5 is expected to be safer in the long term due to its increased processing power.
Parallel to in-vehicle hardware is Tesla’s multi-billion dollar investments in its own supercomputing infrastructure. This includes Dojo, Tesla’s custom-built supercomputer specifically designed for machine learning and processing massive amounts of video data. Alongside the still-in-prototype phase Dojo, Tesla has already deployed Cortex 1.0 on the south side of Giga Texas, with Cortex 2.0 just recently announced for the north side. These two facilities are both large-scale GPU clusters and will be responsible for FSD development for the foreseeable future.
Everything Needed for a Robotaxi Network
For a Robotaxi service to be successful and widely adopted, the experience from opening the app to stepping out at your destination must be as seamless as possible for users and highly efficient for fleet operations. This necessitates building an entire ecosystem around the autonomous vehicle and the network.
A core component of this will be inside the Tesla App, in the Robotaxi section. We’ve previously seen some glimpses into the details, including user interaction, ride-hailing, and managing journey preferences.
Minimizing human interaction and maximizing fleet uptime is key. Robotaxis must be able to sustain themselves effectively - and wireless charging is Tesla’s go-to solution. With the addition of wireless charging to V4 Superchargers in the future, Unsupervised autonomy will be able to expand even further than the current limits - which are based around network hubs that provide two key services - charging and cleaning.
That second key service - cleaning - is another big item. Users won’t mind a less luxurious vehicle if it’s cheaper, but it needs to be clean. Tesla has already shown off its robotaxi cleaning robot, which will be deployed at those network hubs. While this may seem like an ideal job for Optimus, Tesla needs to get its network rolling today - and a single robotic arm specialized to the task could be cheaper and faster than employing a humanoid robot. Although, you can bet that Tesla is already thinking about Optimus for such a role in the future.
Beyond the user-facing aspects, Tesla will need to have a sophisticated fleet management and operational logistics hub. For Tesla, this means intelligent dispatch algorithms, utilizing real-time fleet monitoring, predictive scheduling for times of use, charging, and maintenance, as well as a degree of teleoperation or supervision for critical incidents.
The Vehicle
The physical vehicle itself is, of course, a critical element in this entire plan. The vehicle itself needs specific attributes that can enable safe and reliable autonomous operation. Tesla has remained steadfast in their vision-only approach, and have demonstrated that processing data from cameras, much like the human eyes, is the most scalable path to achieving general autonomy.
For Unsupervised autonomy, especially in a commercial robotaxi service, robust hardware redundancy is non-negotiable. While today’s Teslas already offer backup solutions for many critical systems such as braking and steering, redundant FSD computer nodes can help to make sure the vehicle can maintain control or even pull over to reach a safe area in the event of a critical incident.
While Tesla intends to begin its Robotaxi pilot with the Model Y, the upcoming Cybercab is expected to host two AI4 FSD computers, which will increase FSD’s redundancy and improve the safety margin. The Cybercab, unlike many other Robotaxi-esque vehicles, is being engineered from the ground up specifically around Tesla’s Robotaxi service. It’s optimized for low-cost manufacturing, high utilization, and durability while also being easy to maintain, charge, and clean.
Regulation and Trust
Solving autonomy extends far beyond just software or engineering innovations. It also involves navigating a complex and evolving regulatory landscape. Gaining approvals for fully autonomous commercial operations from authorities like the National Highway Traffic Safety Administration (NHTSA) at the federal level, as well as various state and local bodies, is a significant and ongoing challenge for Tesla.
Winds have changed in the United States for autonomy with new federal autonomous vehicle frameworks looking to standardize the rules and regulations for autonomous vehicles. These frameworks are just the start to actually getting laws in-place that will allow for the operation of Robotaxis outside of smaller jurisdictions.
Equally important is building public trust and acceptance. While people who use FSD swear by it, the average vehicle owner in North America will still be utterly awestruck or panic when they see a Tesla being Summoned from its parking spot to the curb.
Building trust is essential - because nobody will step into a vehicle without a driver and without any means of controlling it unless Tesla can demonstrate consistent safety. That consistent safety must be drastically better than human drivers, and Tesla must be transparent with how it reaches its safety milestones in order to encourage the adoption of autonomous ride-hailing.
Tesla’s approach to autonomy is a vertically integrated strategy that touches every aspect of the challenge - from the fundamental AI software and custom silicon that powers it to the massive processing infrastructure, the physical vehicle hardware, and the entire operational ecosystem required for a future Robotaxi service.
While there will no doubt be challenges, this June, Tesla starts its journey toward an autonomous future.
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