Tesla is entering 2026 not just as an electric‑vehicle manufacturer but as a company that openly wants to be judged as an AI and robotics platform. The company has committed to spending at least 20 billion dollars on AI, autonomy, robotics, and related infrastructure this year, and has also agreed to invest 2 billion dollars into xAI, Elon Musk’s separate artificial‑intelligence startup. At the same time, its first unsupervised robotaxis have begun operating in Austin with no safety driver in the car, putting Tesla into the small club of companies that run truly driverless services on public roads.

For Tesla owners and potential buyers in the US and Europe, this is more than just a headline about big numbers. It raises practical questions: Will my car become more capable in the next few years? Will a robotaxi fleet change how I commute, or whether I even need to own a car? How safe are these systems, and what risks do I carry as the human behind the wheel? This article will walk through Tesla’s AI pivot, the state of robotaxis today, what xAI means inside the car, and how regulation, economics, and risk might shape your experience over the rest of this decade.

1. Tesla’s New Self‑Image: From Electric Cars to AI and Robots

In its latest communications with investors, Tesla has shifted its story from “accelerating the world’s transition to sustainable energy” to a broader ambition of creating a “world of abundance” through AI and robotics. That change in language matters because it frames how the company justifies large capital‑spending plans and strategic choices that might not make sense if you only think of Tesla as a car brand.

1.1 A Strategic Rebranding

During and around its Q4 2025 earnings disclosure, Tesla emphasized that future value will be driven less by selling individual vehicles and more by AI‑enabled services such as Full Self‑Driving (FSD), robotaxis, humanoid robots (Optimus), and grid‑scale energy solutions. At the same time, the company reported its first‑ever annual revenue decline and the smallest profit since the pandemic, making the AI pivot appear both like an opportunity and a necessity.

In that context, Tesla’s market valuation—which already resembles high‑growth technology firms more than traditional automakers—depends heavily on investors believing that the company will successfully deliver advanced autonomy and robotics at scale. This is why management can justify more than doubling capital expenditures compared with the prior year: as a bet that AI will unlock higher‑margin, software‑like revenue streams built on top of the existing vehicle fleet.

1.2 Why This Matters to Owners

For drivers in the US and Europe, Tesla’s new self‑image has several concrete implications. First, more of the company’s engineering effort will be directed at software, data centers, and AI training infrastructure rather than new body styles or traditional mechanical innovations. Second, Tesla is likely to push subscription services (such as FSD) much harder, since these generate recurring revenue and align with the company’s AI‑as‑a‑service narrative.

Third, the company’s success or failure in AI will influence everything from the resale value of your car to the likelihood that fully driverless robotaxis appear in your city. If Tesla meets its targets, a 2026‑era Model Y in Austin might be able to earn money as part of a robotaxi fleet before the end of the decade. If deadlines slip or regulators pull back, the vehicle could remain an advanced but fundamentally conventional car with sophisticated driver assistance.

2. The State of Tesla Autonomy and Robotaxis Today

To understand where Tesla is going, it’s essential to know what is already deployed. As of early 2026, Tesla’s FSD (Full Self‑Driving) system is available under a “Supervised” label, meaning the human driver remains responsible and must keep full attention on the road. At the same time, a small but symbolically important robotaxi operation in Austin is now running rides with no safety driver in the vehicle.

2.1 FSD Subscriptions and Capabilities

Tesla disclosed that it has roughly 1.1 million active FSD subscribers worldwide, up from around 800,000 a year before, making FSD a significant recurring‑revenue stream. Many of these subscribers are in the United States, where the product is more widely available, and features are typically rolled out earlier and in a more aggressive form.​

FSD (Supervised) handles lane‑keeping, adaptive cruise control, automatic lane changes, and, in many scenarios, city‑street navigation, but it still requires drivers to remain vigilant and ready to intervene. Tesla explicitly describes FSD as a system that assists the driver rather than replacing them, which reduces regulatory exposure while the company continues to collect data and improve performance through over‑the‑air updates.​

2.2 Robotaxi Pilots in Austin and the Bay Area

The most dramatic shift in the past months has been the launch of unsupervised robotaxi rides in Austin, Texas. Tesla confirmed that some rides hailed via its app are now served by vehicles operating with no human in the car at all, ending the previous phase during which only employees or supervised pilots were allowed.

Ashok Elluswamy, Tesla’s VP of AI, has explained that these fully driverless rides are initially mixed into a larger fleet that still uses safety monitors to gradually phase out human supervision as the system proves itself. Overall, the company reports more than 500 robotaxis operating across Austin and the San Francisco Bay Area, and Elon Musk has forecast that this fleet will “probably double” every month and could be active in dozens of major cities by the end of the year.

In practice, these numbers should be interpreted as aspirations rather than guarantees, but they illustrate the company’s intent: to shift from a world in which human drivers use FSD to one in which fully autonomous vehicles can run as a service. For now, the key fact is that Tesla has joined Waymo and Zoox in the small group of companies operating truly driverless vehicles for the public, albeit in a limited geographic area.

3. The 2026 AI and Robotaxi Investment Plan

Behind the visible rollout of robotaxis and FSD upgrades lies an unusually large spending plan. Tesla says it will invest at least 20 billion dollars in 2026 on a mix of AI, robotics, energy storage, and the manufacturing infrastructure required to support them. This is a dramatic escalation that clarifies where the company expects its next phase of growth to come from.

3.1 Where the Money Is Going

According to management commentary and reporting, the 20‑billion‑plus capital‑expenditure budget for 2026 will be used to expand AI training capacity, build and scale robotaxi‑focused assembly, develop Optimus humanoid robots, and grow energy‑storage production such as Megapack. A significant portion is expected to support “Cybercab” autonomous vehicles, semi‑truck production, and new or upgraded facilities for batteries and lithium.

This spending is not only about the physical robotaxi vehicles but also about the data centers and compute clusters required to train Tesla’s neural networks on tens of billions of miles of real‑world driving data. Those systems underpin FSD, robotaxi behavior, and eventually robotics products that need to understand and interact with complex environments.

3.2 How This Differs From Traditional Auto Investment

Traditional automakers typically allocate capital to new factories, model refreshes, and powertrain changes, with software treated as a supporting function. Tesla’s 2026 plan inverts this hierarchy by making AI and robotics the central reason for increased spending, while traditional manufacturing investments are positioned as enablers for AI‑driven products like robotaxis and Optimus.

The payoff, if it materializes, is the possibility of software‑style margins: once the AI platform and robotics infrastructure are built, each additional vehicle or robot added to the network can generate incremental revenue with relatively low variable cost. That logic is crucial to understanding why investors tolerate short‑term profit declines and a first‑ever revenue drop while still valuing Tesla as a high‑growth tech company.

4. xAI: Strategic Partner or Conflict of Interest?

Tesla’s 2‑billion‑dollar investment in xAI, announced in January 2026, is the most visible symbol of its AI ambitions and has sparked debate about both strategy and governance. xAI is Elon Musk’s separate AI company, best known for its Grok large language model, and the new deal ties the two entities together more tightly than before.

4.1 What xAI Does and Why Tesla Is Investing

xAI develops advanced language and multi‑modal models intended to compete with offerings from OpenAI, Anthropic, and others. Tesla’s shareholder documents and partner communications describe the investment as a way to bring xAI’s “digital AI” capabilities into Tesla’s “physical AI” products, such as cars, robotaxis, and humanoid robots.

As part of the transaction, Tesla and xAI signed a framework agreement that sets out a structure for AI collaborations. The goal is to integrate xAI’s models into Tesla products where they can enhance decision‑making, driver assistance, in‑car assistants, and even the coordination of large robotaxi fleets. Management has argued that this approach is more efficient than building an entirely separate language‑model stack inside Tesla, since it lets the company leverage xAI’s existing platform.

4.2 Synergies Inside the Car and the Fleet

If the integration is executed well, xAI’s technology could appear in Tesla vehicles as more conversational and context‑aware in‑car assistants, smarter navigation, and better understanding of voice commands. For robotaxis, the same models might help coordinate fleet operations, interpret passenger requests, and respond more intelligently to unusual situations or ambiguous instructions.

A third layer of synergy involves Optimus, the humanoid robot that Tesla is developing for industrial and, eventually, domestic tasks. Combining xAI’s language models with Tesla’s robotics platform could accelerate real‑world deployment by allowing the robot to interpret instructions, explain its behavior, and adapt to changing conditions using natural language.

4.3 Governance and Conflict‑of‑Interest Concerns

However, the xAI investment also raises questions about corporate governance. Tesla is investing shareholder capital into a company controlled by its own CEO, and some investors worry about whether value will be allocated fairly between the two firms. A framework agreement can outline cooperation, but it cannot fully eliminate tension between maximizing Tesla’s value and building xAI as a separate business with its own investors.

Regulators or activist shareholders could, in the future, challenge whether AI‑related intellectual property should belong primarily to Tesla or to xAI when both benefit from shared data and development. For owners, this matters indirectly: any conflict that disrupts AI development, or any legal constraint on data sharing between Tesla and xAI, could slow down improvements to FSD and in‑vehicle AI services.

5. The Robotaxi Vision for US Cities

Tesla’s public vision is clear: fleets of autonomous robotaxis operating across many US cities, generating revenue for both the company and, in some scenarios, for private owners who allow their cars to join the network. Austin is the first visible manifestation of this plan, but the company’s aspirations stretch far beyond Texas.

5.1 Austin as a Testbed

Austin has emerged as Tesla’s initial launchpad for unsupervised robotaxis because it combines several favorable factors: it is in Texas, the company’s de facto home base, has relatively permissive regulatory attitudes toward new mobility services, and is already familiar with Tesla through its large local factory. The city also has a growing population and tech sector, which helps generate early‑adopter demand and local support.

Tesla’s rollout strategy in Austin appears incremental. The company first tested with employee riders and supervised vehicles, then began mixing unsupervised robotaxis into that fleet, and now offers fully driverless rides to the public through its app on a limited basis. This staged approach allows Tesla to gather data on real‑world edge cases, rider behavior, and system failures while keeping the number of fully autonomous vehicles small enough to manage.

5.2 Comparing Tesla’s Approach with Waymo and Zoox

Unlike Waymo and Zoox, which rely heavily on LiDAR sensors and dense pre‑mapped geofences, Tesla is committed to a “vision‑only” strategy that uses cameras and neural networks to learn how to drive. Proponents argue that this method will scale better because it more closely mirrors human perception and does not require detailed mapping of every street in advance.

Critics counter that the lack of LiDAR and HD mapping can make edge cases harder to handle and may increase the risk of rare but serious failures. They also point out that Waymo’s service area, while limited, has grown steadily with relatively few high‑profile incidents, whereas Tesla has faced scrutiny over the safety of its assisted‑driving features in the past. For now, Tesla’s Austin robotaxis are an experiment that may validate its camera‑only philosophy—but they could also expose limitations if incidents occur or regulators grow cautious.

5.3 Expansion Scenarios Across the United States

Elon Musk has predicted that robotaxis will be active in dozens of major cities by the end of the year, although his autonomy timelines have historically been optimistic. In reality, expansion will likely follow a pattern driven by local regulation, street complexity, climate conditions, and public acceptance.​

States such as Texas, Arizona, and parts of Florida may be among the first to see broader deployment because they have already welcomed other autonomous‑vehicle operators and maintain flexible regulatory frameworks. By contrast, California—despite being an early testing ground—has recently shown more skepticism as incidents involving autonomous vehicles have drawn public and political attention. In each city, Tesla will need to negotiate not only regulatory approval but also local concerns about congestion, labor displacement, and safety.

6. The European Angle: Regulation First, Deployment Later

While Tesla is pushing ahead quickly in the United States, Europe presents a more cautious and fragmented environment for autonomy. The European Union has historically taken a more precautionary approach to new technologies that affect safety and privacy, and national regulators vary widely in their willingness to authorize advanced driver‑assistance systems.

6.1 Slower Approval of FSD and Robotaxis

Despite repeated public predictions that Tesla’s FSD would be approved in Europe by certain dates, those timelines have slipped, and regulators remain wary. Concerns include not only the safety of the technology but also questions about driver responsibility, liability in accidents, and the transparency of AI decision‑making.​

As a result, European Tesla owners typically receive more constrained versions of driver‑assistance features compared with their US counterparts, particularly when it comes to city‑street navigation and aggressive lane‑change behavior. The idea of fully unsupervised robotaxi services similar to those in Austin is, for now, a long‑range goal in most EU countries rather than an imminent reality.

6.2 Data Protection and AI Transparency

Europe’s strong privacy framework, including the General Data Protection Regulation (GDPR), requires companies to manage driver and passenger data with greater care. For Tesla, this has two implications: first, it must ensure that data used for AI training complies with local rules, and second, it may need to maintain regional data centers or implement technical measures to limit cross‑border transfers.​

EU institutions are also developing AI‑specific regulations that may impose requirements for explainability, safety certification, and risk classification. Autonomous‑driving systems used in public spaces are likely to fall into high‑risk categories, demanding extensive documentation, testing, and possibly even real‑time monitoring mechanisms. These constraints can slow deployment but may also increase public trust once systems are approved.

6.3 Country‑by‑Country Differences

Within Europe, there are meaningful differences among countries. Germany, for example, has shown interest in structured frameworks for Level 3 systems on highways but remains cautious about full autonomy in urban areas. Nordic countries, with relatively tech‑friendly populations and well‑maintained roads, might appear attractive for early robotaxi trials, but local regulators still require strong evidence of safety and reliability.

For European Tesla owners, this means that the robotaxi dream will arrive unevenly—and likely later than in the United States. FSD and other driver‑assistance features will continue to improve, but the jump from supervised assistance to unsupervised robotaxis will depend on legal and political decisions as much as on technical progress.

7. Economic Impact for Owners: Will Your Tesla Become a Robotaxi?

One of Tesla’s most ambitious promises is that your personal vehicle could, at least in principle, operate as a robotaxi when you are not using it, generating income that offsets ownership costs. To evaluate that claim, it helps to break down both the potential and the practical barriers.

7.1 The Promise: Your Car as an Income‑Generating Asset

In Tesla’s vision, a suitable vehicle equipped with FSD and robotaxi‑ready hardware could be added to a shared fleet when the owner chooses, perhaps through settings in the Tesla app. The car would drive itself to pick up passengers, complete trips, and return home, with revenue split between Tesla and the owner. In high‑demand urban areas, a well‑utilized car could theoretically generate enough income to cover monthly payments or even turn a profit.

For owners in cities like Austin, where unsupervised robotaxis are already operating, this scenario feels less abstract than in the past. If the pilot scales, Tesla will gain real‑world data on utilization rates, maintenance costs, and customer demand that can inform future economics and revenue‑sharing models.

7.2 Wear and Tear, Insurance, and Platform Fees

However, turning a personal car into a revenue‑generating robotaxi also introduces challenges. Increased usage means more frequent maintenance, higher tire and brake wear, and faster depreciation. Insurance frameworks for autonomous vehicles are still evolving, and insurers may charge premiums for vehicles used in commercial service—even if the driving is done by AI.

Additionally, Tesla will almost certainly charge platform fees or take a significant share of trip revenue. Once those fees, taxes, and maintenance costs are accounted for, the owner’s net income could end up much lower than initial topline figures suggest. Depending on local market conditions, running your Tesla as a robotaxi might make economic sense only in high‑demand, high‑fare urban cores.

7.3 US vs. European Use Cases

In the United States, cities like Austin, Phoenix, and parts of Florida may offer early opportunities for owners to join robotaxi networks, assuming regulators and Tesla permit mixed private‑plus‑commercial usage. In Europe, where robotaxis are likely to face more legal and public‑acceptance hurdles, the business case for owners may remain speculative for longer, focused more on improved driver‑assistance than on direct income.

Prospective owners should therefore view the robotaxi narrative as a potential upside rather than a guaranteed feature. Buying a Tesla solely for its hypothetical ability to earn money as an autonomous taxi would be a high‑risk bet until there is clear evidence of sustainable economics and stable regulation in its specific city.

8. Data, Privacy, and Ethical Questions

As Tesla expands its AI and robotaxi programs, the amount of data collected from vehicles and passengers will grow, raising important questions about privacy, ethics, and public oversight.

8.1 Fleet Data as the Fuel for AI

Tesla’s approach to autonomy relies heavily on large‑scale data collection from its global fleet. Each vehicle can, when enabled, upload clips of difficult scenarios, near misses, and novel environments to Tesla’s servers, where they are used to train improved versions of the neural networks that run FSD and robotaxi behavior. This data advantage is central to Tesla’s belief that its vision‑based system will eventually outperform LiDAR‑dependent rivals.​

However, this model also means that Tesla must store and process vast amounts of information that may include identifiable details about locations, other vehicles, and pedestrians. While the company applies filtering and anonymization techniques, regulators and privacy advocates in both the US and EU will continue to scrutinize how this data is handled.

8.2 Privacy and Surveillance Concerns

In the United States, there is a growing public discussion about whether always‑connected vehicles, including Teslas, could be used as surveillance devices, intentionally or otherwise. In Europe, GDPR and upcoming AI regulations give authorities stronger tools to limit or oversee data collection. Questions include how long data is stored, who can access it, and whether users can meaningfully opt out of certain types of data usage without losing essential functionality.​

Owners should be aware that enabling FSD and participating in robotaxi programs can increase the amount of data their vehicles share. Reading Tesla’s privacy notices and understanding regional rights—such as access requests or deletion options—is a prudent step, especially for those concerned about sensitive locations or personal routines being inferred from driving patterns.

8.3 Ethical and Social Implications

Beyond privacy, Tesla’s robotaxi ambitions raise broader ethical issues. Autonomous fleets could displace human drivers who rely on ride‑hailing or taxi work, potentially triggering social and political pushback. At the same time, robotaxis might improve mobility for people who cannot drive, including elderly or disabled passengers, provided vehicles and services are designed with accessibility in mind.

Urban planners also worry about congestion: cheap, convenient robotaxis could encourage more vehicle trips, undermining public‑transport usage and climate goals. How Tesla positions its services—complementary to transit versus outright competitors—will shape these outcomes.

9. Risks, Delays, and the History of Slipping Deadlines

No discussion of Tesla’s AI and robotaxi strategy is complete without acknowledging the company’s track record of optimistic timelines. Elon Musk has repeatedly predicted near‑term breakthroughs in full autonomy that did not materialize on schedule, and some regulators have openly referenced these missed deadlines when explaining their caution.​

9.1 Technical Uncertainties

Driving in complex urban environments remains one of the hardest problems in AI. Edge cases such as unusual construction zones, emergency vehicles behaving unpredictably, or vulnerable road users in chaotic settings can still trigger system failures. Tesla’s vision‑only approach intensifies the need for robust perception and prediction because there is no LiDAR safety net.

Even with 1.1 million FSD subscribers feeding data into its models, Tesla cannot perfectly anticipate every scenario. Each new city will introduce unique traffic norms, infrastructure quirks, and behavioral patterns that may challenge the system. For owners, this means that FSD performance can vary substantially across regions and that reliability should be evaluated not just from internet videos but from local experience.​

9.2 Regulatory Risk and Public Backlash

Any serious accident involving a Tesla robotaxi could trigger a strong regulatory response, as occurred with other autonomous‑vehicle operators in the past. Cities or states that are currently open to experimentation might impose moratoriums or stricter oversight if public trust erodes.

In Europe, such incidents could deepen already‑existing skepticism, further delaying FSD approvals or restricting how and where advanced features are allowed. In the United States, litigation and political pressure could complicate deployment, especially if incidents become lightning rods in broader debates about AI safety. For owners, this means that the capabilities of their cars can change not only because of software updates but also because of external policy decisions.

9.3 Financial and Strategic Risks

Large AI investments are inherently risky. If Tesla’s robotaxi rollout stalls or fails to gain regulatory approval in key markets, the company will still carry the cost of its data centers, specialized factories, and robotics programs. Investors may then reassess valuations that are based on strong assumptions about future robotaxi and AI revenues.

In such a scenario, Tesla might need to refocus on its core EV business, cut spending, or seek partnerships—moves that could slow innovation but stabilize finances. Owners would likely still receive incremental software improvements, but the most ambitious visions, such as widespread robotaxis or in‑home Optimus assistants, could be pushed out by years.

10. How US and European Owners Should Position Themselves

Given the mix of promise and uncertainty, Tesla owners and prospective buyers in the US and Europe need a pragmatic framework for making decisions about FSD, robotaxis, and vehicle purchases.

10.1 Evaluating FSD in 2026

For most drivers, the key question is whether FSD delivers enough value today to justify its cost, either as a subscription or as an upfront purchase where that option still exists. The answer depends heavily on individual driving patterns. Long‑distance highway commuters in regions where FSD works reliably may find that it significantly reduces fatigue and makes daily driving more comfortable. Urban drivers in complex European city centers may see less benefit, especially if local regulations limit functionality.​

A cautious approach is to try FSD on a month‑to‑month basis, if available, during periods when you expect to drive more. This allows you to assess real‑world performance without committing large sums upfront. If in doubt, owners can wait for further upgrades and regulatory clarity before making a long‑term decision.

10.2 Considering Robotaxi Potential as a Bonus, Not a Core Justification

While the idea of turning your Tesla into a robotaxi is exciting, it should not be the primary reason for most people to buy or keep the car. Technical, regulatory, and economic uncertainties are still too large, especially in Europe, to treat robotaxi income as a reliable element of personal financial planning.

Instead, treat the robotaxi narrative as a speculative upside: if it materializes in your city, it could provide additional flexibility or income; if it does not, your ownership experience should still stand on the vehicle’s current benefits—performance, running costs, charging infrastructure, and software updates.

10.3 Comparing Tesla with Alternatives

In both the US and Europe, other automakers are upgrading their driver‑assistance systems, though none offer the same combination of broad FSD rollout and over‑the‑air feature velocity as Tesla. When comparing options, consider:

• How well the advanced driver‑assistance system (ADAS) works on roads you actually use.

• Availability and reliability of fast‑charging networks compatible with the vehicle.

• Software update cadence and how often new features or bug fixes are delivered.

For some buyers—particularly those who value predictability and traditional service networks—a mainstream brand with more conservative ADAS may still be preferable. For others who are comfortable living at the edge of new technology, Tesla’s FSD and robotaxi roadmap may outweigh the risks.

11. Conclusion: High‑Risk, High‑Reward Transformation

Tesla’s journey from EV maker to AI and robotics company is well underway, backed by a 20‑billion‑dollar investment plan, a 2‑billion‑dollar stake in xAI, and live robotaxis on the streets of Austin. For US and European drivers, this transformation offers both tangible benefits—steadily improving driver‑assistance features, the possibility of new mobility services—and meaningful risks, including regulatory uncertainty, privacy concerns, and the chance that ambitious timelines slip again.

The most resilient mindset is neither blind faith nor outright dismissal. Instead, treat Tesla’s AI and robotaxi initiatives as an evolving platform: valuable today for what they already do, and potentially revolutionary if the company can deliver on its promises at scale. Stay informed about regional regulations, test features yourself when possible, and make purchase and subscription decisions based on current reality rather than distant projections.

FAQ

1. When is Tesla likely to offer true driverless robotaxis in my US city?
Timelines vary widely by location. Tesla currently operates fully driverless rides only in Austin and has a robotaxi fleet spread between Austin and the San Francisco Bay Area. Musk has suggested that robotaxis could reach dozens of major cities by the end of the year, but past autonomy deadlines have often slipped, so it is reasonable to expect a gradual rollout over several years rather than a sudden nationwide deployment.

2. Why is Europe so much slower to approve FSD and robotaxis?
European regulators apply a precautionary approach to AI and safety‑critical technologies, with strict rules around testing, liability, and data protection. They have also cited concerns about missing earlier timelines and want strong evidence that systems perform safely under local conditions before approving widespread use. This leads to more cautious and slower deployments compared with some US states.

3. Will my older Tesla ever be compatible with full robotaxi capability?
Compatibility depends on hardware as well as software. Tesla has updated its in‑car computers and sensor suites over successive generations, and older vehicles may lack the redundancy or processing power needed for unsupervised robotaxi service even if FSD (Supervised) features continue to improve. Owners considering robotaxi participation should check hardware requirements and be prepared for the possibility that some older models will never receive full autonomous capability.​

4. Is FSD worth the subscription cost in 2026?
FSD can be worthwhile for drivers who regularly cover long distances in areas where the system performs well and who value reduced workload and early access to new features. For others—especially those in dense European cities or regions with limited feature support—the benefits may not justify ongoing subscription fees. A month‑to‑month trial during a high‑mileage period can help you decide based on your own usage.​

5. How should I think about xAI as a Tesla owner and/or investor?
xAI is intended to provide advanced language and reasoning capabilities that enhance Tesla’s physical AI products, including cars, robotaxis, and robots. As an owner, you may see the results in smarter in‑car assistants and more capable autonomy over time. As an investor, the 2‑billion‑dollar stake introduces both potential synergies and governance questions, since Tesla is channeling capital into a separate company controlled by its CEO, which could raise concerns about how value and intellectual property are shared.