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Insuring the In-Between: Auto Insurance in the Age of Self-Driving Cars

By Bob Phillips

Updated February 10, 2026

Reviewed By Beth Swanson

Edited By Susan Meyer

Jump to

Shift from driver risk to system risk
The complexities of insurance and automation
How insurance is adapting
How data is reshaping insurance
What does this mean for you as a consumer?

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New Technology Requires New Approaches

The future is here, and self-driving cars are on the road in some cities. Waymo is currently operating a fleet of fully autonomous vehicles in Phoenix, San Francisco, Los Angeles, Austin, Atlanta, and Miami, with greater expansion to come in 2026.^[1]

Meanwhile, automakers are making progress toward passenger vehicles with Level4 (L4) autonomous driving capabilities being available. L4 systems are designed to respond to their surroundings without the need for human drivers.^[2]

And yet, while the technology is advancing, there are plenty of legal and insurance complexities to work out. While some states have laws around self-driving cars, there are no federal laws yet.^[3]

Self-driving cars sit in an awkward transitional moment for the insurance industry. The technology is moving quickly, but insurance frameworks were built on the assumption that a human driver controls the vehicle. As automation increases, that assumption becomes less reliable and harder to insure with confidence.

The Shift From Driver Risk to System Risk

One of the first hurdles insurers face is defining what “self-driving” actually means. Most vehicles on the road today rely on advanced driver-assistance systems rather than full autonomy. These systems can steer, brake and accelerate, but they still require human supervision. From an insurance standpoint, that keeps the human driver firmly in the liability chain.

Fully autonomous vehicles challenge that structure in a more fundamental way. When no human is expected to monitor or intervene, responsibility begins to shift away from individual behavior. The focus moves toward system performance, software reliability and operational oversight. Insurance must adapt to a world where the “driver” may be code.

This shift changes how auto insurance thinks about risk. Traditional personal auto underwriting centers on who you are, where you drive and your prior driving history. Autonomous technology reduces the relevance of those factors and elevates technical reliability and system design. Risk becomes less personal and more institutional.

Partially automated vehicles create a shared-control problem. The system may handle routine driving, but the human is still expected to step in during unexpected situations. When a crash occurs, insurers must decide whether the driver failed to intervene or the system failed to respond appropriately. That gray area complicates liability decisions.

Why Claims and Liability Get Messy With Automation

Claims handling looks very different when automation is involved. Here are some of the key differences:

1. Evidence and documentation changes.

Adjusters must evaluate digital evidence such as event data recorders, sensor inputs and system engagement logs. Traditional statements and police reports are no longer sufficient on their own. The claim becomes as much a technical review as a factual one.

2. Claims resolution may slow down.

These additional layers tend to slow down claims resolution. Multiple parties may be involved, including vehicle owners, manufacturers, software vendors and fleet operators. Each has a financial incentive to frame the data in a way that limits exposure. That can prolong disputes and increase loss adjustment costs.

3. Subrogation matters.

Subrogation plays a larger role in self-driving claims. An insurer may pay a claim under a personal or commercial auto policy and then seek recovery from a manufacturer or operator. These disputes increasingly resemble product liability cases rather than routine auto recoveries. Legal complexity becomes part of the loss cost.

How Insurers Are Adapting—and Why It’s Still Complicated

The commercial autonomous vehicle model highlights these issues even more clearly. Robotaxi and delivery fleets typically carry high liability limits to account for worst-case scenarios. Even with lower crash frequency, the severity of a single incident can be significant. Insurance pricing must reflect that imbalance.

1. Underwriting is looking beyond just the individual vehicle risk.

Underwriting these fleets requires a broader assessment of risk. Insurers evaluate not just the vehicle, but the entire operational framework supporting it. Maintenance schedules, software update controls, remote assistance protocols and safety monitoring all factor into pricing decisions. The vehicle itself becomes only one piece of the exposure.

2. New pricing models.

Some insurers are experimenting with pricing models that separate human-driven miles from automated miles. This treats automation usage as a dynamic underwriting variable rather than a static feature. It reflects the belief that risk changes depending on who—or what—is in control. This approach marks a meaningful departure from traditional rating practices.

How Software and Data Are Reshaping Auto Insurance

These data-driven models raise new questions about transparency and fairness. Insurers must decide how much data to collect and how it can be used. Consumers may not fully understand how their driving data affects pricing. Regulators are watching closely as these practices evolve.

Cyber risk adds another layer of complexity. Software updates can change vehicle behavior overnight, altering risk profiles without any physical modification to the car. Outages, data corruption, or system failures can create loss scenarios that traditional auto policies were never designed to address. Insurance programs increasingly need to account for these possibilities.

For autonomous fleets, this often means combining multiple lines of coverage. Auto liability, cyber insurance, technology errors and omissions and product liability may all be part of the risk stack. The boundaries between these coverages can blur during a claim. Coordinating them becomes an underwriting and claims challenge.

Regulation remains fragmented and uneven. Different states apply different rules regarding testing, deployment, and financial responsibility. This inconsistency makes it difficult to standardize insurance products nationwide. Insurers must tailor coverage to local requirements while anticipating future changes.

The long-term promise of self-driving technology is reduced accidents and improved safety. If that promise is realized, insurance pricing will eventually reflect lower loss frequency. In the near term, however, uncertainty, legal complexity and high severity potential keep premiums elevated. Insurance tends to lag innovation, not lead it.

Lemonade Unveils Self-Driving Insurance Product

In January of 2026, Lemonade Insurance premiered a new Autonomous Car Insurance product for Tesla FSD (full self driving). The offering promises to cut rates for FSD-engaged driving by 50% due to the data showing decreased risk. Data captured from the Tesla fleet feeds into the insurer's usage-based risk prediction models and can detect the difference between autonomous and human driving.^[4]

What Does This Mean for You as a Consumer?

Having or in other cases, traveling via a self-driving car means that:

You'll obtain a spotless driving record

According to McKinsey, self-driving cars could reduce the number of road accidents by 90%! This means that self-driving cars can potentially make your driving record look spotless. With a diminished possibility of human error, many of the accidents that happen on the roads every day could be prevented.
You'll be able to relax and unwind

Self-driving cars will one day help make it possible for you to get where you need to go without worrying about driving yourself. This would free up a lot of time and allow you to relax or do other things while on the road.
You'll be spending more to maintain your car

The more sophisticated technology is, the more you will be paying for the damage due to the expensiveness of each car component. In this way, self-driving cars will cost more to fix or repair in the event of an accident when compared to conventional vehicles.
You'll be paying less on car premiums

90% of accidents are attributed to driver error in the United States. Without the possibility of human error, autonomous technology has the potential to make our roads much safer. This could significantly impact car insurance rates and premiums, with drivers of autonomous vehicles potentially paying less than those who choose to stick with human-controlled vehicles.

As long as the technology within the auto industry keeps improving and getting optimized with continuous testing, it won't matter much whether you embrace the self-driving possibilities now or not. Regardless, know that they might be here to stay for good. Of course, self-driven cars will change how we drive, but it's too soon to determine the extent of the changes.

Wrapping Up

Self-driving car insurance is ultimately less about eliminating risk and more about relocating it. Responsibility is moving away from individual drivers and toward systems, operators and the organizations that design and maintain them. Until the legal, regulatory, and technical questions are settled, insurers will continue pricing not just accidents, but uncertainty itself.

Sources

Waymo Opens Up Airport Service in San Francisco. Everything to Know About the Robotaxi. [CNET]
CES 2026: Autonomous Driving Hits an Inflection Point. [Global X]
The Current State of Self-Driving Car Regulations in the U.S. [Urban Desk]
Lemonade Unveils Autonomous Car Insurance, Slashing Rates for Tesla FSD Miles by 50%. [Lemonade]

Jump to

Shift from driver risk to system risk
The complexities of insurance and automation
How insurance is adapting
How data is reshaping insurance
What does this mean for you as a consumer?

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