12 May 2026
Preparing for the rise in SDVs: How insurers can assess readiness and risk
Article Summary
As SDV adoption accelerates, insurers must reassess readiness by understanding vehicle capabilities, today’s installed base and future ecosystem trajectories. In this latest read, we help insurers translate SDV intelligence into smarter underwriting, portfolio strategy and long-term risk management.
Software-defined vehicle (SDV) and autonomous vehicle (AV) technologies are no longer emerging—they are already reshaping how risk is created and managed by insurers.
Preparing for this shift requires a holistic assessment of the vehicle itself, the current SDV ecosystem and future trends, along with the ability to translate those insights into underwriting and portfolio strategy. The depth of that preparation will increasingly determine how effectively insurers can price, manage and accumulate risk in an SDV ecosystem.
SDV and AV technologies are here to stay—and growing
This shift is not theoretical. It is already underway and gaining momentum.
SDVs are reshaping how cars are designed, marketed, and updated, with measurable differences across OEMs. SDV readiness spans from Level 0 (not ready) to Level 5 (fully autonomous), and the market is already showing early leadership differentiation, with a meaningful share of OEMs progressing beyond foundational maturity.
Here is a snapshot of where the industry stands:
- As of 2025, 30.4% of OEMs were above SDV Level 2.
- 78% of the top 10 SDV scorers are EV-native players.
- Adoption of zonal architectures is expected to reach 40% of all vehicles by 2037.
Looking ahead, one out of every five cars produced in 2035 is forecast to reach SDV-readiness Level 4 or 5. (See chart below). Together, these trends point to a market that is evolving and creating new layers of differentiation in vehicle capability and, ultimately, risk.
A framework to assess insurer readiness in the SDV ecosystem
What does the rise of SDVs and autonomous vehicles mean for insurers? Most immediately, it creates urgency: the capabilities to understand and manage risk are already shifting, and insurers that assess their readiness now will be best positioned for success over the next decade.
How can insurers make this assessment? S&P Global Mobility’s risk assessment flywheel contains four core questions they must ask themselves as they ready their organizations to face this evolving market. (See infographic below). These questions range from the micro-level—understanding the vehicle itself—to the macro, including the trajectory of the future SDV ecosystem.
As they analyze each of these issues, insurers must also assess their own readiness to provide a global overview of this changing risk landscape.
1. Understand the vehicle
The first step in assessing SDV risks and opportunities is to understand how these vehicles function. Vehicle risk is no longer defined solely by physical attributes or mechanical systems. Instead, it is shaped by software maturity and the level of autonomy content embedded in a vehicle.
At Levels 0 to 2, where advanced driver assistance systems (ADAS) support the driver, risk remains with the driver. At Level 3 and above, however, the increased level of automated systems that can assume control of the vehicle shift liability from drivers to OEMs or other suppliers involved in software, hardware, and system architecture, including through over-the-air (OTA) updates.
Crucially, these risks are not fixed at the time of sale. Because SDVs can be continuously updated, risks evolve and shift over time, making liability assessment more complex.
To assess readiness, insurers should ask: are you merely classifying vehicles on the lot, or do you understand what they are capable of in real-world operation? Using tools like S&P Global Mobility’s S&P Global Mobility’s SDV-readiness can sharpen this assessment by identifying vehicles’ autonomous capabilities on a continuum, supporting a more accurate view of risk.
2. Understand the current ecosystem
Beyond individual vehicles’ capabilities, risk must also be understood at the fleet level. Insurers must understand today’s installed base, including the distribution of autonomy features, compute content and sensor systems currently in operation. Insurers should evaluate how widely ADAS and other autonomy features are deployed across the fleet and how underlying technologies vary across vehicles.
Just as important are the ecosystem dependencies behind those features. Software suppliers, hardware platforms and shared architectures across OEMs can introduce common points of exposure. Not all vehicles on the road are equal—even within the same model year—but certain technologies may already be widespread enough to influence claims and loss trends.
Tracking vehicles in operation (VIO) can help benchmark portfolio exposure against the broader fleet. Mapping software suppliers and how they interact with OEMs can also help insurers better understand potential liability and how it is distributed across the ecosystem.
To assess readiness, insurers should ask: do you have a clear view of what is actually in your portfolio today? Or are you relying on assumptions about the fleet?
3. Understand the future ecosystem
Risk exposure is shaped as much by where the market is going as by where it stands today. Insurers should use forecasts to anticipate how software-defined and autonomous capabilities will scale through adoption, software maturity and VIO growth. This is essential to project where risk exposure will appear down the road.
Forecasts allow insurers to examine the growth of Level 2+, Level 3 and Level 4 capabilities, as well as the expansion of SDV adoption and regulation. Even a partial shift toward higher automation levels can change liability patterns, increase repair severity and alter claims frequency.
These forecasts provide a preview of how SDV capabilities are expected to be adopted over time, including regional variations and the impact of different powertrains. This perspective helps insurers shape strategy years in advance by identifying where the market is headed and what potential exposures lie ahead.
To assess future readiness, ask: are you planning for today’s fleet—or the portfolio you will be insuring five to 10 years from now?
4. Turn insight into strategy
Finally, insurers need to turn their insights into actionable steps. First, insurers must translate intelligence into underwriting strategy by incorporating feature- and capability-level data into pricing and differentiating risk within the same model based on software and operating functionality. They should then apply these insights at the portfolio level, identifying concentrations of shared technology risk and monitoring exposure to specific platforms, suppliers or autonomy levels.
Vehicle-level intelligence can improve pricing accuracy, policy design and risk selection by strengthening the link between vehicle capability and cost, as higher levels of autonomy are generally associated with higher repair and replacement costs. Software-enabled features may also open up new claim pathways. S&P Global Mobility’s VINtelligence service surfaces VIN-level features, including autonomy content and MSRP, to support more precise pricing and policy decisions by providing a more robust view of individual vehicles.
Insurers should ask themselves: are your insights informing real underwriting and portfolio decisions—or are they sitting in separate analytical silos?
Building long-term readiness for SDV-driven risk
SDV and AV adoption is not a distant scenario. It is already influencing risk and liability, and it is set to grow over the next 10 years. Insurers that build a continuous understanding of vehicles, ecosystems and future trajectories will be better positioned to adapt as risk becomes more dynamic and interconnected.
The shift to SDVs requires insurers to build the capabilities now that will define competitive advantage in the years ahead.
This article was published by S&P Global Mobility and not by S&P Global Ratings, which is a separately managed division of S&P Global.