AI, Autonomous Vehicles, and the Next Decade of Personal Auto Insurance
Personal auto's growth story has an end date. A new note from BMO Capital Markets projects the total addressable market (TAM) for personal auto insurance will peak around $560 billion near 2040, then contract ~4% annually for the following decade as autonomy scales and loss frequency falls.
For carriers with heavy auto exposure, that doesn't just hit written premiums. Lower terminal growth assumptions can compress valuation multiples well before volume declines actually show up. The market is already hinting at that dynamic.
What the numbers say
- TAM peak: ~$560B around 2040 (personal auto).
- Post-peak trend: ~4% annual decline for ~10 years as autonomous adoption grows.
- Safety impact: current advanced driver-assistance systems (ADAS) can reduce collisions by up to ~40%; fully autonomous systems could cut accidents by 75%-90% over time.
If you want independent safety context, early ADAS features like automatic emergency braking and lane-keeping have already shown meaningful crash reductions in studies from organizations such as the IIHS and NHTSA.
Stock exposure snapshot
- Progressive: More than 90% of premiums tied to auto. Shares are down over 11% year to date. Consensus tilts Hold, with typical targets pointing to ~18% upside (per LSEG).
- Allstate: Roughly two-thirds of premiums tied to auto. Shares are off more than 2% in 2026. Most analysts rate it Buy, with ~19% implied 12-month upside (per LSEG).
- No personal auto exposure: Fidelis, Hamilton, Kinsale, RenaissanceRe.
Translation for insurers: high personal auto mix equals higher multiple risk as the market prices in slower terminal growth. Diversified writers and (re)insurers with little to no personal auto exposure should be less sensitive to the thesis.
Implications for carriers and P&L
- Loss frequency: A structural downtrend as ADAS and autonomy spread, with potential step-downs as features go standard.
- Severity mix: Fewer crashes, but cost per claim may remain high due to sensors, cameras, and software diagnostics. Repair networks and parts availability become bigger levers.
- Pricing power: Competitive pressure rises as frequency falls and capacity seeks growth elsewhere. Expense ratio discipline matters more.
- Distribution: Direct writers and partners with embedded channels can defend share while premium pools shrink.
- Liability shift: More losses migrate from driver liability to product/technology liability involving OEMs, Tier 1 suppliers, and software stacks.
Strategic moves to consider now
- Rebalance the book: Set targets to lower personal auto concentration over 3-5 years. Expand homeowners, small commercial, specialty, and excess & surplus where underwriting edge exists.
- Own the ADAS/autonomy rating curve: Build granular pricing signals tied to specific ADAS packages, sensor configurations, and over-the-air software versions. Avoid blunt discounts.
- Claims modernization: Scale AI-enabled FNOL, image estimating, guided repair routing, and parts forecasting to protect LAE and cycle times as severity stays elevated.
- OEM and repair network partnerships: Secure data-sharing agreements for sensor/telematics access, certified repair capacity, and calibrated parts pricing.
- Product innovation: Develop usage-based and feature-aware coverages for semi-autonomous operation; explore mobility-as-a-service, subscription fleets, and embedded sales with automakers.
- Underwrite the shift in liability: Build product liability and errors & omissions capabilities for autonomous software, sensors, and mapping. Consider reinsurance structures to manage tail risk.
- Capital and M&A: Redirect capital to lines with durable growth, and evaluate bolt-ons that add technical pricing, specialty distribution, or OEM data access.
- Regulatory readiness: Track state-by-state frameworks for autonomous operation and data usage; prepare filings that reflect ADAS-driven frequency trends and modern rating variables.
Operational KPIs to track
- ADAS penetration by trim and by garaging ZIP; percent of policies with verified feature data.
- Frequency/claim count by ADAS feature set and software version; false-positive/false-negative incident rates.
- Repair cycle time and parts cost inflation for sensor-heavy vehicles; total loss rates for EVs and ADAS-equipped models.
- OEM data latency and completeness; share of claims routed to certified repair facilities.
- Expense ratio trend vs. premium decline; retention and cross-sell rates as pricing normalizes.
Investment and market signaling
- Expect earlier multiple compression for carriers with outsized auto dependence as investors reset long-run growth assumptions.
- Watch for inflection points: ADAS standardization, regulatory greenlights for higher autonomy, and credible loss trend improvements in quarterly disclosures.
- For diversified names and (re)insurers without personal auto exposure, relative valuation support could persist if the thesis gains traction.
Where to build capability
If your organization is leaning into pricing, claims automation, and strategic planning around autonomy's impact, this resource hub can help: AI for Insurance.
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