Autonomous Trucks on the Horizon: State of the Industry (2025)

Imagine cruising down I-10 in the near future, and the 18-wheeler in the next lane has no one in the driver’s seat. Autonomous trucks are no longer science fiction – they’re on the horizon for U.S. highways, promising fewer accidents and round-the-clock runs. But as self-driving rigs become reality, they’re also driving a major shake-up in the auto insurance industry. Who pays if a computer-driven truck crashes? Will your insurance premiums finally drop after years of nuclear verdicts and soaring rates? These are no longer hypothetical questions. In fact, analysts predict insurance costs per mile could drop by over 50% by 2040 thanks to autonomous technology. At the same time, the entire risk model for insurers is being rewritten, shifting focus from human drivers to algorithms.

From our perspective at Dispatch Republic (a U.S.-based truck dispatch service), this isn’t just an industry curiosity – it’s a trend that will reshape day-to-day operations for truck drivers, owner-operators, and fleet managers. In this in-depth report, we’ll explore how autonomous highway trucking is forcing insurers to evolve: from how they price policies and underwrite risk to new liability laws and partnerships. We’ll also dive into market projections for autonomous trucks, examine how both big insurers and insurtech upstarts are responding, and map out scenarios (including geopolitical wildcards) that could accelerate or pump the brakes on these changes. Finally, we’ll provide actionable recommendations for insurers, investors, and policymakers to navigate this driverless trucking revolution. Let’s hit the road and see what’s coming – and what you should do about it.

Autonomous trucking technology has made rapid strides, but full driverless rigs aren’t mainstream yet. Today’s trucks on the road are at SAE Level 2 at best – meaning they have advanced driver assistance (like lane-keeping or adaptive cruise) butstill require a driver in the cab. Several companies (Waymo, TuSimple, Aurora, and major truck OEMs) are testing Level 4 autonomous semis on select highway routes in states like Texas and Arizona, often with safety drivers on board for now. Pilot programs use a “hub-to-hub” model: a human drives the rig to a highway on-ramp, the system drives autonomously on the interstate, then another human takes over for surface streets. This keeps automation in a controlled domain (mostly open highways and good weather) to ensure safety.

When will we see fully self-driving trucks at scale? Industry experts are a bit divided. Some insurance insiders are skeptical that autonomous trucking will reshape insurance in the next decade, seeing widespread adoption as “a way off still”. They compare it to the slow rollout of past tech (like how expensive HDTVs took years to become common). In contrast, optimists point to big investments and driver shortages as catalysts speeding things up. The American Trucking Association (ATA) estimates a need for 1.2 million new drivers in the next decade – a gap autonomous trucks could help fill. McKinsey forecasts the autonomous truck market (including technology and services) could reach about $600 billion by 2035, and one study suggests 13% of U.S. heavy-duty trucks could be autonomous by 2035. Major retailers are already piloting self-driving trucks in their fleets, hauling goods with reduced human input.

In short, autonomous highway trucking is coming, but gradually. The late 2020s will likely see more route-specific deployments (especially in Sun Belt states with friendly regulations), and broader adoption picking up into the 2030s. This phased rollout actually offers a silver lining: it gives insurers, regulators, and fleet operators time to adapt incrementally rather than overnight.

Shifting Risk Models in the Age of Autonomy

One of the first upheavals is in how insurers model risk for trucking. Traditional commercial auto insurance relies on decades of driver history and loss data – but with autonomous trucks, past data is scarce to nonexistent. “When we underwrite a traditional fleet, we have complete risk history… But in AVs, we do not have any history,” says Leo Grimm of Munich Re Specialty Insurance. Insurers can’t fall back on the old playbook of analyzing human driving records. Instead, they’re developing new risk models that focus on the vehicle’s technology and operating environment.

Key risk factors are shifting from driver behavior to system performance. Underwriters now scrutinize the autonomous tech stack: What sensors and software does the truck use? How reliable are they? The sophisticated Lidar, radar, and AI systems that enable autonomy also introduce new failure points – malfunctions, software bugs, even hacking risks that were irrelevant in human-driven vehicles. Insurers are effectively being forced to think like engineers: evaluating hardware redundancies, safety protocols, and cybersecurity measures as part of the risk profile.

Because there’s little claims history on self-driving trucks, insurers are getting creative to predict losses. One approach is tracking “near-misses” and incident data from testing. Every autonomous test run generates detailed data on how the system responds to cut-offs, sudden stops, weather, etc. – including moments where an accident was narrowly avoided. These near-misses can serve as proxies for understanding what could have gone wrong. “The technology allows us to take additional data from each trip…and transfer that to the risk loadings in our underwriting,” Grimm notes. In other words, big data and simulations are supplementing (or replacing) human claim records in new risk models.

Another factor is the Operational Design Domain (ODD) of the autonomous trucks. Insurers look at where and how the truck is allowed to operate – for example, one fleet might only run driverless between Dallas and Austin on I-35 under fair weather. A well-defined ODD can actually lower risk (fewer surprises), so a policy might be priced more favorably for a tightly geofenced route than for an AV roaming nationwide. Safety driver and engineer oversight are also considered: underwriters may evaluate the safety operators and the company’s training protocols as part of the risk model. In short, risk modeling is becoming a multi-disciplinary exercise, blending actuarial science with computer science. Insurers that succeed will be those who can quickly ingest telemetry data, partner with tech experts, and constantly update their models as the technology evolves.

Premium Pricing: Will Insurance Costs Rise or Fall?

Everyone in trucking wants to know: will autonomous trucks lower our insurance premiums? The answer is a mix of short-term versus long-term effects. In the long run, fewer human drivers should mean fewer crashes – after all, 94% of auto accidents are caused by human error. Eliminate distracted, drowsy, or reckless driving, and logically the frequency of crashes will plummet. Goldman Sachs projects auto insurance costs could decline over 50% in the next 15 years, dropping from about $0.50 per mile in 2025 to ~$0.23 per mile by 2040. For trucking companies, that hints at huge savings on insurance eventually. Fewer accidents also mean less volatility and maybe an end to the era of “nuclear verdicts” that have driven commercial auto rates sky-high in recent years.

Projected insurance cost per mile of autonomous vehicles, per Goldman Sachs. Analysts predict a drop from about $0.50 in 2025 to roughly $0.23 by 2040. However, most of this decline is expected in later years as autonomous adoption becomes widespread.

In the short-to-medium term, however, premiums might not fall much (and could even rise). Why? Early autonomous trucks will carry very expensive technology – sensors, AI computers, and redundant systems – that can cost more to repair or replace after an incident. A minor fender-bender that’s a few thousand dollars on a regular truck might rack up huge bills if delicate Lidar units or cameras are damaged. According to McKinsey, even electric and connected vehicles already tend to increase average repair costs, and thus insurance premiums, despite their safety features. Autonomous rigs will likely follow this pattern initially: higher repair costs and uncertainty could keep premiums elevated. Insurers also price in the unknown – with limited data on AV safety, they may charge a risk premium until proven otherwise. It’s telling that Goldman Sachs expects “modest real growth” in auto insurance premiums for at least the next 10–15 years even as autonomy ramps up. In other words, overall insurance spending may keep rising in the near term because the total number of insured miles and value of insured assets are increasing, even if per-mile costs eventually dip.

Another twist is the shift in what’s being insured. Today, premiums paid by truck owners mostly cover auto liability (for bodily injury/property damage) and physical damage to the truck. In an autonomous future, the liability may shift to manufacturers and software providers, which means the insurance dollars might move into product liability and commercial liability policies rather than personal or fleet auto policies. Goldman analysts noted that the insurance pool could start tilting “towards product liability and cyber coverage – a different risk profile than what auto insurers cover today”. So while an owner-operator’s truck insurance bill might shrink, the autonomous tech company or OEM might be paying more for product liability insurance behind the scenes. (Ultimately, those costs could be baked into the price of the autonomous system or service contract.)

Bottom line: In the long term, autonomous trucking should reduce accidents and claims, allowing insurers to lower premiums – great news for fleet owners and operators. But don’t expect overnight discounts. In the interim, the complexity and cost of the technology, plus uncertainty about liability, mean insurance pricing will be in flux. We may see new pricing models too: for example, usage-based insurance where premiums are charged per mile or even per trip data (since AVs allow granular monitoring). Insurers like Progressive – which pioneered telematics – are well positioned, as they have decades of experience pricing based on driving data. Trucking fleets might also negotiate hybrid policies initially (covering both driver and autonomous modes). Over time, as data proves out safety improvements, the industry could finally enjoy a much-needed downtrend in insurance costs.

Underwriting Practices: From Drivers to Algorithms

Hand-in-hand with pricing, insurance underwriting for trucking is undergoing a transformation. Underwriting is the art (and science) of evaluating a specific risk to decide coverage terms and whether to insure at all. Traditionally, an underwriter for a trucking fleet would look at things like the drivers’ CDL experience, past accidents and tickets (MVR reports), the safety score of the fleet, maintenance records, routes driven, etc. Human factors dominated the equation. Now, underwriters must focus on algorithms and hardware as much as – or more than – the humans.

When underwriting an autonomous trucking fleet, insurers start by asking: What is this vehicle capable of, and how is it supervised? Key considerations include:

• Technology Profile: What sensors (cameras, radar, Lidar) and software stack are on the truck? Are they industry-tested or proprietary? Underwriters might require details on the autonomous driving system’s track record – e.g. millions of test miles, known failure modes, how it handles emergencies. If one system has a clean record and another had a high-profile crash, that will factor in.
• Operational Design Domain: As mentioned, where the truck operates autonomously is crucial. Is it only on limited-access highways in good weather (lower risk), or trying end-to-end deliveries including city streets (higher risk)? Geography and route matter – a state like Texas that permits AVs on simple routes may be viewed differently than a more complex regulatory environment.
• Human Oversight & Redundancies: Insurers will ask if a safety driver is on board (during early deployments) and what their training is. They’ll also look at the company’s remote monitoring capabilities – e.g., is there a command center that can take over or assist the truck if needed? Additionally, redundant systems (backup braking, multiple sensors) reduce risk of total failure, which underwriters like to see.
• Cybersecurity and Maintenance: Since an autonomous truck is essentially an IoT device on wheels, underwriters increasingly consider cybersecurity protocols. A hacked truck could be a liability nightmare. Insurers may require evidence of encryption, regular software updates, and security audits. Maintenance of the sensors and calibration is another factor – poor maintenance could degrade the AV system’s performance, so underwriters might stipulate rigorous maintenance schedules as a condition of coverage.

The lack of historical loss data is a big challenge, but underwriters are mitigating it by demanding data sharing and testing evidence. Some insurers work directly with autonomous tech firms in pilot programs, essentially insuring a small number of test vehicles to gather data in a controlled way. This lets them learn and adjust underwriting models before large fleets roll out. Also, as noted earlier, gradual adoption gives underwriters time. “It’s going to be a very minuscule percentage of miles driven [at the beginning]… we’ll naturally be able to have an uptake of that risk as it moves into the industry,” said Chris Demetroulis of Gallagher. Early underwriters will closely study each incident (even minor ones) to refine their assumptions.

Another emerging practice is multi-line underwriting – evaluating an autonomous operation across various insurance lines. For example, an insurer might underwrite a package that includes auto liability, product liability, and cyber coverage together for an autonomous fleet. This holistic view can help ensure no gaps (and that the insurer isn’t unknowingly double-exposed). It also acknowledges that a single autonomous truck accident could trigger multiple types of claims (auto for injuries, product liability for a technology defect, etc.). We’ll likely see specialized underwriting teams or units within big insurers that focus solely on autonomous and emerging mobility risks.

In summary, underwriting is becoming much more technical and collaborative. Insurers are no longer just dealing with trucking company risk managers; they’re in conversations with engineers, data scientists, and even regulators to truly grasp the risk of autonomous operations. Those insurers that invest in understanding the technology – maybe hiring automotive engineers or partnering with AV companies – will have a competitive edge in selecting and pricing good risks in this new era.

Insurer Adaptation: New Products, Reinsurance, and Data Partnerships

As autonomy scales up, insurance companies must adapt or face irrelevance. Incumbent insurers and agile insurtech challengers are employing several tactics to stay ahead:

Product Innovation: Insurance for a Driverless World

One clear adaptation is developing new insurance products tailored to autonomous vehicles and their unique liabilities. Traditional auto insurance policies might not suffice when the “driver” is an AI. We’re already seeing insurers roll out or pilot special autonomous vehicle coverage. For instance, AXA XL has been noted as an insurer willing to cover autonomous trucks in pilot programs. These policies blend elements of auto, product liability, and even professional liability (to cover any oversight services) into one package. They may also include coverage for software failures or updates – something standard policies never had to consider.

Another innovation is usage-based and on-demand insurance. Autonomous trucks could enable more flexible insurance models: imagine coverage that’s active only when the truck is in autonomous mode, or per-mile insurance that adjusts based on real-time risk metrics. If an autonomous truck pulls off due to bad weather (thus avoiding a high-risk situation), its insurance cost might dynamically lower. Telematics and continuous data from the vehicle make this possible. Insurers like Progressive and insurtechs like Koop Technologies are leveraging such data-driven approaches. (Koop, an autonomous vehicle insurtech, has built an underwriting platform using alternative data streams to evaluate robotics and AV risk, and it’s partnering with major carriers to bring such products to market).

Embedded insurance is another trend: vehicle manufacturers or AV service providers bundling insurance with their product. Tesla’s own insurance for its cars is a prime example in personal autos; for trucking, we might see OEMs selling autonomous truck platforms that come with a built-in insurance solution for the first few years of operation. In fact, Hyundai and Kia recently invested in the insurtech Koop, with an eye toward integrating insurance into the rollout of robotics and autonomous vehicles. The idea is that by bundling insurance, OEMs can reassure customers and create a smoother adoption pathway (while possibly earning a new revenue stream). From the insurer side, partnering with OEMs early secures a slice of this new market and access to valuable performance data.

Expect to also see policy endorsements and riders for specific risks: for example, a “cyber hack coverage” rider on a commercial auto policy, or a “software update liability” clause that covers losses if a bad software update causes downtime or accidents. Parametric insurance could emerge too – e.g., automatic payouts if an autonomous fleet’s uptime falls below X% due to covered tech failures. This would help fleet operators manage the business interruption risk if their trucks are grounded by a software glitch.

Reinsurance and Risk Management for Systemic Risks

With new risks come new challenges in how insurers protect themselves. One big concern with autonomous vehicles is systemic risk – the possibility of a single flaw affecting many vehicles at once. Consider a scenario: a widely-deployed autonomous driving software has a hidden bug that triggers a crash under a rare condition. Once that bug surfaces, dozens or hundreds of trucks could theoretically crash in similar circumstances before the issue is caught and vehicles are grounded. This is very different from human-driven accidents which are mostly independent events. It introduces the risk of correlated losses – many claims all stemming from the same root cause (akin to a product recall or a catastrophe).

Insurers are responding by bolstering reinsurance arrangements and collaborating with reinsurers who specialize in high-severity, low-frequency risks. Munich Re, Swiss Re, and other global reinsurers have been actively studying autonomous vehicle risk and often partner on pilot policies. The reinsurance market might develop specific treaties for “autonomous vehicle liability” or “AV catastrophe cover” to cover those worst-case, widespread events. For example, an insurer might buy reinsurance that kicks in if more than 5 of their insured autonomous trucks have major at-fault accidents in a year – something unlikely unless there’s a systemic problem.

Capital allocation is another aspect: Insurers need to hold capital against potential losses, and if an autonomous system failure could cause, say, a $100 million event, that needs to be factored into solvency planning. Some insurers may be more conservative, limiting how much autonomous exposure they keep net (ceding more to reinsurers), at least until the risks are better quantified. On the flip side, if autonomous trucks really are safer, insurers that figure that out early might actually retain more of the business (to keep the profit) and only reinsure the truly catastrophic layer.

Also noteworthy is insurance pools or captives possibly emerging. If traditional insurers are too slow, large trucking fleets using autonomous tech might band together to form a captive insurer or risk pool, spreading the risk among themselves or taking it in-house. Alternatively, manufacturers might provide insurance warranties – essentially saying they’ll cover certain liabilities (like Volvo did in the past for some of its automated features in cars). This blurs into self-insurance territory, but it’s part of the risk landscape insurers must account for.

Data Partnerships and Ecosystem Collaboration

Data is the new gold in auto insurance, and with autonomous trucks, there’s a firehose of data available – far more than any human driver could ever provide. Each autonomous truck generates detailed logs of its every move, sensor readings, and decisions. Insurers are keen to tap into this data stream to refine underwriting and even handle claims faster (e.g., using crash sensor data to assess fault).

We’re seeing partnerships between insurers and tech companies forming to share data under proper privacy protections. Some AV developers will share safety data with insurers to demonstrate their technology’s safety record, in exchange for better premiums. Conversely, insurers may share aggregated claims data (once they have it) to help AV companies target improvements. Open data standards might emerge so that insurers can plug into an autonomous fleet’s telemetry in real-time (with fleet permission) – for example, to enable that per-mile pricing or to alert the insurer immediately if a crash occurs.

Insurers are also teaming up with governments and academia in data initiatives. For instance, to build public trust, some regulators require reporting of autonomous vehicle incidents. Insurers could use that public data to analyze trends (similar to how the FAA shares aircraft incident data which aviation insurers study). In the U.S., the National Highway Traffic Safety Administration (NHTSA) has been collecting data on AV tests; savvy insurers will be mining those datasets.

Finally, the insurance industry is investing in tech talent and platforms internally. Traditional policy admin systems are being upgraded to handle things like continuous data ingestion, dynamic risk scoring, and API integration with fleet management systems. It’s not just about underwriting either – claims processes will adjust. An autonomous truck crash might require forensic analysis of sensor logs to determine fault (was it the truck’s AI or the other vehicle?). Insurers might partner with the AV companies for that investigation, or even have agreements in place so that if an AV is clearly at fault due to a software issue, the claim shifts to the manufacturer’s insurer without lengthy court battles.

All these adaptations – product innovation, reinsurance backing, and deep data partnerships – point to an insurance industry proactively gearing up for the driverless revolution. There will certainly be winners and losers: those who adapt quickly could capture a new market and operate more efficiently; those who don’t may see their traditional auto insurance business slowly erode as autonomy grows.

Regulatory Catalysts and Liability Shifts

Technology isn’t the only factor steering the future of autonomous trucking – regulation and law will play a pivotal role. In the U.S., the regulatory picture for autonomous vehicles is still a patchwork and a bit of a Wild West. There are no comprehensive federal AV laws yet (as of 2025). Instead, we have a state-by-state mosaic: 29 states plus D.C. have enacted some form of AV legislation, while others rely on executive orders or have no specific laws. States like California and Texas have been early leaders – California with its detailed testing regulations (though it briefly considered banning driverless trucks without human operators, a move vetoed by the governor in 2023 amid industry pushback), and Texas with a more permissive stance that has attracted many pilots (Texas law treats autonomous vehicles similar to human-driven ones, requiring things like a capability to follow traffic laws and carry insurance, but not mandating a driver).

Regulatory catalysts that could accelerate autonomous trucking include:

• Federal action to clarify liability and safety standards: If Congress or federal agencies step in to set uniform rules (for example, defining at what level of autonomy the manufacturer is liable by default, or requiring certain sensor redundancies on all trucks), it could fast-track deployment by reducing legal uncertainty. These complex liability issues will likely end up being addressed by federal courts or Congress eventually. A clear framework would allow insurers to design products with known parameters.
• Insurance requirements for AVs: Regulators might update insurance laws. For instance, some states mandate a minimum insurance coverage for AV test vehicles (often higher than for regular cars, given potential risks). If states or feds require, say, that any Level 4+ truck have a certain high liability coverage or that the manufacturer carry product liability insurance, it formalizes how the risk is to be covered. The UK has already passed an Automated Vehicles Act that forces insurers to pay victims of AV crashes and then recover from the vehicle makers – a model U.S. lawmakers could look at.
• Data sharing mandates: Regulators could require companies to share AV performance data or incident reports. This would indirectly help insurers by providing more information to underwrite and price policies. It also builds public trust, which is crucial. At Dispatch Republic we think that public understanding that AVs follow rules and are properly insured is key to building trust.
• Cross-state agreements: Because trucks cross state lines, differing state rules are a headache. We might see interstate compacts or federal encouragement for reciprocity in AV regulations (similar to how states honor each other’s CDL licenses, etc.). Such alignment would make it easier for an autonomous truck insured in State A to operate in State B without new liability issues – an important point for long-haul trucking routes.

Now, on the flip side, regulatory hurdles or delays could slow things down:

• If states impose bans or overly cautious regulations (perhaps due to labor concerns or safety fears), adoption will slow in those regions. We saw hints of this in California’s attempted restriction on driverless trucks pending further study.
• A lack of federal clarity on liability means that early accidents will likely result in protracted litigation, as multiple parties (truck owner, manufacturer, software developer, etc.) fight over who’s at fault. Massive lawsuits could create a chill until precedents are set.
• Regulatory disparity is itself a risk: if one state allows autonomous trucking and a neighboring state doesn’t, how do insurers cover a route that spans both? Perhaps the truck must switch to human mode at the border – but then what policy covers incidents at that transition? These are real-world issues that insurers and companies are already grappling with in pilot programs.

The Great Liability Shift

At the heart of regulatory and insurance debates is the question of liability: when a human isn’t actively driving, who is legally responsible for an accident? Today, the answer is simple – the driver (or their employer) is liable in almost all cases of a crash, via auto liability insurance. Tomorrow, the answer might be very different. Liability is expected to shift from drivers to manufacturers and software providers as vehicles become more autonomous. In practical terms, this means if a Level 4 truck in autonomous mode causes a crash, the claim might be made against the vehicle’s manufacturer or the developer of the self-driving system for a product defect or negligence, rather than against the trucking company’s auto liability policy.

This shift has enormous implications:

• Auto insurance → Product liability insurance: The $400 billion auto insurance industry could shrink significantly, while product liability and commercial liability for manufacturers grows. Insurers will have to pivot products to cover companies like (hypothetically) “Acme Autonomous Driving Systems Inc.” rather than millions of individual drivers.
• Complex claims involving multiple parties: A single accident might involve claims against the truck’s owner (maybe they failed to maintain the system), the software supplier, the sensor manufacturer (if a Lidar failed), etc. We might see more contracts and indemnification upfront – e.g., an autonomous tech provider’s contract might state they will assume liability when the vehicle is in autonomous mode, while the fleet is liable in manual mode. Insurance policies will need to be carefully coordinated to avoid gaps or disputes. Some policies might evolve to “blanket AV liability” that then subrogates (seeks recovery) from whichever party is ultimately deemed at fault, similar to how worker’s comp pays out and then others sort it out later.
• Driver liability not gone overnight: During the transition, we’ll have mixed scenarios. If a driver is still required to take over in certain conditions (Level 3 or 4 supervised), there will be arguments about whether the driver should have intervened. Think of the recent incidents in passenger cars with advanced ADAS: drivers still got blamed if they weren’t paying attention. So owner-operators and drivers aren’t completely off the hook yet. They’ll need to carry insurance for when they are in control or supposed to be. Only at Level 5 (no human role at all) would the driver’s personal liability be truly gone. But even then, the owner of the vehicle could be strictly liable in some jurisdictions – or a new legal framework might assign strict liability to manufacturers for fully autonomous operation.
• Cyber liability: If a hacker takes control of an autonomous truck and causes harm, is that a cyber incident or an auto incident? Insurers are working that out. Many auto policies today exclude cyber events; going forward, specialized cyber insurance might be needed to cover such scenarios (or auto policies will broaden to include them). This is part of the liability shift as well – blame might go to inadequate cybersecurity by the manufacturer if hacking was enabled by a flaw.

To visualize the changing landscape, consider this simplified comparison of today’s vs. tomorrow’s insurance focus:

(Table: How insurance shifts with autonomous trucking, from driver-centric to product-centric.)

Key Market Trends, Adoption Projections, and Insurer Strategies

Stepping back, let’s consider the big picture trends and how insurers – both incumbent giants and new insurtech challengers – are strategizing in response:

• Autonomous Adoption Projections: Multiple forecasts show autonomous trucking ramping up significantly by the 2030s. As noted earlier, about 13% of heavy trucks could be autonomous by 2035 in the U.S., and roughly one-quarter of new truck sales by that time might be equipped for some level of self-driving. Globally, the market for autonomous trucks (including tech, services, etc.) could approach $180 billion by 2035 according to some market studies. Adoption will likely start with hub-to-hub highway routes in fair-weather regions, then expand geographically and into more complex driving as technology improves. The driver shortage and cost pressures in freight transport are driving interest – fleets stand to save on labor and efficiency by deploying trucks that can run 20+ hours a day (no hours-of-service limitations).

Projected adoption of autonomous trucks in the U.S. heavy-duty fleet. By 2030 only a few percent of trucks might be self-driving, growing to an estimated ~13% by 2035. (Early deployments will be limited in scope, with acceleration in the 2030s as technology and regulations mature.)

• Incumbent Insurers’ Responses: The large insurance carriers like Progressive, GEICO (Berkshire Hathaway), Travelers, and commercial specialists (Liberty Mutual, Zurich, etc.) are actively studying autonomous trends. Progressive, for example, is seen as a likely beneficiary of AVs due to its investments in telematics and segmentation – it has embraced technology for years. Many big insurers are creating innovation labs or task forces to develop autonomous vehicle insurance solutions. We’ve seen partnerships: e.g., Travelers has advertised insurance programs tailored for autonomous vehicle tech companies, and companies like Chubb and AIG have underwritten early autonomous vehicle trials in controlled environments. Incumbents are also lobbying and engaging with regulators – they want to be at the table as new rules get crafted. One strategic move is forming alliances with AV startups: by insuring an autonomous truck startup’s test fleet, an insurer not only earns premium but learns the risk and builds a relationship that could lead to insuring that startup’s customers down the line.
• Insurtech and New Entrants:Insurtech challengers see an opportunity to outpace old-school insurers in this new niche. Companies like Koop Technologies (mentioned earlier) are building insurance platforms specifically for autonomous and robotic risks. Another startup, Koffie Labs, has been using advanced models (though not AV-specific, more focused on trucking insurance modernization). Traditional auto insurtechs like Root or Metromile (now Lemonade Car) have usage-based models that could extend to autonomy. Also, interestingly, OEMs and AV tech firms themselves might become insurers (or at least agencies). Tesla’s model of offering its own insurance using real-time driving data could be mirrored by autonomous truck providers – imagine Waymo or Daimler offering integrated coverage when you buy their self-driving truck system, possibly via a captive insurance entity or partnership with an insurer. This could cut into the market share of conventional insurers unless they collaborate or offer something competitive.
• Fleet Behavior and Demand: Fleet operators are already pressing insurers for any telematics or safety tech discounts. Today, if you have advanced collision avoidance on trucks, some insurers give modest discounts. Tomorrow, a fleet adopting autonomy might negotiate policy terms like higher deductibles (since presumably accidents are fewer) or tailored coverage periods (maybe they don’t need coverage when the vehicle is not in use, etc.). Self-insurance is another strategy – large fleets might opt to self-insure more of their risk if they believe autonomy makes their operations safer and more predictable (and if insurers aren’t offering good rates). This would hurt insurers’ premium volume, so insurers are motivated to come up with attractive products to keep these customers.
• Market Shrink or Transformation: Over a very long term (two or more decades out), if autonomous vehicles reach a point of drastically lower accidents, the overall auto insurance premium pool could shrink significantly. Fewer claims mean less premium needed. Some analysts have warned of this eventual decline – it’s a key reason insurers are diversifying into other areas and focusing on growth markets like cyber insurance or renewable energy projects. However, new insurable risks (cyber, product liability, etc.) will rise concurrently. The savvy insurance companies are those who pivot their portfolios: for example, an insurer heavy in personal auto might move resources into commercial product liability for vehicle manufacturers, or into insuring the software that drives these vehicles.
• Competition and Collaboration: We might see unusual alliances – perhaps insurers partnering with reinsurtech companies or even directly with logistics firms to craft specialized coverage. Reinsurer-backed MGAs (Managing General Agents) could pop up focusing on autonomous trucking insurance, offering capacity and expert underwriting while sharing risk back to big reinsurers. On the flip side, some insurers might exit the space if they feel it’s unprofitable or too uncertain; others will double down, hoping to gain first-mover advantage and brand themselves as the autonomous vehicle insurer of choice.

In essence, the competitive landscape is being reshaped. The ones who treat autonomous tech as an opportunity (to innovate products and risk assessment) will capture new business and possibly enjoy lower loss ratios if indeed machines drive safer. Those who stick to “the way we’ve always done it” could see their books deteriorate – they’ll insure the remaining human-driven market, which over time might become higher-risk (if safer drivers/vehicles are all migrating to autonomy, the residue could be riskier, plus adverse selection issues).

Scenario Analysis: Geopolitical and External Wildcards

While the trajectory of autonomous trucking and insurance change seems set, there are geopolitical and macro-level factors that could significantly alter the timeline or outcomes. Let’s explore a few scenarios that highlight these uncertainties:

Scenario 1: Rapid Global Harmonization – “Fast Lane to Autonomy”
In this optimistic scenario, major economies (U.S., EU, China) quickly align on autonomous vehicle regulations and standards. Perhaps spurred by a global agreement or competitive race, they establish common safety certifications and legal frameworks by the early 2030s. Cross-border operations become feasible – e.g., Canada and the U.S. recognizing each other’s autonomous trucking rules, allowing driverless trucks to roll through from Toronto to Texas seamlessly. Trade flows benefit as autonomous trucks ease bottlenecks (imagine automated convoys expediting port traffic). There are minimal trade restrictions on the needed technology; semiconductor and sensor supply chains remain robust and globally integrated, keeping equipment costs trending down. Infrastructure investment also gets a boost: highways are upgraded with smart infrastructure (V2I communication units, consistent lane markings, dedicated AV lanes in some corridors). In this world, autonomous trucking adoption accelerates beyond current forecasts – maybe 20%+ of trucks by 2035. Insurers in this scenario need to adapt very quickly: the liability shift happens sooner, and those not ready see their auto insurance premiums start declining faster than expected. However, the overall economic benefit from safer roads is realized earlier too. Insurers collaborate internationally to manage risk (e.g., global data sharing on AV performance). They introduce new products in sync with new regulations (like internationally valid autonomous liability coverage). Policymakers in this scenario have coordinated safety standards and perhaps an international treaty on liability to smooth out differences. Investors enjoy clarity and put more capital into both AV tech and insurance innovations, expecting stable growth.

Implications: Insurers would need to have global strategies, possibly forming consortia to cover large autonomous fleets that operate trans-nationally. The fast adoption could mean a near-term spike in product liability claims (as kinks are ironed out), but a steep drop in conventional claims. Winners would include insurers and insurtechs that moved early into AV insurance (locking in market share), and potentially trucking companies that embraced autonomy (lower operating costs and claims). Policymakers in this scenario successfully mitigate patchwork issues, enabling the technology’s benefits with fewer delays.

Scenario 2: Fragmented Regulation and Techno-nationalism – “Slow and Bumpy Road”
In this pessimistic (but possible) scenario, the world sees rising geopolitical tensions and a lack of regulatory consensus. The U.S. continues with a state-led approach; some states like Texas, Arizona go full speed with AVs, while others like New York or maybe some EU countries impose strict constraints (perhaps due to union pressure or caution after an early accident). Internationally, regulations diverge sharply – China mandates its own standards and doesn’t accept foreign AV systems without heavy scrutiny; Europe insists on its safety protocols. Cross-border trucking with AVs becomes nearly impossible: for example, a driverless truck can operate in the U.S. but must stop at the Canadian or Mexican border for a manual handoff because laws differ. Meanwhile, trade restrictions hit the tech supply: imagine export controls on AI chips or Lidar sensors between the U.S. and China. This could lead to shortages or higher costs, slowing the rollout of autonomous fleets (especially if U.S. companies can’t source affordable hardware, or Chinese companies can’t sell their relatively cheaper tech abroad). On infrastructure, suppose government funding for smart highways stalls (maybe due to political gridlock or other priorities), leading to infrastructure delays – many roads simply aren’t prepared for optimal autonomous operations (faded lane lines, lack of 5G coverage in rural areas, etc.). Additionally, a couple of high-profile AV truck crashes occur in the late 2020s, leading to public backlash and more cautious regulatory oversight (perhaps a temporary moratorium or stricter testing rules). All this results in adoption moving at a crawl – maybe only a few percent of trucks by 2035 are autonomous, mostly confined to pockets where allowed. Human drivers remain essential for most routes.

Implications: For insurers, this scenario means slower change – they have more time to adapt, and in fact their traditional auto insurance business persists longer (which could be a relief in the short term). However, the promised safety gains and cost reductions from autonomy also take much longer to materialize. Insurers might face a protracted period of insuring mixed fleets, dealing with complexity in some states/countries vs others. The uncertainty could make pricing challenging – e.g., if only a small number of AVs are on the road, loss data remains thin, keeping premiums for those vehicles high. And if an accident causes an expensive lawsuit, insurers may become more gun-shy in underwriting AV risks at all. Insurtech challengers might struggle or pivot away due to the slower uptake (less immediate market to disrupt). Investors in autonomy could pull back if they sense headwinds, impacting the pace of innovation. Policymakers in some regions might double down on caution (perhaps influenced by labor concerns, as displaced driver jobs become a political issue). Labor unions could be stronger in this scenario, effectively slowing adoption via political channels (as hinted by Teamsters’ reactions in California). Interestingly, safety on roads overall might not improve much if human drivers remain dominant, meaning the insurance losses from human error continue to plague the industry longer than needed.

Scenario 3: Tech Leap but Geopolitical Conflict – “Autonomy Meets a Fork”
In this scenario, the technology for autonomous trucking advances rapidly (say major breakthroughs in AI and sensors by 2027 make AVs extremely reliable), but a geopolitical crisis or conflict erupts that disrupts global trade and cooperation. For example, if a conflict involving major powers occurs, we could see severe trade restrictions, sanctions, or even physical attacks that affect infrastructure. Perhaps oil price shocks or fuel supply issues hasten the need for efficient autonomous electric trucking, but at the same time, cyber warfare risk increases (AV fleets become targets for hacking by adversaries). Governments might appropriate autonomous tech for military/logistics use in conflict zones, temporarily sidelining civilian rollout. Insurance in this scenario faces extreme uncertainty – war/terrorism exclusions might come into play if cyber-attacks cause AV crashes (is it an act of war or a covered event?). If international data sharing halts due to mistrust, the learning curve for safety slows (each company and insurer is on their own). Cross-border trucking could be hampered by not just regulation but actual border shutdowns or sanctions (e.g., no AV components can be imported from certain countries). On the flip side, if automation is seen as a strategic advantage (reducing reliance on human drivers in dangerous areas), governments might pump money and mandate adoption for certain corridors (e.g., to secure supply lines).

Implications: Insurers would need to tighten policy wordings (to clarify cover in events of cyber terrorism, etc.), possibly work closely with governments on risk pools for catastrophic risks (akin to how some countries have terrorism insurance pools). Investors might flock to companies with domestic supply chains for AV tech, and insurers might favor those as well (less risk of parts shortages). The timeline for civilian autonomous trucking might bifurcate: some secure routes see lots of AVs (government-endorsed), while other areas stagnate. This scenario underscores the importance of robust risk management and contingency planning for insurers – ensuring they don’t overexpose themselves to correlated risks or geopolitical shifts.

Of course, reality could mix elements of these scenarios. The key takeaway is that external factors – from politics to infrastructure – can significantly speed up or pump the brakes on autonomous trucking’s impact on insurance. Insurers and stakeholders should engage with policymakers to advocate for balanced regulation that promotes safety and innovation, invest in resilience against disruptions (like diversifying supply sources, incorporating cyber defenses), and remain agile to pivot strategies as the world scene evolves.

Conclusion: Actionable Recommendations for Insurers, Investors, and Policymakers

The road to autonomous trucking at scale may be winding, but the direction is clear: we are headed toward a future where highway trucking has far less human involvement, and the auto insurance industry must reinvent itself to stay relevant and profitable. Here are some actionable steps for key stakeholders to navigate this transition:

For Insurers and Brokers:

• Invest in Expertise and Data: Insurers should build in-house autonomous vehicle teams that include not just underwriters, but engineers and data scientists. Understanding the nuances of LiDAR systems or AI driving behavior is crucial for accurate risk assessment. Partner with AV companies to get access to data (e.g., through pilot program collaborations). The more real-world data you have on autonomous truck performance, the better you can price and tailor products.
• Develop New Insurance Products Now: Don’t wait for full autonomy to be everywhere. Begin offering hybrid policies or endorsements that cover semi-autonomous operations, product liability for onboard tech, and cyber incidents. Experiment with usage-based insurance models for fleets with advanced driver-assist or autonomous features – this will position you for the eventual per-mile or per-trip insurance paradigm that AVs may demand.
• Reevaluate Your Risk Models: Proactively update underwriting models to factor in lower frequency but higher severity risks. Incorporate scenario analysis (what if a software glitch causes X losses?). Adjust pricing strategies anticipating that overall loss frequency may decline (so look at lower base rates) but tail risk remains (so perhaps maintain or increase catastrophic loss loads, and secure reinsurance accordingly). Also, consider how to differentiate pricing for autonomous-equipped fleets vs. traditional ones – if data shows safer outcomes, reward those fleets early to win their business.
• Secure Reinsurance & Diversify Portfolio: Given uncertainty, ensure you have strong reinsurance partners for catastrophic scenarios involving autonomous tech. At the same time, look to diversify into lines of business that complement or offset the potential shrinking of auto. For example, expanding into product liability insurance, commercial general liability for tech companies, or cyber insurance will align with the new demand as liability shifts.
• Educate and Align with Clients: Start conversations with your trucking clients (fleets, owner-operators) about autonomy. They may be wary or excited – in either case, position yourself as a knowledgeable advisor. Help them understand how adding autonomous capabilities could affect their coverage needs and premiums. By being a forward-thinking partner, you’ll retain their loyalty. Brokers, in particular, should educate themselves and be ready to advise clients on blending traditional and new coverages during the transition.

For Investors (in Insurance and Transportation):

• Identify Adaptable Insurers: Investors in insurance companies should assess which insurers are truly preparing for the autonomous shift. Look for those investing in technology, partnerships, and talent – they are more likely to maintain market share and find new revenue streams (like insuring manufacturers or offering embedded insurance deals). As Goldman Sachs highlighted, tech-embracing insurers like Progressive stand to gain whereas laggards could face decline.
• Opportunities in Insurtech and Data: The evolving risk landscape is a fertile ground for insurtech startups (think of companies like Koop). Consider investments in firms that provide data analytics, risk modeling, or insurance services specifically geared to autonomous and connected vehicles. These firms could be ripe acquisition targets for larger insurers later, providing a nice exit strategy.
• Autonomous Tech Firms & Partnerships: If investing in autonomous trucking tech companies or freight companies adopting AVs, evaluate their approach to risk management. Companies that proactively address insurance (perhaps via captive insurance or partnerships) will de-risk their operations and potentially have smoother adoption. Support businesses that collaborate with insurers – this integration can be a competitive advantage (e.g., an autonomous truck service that comes with guaranteed insurance might attract more fleet customers).
• Infrastructure and Cybersecurity Investments: Don’t overlook the picks-and-shovels. Investments in infrastructure companies (upgrading roads, telecom for V2X communications) and cybersecurity firms focused on vehicles will underpin the autonomous ecosystem. These indirectly affect insurance too (a more secure and well-equipped infrastructure means fewer losses). Insurers may even invest through venture arms in these areas (many big insurers have corporate venture funds eyeing mobility and safety tech).
• Long-term Portfolio Strategy: Consider that a successful autonomous revolution could reduce auto insurance as a profit center overall by mid-century. If you are heavily invested in traditional auto insurance carriers, you may want to diversify your portfolio over time. Conversely, consider reinsurance and specialty insurance firms which might benefit (as product liability and complex risk coverage demand grows).

For Policymakers and Regulators:

• Update Legal Frameworks Proactively: It’s better to set the rules of the road now than after problems arise. Work on laws that clearly define liability for autonomous vehicle operations (perhaps adopting a model where if a vehicle is certified autonomous, the manufacturer (or its insurer) is primarily liable when in autonomous mode). Clarify how insurance claims should be handled – this will reduce court clogging and encourage responsible deployment. Also consider requiring that autonomous vehicle companies carry adequate liability insurance or bonds (many states do this for testing, but requirements for commercial deployment should be assessed).
• Standardize Across Jurisdictions: Collaborate across state lines (and federally) to harmonize regulations as much as possible. Inconsistent rules not only hinder technology adoption but also complicate insurance coverage (imagine an insurer needing separate policy terms for each state). By aligning definitions (e.g., what constitutes “autonomous mode”), safety requirements, and data reporting standards, you’ll facilitate interstate commerce and give insurers a stable environment to develop nationwide products.
• Encourage Data Sharing and Transparency: Implement policies that require or incentivize the sharing of autonomous vehicle performance data, incident reports, and even near-miss analyses (anonymized as needed). This could be through a central database (similar to aviation incident reporting) accessible to stakeholders. More transparency will build public trust (knowing AVs are meeting certain benchmarks) and help insurers price risk more accurately (leading to fairer premiums for all). Consider protections (like a “safe harbor” for sharing data without excessive liability) so companies aren’t afraid that reporting an incident will automatically lead to lawsuits.
• Focus on Cyber and Infrastructure Resilience: Ensure that your regulatory scope covers the cybersecurity of vehicles – perhaps mandate minimum cybersecurity standards for autonomous trucks, regular security audits, and a procedure for disclosure of software vulnerabilities. For infrastructure, invest in and require basic elements that help AVs (consistent road markings, digital mapping support, maybe even dedicated autonomous truck lanes on key freight corridors once volume warrants). Public-private partnerships can accelerate these improvements. By doing so, you reduce the risk of accidents (good for public safety and insurers) and likely attract businesses to your region who want to deploy AV tech.
• Mitigate Societal Impacts: While not directly an insurance matter, it’s related – address the workforce transition for truck drivers. Thousands of drivers could be affected as autonomous tech takes hold. Consider policies for retraining drivers into new roles (like remote vehicle overseers or dispatcher roles, or other industries), and engage with industry and labor groups to manage the change humanely. This can reduce political resistance and create a smoother path for adoption, which in turn allows the insurance benefits (fewer accidents, etc.) to be realized. Perhaps any cost savings companies get from lower insurance could be partly invested in workforce development – a win-win for safety and society.

For Trucking Businesses (Fleet Owners, Owner-Operators): (It’s worth noting some recommendations for the target readers of this piece.)

• Stay Informed and Engage: Keep a pulse on autonomous tech developments and pilot programs in your segment of the industry. If you’re a fleet manager, start conversations with insurance providers and brokers about how incorporating advanced driver-assist or autonomy (even in a testing capacity) might impact your coverage. If you’re an owner-operator, understand that things like collision avoidance systems in new trucks can already fetch you insurance discounts – take advantage of these stepping stones.
• Risk Management Adjustments: Begin to treat your technology providers as part of your risk profile. If you buy an autonomous system, you’ll need to vet that company’s safety record and perhaps even their insurance backing. You might negotiate warranties or liabilities with them (e.g., will they cover damages if their system fails?). Incorporate such considerations into your contracts and operational planning.
• Pilot Autonomy in Low-Risk Areas: Consider trialing autonomy (or even driver-assist platooning tech) on specific lanes or routes where it’s legal, perhaps with a safety driver. This can give you internal data on safety and cost impacts. Share positive results with your insurer – it might help in negotiations. Also, developing some in-house expertise will make you an attractive client to insurers and a competitive carrier to shippers who value innovation.
• Budget for Transition Costs: Don’t assume insurance costs will drop immediately once you get an autonomous truck. Plan financially for a period where you might have overlapping costs – for instance, you might still need driver coverage and also new tech insurance. Over time, these should streamline, but have some cushion in your budgets. Also consider higher upfront insurance limits; some customers might require higher liability limits for autonomous operations, or states might mandate it.
• Work with Dispatch and Logistics Partners: Autonomous trucks will change logistics patterns (e.g., hub-to-hub operations and transfer hubs will emerge). Ensure your dispatching (whether in-house or using a service like Dispatch Republic) is adapting too, scheduling around new capabilities (like nearly 24/7 driving). From an insurance view, coordinated dispatch can reduce empty miles and exposures. As a dispatch company, we at Dispatch Republic are already considering these shifts – planning how to route freight efficiently when autonomous legs become available, and how to help our carrier partners capitalize on longer run-times safely. We advise carriers to start imagining dispatch and operations in a semi-automated context. It’s coming sooner than you think, and preparation is key to staying competitive and safe.

At Dispatch Republic, our mission is to empower truckers and fleets with the latest industry insights and support. The rise of autonomous trucking presents challenges – and also opportunities – for everyone in the logistics chain. Don’t get left behind. Stay informed, start adapting your risk management strategies, and lean on experts who understand both trucking and emerging tech. Whether you’re worried about insurance costs, liability questions, or how to integrate autonomous trucks into your fleet, we’re here to help. Contact Dispatch Republic for guidance on navigating these changes and to keep your operation running safely and profitably into the future. Together, let’s embrace innovation while protecting your business on the road ahead.

Ready to make the most of your trucking business? 🚚💨 Reach out to Dispatch Republic and let our experts help maximize your earnings with tailored hotshot dispatch service and flatbed dispatch service solutions. We’ll handle the logistics while you keep on truckin’. Contact us today to get started on the road to greater profits and less hassle!

For more detailed guides, check Dispatch Republic’s resources on dispatching and the trucking business. Read ELD compliance: What Dispatchers Need to Know About Electronic Logs if you’re weighing career paths, and How to Become a Truck Dispatcher to understand the dispatch side of the business.

If you’re an owner-operator juggling multiple responsibilities, consider partnering with a professional truck dispatch service to take the load off your shoulders—literally. At Dispatch Republic, we specialize in helping carriers run smarter and earn more by expertly managing load boards, negotiating top rates, and handling paperwork for dry vans, reefers, flatbeds, box trucks, step decks, and even hotshots. Our team monitors multiple premium load boards around the clock, ensuring your truck stays loaded with the right freight, at the right rate, on the right lane. Whether you’re scaling up or just getting started, having a dedicated dispatch team in your corner means fewer empty miles, less stress, and more time to focus on driving and growing your business.

Frequently Asked Questions

Ready to Take Your Trucking Career to the Next Level?

Whether you’re an owner-operator, a company driver, or a carrier company in need of truck dispatch services, Dispatch Republic is here to help. Our teamof experienced truck dispatchers offers affordable, professional truck dispatch solutions designed to save you time, increase your earnings, and make your business more efficient.

Thinking about outsourcing your truck dispatching? Contact Dispatch Republictoday and move smarter, not harder.

Found our Blog useful? Spread the word:

Check our latest posts:

[latest_posts_grid]

Contact us today to see how our team can support your trucking business.