Plunging Costs for Autonomous Vehicles

Many say autonomous cars are years away, but costs are tumbling, and, as Sun Tsu said, all battles are won or lost before they are ever fought.

Personal auto liability is U.S. property/casualty insurers’ largest line of business, and personal auto insurers face a long and daunting list of challenges. But many of those challenges will merely alter competitive dynamics within auto insurance markets, enabling the best insurers to gain market share at the expense of weaker competitors (e.g., those insurers that master telematics and the associated big data issues can look forward to stealing share from those that don't.) Unlike the majority of other challenges, the advent of autonomous vehicles threatens all personal auto insurers, because liability will shift from vehicle owners to auto manufacturers or those who provide the systems and software that enable autonomous driving. Simply put, the market for personal auto liability insurance is likely to shrink dramatically at some point, with a number of auto manufacturers already committing to accept liability when their autonomous vehicles are at fault in accidents. None of this would be of any consequence if the cost of autonomous vehicles placed them out of reach of the typical consumer. But technology costs for autonomous vehicles are plunging. According to a recent article in the Washington Post, the cost of LIDAR (the "eyes" for autonomous vehicles) is poised to drop from $75,000 to a mere $500 or less. (See here) Yes, it will be years before autonomous vehicles constitute the lion's share of the vehicles on the road, and today's personal auto liability insurers have some good years ahead of them. But change is coming, and, as Sun Tsu said, all battles are won or lost before they are ever fought. Is it really too soon for personal auto liability insurers to begin positioning for the world just now coming in to focus on long-range scanners?  

Michael Murray

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Michael Murray

Michael Murray is a University of Chicago-trained economist passionate about providing decision-quality information and insight that helps others profit from deep understanding of both the big picture and subtle nuances.


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