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other industries, the economy overall, and, as a result, the commercial real estate space demand — self-driving cars being the chief example. The Road Ahead fact remains that people still won’t be able to engage in non- work activities during the commute, such as spending time with family and friends or engaging in outdoor activities. Will workers really want to spend more time away from home to be working in the car? The market potential for self-driving car technology is enor- mous. There are 260 million cars, motorcycles, and buses Property Sector Impacts in the U.S. In 2016, $2.25 trillion was spent on car owner- For office space, it’s theorized that much less parking space ship, public transportation, rental cars, taxis, limousines, will be required as cars will zip around shuttling people and black cars. When considering the adoption timeline elsewhere instead of sitting idle while employees work. for the technology, it is important to understand that most Optimists point out that this will free up previously under- predictions from industry experts and global automakers are utilized land and space, while pessimists claim the potential light on acknowledging the significant potential for dispar- loss of NOI for office landlords as income from parking ity between assumptions and eventual reality. Despite the could be significant. potential of self-driving technology, challenges exist such as For multifamily, pessimists posit that self-driving cars legislation hurdles, cybersecurity risks, and pushback from will induce urban sprawl, negatively impacting the rela- incumbents like insurance providers. tive value of urban properties and punishing investors Many assume autonomous self-driving cars will improve who over-allocated investments to urban cores. Opti- efficiencies related to commutes. It’s also argued that self-driv- mists argue that reduced parking requirements could ing cars will increase worker productivity during commutes, boost the potential for housing density and commercial because passengers could catch up on emails and perform other property. This will create more vibrant environments, and tasks. Because of these efficiency and productivity gains, it is future development will be less costly thanks to reduced assumed that people may relocate farther away from a city parking requirements. center and into the suburbs, increasing commute times while For retail and industrial properties, shuttered suburban retail productivity remains steady. assets will be reborn, either as retail or last-mile distribution These posited efficiency gains may be quickly mitigated for the same New Vehicle Market Share of Fully Autonomous Vehicles reason lane widening on freeways High-Disruption Scenario Entails doesn’t lead to improved traffic times. • Regulatory Challenges Overcome in Key Markets In economics, the concept of induced • Safe and Reliable Technical Solutions Fully Developed demand, also known as Jevons para- 100 % High-disruption scenario for • Consumers Enthusiastic and Willing to Pay conditional or better autonomy (L3+)* dox, occurs when technological High-disruption scenario for 90 progress increases the efficiency with full autonomy (L4)* which something is used (reducing the 80 amount necessary for any one task), but the rate of consumption rises Ramp-up as AV availability 70 spreads across popular because of increasing demand. consumer models This dynamic is omnipresent in 60 transportation and has even been Slow consumer uptake Commercial introduction referred to as the Iron Law of Con- driven by low perceived of full autonomy by new 50 value proposisiton or tech players and premium OEMs gestion. Thus, while Marchetti’s con- negative publicity following critical incidents 40 stant would tell us self-driving cars will cause sprawl, Jevons paradox tells Low-disruption scenario for Technical and Manufacturing 30 conditional or better autonomy (L3+)* us this sprawl will be mitigated due to regulatory barriers capacity for tech Mass market delay commercial players ramps leaders more people commuting on roadways. scale introduction up gradually introduce full 20 of autonomous autonomy Whether commuters are willing to vehicles locate further from their work envi- 10 Low-disruption scenario for ronment, the key question is: While full autonomy (L4)* 15% productivity could increase, do work- 0 ers really want to spend more time 2020 2025 2030 2035 2040 away from home? Said another way, *Based on the National Highway Traffic Safety Administration's levels of automation while productivity could increase, the Source: McKinsey CIREMAGAZINE.COM September | October 2019 35