Artificial intelligence (AI) is transforming the automobile. In so doing, it will transform much more than that. Given how central automotive transportation is to our cities, commerce, and daily lives, saying that AI will change life as we know it is no understatement.
To understand where this new mobility might take us, it’s important to distinguish between two types of AI-powered motor vehicles: self-driving and driverless. Self-driving vehicles offer the options of automated and manual driving. Either way, there’s someone in the driver’s seat. Driverless vehicles, on the other hand, have neither driver nor (eventually) a steering wheel. This distinction is important because the driver is typically the most expensive part of a transport business, be it taxi services, last-mile logistics, or long-haul trucking. Self-driving capabilities can boost safety and driver productivity. By eliminating the driver altogether, businesses could slash costs by as much as 60%, depending on the industry.
In combination with the sharing economy, driverless vehicles are likely to be deployed in fleets, benefiting higher utilization in urban settings. This portends a dual-track future. While sharing and driverless will converge for the 1.7 billion population living in sizable cities, the remainder of the population will also benefit, but largely from the safety advantages of self-driving cars that they will own.
Where and When the Technology Might Be Deployed
Automakers are already producing self-driving autonomy features for specific uses, such as highway driving, in premium vehicles. As expected, uptake has been slow because extra costs are limiting demand, but the rollout is growing.
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How it will impact business, industry, and society.
By contrast, driverless vehicle adoption depends on overcoming three factors: infrastructure maturity, technology readiness, and regulation. Of the large markets, the U.S., thanks to a mature infrastructure and, thus far, supportive regulatory environment, is at the forefront, and driverless technology is undergoing real-world, large-scale testing to train machine learning algorithms. We expect Europe (excluding the UK) to lag the U.S., given the higher technical complexity of medieval cities and regulations resulting in limited on-the-ground testing. China and India are still in process of building out their infrastructure; their technology will need more effort to adapt to their complex street environments.
What Leaders Need to Consider
It’s time for boards and executives to ask themselves hard questions about how the new mobility could affect their business models. For example:
Infrastructure. As mobility changes around us, how should we approach our master plans for airports, car parking, high-speed trains, energy, ports, toll roads, and so forth? These plans have investment horizons of 15 to 30 years or longer. What will happen to demand, pricing, and usage patterns over that horizon? How do we de-risk our investments, and how can we accommodate for different future scenarios?
Cities. How will autonomous vehicles affect congestion? Can we balance their benefits against the probable increase in demand as mobility costs decline? How do we navigate their integration into our emerging “mobility as a service” offerings and realize the benefits of less congestion and lower pollution? How will road pricing models need to change? How will we need to change urban planning in this future?
Transportation. How will driverless vehicles complement existing public transit infrastructure? How can we remain relevant in this future?
Automotive OEMs. How do we reposition ourselves to sell not just vehicles, but mobility? What’s our role in the value chain: facilitator, fleet operator, driverless “driver” supplier (versus vehicle manufacturer)? What should we buy or partner with instead of building? Where and how do we develop a relationship with cities? How can we help businesses benefit from greater vehicle automation?
Aftermarket automotive. What is our role in a fleet-led urban future? How can we embrace the opportunities that connected vehicles create?
Insurance. What strategic moves should we pursue as increased autonomy shrinks the motor claims pool? What products will be relevant in this evolving future where fleets and product liability become more important?
Financial services. How will vehicle ownership patterns evolve as Millennial and Generation Z customers claim a greater share of mobility consumption? How can we finance fleets through leasing and/or mobility securitization?
Energy. How does the confluence of autonomy, sharing, and electrification change the fuel mix in automotive applications? What will our retail footprint be? In a driverless world, how could vehicle-to-grid (V2G) help us create new ways to distribute and store energy?
Retail and consumer business. If new mobility can dramatically reduce distribution costs, should we rethink the industry’s value chain and distribution access to customer? How does our logistics footprint need to evolve, and how can we realize the savings? What new propositions can we create? What customer segments could this “mobility as a platform” allow us to serve?
Health care. How do these changes help us manage the needs of our aging population? How can we use driverless vehicles to reduce health care costs?
Public policy. How will society adapt to the loss of service jobs that results from automated driving? What new roles could fill this gap, and how can policy makers ease the transition?
Modern vehicles are safer and more tech-enabled than ever, but AI-enabled mobility holds the promise to an accident-free future. Some disruptors’ systems already outperform humans on the open road. It is a matter of time before we start seeing robo-taxis and autonomous commercial vehicles appear and upend today’s business models. Now is the time for business leaders and city administrators to get in front of the transformation.