The share of GenZ’s getting their driver’s licenses has fallen drastically since the 1980s.
Remember when you where young how you really wanted to drive? That is also something you do not have in common with new generations, because according to PR Newswire, Generation Z’s distinct attitudes and preferences are set to dramatically transform the mobility sector.
The Wall Street Journal reports that members of Generation Z (those born after 1997) are buying far fewer new cars than millennials before them. J.D. Power even estimates that Gen Zers will purchase about 120,000 fewer new vehicles during 2019 compared with millennials in 2004.
Preference shifts have also presented themselves in the form of driver’s license, this because GenZ’s have left behind the duty to obtain them.
According to CB Insights, there are several reasons that are contributing to teenagers skipping out on their licenses and automotive purchase, these could be:
- The high cost of insurance and car loan payments
- The ability of smartphones to provide access to ride-hailing, food delivery, and video chat
- A more difficult driver’s-ed process
- Rising auto prices
Automakers will inevitably have to start betting on younger generations — who have grown with various mobility options — to buy their cars.
PR Newswire also reported that Gen Z customers seem to be more comfortable with the idea of autonomous vehicles and more focused on their function (represented by the vehicle’s interior design) rather than their form (as showcased by their exteriors), primarily concerned with vehicle price and safety.
“The automotive industry is starting to explore what Gen Z wants in a car,” explains Lynne Goulding, Principal Consultant in Frost & Sullivan’s Visionary Innovation Group, Frost & Sullivan. “Designing specifically for digital natives means dispensing with standard assumptions behind automotive design (…) As Gen Z will be more concerned with the interior of the vehicle than the exterior, we will see OEMs place more emphasis on technology and personalisation. For example, deep machine learning and predictive processes will mean that, with each journey, vehicles will become more familiar with user likes and preferences,” Goulding added.