Artificial Intelligence (AI), also known as machine learning, will transform the reality of our field-sector as we know it. Terms like Big Data, Internet of Things (IoT), or the application of algorithms that allow machines to identify conduct patterns, make decisions, even anticipate our needs and learn autonomously through reinforcement, will be more and more common.

The use of AI in the industry is not new, and makers have already made great improvements in this field. So much so that completely autonomous driving is very close to become reality (Uber and Volvo have recently presented their first car with total autonomous driving capacity and ready to be made). But, for now, it is forecasted that around 250 million vehicles will be connected in 2020.

The impact of AI on the automobile sector will allow long distance driving in less time, with safety improvements, comfort, environment… And all that with an intelligent, autonomous car, capable of processing in real time a huge volume of data regarding the conditions of the road, surrounding vehicles, temperature, aspects related to its surroundings and signals that will transform the concept of ‘I need to go somewhere’. But this model change will imply a complete adaptation by the sector.

In a while, automobile makers will go from selling cars to clients to selling them a service that will meet their needs of moving around. If we think about it, the majority of drivers use their cars to travel short distances (commuting, picking kids up, getting groceries…). This way, if we analyze the amount of time the car is being used, it is barely 10% of its total use. Put it in a different way: 90% of the time, the car we own is not adding value.

Shared cars

Technology can make the model of use evolve towards a concept where the user would have the option of using shared autonomous cars in urban areas and pay only for the time used, avoiding maintenance costs, taxes, parking, inspections… In the future, for example, the client will ask for a vehicle that will pick him/her up and be transported to the destination, paying to satisfy his/her ‘need to go somewhere’ without creating other needs such as ‘I have to have my car inspected’, ‘I need a mechanic’, ‘I need to wash my car’ or ‘I have to get gas’.

This rationalization in the way of satisfying the users’ needs will affect other needs that won’t apply to the user anymore, impacting areas such as the warranty period, professional drivers (truck or bus), insurance, delivery fleets… This will be a major impact, and that’s why those sectors will need to readapt in order to guarantee their profitability and efficiency facing the paradigm change proposed by technology.

Private cars won’t disappear

So, will private cars disappear? No. But even those who decide to own a car will be able to share it. So, instead of leaving their car parked, they will have the opportunity to offer a ‘peer to peer’ service for other people to move around by taking advantage of the time the car is not active.

What will be the consequences of these changes? It will probably mean a reduction in the fleet of urban vehicles as their usage will be maximized, and it will change the aspect of cities because there will be less parked vehicles- they will be moving around-.

However, it is not all advantages: machines break down and, more importantly, have no ethical values. What will a car do if it must swerve to avoid a distracted pedestrian that suddenly crosses the road or to preserve its passengers’ safety? The lack of ethical values and ‘humanity’ in machines still poses an uncertainty that must be addressed.

Industry investment

According to a study by Capgemini Research Institute, the automotive sector has invested 9.953 million euros in ‘start-ups” specialized in AI since 2014. However, this study details that, since 2017, the number of automotive companies that have successfully implemented AI on all of their organizational levels (to scale) has only increased marginally (from 7 to 10%). On the other hand, the increase in the number of companies not using AI at all has been more significative (from 26% to 39%).

Share