Adopting generative AI to drive the softwarization of cars
Gone are the days when automakers were scratching their heads over ways to tackle the challenge of electrification. Innovation after innovation means that 14% of all new cars sold in 2022 were electric – three times more than in 2020. However, manufacturers should not be too quick to celebrate the next big challenge of softwareization: using a software solution instead of traditional hardware to solve a problem – comes their way. As the automotive industry moves toward smart devices on wheels, manufacturers must embrace tools that help them develop, deploy and maintain software. These challenges are why the advent of generative AI (GenAI) presents such an opportunity for manufacturers. In this article, we look at how GenAI can help solve the challenges of softwareization, where it is already being used, and how others can adopt it.
Becoming software companies
Modern vehicles are gradually becoming computers on wheels; their computing platforms are made of powerful, rapidly connected “vehicle servers” containing more than a hundred million lines of code. Therefore, it is critical to integrate and update these systems across the supply chain of existing and new partners to ensure safety, longevity, sustainability, durability and performance.
As the automotive industry rapidly evolves, software and connectivity are transforming the next generation of driving experiences. Such developments pose a challenge to traditional manufacturers whose hardware-centric culture does not match the needs of a software-centric world. Today, the software engineering department at most automakers is notoriously overstaffed and underfunded. For traditional manufacturers this is undeniably a problem, but for forward-thinking car makers it is an opportunity to innovate.
But here lies the conundrum: companies known for their superior hardware may find it difficult to introduce themselves as a computer or AI company. But with the number of automakers investing in AI expected to reach a compound annual growth rate (CAGR) of 22.7% between 2023 and 2030, these companies simply must do so to stay competitive.
Vice President at Wipro Engineering.
The global race towards generative AI in automotive production
While automakers may find it challenging to think of themselves as software companies, we are already witnessing this phenomenon with the rise of Tesla – seemingly the only global automaker that is a technology company first and a car manufacturer second. As a software company that makes cars, they use AI at fleet scale to develop new innovations faster. For example, they recently started using an advanced generative modeling technique that allows them to predict possible outcomes based on past observations, consistently across multiple camera views. In fact, this is a great example of the power of GenAI: facilitating the conversion of an idea into a software function.
But the US isn’t the only country taking bold steps toward the emerging technology. About 1.4 million Chinese engineers are qualified annually, six times as many as in the US, and at least a third of them in AI. For example, Chinese automakers like BYD are 70% to 80% vertically integrated across their entire supply chain, while in the US it is less than 25%. For example, they can produce batteries for much less. Such savings give them much more leeway in aggressively pricing all their vehicles. The bottom line is that cheaper vehicles mean more vehicles on the road, and therefore more data.
China is keenly aware of generative AI’s potential to drive softwarization, and they have the technological foundation and engineering talent to translate that potential into practice. Vehicle affordability is always important, and softwareization will be key to delivering value at the point of purchase – and increasing residual value as the vehicle ages.
Embrace generative AI now
While automakers can gradually add software capabilities to their vehicles, this is not an easy process as hardware is still a challenge, especially when it comes to storage. Essentially, vehicles must come with greater computing power than the bare minimum.
GenAI allows manufacturers to use a software sandbox in every vehicle they ship, compare the performance of their software against the human usage base, and test new features on a limited number of vehicles. Additionally, manufacturers can come up with new ideas while gaining valuable insights into how the new software features work. This means they can implement new features faster, minimizing the risk of failure.
Looking at the benefits for drivers, GenAI allows vehicles to examine driving behavior and individualize and optimize the driving experience for each driver. Essentially, drivers get used to their new car, and their new car will get used to them. That’s a powerful selling proposition for any car company.
In addition, by having enough computing space for innovation, manufacturers can use vehicle-specific data to help service representatives better understand the user experience. Therefore, they can share personalized messages with the vehicle owner via email, SMS and possibly in the future via the dashboard itself.
Softwareization is inevitable!
The future of the automotive industry lies in softwarization, and emerging technologies that are gradually becoming ubiquitous could potentially drive innovation faster and easier than ever. Manufacturers should pay attention, because generative AI already has the potential to deliver a superior, personalized driving experience. This is the moment when automakers need to take the wheel and make that turn, visualizing themselves as the next generation of pioneers.
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