AI pushes mobility industry into digital era after electrification
AI‑driven digitalization is emerging as the next battleground in mobility, reshaping vehicle development, services, and global supply chains
Artificial intelligence (AI) is set to define the next phase of transformation in the automotive industry as manufacturers move beyond electrification and focus on digital capabilities embedded in vehicles, production systems and mobility services.
The shift marks a transition from the first phase of the electric‑vehicle revolution to a new period in which software, AI models, and intelligent systems increasingly determine how vehicles are designed, manufactured, and operated.
“The automotive industry today is like a football match. The first half is electrification, and the second half is digitalization driven by AI,” said Bono Ge, country manager for the UK and Ireland at BYD. “This is what we see in China. Customers have a very strong demand for intelligent features and smart functions in their cars.”
Ge said AI applications extend beyond autonomous driving and include in‑car language models that allow vehicles to distinguish whether a driver is speaking to the car or to passengers. He said the system must understand context so that if a parent tells a child in the back seat to stop, the vehicle does not interpret the instruction as a command directed at the car.
AI systems are also being applied to energy management in electric vehicles. Charging routes and strategies can be optimized through AI models that analyze driving patterns and infrastructure availability.
The growing demand for these digital capabilities reflects changing consumer expectations, particularly in markets where electric vehicles have already reached significant adoption levels.
AI development cycles
Executives shared their perspectives during a panel discussion titled “Shifting gears with AI: the future of mobility” at Sustainability Week in London on March 2. The event was organized by Economist Impact. The session was moderated by Vijay Vaitheeswaran, global energy and climate innovation editor at The Economist.
Apart from BYD’s Ge, other speakers included Manuel Schneider, head of open innovation at BMW, and Karin Svensson, chief sustainability officer at Volvo Group.
Schneider said AI is already reshaping how vehicles are developed inside automotive companies, compressing the time required to move innovations from concept to production.
“We have been working on AI for about 15 years, so this is not new for BMW,” Schneider said. “What we see is that AI will speed up the process from the very first idea to seeing it implemented in the car.”
“It affects everything from deriving a business case, validating a product with customers, engineering and crash simulations, all the way to physical AI on the shop floor,” he said. “We will see significant speed improvements across the entire development process.”
AI‑driven engineering tools are transforming internal workflows in automotive companies. Digital simulation, predictive testing, and automated design processes enable engineers to evaluate concepts faster and reduce development costs.
Across the value chain
Beyond product development, AI is influencing nearly every stage of the mobility value chain, from vehicle design and factory operations to logistics and after‑sales services.
“We see AI as central to creating business value across the entire value chain,” said Svensson. “It affects everything from design and production to customer interfaces, operations and services.”
“The need for transportation is constantly increasing, and we need to make it cleaner, safer and more efficient,” she said. “AI can absolutely help increase sustainability, but we also need to think about sustainable AI.”
For commercial‑vehicle manufacturers such as Volvo Group, the technology is particularly important for monitoring vehicle performance and minimizing downtime.
“For our customers, uptime is extremely important,” Svensson said. “AI is a tool that helps us understand how to keep vehicles running on the road and operating efficiently.”
The adoption of intelligent systems also varies across regions. Executives noted that consumer behavior and market maturity can shape the pace at which drivers adopt AI‑enabled features.
Ge said Chinese consumers tend to adopt in‑car digital features more quickly, including voice control and other intelligent systems.
“In Europe, many customers still focus more on engineering aspects of the vehicle,” he said. “When we ask some customers whether they use voice control, they say they have never used it.”
Competing AI ecosystems
Automakers are increasingly relying on multiple AI ecosystems as they integrate large language models and machine‑learning systems into vehicles and development processes.
Schneider said BMW maintains a technology‑agnostic strategy that allows the company to use different AI models depending on the application.
“We follow a technology‑agnostic strategy,” he said. “We try to work with the best models for each use case. That might be Gemini, Anthropic, OpenAI, or DeepSeek in China.”
He added that innovation is advancing rapidly across markets, particularly in China, where developers are quickly adopting AI tools in software engineering and product development.
“We definitely see many advancements coming from China that are beneficial for the whole world,” Schneider said. “It would be wrong not to study them and make use of them.”
“We see massive speed in China,” he added. “There is a very natural way of engaging with AI when developers build software there.”
The automotive industry remains deeply dependent on global supply chains. This dependence makes it sensitive to geopolitical tensions and trade disputes.
Tariffs and geopolitics
BYD has seen strong sales growth in the United Kingdom, where imported electric vehicles are not subject to the additional anti‑subsidy tariffs imposed by the European Union. In October 2024, the EU introduced definitive duties on Chinese EVs ranging from about 7.8% to 35.3%, on top of the bloc’s standard 10% import tariff.
In an interview with TechJournal.uk, Ge said companies must remain aware of geopolitical risks that could disrupt supply networks.
“Tariffs are certainly one factor, but the main issue is whether customers understand and like the technology,” he said. “Our cars deliver good value for money, so tariffs have not been the most important factor.”
“As a company, we always need to be aware of geopolitical risks,” he said. “Supply chains and transportation can be affected, so we must watch those developments closely.”
“The automotive industry is global,” Ge added. “If something happens in China or in the Middle East, it can affect manufacturing in Europe.”
BYD’s expansion strategy reflects its vertically integrated technology model, which combines vehicle manufacturing with battery production, semiconductor development, and energy‑storage systems.
Ge said the company views this integration as a key advantage as vehicles become increasingly digital platforms driven by software and AI.
The Chinese manufacturer has already built a significant presence in the UK through electric buses and energy‑storage projects, which Ge said helped establish brand recognition before its passenger‑car expansion.
Since launching its bus business in Britain in 2015, BYD now operates about 2,800 electric buses there and has also deployed roughly 2 gigawatt‑hours of battery‑energy storage connected to the power grid, with another gigawatt‑hour under development. These projects, he said, demonstrate how mobility companies are evolving into broader providers of clean‑energy and digital‑technology services.
Future vehicle services
Looking ahead, automakers expect AI to open new revenue streams by enabling services that extend beyond traditional vehicle manufacturing.
Increasingly sophisticated sensors and onboard computing systems allow vehicles to monitor drivers, passengers, and mechanical systems in real time.
“We have many sensors in cars, and the question is what we do with that data,” Schneider said. “Can we measure heart‑rate variability or blood pressure and provide medical services inside the vehicle?”
He said such concepts remain experimental but illustrate how automotive companies are exploring new partnerships and digital services.
“This is still a small pilot project, but it shows how the automotive ecosystem is opening up to new business models,” he said. “Car manufacturers are connecting to new partners and technologies.”
Battery analytics represent another emerging application for AI systems in electric vehicles.
Svensson said AI could help increase sustainability in transport, but added that companies must also consider what she called “sustainable AI.”
“We also use AI models to monitor the battery,” Ge said. “We look at the state of charge and the state of health to understand how the battery performs over time.”
As digital capabilities expand, AI will increasingly determine how vehicles interact with drivers, infrastructure, and other vehicles, turning automobiles into connected software platforms rather than purely mechanical machines.