Artificial intelligence is becoming totally ingrained into business. Possibly none more so than the automotive industry with autonomous cars being the most talked about.
At IAA Mobility 2025, XPENG showcased its AI-defined vehicles and Level 4 autonomous driving goals, Mercedes-Benz unveiled its AI-driven MB.OS, and Uber and Momenta announced plans for AI-driven autonomous taxi testing in Munich starting in 2026.
There can be no doubt that autonomous driving has gone from fad to a very real part of the automotive industry. Meaning that OEMs across the globe have had to sit up and take notice as all major manufacturers are starting or have completed the journey from Level 0 cars with no automation, to Level 4 cars that allow for the vehicle to have full control with less limitations.
Proof of the drive to see more self-driving cars on the road comes from the fact that European Commission President Ursula von der Leyen has called for a continent-wide push to develop self-driving cars, saying artificial intelligence could help revive the region’s struggling automotive sector and improve road safety.
The vehicle offers continuous support for either steering or acceleration/braking, such as through adaptive cruise control or lane centering assist, but not both functions at the same time.
The vehicle continuously assists with both steering and acceleration/braking simultaneously through features like dynamic lane management and traffic jam assist, while the human driver remains fully responsible for monitoring the surroundings and intervening when necessary.
The system manages all aspects of driving under specific conditions, but the human driver must remain available to take control when prompted, such as when the system encounters scenarios beyond its capabilities.
The system assumes full responsibility for driving tasks within a defined operational design domain, such as specific routes or areas, eliminating the need for a human driver, and is also accountable for safely managing any errors that arise.
The system takes full responsibility for all driving tasks in every condition and on all roads, eliminating the need for a human driver and with no requirement for a steering wheel or pedals, these vehicles can function as fully automated passenger transport.
Level 5 self-driving cars are unlikely to be widely available for personal use for at least another decade, with expert predictions often placing commercial availability between 2035 and 2040, and some experts believe it could take even longer.
It may not come as a surprise, but as with most things in the automotive world right now, China’s OEMs seem to be much further down the road with a host of brands already adopting higher levels of autonomous vehicles than their European counterparts.
JATO data points to the fact that in China, from the period of 2020 to 2025, the market adoption of Level 2 vehicles in 2020 was 2,747,644. Fast forward to 2025, and those figures have leaped to 6,230,487 in H1 of 2025 alone.
In this market, BYD is head and shoulders above the competition with numbers of Level 2 automation vehicles purchased substantially increasing from 46,907 in 2020 to 1,107,807 in H1 2025. When you compare that to say a leading European brand like BMW, there is a massive divide. In 2020 BMW sold just 28,844 Level 2 vehicles in 2020, growing to just 135,693 in H1 2025.
At IAA Mobility 2025 in Munich, it was made unmistakably clear that the next wave of automotive innovation will be powered by software and shaped by AI. As safety systems, infotainment, and autonomous capabilities increasingly intersect, vehicles will require compute platforms that deliver efficiency, scalability, and unwavering reliability.
The technologies displayed at the show offered a compelling glimpse into how AI is rapidly redefining the automotive landscape. At the heart of these breakthroughs lies the Arm platform, serving as the essential compute backbone for the vehicles of tomorrow.
Autonomous vehicles are just the start. AI is rapidly expanding its influence across key sectors of the automotive ecosystem, including leasing and fleet management, manufacturing, retail, and financial services.
While perspectives on the futuristic technology may vary, some view it as a strategic asset, others as a disruptive force, its presence is undeniable. Month by month, the technology continues to reshape operations, decision-making, and customer engagement across the global automotive industry.
AI is rapidly redefining the automotive landscape, serving as a catalyst for enhanced safety, operational efficiency, and product innovation. Its integration across the value chain is not only accelerating performance but also laying the groundwork for long-term sustainability and competitiveness.
In a relatively short space in time, cognitive computing has become integral to the development and deployment of Advanced Driver Assistance Systems (ADAS), which are enhancing both vehicle safety and driver comfort.
Market projections underscore the significance of this trend. Yole Intelligence predicts that the integration of AI in driver-assistance systems is expected to grow at a compound annual growth rate of 20% between 2023 and 2028. This growth reflects its expanding role in redefining road safety, enhancing the driving experience, and potentially influencing downstream factors such as vehicle insurance costs.
Machine intelligence is driving a paradigm shift in automotive manufacturing, delivering substantial gains in operational efficiency, cost reduction, and product quality. AI-powered robotic systems and intelligent automation platforms are increasingly being deployed to execute repetitive tasks with high precision, facilitate predictive maintenance, and optimise production workflows, resulting in reduced waste and downtime.
These advancements are enabling manufacturers to maintain competitiveness in a dynamic market environment while meeting growing demand for high-quality, cost-effective vehicles.
The technology is significantly enhancing quality control in automotive manufacturing, with projected improvements in defect detection, production efficiency, and predictive maintenance. McKinsey & Company predicts that AI-based machines can detect defects 90% more accurately than humans, while Körber Digital predicts that over 50% of manufacturing companies will integrate AI into their quality control processes by 2025, resulting in a 30% improvement in defect detection rates.
By optimising manufacturing processes, smart technologies are ensuring that resources are allocated effectively, thereby minimising waste and maximising output. Additionally, the technology looks to be improving supply chain management by forecasting demand, identifying bottlenecks, and streamlining logistics.
These capabilities continue to work in tandem to create smoother workflows, reduce operational disruptions, and ultimately drive greater productivity and profitability across the enterprise. Two AI technologies, namely machine learning and deep learning are seemingly at the heart of these advances.
Through algorithmic modelling, machine learning can examine extensive datasets to detect trends and automate decisions that streamline operations. Several top OEM makers are using it to beneficial effect and profiting handsomely in the process.
Conversely, deep learning, a subset of machine learning, has demonstrated exceptional capabilities in identifying microscopic defects in components that are undetectable through manual inspection or conventional quality assurance methods. This technology enables OEMs to uphold quality standards that exceed those achievable by traditional approaches.
Several leading OEMs have successfully implemented deep learning-based inspection systems, yielding measurable improvements in defect detection accuracy and overall production quality.
AI is optimising production processes, streamlining supply chains, and minimising downtime through predictive maintenance. In fact, Verysell AI predicts that the market for the technology in manufacturing is projected to reach $68.36 billion by 2032, reflecting the industry's increasing reliance on these technologies.
AI algorithms are playing a pivotal role in transforming the automotive industry by analysing vast amounts of data to uncover patterns in consumer behaviour and preferences.
This deep understanding is empowering automotive manufacturers to deliver highly personalised in-vehicle experiences by integrating adaptive infotainment systems and intuitive driver assistance technologies. Through the analysis of user interactions, driving behaviours, and lifestyle data, manufacturers can design vehicles that align more closely with individual preferences and expectations.
This data-informed approach is facilitating the development of a new generation of intelligent vehicles that not only fulfil functional requirements but also enhance user engagement and satisfaction.
OEMs are being forced to meet their Environmental, Social and Governance targets. The message is clear, do it or suffer the financial consequences of large-scale fines originating from non-compliance.
Fortunately, OEMs can mitigate the risk of regulatory penalties by adopting advanced AI-driven energy management solutions. These systems optimise fuel consumption and battery performance, contributing to reduced vehicle emissions and enhanced energy efficiency.
Additionally, the technology is facilitating the development of sustainable materials and environmentally conscious design practices by analysing lifecycle data and environmental impact metrics. Collectively, these innovations underscore AI’s strategic role in advancing low-emission mobility and promoting more sustainable manufacturing processes across the automotive sector.
JATO Dynamics continues to provide its automotive customers with industry leading data on what their competitors are buying and how they are buying vehicles. Using AI to gather and clear the data to ensure the most accurate picture of the market presented, we are constantly able to unearth the right competitor vehicles in the market for customers to benchmark against.
Dean Miles, JATO’s Head of Automotive says, “This fast-changing world of data on what the market is doing is invaluable to vehicle manufacturers. We are using AI to move to an Insights led service to customers and away from pure data. We can use AI to generate KPI’s in the cloud for our customers, delivered live via alerts as the changes happen in the market.”
A powerful wave of industry investment is propelling a revolution in automotive, with AI at its core. Visionary leaders like Tesla, Toyota, and BMW aren’t just adapting, they’re shaping the future. By establishing innovative AI research hubs, these automakers are unlocking breakthroughs in generative design, autonomous mobility, and energy optimisation, setting new standards for performance, sustainability, and innovation. Will everybody be able to keep up? Only time will tell.
JATO Dynamics, founded in 1984, now has representation in over 51 countries around the world. We provide precision under pressure, providing the world’s most timely, accurate and up-to-date automotive information on vehicle specifications, pricing, sales and registrations for over 30 years. We offer more than just data, as we have watched the world change, and consumer mindsets alter with it we have been able to offer insights that help inform the industry. We are able to react to short-term market movements, plan for long-term developments and ultimately to meet the needs of our clients.