By Ramki Krishna, GVP, GM, and Global Leader for Mobility, Industrial, and Energy at GlobalLogic, a Hitachi Group Company
The automotive industry is being transformed by the integration of Artificial Intelligence (AI), which is powering a new wave of smarter, more personalized innovations. From enhancing in-vehicle safety systems to enabling semi-autonomous driving features, AI is redefining what’s possible in vehicle functionality and shaping the driving experience in unprecedented ways.
Tesla has been instrumental in advancing the perception and adoption of autonomous driving technology through its innovative Autopilot system1, which uses AI to interpret real-time data gathered from various sensors and cameras, enabling the vehicle to safely navigate through complex driving conditions.
BMW’s Intelligent Personal Assistant2 allows drivers to control the car’s features—like climate control or navigation—through simple voice commands, creating a seamless and hands-free interaction.
Meanwhile, Toyota's "Yui" AI system3 goes a step further by adapting to a driver’s emotions, preferences, and behaviors, aiming to deliver a more intuitive and personalized in-car experience.
These are only a few examples illustrating how AI is not just enhancing vehicle performance but also recasting the relationship between the driver and the machine, making it more responsive, predictive, and personalized. Indeed, 44% of automotive companies are now actively exploring AI applications with implications for the way vehicles are designed, produced, and operated4.
To understand AI's impact on the industry, consider the shifts occurring across the automotive landscape, particularly the transition toward software-defined vehicles. Modern vehicles have moved from distributed architecture, where numerous electronic control units (ECUs) manage different functions, to a more centralized, high-performance computing model.
This transformation has streamlined the vehicle architecture, enabling over-the-air software updates, more efficient management, and reducing overall complexity.
Simultaneously, many automakers are embracing vertical integration strategies—taking control of the entire software stack from chip development to application integration. This approach helps automakers differentiate their offerings, with software becoming the key to creating compelling customer experiences.
In vehicle design, AI-powered algorithms can analyze vast amounts of data to identify consumer preferences, enabling automakers to offer personalized in-car experiences.
As AI systems collect data from drivers and passengers, they can offer more intuitive and customized experiences, such as suggesting personalized route optimization, recommending restaurants based on your cuisine/chef preference, or finding parking spots in real-time with integrated in-car payment solutions. The capability to process this real-time data was nearly impossible before the integration of AI and new vehicle architectures.
AI is also having a profound impact on the production process. According to McKinsey, automotive companies using AI in manufacturing have seen up to a 20% increase in production efficiency5. From optimizing assembly lines to improving supply chain management, AI-driven systems can predict maintenance needs, prevent disruptions, and enhance overall operational efficiency. By forecasting potential production line failures and dynamically adjusting schedules, AI ensures manufacturers maintain seamless operations—especially important as more automakers transition to direct-to-consumer sales models.
As automakers push towards higher levels of vehicle automation, AI will play an even more critical role. While today's cars feature Level 2 automation6, which includes partial driving automation like adaptive cruise control, parking assistance and lane change assist, the industry is pushing toward Level 3 and Level 4 automation7. These advanced levels of automation will enable vehicles to drive themselves in more complex environments.
Indeed, autonomous driving is one of the most prominent applications of AI in the automotive industry. It incorporates a range of AI-powered technologies like adaptive cruise control, automatic emergency braking, and lane-keeping assistance, allowing vehicles to navigate complex road conditions autonomously. These systems enable cars to detect objects, evaluate road environments, and make real-time decisions to improve both safety and comfort for drivers and passengers.
The impact of these technologies is reflected in the rapid growth of the global market for Advanced Driver Assistance Systems (ADAS), which is projected to reach $72.2 billion by 20308. This expansion is primarily driven by the increasing integration of AI technologies into vehicle safety and automation systems, highlighting the crucial role AI plays in the future of automotive innovation.
The automotive industry is also exploring the potential of generative AI (GenAI). One simple yet impactful example would be the replacement of cumbersome 200-page vehicle manuals with voice-activated AI assistants. Instead of consulting a manual or calling customer support when a warning system pops up on the dashboard, the AI system could answer the query by cross-referencing data from the car's diagnostics. It would instantly generate a detailed explanation of the issue along with potential solutions.
GenAI also offers potential for more advanced applications, such as predictive maintenance, where AI can analyze vehicle data and forecast potential failures before they occur. This would mark a shift toward an era of personalized vehicle recommendations and optimized repair services based on predictive analytics. By addressing issues proactively, manufacturers and service providers could reduce breakdowns, improve vehicle reliability, and enhance overall customer satisfaction.
GlobalLogic, a Hitachi Group company, is a leading player in the automotive AI space and is helping automakers integrate AI into their operations by building upon years of expertise in creating in-vehicle software and connected car platforms.
One example of Hitachi’s contribution is in predictive maintenance, where it has helped to develop AI-driven solutions for clients such as Penske. These solutions not only predict when parts may fail but also provide guided repair instructions based on the failure patterns of specific vehicle components. GlobalLogic’s deep understanding of vehicle architecture allows it to build solutions that are robust and safe, meeting the stringent regulatory requirements of the automotive industry.
Elsewhere, machine learning experts from GlobalLogic partnered with a leading fleet management client to enhance their dash camera system with ADAS technology that would detect distracted driving and alert drivers to risky behaviors through in-cab notifications. This has been a boon for overall road safety, with fleet owners reporting significant benefits, including a reduction in claims costs by as much as 80%. GlobalLogic also helped to develop a cutting-edge video anonymization system that safeguards personal data. With new privacy regulations, protecting sensitive data has become essential for fleet management services. The technology GlobalLogic spearheaded uses advanced machine learning to blur faces and license plates in real-time video footage. Powered by a custom detection model that identifies objects in images and videos in real-time, the solution ensures fast video stream processing (under 100ms) while maintaining over 95% accuracy. Companies can now offer video services securely and comply with privacy standards, all without compromising on performance or data protection.
Despite the clear benefits of AI and machine learning, the automotive industry still faces challenges in fully adopting the technology. Traditional automakers, accustomed to long product cycles and extensive safety regulations, are often slow to adopt AI compared to new-age companies like Tesla. However, as more use cases prove successful, the pressure to adopt AI will grow.
GlobalLogic and other industry leaders are helping automakers navigate these challenges by providing expertise in both AI development and automotive engineering.
As more organizations recognize the competitive advantages that AI offers, the groundwork is being laid for transformative change in the automotive industry. From enhancing the in-vehicle experience to boosting safety and operational efficiency, AI is poised to unlock new possibilities for personalized, intelligent, and efficient mobility, reshaping transportation for years to come.
Now is the time for automotive leaders to invest in AI strategies that drive innovation and create a competitive edge in a rapidly evolving market. Companies like GlobalLogic are at the forefront, empowering automakers to harness the full potential of AI and lead the future of mobility.
To learn more about GlobalLogic’s Enterprise-Grade GenAI Solutions, click here.
GVP, GM, and Global Leader for Mobility, Industrial, and Energy, GlobalLogic, a Hitachi Group Company
In his over twenty years of experience in product engineering and P&L management, Ramki Krishna has developed a successful track record of establishing global client engagements that deliver maximum value through innovative technologies, processes, and commercial models.
Prior to joining GlobalLogic, Ramki served as Vice President and Global Head of Sales & Strategic Initiatives for Wipro’s Product Engineering Services (PES) business, where he was responsible for a $500M+ revenue portfolio across several industries. During his tenure at Wipro, Ramki incubated new initiatives that delivered consistent revenue growth and market leadership positions in several industry domains. Before Wipro, Ramki held sales and account management leadership roles at Cyient and Alfa Laval in India and the Americas.
Ramki holds a BS degree in Science and a postgraduate degree in Chemical Engineering. He loves sports and adventure, and he is active in the Dallas Cricket League.
Search
U.S.A.
