The automotive industry is experiencing a profound transformation as it increasingly integrates AI into its operations, fundamentally altering how manufacturers engage with consumers and streamline processes. This shift is not merely about enhancing efficiency; it reflects a broader strategy to redefine the mobility landscape in response to evolving market demands.
AI technologies are being deployed across various dimensions of the automotive sector, from supply chain optimization to predictive analytics and safety enhancements in advanced driver-assistance systems (ADAS). These applications are pivotal in improving operational efficiencies and ensuring the safety and reliability of vehicles in a competitive environment.
Central to this evolution is the focus on enhancing customer experiences. Automakers are leveraging AI to develop personalized services and intelligent virtual assistants that facilitate more meaningful interactions with consumers. This capability enables vehicles to adapt to individual preferences, thereby creating a more intuitive driving experience. As consumer expectations continue to rise, such personalized engagement is becoming increasingly vital for manufacturers aiming to maintain a competitive edge.
The move toward greater vehicle autonomy presents its own set of challenges, particularly regarding safety. Here, AI plays a critical role in addressing complex issues related to sensor fusion and data analytics. Companies like DXC Technology are at the forefront of these efforts.
To learn more, S&P Global Mobility's Matthew Beecham spoke to Matthias Bauhammer, director Data & AI — Automotive & MFG at DXC Technology. The company provides IT services, including managing critical systems, modernizing IT infrastructure, optimizing data structures and ensuring security and scalability across different cloud environments for businesses and public sector organizations.
Image source: DXC Technology
Key takeaways:
- The integration of AI technologies, such as multimodal input methods and Generative AI, is transforming user interactions within vehicles. By enabling voice, touch and gesture controls, automotive companies can create a more intuitive and engaging experience for drivers and passengers.
- As the automotive industry moves toward greater autonomy, the implementation of AI in safety-critical functions is paramount. Companies like DXC Technology are addressing complex challenges related to sensor fusion and data analytics to ensure compliance with safety regulations.
- Effective data management systems are essential for handling the vast amounts of data generated by connected vehicles. Companies are developing robust processes to ensure data integrity and compliance with regulations such as General Data Protection Regulation (GDPR) and ISO 26262.
- The rise of agentic AI is leading to innovative applications in predictive maintenance and personalized in-car experiences. This technology allows for real-time decision-making and automation, which can significantly reduce operational costs and improve service delivery.
The following is an edited transcript of the conversation.
S&P Global Mobility: What were the most significant challenges your business encountered this year? How is DXC Technology currently integrating AI technologies into automotive solutions, and what specific areas are showing significant measurable improvements in efficiency, performance and customer interactions?
Matthias Bauhammer: As a trusted global partner for the automotive industry, DXC Technology is actively integrating AI technologies into automotive solutions, focusing on three main aspects: AI within vehicles, AI supporting value streams (e.g., engineering, aftersales, production, sustainability and sales) and AI governance and platforms for efficient large-scale AI operations.
DXC Technology is leveraging AI across multiple domains within vehicles. We’re transforming user interactions by integrating multimodal input methods—voice, touch, gestures and facial expressions—into large language model-based systems, such as GPT-4, supported by generative AI platforms for scalability and robust development.
However, the most challenging application of AI lies in autonomous driving. Achieving higher levels of autonomy demands AI functions to be on embedded hardware, which is critical for safety-sensitive actions like braking and steering. These challenges also highlight the need for superior driving scenario comprehension, particularly in rare or user-interactive situations. DXC is actively researching and implementing AI-driven trigger functions, such as out-of-distribution detection and cyclist detection in cornering scenarios with occlusions. Through partnerships like the German Ministry-funded just better DATA project, we’re advancing our capabilities and paving the way for next-generation car development and autonomous driving fleets.
Beyond vehicles, DXC’s AI integration spans engineering, aftersales and sustainability. In engineering, we employ AI and Generative AI to accelerate and validate processes across the development lifecycle. For instance, in HMI development, Agentic AI helps optimize design and coding workflows, enabling faster creation of country-specific variations, reducing development time and enhancing customer satisfaction. Our use of GenAI frameworks has significantly improved code conversion and test-case generation efficiency.
In aftersales, AI enhances parts forecasting and preventing overstock and understock while improving margins. AI-driven computer vision streamlines vehicle inspections on factory lines, reducing costs through optimized edge-based models. Predictive maintenance remains a cornerstone application. By analyzing vast datasets collected by original equipment manufacturers, AI improves vehicle reliability, reduces warranty claims and optimizes service intervals. Looking ahead, we plan to deploy more in-car AI models to identify and predict issues even earlier, driving further advancements in automotive innovation.
What emerging AI technologies or trends do you foresee shaping the future of the automotive industry, and how is your company preparing to address these changes while enhancing user experience?
We see now that GenAI adaptations are going deeper into the value stream of a carmaker, and available models are mapped to support specific processes more efficiently. One of the biggest potentials we see is in the Test & Validation Process. Using available open source or commercial GenAI models, we can map specific test and validation steps of a domain like AD or HMI and speed up the testing. DXC brings the software-defined car and data-driven development capabilities together to develop and operate AI at scale from the edge to the cloud. At this stage, we focus on specific value streams in engineering and production use cases.
What role does DXC Technology play in integrating AI for safety systems, particularly in ADAS and cybersecurity measures for connected vehicles and how do these innovations contribute to regulatory compliance?
The integration of AI into safety-critical functions, especially in the autonomous driving domain, is a challenge that requires mastering a variety of disciplines. It starts with the understanding of camera-based perception algorithms, continues into sensor fusion and situation interpretation to also understand other traffic participants’ intentions and ends at sophisticated data analytics and infrastructure capabilities.
DXC Technology is the backbone of our customers’ modernization journey. With our deep engineering and industry expertise, we are helping drive mission-critical operational excellence at scale. DXC integrates AI into safety systems for ADAS by offering comprehensive data analysis, risk evaluation and machine learning studies. We perform scenario-based analyses, Monte Carlo simulations, to assess residual risks and evaluate machine learning algorithms for safety weaknesses. Our human factor assessments ensure usability and safety in real-world conditions. These innovations contribute to regulatory compliance by thoroughly documenting risk analyses, validating safety measures and aligning with industry standards, helping OEMs meet stringent safety regulations.
For example, DXC Technology was part of the VDA LI project KI Absicherung, which paved the way for standardizations of ISO PAS 8800. We will also invest in the future to enable a safety assurance case generation for the homologation of AI-containing AD functions necessary for L3 and even more L4 vehicles.
What primary challenges do you face in implementing AI solutions within the automotive sector, especially regarding data management and analysis, and how are you addressing these?
One of the main challenges we face when implementing AI solutions in the automotive sector is handling and analyzing massive amounts of data while making sure we comply with regulations like ISO 26262, WP.29 and GDPR. Protecting data privacy and security is crucial, especially when we are working with sensitive information from connected vehicles. To deal with these challenges, we've developed robust data management systems that focus on data integrity and confidentiality. We use advanced encryption and anonymization techniques to keep personal data safe, ensuring we're fully compliant with GDPR. Our data analysis processes are carefully designed to meet automotive safety standards, with safety considerations built into every step.
Another big hurdle is navigating the complex decision-making structures within major OEMs. This is often due to the emerging nature of AI and especially generative AI combined with siloed organizations. We tackle this by closely collaborating with our OEM customers and aligning our AI solutions with their specific needs and compliance requirements. Looking at the massive automotive data volume we generate in test and production fleets, there is a need for fully automated and governed data quality pipelines, as well as machine learning pipelines, to cope with the volume and complexity of data, as well as the increasing number of AI models in the future. Existing AI platforms also need to be extended to cope with GenAI capabilities. At DXC, we provide services to build and govern companies' AI platforms and processes at scale.
Have any unexpected use cases for AI emerged recently?
Agentic AI has emerged as a transformative innovation, enabling systems to adapt and make decisions in real-time with minimal human intervention. Unlike traditional AI, it operates independently, analyzing complex datasets, forecasting outcomes and determining optimal actions — making it highly versatile for automating tasks.
In the automotive space, agentic AI has introduced unexpected and rapidly expanding applications. Predictive maintenance is a standout example: It analyzes sensor data through modules for perception, cognition, action and learning. These systems detect patterns and anomalies, schedule repairs and improve over time through feedback, reducing downtime and operational costs.
Agentic AI also elevates in-car experiences by personalizing infotainment. It suggests routes, music and podcasts based on real-time traffic, weather and user preferences. By learning from interactions, it adjusts to new routines, provides proactive assistance and integrates with external systems to optimize journeys, such as suggesting charging stations or detecting driver fatigue.
Additionally, in software development, agentic AI automates tasks like coding, debugging and testing, streamlining workflows in AD/ADAS functions. It can manage entire development pipelines, continuously improving performance and enabling developers to focus on creative problem-solving.
These advancements showcase how agentic AI is unlocking innovative use cases, revolutionizing efficiency and personalization across sectors. As a trusted partner, DXC delivers innovation, engineering talent and unmatched industry knowledge to help customers leverage these cutting-edge solutions.
