68% of automotive organizations use or pilot agentic AI for product development, but only 5% report mature AI governance

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68% of automotive organizations use or pilot agentic AI for product development, but only 5% report mature AI governance

• Organizations generating the most value from AI are achieving up to 3x faster gains in time-to-market and greater productivity than their lower-performing peers
• More than seven in ten executives believe agentic AI can improve engineering decision-making, yet confidence drops significantly as AI moves closer to safety-critical activities
• Only 10% of organizations have established shared lifecycle accountability across the ecosystem, highlighting a major collaboration gap in automotive product development

Paris, October 12, 2026 – According to the Capgemini Research Institute’s latest report ‘Rewiring automotive product development: how organizations can pull ahead in the AI race’, automotive organizations are rapidly moving agentic AI from pilots into product development. Nearly seven in ten organizations already use (33%) or pilot (35%) the technology, while adoption across non-core engineering activities is expected to increase from 26% today to 68% within the next two to three years. The perceived value is significant, with 83% of executives believing agentic AI will enable engineers to spend more time on core engineering work rather than administrative and coordination tasks. However, very few (5%) organizations report fully mature AI governance, highlighting ongoing challenges around data quality, traceability, accountability and ecosystem collaboration.

Agentic AI is creating a new performance gap across the industry
Based on a global survey of 800 automotive senior executives across 12 countries in North America, Europe and Asia-Pacific, the research identifies agentic AI as the next frontier in automotive product development. While most automotive organizations are investing in AI, a select group is already achieving significantly greater returns than its peers.

These high-value realizers report 17% faster development cycles, 19% gains in engineering productivity, and a 19% reduction in time-to-market. According to the report, their advantage stems less from adoption of AI itself and more from stronger data foundations, clearer business cases, and more disciplined governance and operating models. As agentic AI adoption accelerates, these capabilities are emerging as the key differentiators between organizations generating measurable value and those still struggling to scale.

AI maturity varies significantly across markets. Respondents in the US and Europe report the highest levels of AI strategy execution and cross-functional AI planning. Among OEMs in these regions, 53% and 46%, respectively, are already implementing AI initiatives, while 18% (US) and 16% (Europe) have a comprehensive cross-functional AI strategy, vision, and roadmap in place. In China, four in ten respondents report being in the implementation phase, while just 7% have reached a comparable level of strategic maturity. Elsewhere in Asia-Pacific, implementation maturity remains lower.

“Over the past decade, the automotive industry has undergone a profound transformation with the shift to software-defined vehicles, establishing the digital foundations that are now enabling the next wave of innovation. Agentic AI is creating a new performance divide in the automotive industry,” said Laurence Noël, Global Head of Automotive at Capgemini. “The organizations generating the most value are not simply adopting AI faster, they are redesigning workflows, strengthening ecosystem collaboration, building trusted data foundations and establishing clear accountability for AI-enabled decisions. The leaders of tomorrow will be those that successfully embed AI into the engineering processes at scale.”

Trust emerges as the key barrier to scaling agentic AI in product development
As organizations expand the use of agentic AI across engineering workflows, confidence in technology varies substantially depending on where it is applied. Executives say they are most comfortable using agentic AI in upstream research and concept activities, where trust reaches 59%, but confidence falls to 40% in development activities, where AI-generated results can have more direct implications for engineering outcomes, product quality, and safety.

The findings suggest that many automotive organizations have yet to establish the evidence, traceability and accountability layers required to deploy it confidently at scale. Trust is becoming a critical factor in determining how quickly organizations can move from experimentation to enterprise-wide transformation.

The vehicle feedback loop remains incomplete
The research also highlights a challenge beyond AI adoption itself: the industry’s ability to turn real-world vehicle data into continuous product improvement. While connected vehicles generate vast volumes of operational and usage data, many organizations still struggle to translate these insights into action.

Nearly two-thirds (64%) of organizations report that learnings from vehicles in use primarily inform future vehicle programs rather than improvements to vehicles already on the road. Meanwhile, over-the-air updates remain concentrated on areas such as cybersecurity and navigation, with comparatively fewer organizations deploying updates that modify driving functions or assisted-driving capabilities. The findings suggest that industry’s next competitive advantage will depend not on collecting more data, but on accelerating the journey from vehicle insight to engineering action.

Scaling AI will require more than technology
According to the report, the industry’s biggest barriers to scaling AI are increasingly organizational rather than technical. Six in ten executives report that delays are primarily driven by process inefficiencies rather than technology limitations, while 45% have yet to define a strategy and roadmap for AI in product development

The research also points to the growing importance of ecosystem collaboration. As software-defined vehicles become more complex and development becomes increasingly distributed across OEMs, suppliers and technology partners, success will depend on greater alignment across the value chain. However, only 30% of organizations report co-development models built around shared outcome metrics, while just 10% have established shared lifecycle accountability across their ecosystem. This highlights the challenge many organizations face in aligning partners around common goals and shared responsibility for product outcomes.

Methodology of the report
The Capgemini Research Institute surveyed 800 senior executives from the automotive industry, comprising 400 automotive OEMs, 160 tier-1 suppliers, and 240 technology providers. Respondents represented organizations across North America, Europe, and Asia-Pacific, and included leaders from product development, engineering, technology, data and AI strategy, and related functions. The Institute also conducted in-depth interviews with 24 automotive industry executives and technology providers to the automotive industry. The survey was conducted in July 2026.

About Capgemini
Capgemini is the business transformation partner for enterprises in the age of AI. We help organizations imagine and build an intelligent, sustainable future, combining AI, technology and human ingenuity to transform how they operate, innovate and grow. With unique end-to-end capabilities spanning strategy, technology, engineering and intelligent operations, we bring together deep industry expertise and market-leading capabilities in AI, cloud and data to turn ambition into measurable business outcomes at scale. Supported by a robust ecosystem of partners and nearly 60 years of expertise, Capgemini is a responsible and diverse global organization of over 410,000 team members in more than 50 countries. The Group reported 2025 revenues of €22.5 billion.

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About the Capgemini Research Institute
The Capgemini Research Institute is Capgemini’s in-house think-tank on all things digital. The Institute publishes research on the impact of digital technologies on large traditional businesses. The team draws on the worldwide network of Capgemini experts and works closely with academic and technology partners. The Institute has dedicated research centers in India, Singapore, the United Kingdom and the United States. It was ranked #1 in the world for the quality of its research by independent analysts for six consecutive times – an industry first.

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Attachments

• 2026_10_12_ Capgemini_Rewiring automotive product development report_Press release _
• Final-Infographic_Capgemini_Rewiring automotive product development CRI report