Capgemini survey: 68% of automotive organizations use or pilot agentic AI, but only 5% report mature governance
Nearly seven in ten automotive organizations are already using or piloting agentic AI in product development, but just 5% say their AI governance is fully mature.
- 68%
- 5%
- up to 3x faster
- 800
What Happened
The Capgemini Research Institute's report 'Rewiring automotive product development: how organizations can pull ahead in the AI race' draws on a global survey of 800 automotive senior executives across 12 countries in North America, Europe and Asia-Pacific. It found that 33% of organizations already use agentic AI in product development and 35% are piloting it, while adoption across non-core engineering activities is expected to rise from 26% today to 68% within the next two to three years. Some 83% of executives believe agentic AI will let engineers spend more time on core engineering work rather than administrative and coordination tasks. Yet only 5% of organizations report fully mature AI governance, with challenges remaining around data quality, traceability, accountability and ecosystem collaboration.
The Capgemini Research Institute surveys 800 automotive senior executives from 400 OEMs, 160 tier-1 suppliers and 240 technology providers across North America, Europe and Asia-Pacific, plus 24 in-depth interviews with industry executives and technology providers.
The report 'Rewiring automotive product development: how organizations can pull ahead in the AI race' is published, dated Paris.
- 17% faster development cycles
- 19% gains in engineering productivity
- 19% reduction in time-to-market
- Their advantage stems less from adopting AI itself than from stronger data foundations, clearer business cases, and more disciplined governance and operating models
“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. 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.”
- 53% of OEMs already implementing AI initiatives; 18% have a comprehensive cross-functional AI strategy, vision and roadmap
- 46% of OEMs already implementing AI initiatives; 16% have a comprehensive cross-functional AI strategy, vision and roadmap
- Four in ten respondents in the implementation phase; just 7% at comparable strategic maturity. Implementation maturity is lower elsewhere in Asia-Pacific
As organizations expand agentic AI across engineering workflows, confidence varies substantially depending on where the technology is applied. Executives say they are most comfortable using it 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. 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. The findings suggest many organizations have not yet established the evidence, traceability and accountability layers required to deploy it confidently at scale.
- Six in ten executives say delays are driven primarily by process inefficiencies rather than technology limitations
- 45% have yet to define a strategy and roadmap for AI in product development
- Only 30% report co-development models built around shared outcome metrics
- Just 10% have established shared lifecycle accountability across their ecosystem
- 64% say learnings from vehicles in use primarily inform future vehicle programs rather than improvements to vehicles already on the road
- Over-the-air updates remain concentrated on cybersecurity and navigation, with comparatively fewer organizations deploying updates that modify driving functions or assisted-driving capabilities
Why this matters
The findings suggest the industry's AI race is being decided less by who adopts agentic AI first than by who can govern and trust it: only 5% of the organizations surveyed report fully mature AI governance. That gap touches the engineers expected to shift from administrative tasks to core engineering work, and the OEMs, suppliers and technology partners who must share accountability across a distributed development chain.
Terms in This Story
- agentic AI
- AI systems that can act with a degree of autonomy to carry out tasks or workflows on a user's behalf, rather than only responding to single prompts.
- AI governance
- The rules, oversight and accountability structures an organization puts in place to manage how AI systems are developed, evaluated and used.
- over-the-air updates
- Software updates delivered to a vehicle remotely, without requiring a visit to a dealer or workshop.
- software-defined vehicles
- Vehicles whose features and functions are increasingly controlled by software that can be updated over time.
Summarised from the linked release; details can be imperfect — always verify against the original source.