Capgemini’s latest report reveals that nearly seven in ten automakers are already deploying or testing agentic AI across product development. For the everyday buyer, that means the next generation of cars could arrive on the lot faster, with more polished features and potentially lower price tags as development cycles shrink.
Out of those, 33% are actively using the technology while another 35% are still in pilot mode. The gap suggests that while the industry is enthusiastic, many firms are still ironing out how to weave AI into the core of engineering workflows.
High‑value adopters report a 17% reduction in development time, a 19% lift in engineering productivity and a 19% cut in time‑to‑market. In plain terms, the cars you’ll see on the showroom floor could get there a few months earlier, and the parts that go into them may be cheaper to produce.
Only 5% of firms say they have mature AI governance. That lack of clear oversight raises safety and reliability questions, especially for features that directly influence driving behaviour. Buyers should be mindful of the maturity of the AI stack behind the car’s software.
Even though connected vehicles churn out massive amounts of data, 64% of respondents say they use that data mainly to inform future programmes, not to tweak the cars already on the road. OTA updates tend to stay locked to cybersecurity and navigation, leaving in‑vehicle driving‑assist features largely static.
Process bottlenecks dominate the slowdown: six in ten executives cite inefficiencies rather than tech limits. Coupled with low collaboration across OEMs, Tier‑1s and tech partners, this can keep prices high and limit the pace of new feature roll‑outs.
The study was conducted in July 2026, with industry insiders expecting wider AI adoption to reach a tipping point by 2028. By that time, consumers could start seeing more AI‑driven cars on the road, but the pace will depend on how quickly firms build governance, collaborate and use vehicle data for real‑time improvements.