Kinaxis is a supply chain specialist providing companies with an AI-infused supply chain platform to aid transparency and business planning. We asked Jonathan Jackman, VP EMEA at Kinaxis, about the outlook for automotive supply chain issues.
At the end of last year, semiconductor shortages impacting automotive companies emerged again. Will this be an ongoing issue in 2026?
Today’s semiconductor shortages are a pattern we will see repeat again and again in the next few years, as demand for chips grows across every industry, not just automotive. Each wave of shortages exposes how interconnected and fragile global supply chains have become, and how vulnerable they are to shocks such as the ongoing trade dispute between the US and China.
Jonathan Jackman
**Do you think the disruption will get worse as AI applications in automotive expand? **
It is likely that disruption will increase as AI applications become more deeply embedded in vehicles and manufacturing. AI-driven functionality significantly increases the dependence on advanced semiconductors, specialised components and complex supply networks. This heightens exposure to bottlenecks, capacity constraints, and geopolitical risk, particularly if critical technologies are concentrated among a relatively small number of suppliers.
That said, AI also plays a critical role in helping organisations cope with volatility more effectively. In an increasingly unpredictable global environment, AI can provide earlier visibility of disruption, faster insights, and better anticipation of risk, which enables more informed, agile decision-making across the supply chain.
Ultimately, success will hinge on how AI is applied. Organisations that use AI to orchestrate an end-to-end, adaptable supply chain, rather than limiting AI use to isolated functions, will be far better positioned to absorb shocks, respond to change, and maintain resilience as disruption becomes the norm.
What can companies in the auto industry do to mitigate the risk of future supply chain disruption?
The most important step is moving away from fragmented planning toward fully integrated, end-to-end decision-making. Our recent research with The Economist Group found that 71% of global businesses have accelerated their AI adoption, though only one in five can act on insights in real-time today. That being said, scenario modeling activity among auto manufacturers in November this year was more than three times higher than in November last year. This immense growth underscores just how rapidly the industry is scaling its investment in real-time risk analysis. When supply, demand and production plans are aligned in near real-time, companies can respond faster and with greater confidence as conditions change.