Semiconductor shortages affecting automotive companies resurfaced late last year, raising questions about their persistence into 2026. Jonathan Jackman, Vice President EMEA at supply chain specialist Kinaxis, stated that such shortages will recur repeatedly in coming years as chip demand grows across all industries.
He noted that each shortage wave reveals the interconnectedness and fragility of global supply chains, highlighting vulnerability to shocks like the ongoing US-China trade dispute.
As AI applications expand in vehicles and manufacturing, disruption is likely to increase, Jackman said. AI-driven functionality heightens dependence on advanced semiconductors, specialized components, and complex supply networks, amplifying exposure to bottlenecks, capacity constraints, and geopolitical risk, especially if critical technologies are concentrated among few suppliers.
However, AI also helps organizations cope with volatility more effectively, Jackman added. In an unpredictable global environment, AI can provide earlier visibility of disruption, faster insights, and better risk anticipation, enabling more informed, agile decision-making across supply chains.
Success will hinge on how AI is applied, he emphasized. Organizations using AI to orchestrate end-to-end, adaptable supply chains—rather than limiting it to isolated functions—will be better positioned to absorb shocks, respond to change, and maintain resilience as disruption becomes normal.
To mitigate future disruption risk, Jackman said the most important step is moving from fragmented planning to fully integrated, end-to-end decision-making. Research with The Economist Group found 71% of global businesses accelerated AI adoption, though only one in five can act on insights in real-time currently.
Scenario modeling activity among auto manufacturers in November this year was more than three times higher than in November last year, Jackman reported. This growth underscores rapid industry scaling of investment in real-time risk analysis. When supply, demand, and production plans align in near real-time, companies can respond faster and with greater confidence as conditions change, he explained.
Adaptability must be the industry’s central objective, Jackman stated. Through new AI technologies, businesses can quickly build resilience and develop pivoting ability as new challenges emerge. Orchestration will also play a key role, helping supply chain professionals move beyond constant firefighting to intentionally design “shock absorbers” into their supply chains.
In the last three months alone, scenario-modeling activity by automotive manufacturers using Kinaxis grew by nearly 500%, Jackman noted. That’s almost a sixfold increase in scenario simulations since late summer, as companies leverage ‘what-if’ planning to test responses to everything from supply shocks to demand surges. This rapid acceleration signals automotive brands are moving from reactive to true anticipation and orchestration, enabling faster, more confident responses.
Companies that thrive will not just invest in AI but use it to accelerate adaptability at scale, Jackman said. This means rethinking roles, redesigning decision-making, and building human-plus-machine operating models that anticipate disruption rather than simply react. For automotive brands, moving beyond automation toward anticipation will be critical in an increasingly volatile world.
Historically, automotive supply chain models focused on cost efficiency and scale, with low-cost supplier outsourcing and just-in-time manufacturing at their center, Jackman observed. These approaches worked when demand patterns were relatively predictable and global trade flows stable, but today’s challenges differ.
The automotive industry faces more frequent and overlapping disruption sources that aren’t going away soon—geopolitical tensions, semiconductor shortages, regulatory pressures, and the EV transition, among others, he listed. These combined forces reveal how fragile just-in-time networks are, with little room to absorb shocks.
As a result, supply chains are evolving from lean cost centers into strategic functions that must balance efficiency with adaptability, Jackman said. The priority is no longer just reducing cost but building networks that sense disruption early, respond quickly, and continue operating as conditions change.
This transformation is visible in data: in the last three months alone, automotive scenario-planning volumes on Kinaxis’s platform increased nearly sixfold, he reported. This trend highlights how companies are not only aware of new risks but actively building resilience and optionality into their networks through advanced scenario analysis and real-time orchestration.
Asked if he is optimistic the auto industry can meet supply chain challenges ahead given huge challenges from electrification, ADAS, and other advanced tech, Jackman said he is optimistic, but only for businesses willing to fundamentally rethink how they plan and operate their supply chains.
Electrification, ADAS, and software-defined vehicles add significant cost and complexity, but the industry is still under pressure to move faster and operate more efficiently, he acknowledged.
His optimism stems from many organizations already recognizing the need to change, Jackman explained. Research found 67% of British businesses are focusing on restructuring to reduce supply chain risk.
The key shift is treating the supply chain as a strategic capability rather than an afterthought, he stated. The most advanced organizations show tighter connection between product strategy, supply planning, and execution helps manage complexity at scale and move faster and more efficiently.
Those embedding advanced planning, orchestration, and adaptability into their operating models are best positioned to turn disruption into competitive advantage rather than constraint and manage challenges today and in the future, Jackman concluded.