How companies can plan for supply chain disruption and reduce risk

Kinaxis is simply a proviso concatenation specializer providing companies with an AI-infused proviso concatenation level to assistance transparency and concern planning. We asked Jonathan Jackman, VP EMEA astatine Kinaxis, astir the outlook for automotive proviso concatenation issues.

At the extremity of past year, semiconductor shortages impacting automotive companies emerged again. Will this beryllium an ongoing contented successful 2026?

Today’s semiconductor shortages are a signifier we volition spot repetition again and again successful the adjacent fewer years, arsenic request for chips grows crossed each industry, not conscionable automotive. Each question of shortages exposes however interconnected and fragile planetary proviso chains person become, and however susceptible they are to shocks specified arsenic the ongoing commercialized quality betwixt the US and China.

Do you deliberation the disruption volition get worse arsenic AI applications successful automotive expand? 

It is apt that disruption volition summation arsenic AI applications go much profoundly embedded successful vehicles and manufacturing. AI-driven functionality importantly increases the dependence connected precocious semiconductors, specialised components and analyzable proviso networks. This heightens vulnerability to bottlenecks, capableness constraints, and geopolitical risk, peculiarly if captious technologies are concentrated among a comparatively tiny fig of suppliers.

That said, AI besides plays a captious relation successful helping organisations header with volatility much effectively. In an progressively unpredictable planetary environment, AI tin supply earlier visibility of disruption, faster insights, and amended anticipation of risk, which enables much informed, agile decision-making crossed the proviso chain.

Ultimately, occurrence volition hinge connected however AI is applied. Organisations that usage AI to orchestrate an end-to-end, adaptable proviso chain, alternatively than limiting AI usage to isolated functions, volition beryllium acold amended positioned to sorb shocks, respond to change, and support resilience arsenic disruption becomes the norm.

What tin companies successful the car manufacture bash to mitigate the hazard of aboriginal proviso concatenation disruption?

The astir important measurement is moving distant from fragmented readying toward afloat integrated, end-to-end decision-making. Our caller probe with The Economist Group recovered that 71% of planetary businesses person accelerated their AI adoption, though lone 1 successful 5 tin enactment connected insights successful real-time today. That being said, script modeling enactment among car manufacturers successful November this twelvemonth was much than 3 times higher than successful November past year. This immense maturation underscores conscionable however rapidly the manufacture is scaling its concern successful real-time hazard analysis. When supply, request and accumulation plans are aligned successful adjacent real-time, companies tin respond faster and with greater assurance arsenic conditions change.