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Can AI strengthen supply chains as the auto industry decarbonises?

Leveraging AI can help companies in the automotive and manufacturing industry to alleviate risk threats in their supply chains, giving them competitive advantage.

Supply chain risks are challenging the stability and resilience of organisations within the automotive industry. As this sector evolves to reach decarbonisation targets, it is crucial companies consider how artificial intelligence (AI) can be leveraged to reduce the risks associated with changing supply chains.

Transformation within the automotive industry

The global automotive industry is undergoing significant change to attain sustainability goals. Legislation from the UK Government has mandated that, by 2035, 100% of new vehicles sold in Great Britain are to be zero emission – a move similar to revised rules adopted in the EU. Additionally, in the US, new emissions standards were recently released for new automobiles.

To decarbonise the sector and reduce emissions in the coming years, manufacturers will need to produce fewer internal combustion engine (ICE) vehicles and instead focus on zero emission vehicles. To reach the mandated targets, it is expected that the main source of zero emission vehicles will be battery electric vehicles (BEVs).

The automotive industry, particularly the BEVs sub-sector, is expected to be an integral part of the future economic landscape in China, Europe, Japan, North America, and South Korea. To prepare for the potential supply chain disruption this could entail, businesses need to understand and manage risk in their end-to-end business ecosystem.

Pivoting from ICE to BEVs

Supply chain risks are not new to the automotive industry and are likely to become more strained as manufacturers slow down production of ICE components and ramp up BEV lines. Disruptions, for both ICE and BEV components alike, can occur with minimal warning – leaving little time for manufacturers to address their supply chain vulnerabilities.

The manufacturing of BEVs requires more sophisticated technology than ICE vehicles, with materials and components much more difficult to source and mass produce. Currently, the overwhelming majority of BEVs use batteries constructed from lithium, nickel, and cobalt – raw materials that can be challenging to reliably obtain. The growing adoption of zero emission vehicles and other net-zero measures has seen BEVs constitute 60% of lithium demand in 2022, up from 15% in 2017.

Major systems and components essential to ICE vehicles, are absent from BEVs. Inevitably, as BEVs become more mainstream during the decarbonisation transition, business models will change and companies unable to pivot will face disruption. Organisations may need to change supply chains and work with unfamiliar partners, potentially losing some control over business processes as they take on new risk exposures.

AI as a solution

It is crucial that organisations within the automotive industry consider all potential options that can help mitigate and alleviate threats to their supply chains. AI can be used by manufacturers to identify skill shortages, bottlenecks, logistical issues, and material costs and availabilities – making it a practical option for businesses improving supply chain resilience.

Both large and small BEVs manufacturers may have limited visibility of dependencies or exposures beyond their own facilities. Traditional approaches for managing supply chains are typically cumbersome and costly. However, AI can analyse vast volumes of data and records at a rapid pace and with a great degree of accuracy – helping it emerge in recent years as a viable solution for minimizing supply chain risks.

Embracing newer technologies can help foster a culture of more proactive risk management – helping reduce the risk of business interruption. Organisations leveraging the capabilities of AI can produce detailed maps of where their materials and components originate, for example – a typically labour-intensive task. Gaining a much deeper understanding of suppliers in supply chains, including those at tier2 or tier3 levels, enables businesses to unearth and manage risks much more effectively.

Next steps

As the automotive industry continues to change, manufacturing companies − operating in an industry with high supply chain risk exposures − must prioritise stability and resilience. Marsh McLennan has recently released Sentrisk, an AI-powered platform that harnesses data capabilities to illuminate supply chain risk exposures and reveal potential opportunities – helping businesses prioritise their most pressing issues.

In a complex world, supply chain resilience can be a competitive advantage. For further information on Sentrisk and other support available to mitigate supply chain risks in the automotive industry, please contact your Marsh adviser.

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Can AI strengthen supply chains as the auto industry decarbonises?