Take supply chain resilience and efficiency to the next level with agentic AI

Any inefficiencies, delays, or risks affect a business in real time, and therefore real-time responses to changing business conditions are essential.

Agentic AI makes these real-time responses achievable – one reason why its adoption within supply chains is accelerating rapidly. For automotive companies facing today’s disruptions and uncertainties, agentic AI could therefore be a gamechanger.

Current uncertainty around tariffs is just the latest contributor to today’s high levels of supply chain disruption, described in earlier blog posts like this one. As we reasoned then, AI has a major part to play in helping automotive companies deal with successive waves of disruption. The example given was that by reinforcing forecasting and planning capabilities with AI, companies can respond much more effectively to disruption.

This blog post will look specifically at how agentic AI can enable real-time responsiveness in the automotive supply chain, and thereby build resilience. It follows on from a recent Capgemini article about the value of agentic AI for supply chains in general.

How AI agents can help companies build automotive supply chain resilience

An important application of agentic AI within the supply chain is the use of agents to make persona-based recommendations. The “persona” in this instance could be the COO, CFO, CSCO, or CPO, or a member of their teams.

An AI agent can monitor conditions in a given area against preset business goals. When exceptions arise or thresholds are crossed, the agent can automatically recommend a course of action suited to the persona in question. Areas to be monitored might include:

• The accuracy of supply chain forecasts. The AI agent can assess the risk of forecasting errors occurring and predict their impact on inventory and service levels. Then it can recommend corrective action to the COO’s team, and even, if required, execute the selected actions itself.
• Quality risks and delivery risks associated with incoming parts. “Right first time” is key to automotive quality. The quality of parts received from suppliers, and the reliability of delivery, directly affect the quality of finished vehicles. Agentic AI can assess a part’s quality and delivery risks by analyzing vast sets of historic and real-time data. After comparing the results with the company’s risk thresholds, the AI agent can recommend ways for the CSCO’s team to mitigate unacceptable risks.
• The financial impact of specific supply chain disruptions. The AI agent can compare the impact of different disruptions to help the CPO’s team prioritize possible investments in resilience.
• The drivers of supply chain costs. The AI agent can recommend which drivers could be targeted for cost reduction, freeing up more funds for the CSCO’s team to invest in resilience-boosting measures.

In addition to the persona-based recommendations, agentic AI can further increase resilience if it is used in a coordinating role that transcends all these functions. Drawing data from internal functions and directly from the supplier ecosystem, an AI agent can monitor the entire supply chain, flag up risks, and coordinate the responses of every part of the organization. It can then proactively suggest adjustments to planned actions, internal and external, based on the results.

The potential impact of agentic AI on the automotive supply chain is sizeable and diverse, with research indicating that significant reductions in logistics spend, for example, are achievable. As adoption proceeds, even more business benefits are likely to emerge, and they will become easier to quantify.

AI agents are already in use

Although the concept of agentic AI is relatively new, companies are already embracing it. A recent Capgemini Research Institute report on agentic AI shows that 14% of organizations have implemented AI agents at partial (12%) or full scale (2%). Nearly a quarter (23%) have launched pilots, while another 61% are preparing for or exploring deployment.

Looking now at some functional areas closely linked to the supply chain, 39% of respondents from Operations expect AI to manage at least one process or sub-process daily within the next 12 months, and a total of 75% believe this will be the case within three years. For Finance, the corresponding figures are 30% and 63%.

Despite significant misgivings, including ethical concerns around AI, a sizable 38% of respondents expect AI agents to be functioning as members of human-supervised teams within the next three years.

How automakers can integrate AI into supply chain solutions

The CRI report on agentic AI makes a number of practical recommendations to help companies harness the full power of AI agents. Ensuring smooth collaboration between humans and AI agents is of fundamental importance, and depends on trust; the recommendations therefore center on the need to build trust in AI. Specific recommendations range from addressing ethical issues to overhauling processes, business models, and organizational structures to accommodate joint human-AI teams.

When agentic AI is deployed in the automotive supply chain, an additional dimension of trust needs to be considered. The all-important trust between supplier and OEM could be jeopardized by the introduction of AI agents without supplier acceptance. Therefore, companies should communicate with their suppliers up front about the intended use of AI, addressing any concerns raised. This openness is especially important if AI agents will interact directly with suppliers – for example to reroute transportation in response to a disruption.

Prewave and our commitment to revolutionizing supply chain risk management

Capgemini believes that agentic AI, and AI in general, is pivotal to making the automotive supply chain into a source of competitive advantage.

We’re helping our clients realize that advantage in a variety of ways. One is that we’ve joined forces with Prewave, a leading AI-driven supply chain risk intelligence platform that leverages cutting-edge AI technology to monitor and predict supply chain disruptions.

By combining Capgemini’s expertise in digital transformation with Prewave’s innovative solutions, we deliver end-to-end enhancements in supply chain transparency, compliance, and resilience.

Let’s talk agentic AI and supply chain at IAA Mobility 2025

Capgemini will be at IAA Mobility 2025. Our team will be ready to discuss any of the issues raised in this article, as well as other aspects of the automotive supply chain.

In addition, Capgemini and Prewave will be demonstrating an agentic AI solution that uses data to build a resilient supply chain – one that responds to change in real time, and even proactively.

Please find details of Capgemini’s IAA Mobility activities here. And if you’re coming, do remember to register.