Automotive Suppliers How Suppliers Can Best Utilize AI

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Automotive suppliers must take advantage of opportunities through artificial intelligence (AI) in the short term and realistically and long term assess the added value.

*both from Berylls by AlixPartners

The enthusiasm for artificial intelligence in the automotive industry is unbroken in the media. The management expectations for cost reduction and profit increase through AI are high—justifiably so. Among the top 100 suppliers who are most active in the media, AI is a topic in over five percent of all reporting, and at class leader Harman even in more than ten percent.

The dynamics of recent years, however, also show: In times of economic challenges, investments in the "future topic of AI" also always face risks - on the one side the risk of underestimating the importance of AI; much more serious, however, is the risk of false restraint. This article helps to successfully navigate the use of AI in the supplier industry using a few questions: What needs to be done, what should be avoided? Where is it worthwhile to set accents for a long-term successful competitive position, and where is technological innovation "simply a must"?

Among the top 100 suppliers most active in the media, AI is a topic in over 5% of overall reporting, and at the frontrunner Harman (Samsung) even in over 10%.
Source: Berylls by AlixPartners

Improve predictable tasks mechanically

Key question: What needs to be done? Our experience shows: The companies leading in the use of AI have acted quickly and have been determined to optimize business processes through AI and actively seize opportunities. The focus of these efforts is on efficiency gains "along the process" and "in the product".

"Along the process" includes optimization at all points that are suitable for machine optimization due to quantity, duration, effort or complexity. These are "predictable" tasks, such as the typically manual creation and control of specifications. However, AI can also be suitable for "unexpected" use cases, such as AI-supported reduction of electricity costs in production through leakage detection in compressed air lines. The spectrum is very broad and individually tailored prioritization of the right cost-benefit ratio is crucial for success.

AI in sales

Even though AI "in the product" is usually associated with personalization in the vehicle, it also has its justification in the individualized interaction between companies. The focus is on initially providing information for customers, for example through context-sensitive digital agents and chatbots. From a supplier's point of view, this may seem to play only a subordinate role, but it is precisely here that undiscovered opportunities may lie: The low-threshold access to product and order information through a chatbot agent can help new customers in sales and scale very efficiently—without increasing staff.

Furthermore, AI-supported sales tools can be built on existing product data with little effort and create transparency about user behavior by analyzing the inquiries made. This in turn provides a sound basis for decision-making for incremental improvement. Thus, AI investment "in the product" can also be worthwhile in the medium term for ostensibly non-digital product portfolios.

Choosing the right AI partners

Follow-up question: What should be avoided? The use of AI always comes with a discussion of risks. Concerns about secure handling of confidential and competitive data, commercial concerns about initial development costs and long-term "lock-in" effects, as well as ethics & bias play a role— because the nature of (generative) AI sometimes makes it harder to uncover result errors or unconscious prejudices and unintended behavior of an AI model. Suppliers must not let this paralyze them.

It is important to base the use of technology on the right foundation. A central cornerstone is the right mix of AI partners who—in addition to their own experts—play an important role in the implementation of AI solutions. The technology partner helps to address the risks directly. Especially in the field of digital agents, the business model of the technology partner often depends on the successful use of AI by the customer—thus, high result quality, data security and long-term use of a digital agent are in the direct interest of the partner.

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Looking at the market, it becomes apparent that this calculation works: due to the high speed of technological development, there is increasing acceptance of trying out "fast-spinning start-ups" instead of just relying on established service providers. Especially in scenarios that require a quick ROI, start-up solutions can be a good alternative.

Build expertise

Final question: Where should suppliers consciously set accents with AI? The ongoing battle for the best competitive position is not decided in a sprint with AI, but in a marathon. For this, the right talent is essential. Suppliers therefore need to not only check the relevance of AI in their own companies. Rather, it is important to expand their own abilities to evaluate, develop and scale AI solutions and create an attractive environment for AI pioneers and enthusiasts. Only when it is possible to increase the attractiveness and use of AI solutions within the company, can the hoped-for potentials for cost reduction and performance enhancement be activated.

A look at the market also allows for a confident conclusion: Our analysis shows that the suppliers who have intensively dealt with (generative) AI in the past 18 months have experienced significant growth in AI expertise— the last 100 added employees of the most AI-focused suppliers have industry knowledge from relevant companies. Particularly from the perspective of these suppliers, there should be nothing standing in the way of stressing. (kt)

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