Modest AI Implementation Progress in the Automotive Sector: Capgemini Research

A new study from the Capgemini Research Institute has found that just 10% of major automotive companies are implementing artificial intelligence (AI) projects at scale, with many falling short of an opportunity that could increase operating profit by up to 16%. The research also shows that fewer automotive companies are implementing AI than was the case in 2017, despite the cost, quality and productivity advantages, many report it delivering.

The “Accelerating Automotive’s AI Transformation: How driving AI enterprise-wide can turbo-charge organizational value” study surveyed 500 executives from large automotive companies in eight countries, building on a comparable study from 2017, to establish recent trends in AI investment and deployment. The research highlighted the following potential reasons for the modest progress in relation to AI implementation.

The roadblocks to technology transformation are still significant, such as legacy IT systems, accuracy and data concerns, and lack of skills.

The hype and high expectations that initially came with AI may have turned into a more measured and pragmatic view as companies are confronted with the reality of implementation.

Markus Winkler, Executive Vice President, Global Head of Automotive at Capgemini concludes, “These findings show that the progress of AI in the automotive industry has hit a speedbump. Some companies are enjoying considerable success, but others have struggled to focus on the most effective use cases, vehicle manufacturers need to start seeing AI not as a standalone opportunity, but as a strategic capability required to shape the future which they must organize investment, talent and governance around.”

He continues, “As this research shows, AI can deliver a significant dividend for every automotive business, but only if it is implemented at scale. For AI to succeed, organizations will need to invest in the right skills, achieve the requisite quality of data, and have a management structure that provides both direction and executive support.”

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