The automotive sector is still at an early stage when it comes to adopting Artificial Intelligence (AI). Yet it is uniquely positioned to benefit from AI-driven step changes in efficiency and performance. Given the sector's extensive data pools, AI is the next logical lever for creating advantage in a highly cost-competitive industry. We therefore expect to see it in widespread use by the end of the next decade right across automotive players' functional units – from R&D and production to sales and aftersales. The new technology will contribute to higher efficiency, better quality and improved performance for companies, at the same time as mitigating risk. The result? A fundamental change in the way automotive players' functions are structured.
One of the four PACE megatrends highlighted in the Roland Berger Automotive Outlook 2040 is automation. Automation is transforming the automotive industry and its supply chains, particularly with the widespread application of AI right across the entire vehicle value chain.
AI has unique potential to increase efficiency and improve the performance of the industry – for a number of reasons. For many years, automotive players have been trying to reduce costs using traditional levers. The potential of these traditional methods is now largely used up, making AI the next logical option for boosting profits. AI can also help address the complexity of the industry, with its global supply chains, different vehicle configurations, various technologically complex components, tight safety requirements and so on. In addition, automotive players have an extensive data pool available that they can use to train AI models, including both functional data and end customer data.
With that in mind, we believe that all players will be applying AI in all their functional units by 2040. In R&D (research and development), for instance, the entire R&D process may be driven by AI models, with humans focusing on monitoring output quality – leading to efficiency improvements of 30 to 50 percent in an optimistic scenario. In sales and marketing, new AI-driven solutions will enable hyper-individualized marketing strategies, reduced time to market, increased revenue potential and customer behavior-based sales models. In aftersales, AI can improve customer experience through predictive maintenance and remote diagnostics, while boosting companies' financial performance thanks to real-time inventory management, demand forecasting and optimized fleet management.
For automotive players to fully benefit from AI, they need good access to data, effective approaches to training their AI models and the ability to effectively use the insights that AI generates. Master these three areas and they can translate AI into competitive advantage. However, we do not expect to see all players progressing at the same speed or benefiting to the same extent. This is due to differences in regulatory environments, combined with players' varying levels of access to the capital required for investing in AI, the skills and talent needed to exploit it and the data necessary for training it – all of which are impacted by structural factors such as the company's location, size and position in the value chain.
On the basis of our detailed research, we make a number of recommendations for how companies can maximize the benefit they derive from new, AI-driven technology and ensure that they stay ahead of the pack. For example, they should first assess the potential impact of AI on their organization and launch quick-win pilot projects in the most promising functions. They must integrate their AI initiatives into a broader corporate transformation plan, gradually rolling out the technology across different functions. To ensure a first-mover advantage, we recommend identifying strategic partners early on and drawing extensively on their expertise. At the same time, savvy players will remain aware of the limitations of Artificial Intelligence and exercise careful quality control over the output it generates.
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