Europe has a strong opportunity to lead in industrial AI, according to Thomas Saueressig, a board member at German software giant SAP. He emphasized that the continent’s expertise in industrial processes, access to sector-specific data, and technical know-how give it a competitive edge, even as Europe lags behind the United States and China in large-scale AI development. Unlike general-purpose large language models, industrial AI focuses on targeted, smaller-scale applications—such as optimizing manufacturing workflows, designing electrical systems, or improving construction planning—where European companies can differentiate themselves.
Saueressig highlighted that Europe does not need to compete solely on massive AI models but can excel with specialized models tailored to industrial tasks. Examples of this approach are already emerging: German automaker BMW is piloting AI-powered humanoid robots in factories, aiming for autonomous decision-making in production. Similarly, Deutsche Telekom and Nvidia launched an industrial AI hub to help European firms adopt AI in design, robotics, and automation, emphasizing a “sovereign AI platform” to reduce dependence on U.S. and Chinese technology.
SAP has seen growing demand for solutions that ensure “digital sovereignty,” though Saueressig cautioned that some concerns about reliance on U.S. tech are exaggerated. Despite challenges—such as lower data center capacity, competition from China, and limited start-up funding—experts like Antonio Krueger of the German Research Centre for Artificial Intelligence stress that the AI race is still in its early stages, and Europe can still build globally competitive industrial AI solutions.
In short, Europe’s strategy centers on leveraging deep industrial knowledge and domain-specific data to carve out a leadership position in AI applications for manufacturing, design, and other sector-specific tasks, rather than competing head-on with U.S. and Chinese tech giants on general-purpose AI.
