German companies are focusing on niche software solutions, particularly in industry, where AI enhances productivity. SAP’s CEO, Christian Klein, highlights the country’s AI expertise but warns that bureaucratic hurdles and inconsistent regulations stifle innovation. The US outpaces Germany in AI investment, prompting concerns about risk aversion and talent migration. Collaboration among companies is essential for growth, as seen in SAP’s AI system development. Experts advocate for leveraging Germany’s engineering strengths to better integrate AI into various sectors.
What is the Optimal Strategy for Competing in the Global Artificial Intelligence Landscape?
German enterprises are concentrating on developing highly specialized software solutions, particularly in industrial sectors. Despite the fact that human workers assemble products, artificial intelligence (AI) can enhance their efficiency and accuracy. For instance, SAP, a software giant based in Walldorf, has introduced a system that guides assembly workers through workflows while leveraging camera technology to ensure compliance with processes and product quality.
Christian Klein, CEO of SAP, emphasizes that Germany possesses significant AI expertise. However, he notes that excessive bureaucracy and rigid regulations surrounding data access hinder innovation. “While data protection is crucial, it shouldn’t overshadow our ability to innovate,” he cautions. Klein argues that the focus should not always be on potential pitfalls. Furthermore, he highlights the inconsistency of regulations across Europe, calling for urgent political reform to enhance Germany’s and Europe’s competitive stance on the global stage.
Although SAP reports robust performance, challenges remain.
Overcoming ‘General Risk Aversion’
Can Germany still succeed in this competitive arena? In 2023, the AI sector in the United States attracted a staggering $70 billion from private investors, while Germany managed to secure only about €2 billion. “There is a pervasive risk aversion here,” asserts Jonas Andrulis, founder of the Heidelberg-based AI firm Aleph Alpha.
A few years prior, Aleph Alpha was among the pioneers with its self-developed AI language model. “We’ve always had exceptional research capabilities here,” Andrulis states. He notes that the modern AI revolution has its roots in Europe. “However, we face challenges in generating value from AI and other new advancements,” he observes, lamenting the brain drain as talented professionals trained in Europe migrate to the US.
Currently, Aleph Alpha has shifted its focus away from the ambition to outpace the US in developing the premier AI language model. “Our clients don’t require another model that can merely compose a poem for grandma’s birthday,” Andrulis explains. Instead, the firm is utilizing existing AI technologies to create specialized software, such as intelligent document management systems.
Recently, Aleph Alpha secured an additional $500 million in its second round of funding.
The David vs. Goliath Challenge
The struggle against international tech behemoths feels like a classic David versus Goliath tale for Germany, according to Katharina Hölzle from the Fraunhofer Institute for Industrial Engineering and Organization in Stuttgart. “But we know that David can defeat Goliath,” she quips, “through clever tactics and the right tools.”
Germany’s economic strength lies in its leadership in fields like mechanical engineering, precision engineering, and electrical engineering. “We must integrate this expertise with AI capabilities to achieve success,” she asserts.
Despite a wealth of impactful research, the application of such innovations remains a challenge. “There are initial efforts that have yet to gain traction,” Hölzle remarks. “We need to pinpoint the specific challenges in our industry that require AI solutions.”
As federal elections approach, misinformation is spreading with the intent to influence public opinion.
Is Collaboration the Key to Success?
Hölzle believes that enhanced collaboration among companies could fortify the domestic AI sector. Currently, there exists a significant reluctance to share data, and a culture of collaboration is still underdeveloped. “The mindset that if we collaborate, we can expand the pie, leading to larger portions for everyone—this needs to be cultivated,” she emphasizes.
SAP’s AI assistance system serves as a positive example of this collaborative spirit, having been developed in partnership with other firms. However, it remains a prototype and has yet to be implemented in any production facility.
This article was initially reported by tagesschau on January 22, 2025, at 8:00 PM.