Growing concern over reliance on foreign AI corporations, according to poll findings revealed
Artificial Intelligence Gains Traction in Germany
Germany's love affair with Artificial Intelligence (AI) is heating up, according to a recent survey by Bitkom. A staggering 67 percent of the population uses generative AI, with ChatGPT being the front-runner. Yet, concerns about the country's growing dependence on foreign AI providers have also intensified.
The survey revealed that Germany fears dependency on the US and China in the AI field. Nearly two-thirds of respondents (68 percent) expressed such concerns, with 60 percent urging Germany to reduce its reliance on US AI corporations.
While ChatGPT, Microsoft Copilot, and Google's Gemini lead the pack, other AI services like DeepSeek, Claude, Perplexity, and Grok from Elon Musk's xAI company are barely used. Lack of interest and trust are the primary reasons for this avoidance, with 77 percent of non-users stating these concerns. Nearly half (48 percent) voiced no need, while 14 percent considered the AI applications too expensive.
"Artificial Intelligence has swept across Germany like a storm, gaining rapid acceptance from the people," said Bitkom President Ralf Wintergerst. He emphasized the need to avoid new digital dependencies, suggesting the need for a sovereign German and European AI industry.
To achieve this, Wintergerst proposed setting aside at least 10 billion euros from the federal special fund over the next five years for promoting the AI sector. The survey, based on 1005 participants aged 16 and over in Germany, was conducted in March and April.
When it comes to promoting a homegrown AI industry, Germany rolled out strategies focusing on public-private collaboration, infrastructure investment, and regulatory innovation. These strategies aim to reduce the reliance on foreign AI providers while ensuring ethical AI and industrial automation.
Some key strategies include public investment and infrastructure initiatives like the "AI Gigafactory," national funding to foster research, education, and applied projects, and the integration of AI in sectors such as automotive and manufacturing.
Regulatory and ethical frameworks are also being addressed, such as balancing innovation and compliance with the EU AI Act, copyright and transparency reforms, and ensuring fair remuneration for creators and transparent AI training data usage to protect intellectual property.
The government is also working on supporting startups, expanding funding for ventures like Aleph Alpha and DeepL, and bridging academic research and industrial applications through platforms like the Smart Data Innovation Lab.
International and domestic collaboration is crucial to fill funding gaps for scaling AI firms, attract U.S. investors, and encourage cross-sector partnerships between universities, industry leaders, and policymakers.
By implementing these strategies, Germany aspires to position itself as a leader in ethical AI and industrial automation, reducing reliance on foreign providers while addressing structural challenges in startup growth and regulatory complexity.
- The Bitkom survey revealed that, while ChatGPT leads in generative AI usage among Germans, concerns about dependency on US AI providers are high, with 68% of respondents expressing such concerns.
- Bitkom President Ralf Wintergerst suggested the need for a sovereign German and European AI industry to counter these growing dependencies, proposing the allocation of at least 10 billion euros from the federal special fund over the next five years for AI sector promotion.
- In an effort to reduce dependence on foreign AI providers, Germany has launched strategies focusing on public-private collaboration, infrastructure investment, and regulatory innovation, including the "AI Gigafactory," national funding for research, education, and applied projects, and integrating AI in sectors like automotive and manufacturing.
- To further support a homegrown AI industry, the government is working on initiatives such as supporting startups, expanding funding for ventures like Aleph Alpha and DeepL, and bridging academic research and industrial applications through platforms like the Smart Data Innovation Lab, with international and domestic collaboration being crucial for filling funding gaps and encouraging cross-sector partnerships.
