Germany was among the first countries to recognise the transformative potential of artificial intelligence (AI). In 2018, it demonstrated early vision and leadership by launching a national AI strategy aimed at strengthening both German and European competitiveness, while firmly anchoring AI development in a human-centred approach that prioritised workers’ rights and societal benefit. This early move positioned Germany as a serious global player in AI research and governance.

Six years later, however, the context in which this strategy operates has changed profoundly. The COVID-19 pandemic disrupted global supply chains, while Russia’s war of aggression against Ukraine triggered an energy crisis that fuelled inflation and threatened the competitiveness of German firms. At the same time, demographic change has intensified labour shortages and driven up healthcare costs. Against this backdrop, AI has evolved at breathtaking speed, particularly since late 2022, when general-purpose and generative AI systems began reshaping entire industries. Their rapid diffusion sparked an international “AI race”, intensifying both economic competition and concerns about governance, safety, and societal impact.

As Germany navigates this broader challenge in its economic and political trajectory, AI has become an increasingly important lever for maintaining its position as an industrial and innovation powerhouse. Initiatives under the national AI strategy have already laid strong foundations. Germany is now among the global leaders in AI research output, with both public research institutions and private actors producing high-impact publications. The country has also succeeded in attracting skilled AI professionals, though expanding and diversifying this talent pool remains a pressing task.

A key challenge lies in workforce readiness. While AI promises gains in productivity, physical safety, and job satisfaction, it also raises concerns about automation, bias, transparency, accountability, and work intensification. Preparing workers for the AI era requires far more than technological deployment. Germany needs more AI-related programmes at universities, stronger lifelong learning opportunities, and incentives for companies to offer structured on-the-job training. Increasing the participation of women in AI research and leadership is particularly crucial to closing the gender gap and addressing talent shortages.

Infrastructure and data access are further bottlenecks. Germany has solid AI compute capacity, especially in research, but a systematic assessment of future needs would help guide strategic investment. Data availability remains one of the biggest constraints on AI adoption. Uncertainty around personal data protection, limited access to industrial data, and underused open government data hinder progress. Clearer regulatory guidance, stronger frameworks for responsible data sharing, and requirements for public authorities to publish non-sensitive data in open formats could significantly unlock AI’s potential.

German companies are increasingly adopting AI solutions, driven in part by labour shortages and advances in generative AI. However, sustaining this momentum requires targeted financial support, clearer business cases, and stronger complementary assets such as digital infrastructure and skills. Start-ups are playing a vital role in bringing innovative AI applications to market, but Germany’s AI entrepreneurial ecosystem still needs more active nurturing to support scaling and long-term growth.

The public sector also stands to benefit. AI can enhance efficiency, improve decision-making, and modernise public services. Yet progress is uneven. Many initiatives remain isolated, and low levels of digitalisation limit the impact of AI deployment. Better co-ordination across government levels, clearer responsibilities, upskilling of civil servants, and an updated public-sector AI roadmap could accelerate transformation.

Healthcare and environmental sustainability represent two areas where Germany could emerge as a global leader. AI can speed up diagnostics, drug discovery, and decarbonisation across energy, transport, industry, and agriculture. Still, challenges around data interoperability, compute capacity, and stakeholder buy-in persist. Strong safeguards for privacy and citizens’ rights, combined with interdisciplinary and inter-ministerial co-operation, will be essential to scaling impact responsibly.

Public perception adds another layer of complexity. While AI use is widespread (66% of Germans already use AI privately, professionally, or in their studies) trust remains low. Only 32% say they trust AI-generated information, placing Germany below the international average. AI literacy is also lagging with just 20% of Germans who have received AI training, and many use AI tools without critically assessing outputs. This gap between usage and understanding fuels scepticism and risky practices, particularly in workplaces where clear guidelines are often missing.

Ultimately, Germany stands at a crossroads. It is well positioned to be a global AI leader, but doing so requires updating the national AI strategy to reflect today’s realities. Leveraging AI to address pressing challenges (from green transition and administrative efficiency to healthcare quality) demands strategic vision at the highest political level, robust data and infrastructure foundations, a skilled and inclusive workforce, and, above all, societal trust.

References

KPMG. (2025, May 12). Between everyday life and concern: two thirds of Germans use AI – but only a few trust the technology. Retrieved from KPMG: https://kpmg.com/de/en/home/media/press-releases/2025/05/Between%20everyday%20life%20and%20concern:%20two%20thirds%20of%20Germans%20use%20AI%20-%20but%20only%20a%20few%20trust%20the%20technology.html

OECD. (2024). OECD Artificial Intelligence Review of Germany. Paris: OECD Publishing; https://doi.org/10.1787/609808d6-en.

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