Germany demonstrated vision and leadership by being one of the first countries to establish a national strategy for artificial intelligence (AI) in 2018. Since then, the Federal Government has steered AI development to strengthen both national and European competitiveness in AI, prioritising human-centred AI for the benefits of workers and society.
Six years later, the geopolitical and economic context has changed drastically. Challenges include supply chain disruptions due to the COVID-19 pandemic and an energy crisis triggered by Russia’s war of aggression against Ukraine, which has fuelled inflation and threatened German firms’ competitiveness. Domestically, demographic shifts have resulted in healthcare costs and exacerbated labour shortages.
At the same time, the AI landscape has been evolving very rapidly. The rise of general-purpose AI systems took the world by storm in late 2022 due to their significant potential to transform entire industries and boost productivity. These promises ignited an international “AI race”, with countries competing to secure economic and political advantages and assert leadership in the technology and its applications. Rapid advancements also heightened concerns about AI development, deployment, and governance.
As Germany grapples with establishing a “new era” (Zeitenwende) of economic and political trajectory, AI should be considered an important lever for preserving its international position as an economic powerhouse. Tackling persistent challenges and unlocking AI’s full potential across sectors requires a strategic shift.
Initiatives implemented as part of the national AI strategy laid the foundation for Germany to emerge as a global leader in AI research. Germany has made significant strides in impactful AI research, with both public and private institutions featuring among global leaders in AI research publications.
Germany’s efforts to attract skilled AI professionals have also been successful, but more needs to be done to broaden the AI talent pool and to prepare the workforce. Stronger participation of women in AI research and leadership is crucial to expand the talent pool, and to narrow the gender gap. Preparing the workforce for the AI era also requires more AI programmes at German universities. Furthermore, proactive measures such as conducting in-depth skill anticipation on AI, promoting lifelong training opportunities and incentivising companies to provide on-the-job training on AI will be essential.
AI can improve physical safety, enjoyment at work and productivity. However, it also carries risks, including concerns about automation, data privacy, bias, accountability, transparency and increased work intensity. Social dialogue and training are vital for a trustworthy use of AI in the workplace. Involving workers in the adoption of AI tools can improve working conditions and performance. Yet, social partners face expertise and resource limitation. As seen in Germany’s Works Council Modernization Act, training and expert consulting are instrumental for informed decision making on AI in workplaces.
Infrastructure for AI is critical to AI advances and is expected to continue to be a driver of AI capabilities over time. While Germany has solid AI compute capacity, particularly in the research sector, a comprehensive assessment of its capacities and needs can identify gaps and help guide future investments.
Data are needed for AI applications but remain a significant bottleneck due to uncertainty about personal data protection and limited availability of industrial and open government data. Data quality and availability to train AI could be increased by requiring government agencies to publish non-sensitive data in open formats, reinforcing frameworks for responsible sharing of industry-specific data, and by providing regulatory guidance on using personal data.
German firms increasingly use and are interested in AI solutions, possibly due to developments in generative AI and to labour shortages. Sustaining this momentum requires targeted financial support to help enterprises understand business cases and strengthen key complementary assets, namely skills, digital infrastructure, and broader digitalisation. Start-ups are developing and bringing to the market innovative AI solutions. To fuel AI development, Germany should more actively nurture its AI entrepreneurial ecosystem and support start-up growth.
AI can enhance the public sector’s efficiency and decision making and improve public services. Germany is seizing this opportunity in various government levels, but initiatives are often standalone, and the low level of digitalisation in the public sector limits the potential for AI use. Improving co-ordination, clarifying responsibilities, upskilling civil servants, and updating the roadmap for public sector initiatives could accelerate the transition towards a more innovative and agile public sector.
Germany is taking action to build a robust policy and legal foundation for AI’s use in healthcare. AI can accelerate diagnostics and drug discovery, freeing time for health professionals to focus on patient care. However, developing and scaling AI healthcare applications faces challenges related to data access and interoperability, securing stakeholder buy-in, and human and AI compute capacity. Updated guidance on practices could help to create value from secondary use of data, with strong measures to protect citizens’ rights including privacy.
Germany is poised to be a global leader in AI and environmental sustainability, given its well-funded initiatives, world-leading researchers, and innovative companies. AI can help accelerate decarbonisation in energy, transport, industry, and agriculture. Yet strengthening Germany’s leadership position requires inter-ministerial and interdisciplinary co-operation, knowledge-sharing and widening the focus of what constitutes sustainability beyond energy and resource efficiency, while measuring and mitigating the negative environmental impacts of developing and using AI itself.
German public perception of AI is fairly positive among the general population, specialised users and workers. However, vigilance is needed in the face of rapidly evolving societal risks, including threats to human rights and democratic values. Germany could also involve a broader set of stakeholders in AI policy discussions, and regularly monitor public perceptions to understand how citizens’ views evolve as AI increasingly becomes part of everyday life.
Germany should adjust its national AI strategy’s vision and approach to navigate today’s new realities effectively. Germany should leverage AI to meet its most pressing challenges, including the green transition, administrative and industrial efficiency, and healthcare quality. This requires strategic vision and co-ordination at the highest political level, alongside a solid technology, data and infrastructure foundation, a skilled workforce to diffuse AI across sectors, and societal trust.