Progress in Implementing the European Union Coordinated Plan on Artificial Intelligence (Volume 1): Germany

Table of contents

• Set enabling conditions for AI development and uptake in the European Union
• Make the European Union the right place: Excellence from lab to the market
• Ensure AI technologies work for people
• Build strategic leadership in priority sectors

The European Union (EU) Coordinated Plan on Artificial Intelligence (AI) is a strategic initiative by the European Commission and EU Member States to promote AI development, investment and co-operation. In 2024, the OECD conducted a survey and interviews to take stock of implementation progress made by the EU Member States in implementing the actions set in the EU Coordinated Plan on AI. Drawing on the information collected, the OECD prepared country notes for each EU Member State. This document presents the country note for Germany, which summarises key initiatives and implementation progress.

Key messages

• Human-centred artificial Intelligence (AI) governance with continuous improvement: Germany was among the first countries worldwide to launch a national AI strategy in 2018. With a comprehensive update in 2020 and ongoing evaluations, including an OECD analysis, Germany demonstrates a strong commitment to continuously refining its strategy to address emerging challenges and opportunities.

• Investments in AI infrastructure: Germany is investing significantly in digital infrastructure and high-performance computing (HPC) capabilities. These efforts include initiatives to enhance computational resources for research institutions and businesses, focusing on energy efficiency and secure operations.

• Focus on data governance and interoperability: Germany has implemented initiatives to standardise cloud solutions, facilitate decentralised data-sharing platforms and strengthen data management frameworks.

• Driving excellence in AI research: Germany’s AI research ecosystem is powered by centres of excellence, strategic funding and programmes supporting small and medium-sized enterprises (SMEs) and academia. These initiatives are targeted at enabling cutting-edge research, fostering industry collaboration and strengthening AI innovation.

• Accelerating commercialisation and adoption of AI across industries, with a strong focus on SMEs: By showcasing concrete use cases and providing tailored support, Germany supports bridging the gap between scientific expertise and business applications to empower companies to innovate and enhance competitiveness.

• Support for AI talent development: Germany prioritises AI education and workforce development through funding schemes, university AI professorships and training programmes. These initiatives aim to expand the AI talent pool and ensure a skilled workforce for its growing AI ecosystem.

• Commitment to climate and societal benefits: Germany is harnessing AI to address societal challenges, with dedicated funding for projects that target climate action and sustainable development. These initiatives underscore the country’s commitment to integrating AI into its broader sustainability goals.

• Advancing AI in public administration: Germany is transforming public administration through several initiatives which promote ethical AI usage and collaboration across government agencies. These efforts should enable innovative applications, such as large language models (LLMs), to enhance administrative efficiency and public services.

Set enabling conditions for AI development and uptake in the European Union

Acquire, pool and share policy insights

In 2018, Germany was one of the world’s first countries to release a national AI strategy (German Federal Government, 2020[1]). This strategy was updated in December 2020 to address new challenges, particularly those brought forward by the Coronavirus disease 2019 (COVID-19) pandemic and increasing emphasis on environmental sustainability and climate protection. Germany’s three main objectives for AI are: i) securing the country’s future competitiveness and establishing Germany and the European Union as leading hubs for AI development and application; ii) ensuring responsible AI development with a focus on the common good; and iii) embedding AI in society ethically, legally, culturally and institutionally through extensive public engagement and policy initiatives. Furthermore, the strategy focuses government efforts on five key areas: i) fostering AI talent; ii) advancing research; iii) supporting AI transfer and applications; iv) building a robust regulatory framework; and v) integrating AI within society. To address pressing societal issues, the strategy also includes new initiatives centred on sustainability, environmental and climate protection, healthcare, pandemic control and European Union (EU) and international collaboration.

Initially, the strategy was allocated a budget of EUR 3 billion through 2025, later supplemented by an additional EUR 2 billion in June 2020 under the Economic Stimulus and Future Package (German Federal Government, 2020[2]). EUR 3.5 billion have been distributed among the federal ministries, though details on the allocation across areas or ministries are not explicitly provided. By June 2024, EUR 3.38 billion had been directed towards specific projects supporting implementation.

Three federal ministries jointly oversee the development and implementation of Germany’s AI strategy: the Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung, BMBF), the Federal Ministry for Economic Affairs and Climate Action (Bundesministerium für Wirtschaft und Klimaschutz, BMWK) and the Federal Ministry of Labour and Social Affairs (Bundesministerium für Arbeit und Soziales, BMAS). These ministries maintain regular co‑ordination and collaboration with other relevant ministries. Furthermore, the federal government and the federal state governments engage in consistent dialogue on the national AI strategy, aligning it with respective regional strategies.

While the strategy highlights multiple measures under each of its core areas, it lacks a detailed implementation roadmap, including concrete steps, timelines and with limited exceptions, specific targets or indicators to track progress. However, each ministry remains accountable for monitoring the actions under its responsibility. Additionally, in 2023-24, the three lead ministries conducted an evaluation of the national AI strategy, inviting the OECD to assist through an international benchmarking of Germany’s AI landscape (OECD, 2024[3]).

Regional AI networks play a critical role in fostering AI innovation and collaboration across regions. For instance, the Bavarian AI Council, comprised of 21 leading AI experts from science and industry, advises the Bavarian State Government on AI initiatives and promotes “AI Made in Bavaria” as a seal of approval for the quality of Bavarian AI research internationally (BAIOSPHERE, 2024[4]). Similarly, the Hessian Center for Artificial Intelligence, a network of 13 universities in Hesse, focuses on conducting high-quality research with practical relevance and supports technology transfer to industry and society (hessian.AI, 2024[5]).

Tap into the potential of data and foster critical computing capacity

Germany is enhancing its digital infrastructure through comprehensive strategies focused on data management, digital sovereignty and interoperability. Key efforts include establishing a unified framework for responsible and efficient data use, standardising cloud solutions for public administration to ensure secure and seamless operations, and promoting decentralised data-sharing platforms to strengthen EU digital autonomy. Additionally, Germany supports advancements in HPC, emphasising both computational power and energy efficiency.

Table 1. Set enabling conditions for AI development and uptake in the European Union: Key initiatives

Name	Start year*	Short description (main goals)	Funding (including EU funding use)
Administrative Cloud Strategy (DVS)	2020	The DVS is part of Germany’s efforts to enhance digital sovereignty in public administration by establishing a standardised, modular federal cloud infrastructure. The strategy aims to enable interoperability across federal, state and local government levels by creating open standards and interfaces. It seeks to reduce dependence on single providers by fostering a diverse ecosystem of specialised information technology (IT) service providers. The DVS focuses on five key areas: i) standardised development platforms; ii) application management; iii) code repository systems; iv) infrastructure services; and iv) a harmonised operational model. These measures collectively aim to make federal cloud solutions interoperable and compatible across all levels of government, thereby enhancing the efficiency and resilience of Germany’s public sector IT systems (IT-Planungsrat, 2020[6]).	Not reported
Framework Programme for Research and Innovation 2021‑2024 “Microelectronics. Trustworthy and Sustainable. For Germany und Europe”	2021	Running from 2021 to 2024, this German Federal Government framework programme focuses on promoting research and innovation in microelectronics with a commitment to trustworthiness, sustainability and technological sovereignty. It emphasises the development of secure and reliable microelectronic components, aiming to reduce EU dependence on non-EU technologies. The programme also advocates for environmentally friendly manufacturing processes within the microelectronics sector. By fostering advancements in microelectronics, it seeks to strengthen Germany’s and the European Union’s technological foundations, ensuring that the continent remains competitive in critical technology areas (BMBF, 2021[7]).	EUR 400 million (plus significant budget from the German economic stimulus package)
Gaia-X	2019	Gaia-X was announced in October 2019 as a collaborative effort led by France and Germany to create a secure, federated data infrastructure for the European Union. Its goal is to facilitate decentralised data exchange across businesses and research institutions, ensuring interoperability and data sovereignty. Gaia-X is designed to support a wide range of industries, enabling participants to share data and access services on a large scale while retaining control over their data (Gaia-X, 2024[8]).	EUR 117 million
Gauss Centre for Supercomputing (GCS)	2017	The GCS is a collaboration between Germany’s three leading national supercomputing centres: High-Performance Computing Center Stuttgart (Höchstleistungsrechenzentrum Stuttgart, HLRS), Jülich Supercomputing Centre (JSC) and Leibniz Supercomputing Centre (Leibniz-Rechenzentrum, LRZ) in Garching. The GCS provides Germany with HPC resources, supporting a wide range of scientific research and industrial applications. It is instrumental in advancing Germany’s capabilities in computational science and engineering, addressing challenges across diverse fields, from climate research to medicine. It is jointly funded by the German Federal Government and the respective host federal states, providing essential infrastructure for both national and international research collaborations (GCS, 2024[9]).	EUR 1.17 million
High- and Highest-Performance-Computing for the Digital Age (Hoch‑ und Höchstleistungsrechnen für das digitale Zeitalter)	2021	This initiative by the BMBF aims to enhance Germany’s position in HPC through targeted investments in three major areas. First, the SCALEXA programme focuses on developing new methods and technologies for exascale computing, which enables processing at a scale that is orders of magnitude beyond current capabilities (BMBF, 2021[10]). Second, the GreenHPC initiative promotes energy-efficient solutions in HPC, addressing environmental sustainability concerns associated with large-scale computing infrastructure (BMBF, 2021[11]). Third, Germany participates in the European High Performance Computing Joint Undertaking (EuroHPC JU), an EU initiative to advance supercomputing capabilities across the European Union.	EUR 75 million
Important Project of Common European Interest – Next Generation Cloud Infrastructure and Services (IPCEI-CIS)	2021	The IPCEI-CIS is a significant EU initiative involving over 100 companies and research organisations across 12 EU member states, with Germany playing a co‑ordinating role. This project aims to establish a decentralised cloud-edge ecosystem that will reduce technological dependencies and foster new data‑driven business models. The primary goal of the IPCEI-CIS is to create a Multi-Provider Cloud-Edge Continuum, which allows for advanced use of data processing resources from cloud to edge environments. This open ecosystem will support AI and Internet of Things (IoT) applications across various industries, including manufacturing, mobility and energy, enhancing EU digital resilience and competitiveness (8ra, 2024[12]; BMWK, 2023[13]).	Around EUR 560 million in total (as part of the German recovery and resilience plan)
National data strategy	2023	The national data strategy aims to maximise the potential of data across sectors in Germany, including public administration, research, industry and civil society. This strategy outlines a comprehensive approach for responsible, effective and sustainable data usage, rooted in both EU and national laws. Key objectives include expanding data availability by creating more datasets and facilitating access to government data, improving data quality through standardised descriptions and quality assurance, and fostering a culture of data-driven decision making across society. These efforts are particularly driven by the development of the National Research Data Infrastructure. Additionally, the strategy includes an implementation roadmap through the fourth quarter of 2024, aligning with EU legislation and federal regulations. To support these goals, interconnected data laboratories with chief data officers and open data co‑ordinators are active within each federal ministry, driving innovation and co‑ordination across government agencies (BMV, 2023[14]).	The national data strategy itself does not have a budget, but some of the measures mentioned in its roadmap do
National digital strategy	2022	The national digital strategy consolidates the German Federal Government’s priorities for digital transformation under a unified framework, with objectives set for completion by 2025. It outlines a vision for a digitally sovereign and networked society, promoting digital transformation across various sectors, including the economy, workforce and public administration. The focus areas include enhancing digital infrastructure to support data sovereignty, fostering digital innovation within businesses, upskilling the workforce for a digital economy and modernising public services to create a learning digital state (BMV, 2022[15]).	Not reported

Make the European Union the right place: Excellence from lab to the market

Germany’s AI research landscape is supported by a range of initiatives aimed at fostering innovation, building talent and facilitating industry-academia collaboration. Key programmes focus on promoting diversity in AI leadership, establishing centres of excellence and providing computing infrastructure to support research and development (R&D). These efforts are complemented by targeted funding for SMEs to explore AI applications and dedicated hubs that offer guidance and training in digitalisation and AI adoption. Through initiatives like the Fraunhofer Society’s AI Innovation Center (KI-Fortschrittszentrum) and the Platform Learning Systems, Germany ensures that AI research not only advances scientific knowledge but also translates into practical, industry-relevant applications, strengthening its position as a leader in AI R&D in the European Union.

Table 2. Make the European Union the right place: Excellence from lab to the market: Key initiatives

Name	Start year (period covered)	Short description (main goals)	Funding (including EU funding use)
AI for SMEs Grants (KI4KMU)	2020	The grants support innovative AI projects led by SMEs in partnership with universities and start-ups. This programme encourages SMEs to explore advanced AI solutions in areas such as automated decision making, privacy-by-design and data engineering, with a focus on industry-specific applications like renewable energy, mobility and manufacturing (BMBF, 2020[16]).	EUR 81 million
AI Innovation Competition	2019(-25)	The AI Innovation Competition, launched by the BMWK, provides funding for exceptional approaches to developing AI-driven platform economies in key sectors of the German economy. The initiative aims to leverage AI methods as catalysts for innovative value creation networks and the development of new products and business models across various industries. Since 2019, 3 funding calls have been issued, resulting in support for a total of 26 R&D projects to foster the growth of AI ecosystems in Germany (BMWK, 2025[17]).	EUR 280 million (across 3 calls)
AI Professorships (KI‑Professuren)	2020	As part of the national AI strategy, Germany aimed to fund 100 new AI professorships by 2025, a target achieved in 2022 with a total of 150 created by 2023. These include positions supported by various measures, such as the Alexander von Humboldt Professorship for Artificial Intelligence, university AI competence centres, the tenure-track programme, Deutsche Forschungsgemeinschaft projects and collaborations with non-university research institutions (BMBF, 2022[18]).	Not reported
AI Service Centres (KI‑Servicezentren)	2022	Established in 2022, these service centres provide advanced computing infrastructure and tailored services to support AI application development, particularly for SMEs and academic institutions that lack such resources. By offering HPC resources, developing tailored services and fostering innovation ecosystems, the centres help businesses and researchers develop, understand and integrate AI technologies into their work (BMBF, 2022[19]).	EUR 64.7 million
Company Level Spaces for Learning and Experimentation with AI (KI Lern- und Experimentierräume)	2019	Part of the New Quality of Work Initiative (Initiative Neue Qualität der Arbeit) (INQA, 2024[20]), this programme provided SMEs with dedicated spaces to experiment with and learn about AI applications within an operational context. Running from 2019 to 2024, the initiative aimed to demonstrate how AI can enhance workplace practices and benefit SMEs in various industries (BMAS, 2024[21]).	EUR 17 million
Fraunhofer Society (Fraunhofer-Gesellschaft)	1949	The society, with 76 institutes across Germany, plays a crucial role in transferring AI research into business applications (Fraunhofer, 2024[22]). Three Fraunhofer Institutes are particularly relevant for the transfer of AI research: i) the Fraunhofer Institute for Intelligent Analysis and Information Systems (Fraunhofer IAIS, 2024[23]); ii) the Fraunhofer Institute for Manufacturing Engineering and Automation (Fraunhofer IPA, 2024[24]); and iii) the Fraunhofer Institute for Industrial Engineering (Fraunhofer IAO, 2024[25]). Through their AI Innovation Centre, Fraunhofer IPA and IAO offer companies support in exploring, assessing and implementing AI solutions, including proof-of-concept projects. To date, over 250 companies, including many SMEs, have participated in these programmes, with 30% implementing operational AI systems.	Annual research volume of EUR 3 billion for the entire society across all topics; funding for AI‑related initiatives is not available
Generative AI for SMEs	2025	Funded by the BMWK, this technology programme aims to facilitate the effective adoption of generative AI in businesses by showcasing practical use cases in areas such as knowledge management, maintenance, healthcare and production. The programme is specifically designed to address the unique needs and opportunities of SMEs, ensuring that AI solutions are both relevant and accessible to them (BMWK, 2025[26]).	EUR 30 million
Hubs for Tomorrow (Zukunftszentren)	2023	Funded by the European Social Fund (ESF) and the BMAS, the Hubs for Tomorrow were launched nationwide in 2023 to provide SMEs with guidance and training on digitalisation and AI applications (see Box 1).	EUR 125 million from the ESF, federal and state funding for 2023 to 2026
National Initiative for Artificial Intelligence and Data Economy (MISSION KI)	Not reported	MISSION KI, established by the Federal Ministry for Digital and Transport (BMDV), focuses on accelerating the transfer of cutting-edge AI research into practice and fostering the growth of outstanding AI innovations. To further advance the development of trustworthy AI by design, the initiative is developing and testing a voluntary AI quality standard and corresponding testing procedures, particularly for low-risk AI systems, in alignment with the EU AI Act. Through AI Innovation and Quality Centres, MISSION KI supports companies in the development and implementation of trustworthy AI. Additionally, the AI Founder Fellowship is launching an innovative start-up programme aimed at bridging the gap between advanced AI research and successful start-ups, by supporting doctoral students and post-doctoral researchers in transforming their AI research into innovative businesses. MISSION KI also strategically connects AI start-ups and SMEs. By identifying the specific innovation needs of SMEs, the initiative works with partners to match them with suitable AI developers, fostering long-term collaborations that create mutual benefits. To enhance the exchange and utilisation of data for cross-sector AI innovations and new business models, MISSION KI develops open-source products and services that focus on ensuring the interoperability of data spaces across industries and national borders (Mission KI, n.d.[27]).	Not reported
National High-Performance Computing at Universities (Nationales Hochleistungsrechnen an Hochschulen, NHR)	2021	Since 2021, the BMBF, in collaboration with the federal states, has supported HPC at universities, with an annual investment of EUR 62.5 million. This initiative provides the AI community with computing resources, specialised training and consulting to strengthen research capabilities and advance scientific computing skills within academic institutions (NHR, 2024[28]).	EUR 62.5 million annually
Mittelstand-Digital Innovation Hub (MDIH) Network	2021 (current period)	Since 2015, the precursors of the MDIHs (Mittelstand 4.0 Centres of Excellence) have laid the foundation for a comprehensive nationwide network aimed at advancing the digitalisation of SMEs, skilled crafts and start-ups. Today, more than 20 MDIHs actively promote AI readiness and implementation, cybersecurity and resilience, as well as broader digitalisation efforts for SMEs. Around 100 specialised “AI instructors” based at the MDIHs collaborate closely with SMEs, providing targeted support on all aspects of AI adoption. This approach facilitates the transfer of scientific expertise from MDIH consortium partners into practical business applications, thereby strengthening the innovation capacity and competitiveness of German SMEs. Furthermore, cross-cutting issues such as sustainability are also integrated into the MDIH agenda (BMWK, 2024[29]). The MDIH Network works in close partnership with the German Network of European Digital Innovation Hubs (EDIHs).	EUR 216.7 million for MDIHs for 2021‑24 (including EUR 28.7 million for AI instructors)
Network of German Centres of Excellence for AI Research (Netzwerk der Deutschen Kompetenzzentren für Forschung zu Künstlicher Intelligenz)	Start year varies by centre	The BMBF funds six Centres of Excellence for AI Research, which form the core of Germany’s AI research ecosystem, fostering a network for knowledge exchange and ensuring the international visibility of German AI research. Key centres include: i) the Berlin Institute for the Foundations of Learning and Data (BIFOLD); ii) the German Research Center for Artificial Intelligence (Deutsches Forschungszentrum für Künstliche Intelligenz, DFKI); iii) the Munich Center for Machine Learning (MCML); iv) the Lamarr Institute for Machine Learning and Artificial Intelligence North Rhine-Westphalia (LAMARR); v) the Center for Scalable Data Analytics and Artificial Intelligence Dresden/Leipzig (ScaDS.AI); and vi) the Tübingen AI Center (TUE.AI) (DFKI, 2024[30]).	EUR 61 million annually through federal funding plus additional state funding
Platform Learning Systems (Plattform Lernende Systeme)	2017	Founded by the BMBF in 2017, this expert network fosters interdisciplinary dialogue on AI, involving around 200 members from academia, business and civil society. It develops guidance on responsible AI use, including resources like the AI Roadmap for SMEs, which provides practical advice for AI adoption in firms (Plattform Lernende Systeme, 2024[31]).	EUR 17.2 million

Ensure AI technologies work for people

Nurture talent and improve the supply of skills necessary to enable a thriving AI ecosystem

Germany’s approach for developing AI and digital skills focuses on building expertise across academia, workplaces and society. Key efforts include expanding academic capacity through a significant increase in AI-focused professorships, attracting international talent through advanced study programmes, and supporting diversity by encouraging more women in AI research leadership roles. In the workplace, initiatives empower employees to understand and engage with AI applications, while dedicated research bodies explore the broader impacts of AI on labour rights and social well-being. Programmes in schools and teacher training aim to enhance digital literacy and prepare the next generation for a digital future.

Box 1. In focus: Hubs for Tomorrow (Zukunftszentren)

The Hubs for Tomorrow initiative is a nationwide programme spearheaded by the BMAS. It is designed to support workers and businesses in navigating the challenges and opportunities of digital transformation, particularly in SMEs. Launched to address the evolving needs of the German workforce and economy, the hubs offer tailored guidance on integrating digital and AI-driven solutions, fostering a more adaptive, resilient and inclusive labour market.

Key objectives and services

• Digital skills development: The hubs provide training to enhance the digital competencies of employees, focusing on practical, hands-on learning experiences. This includes upskilling in digital tools, AI applications and industry-specific technologies to prepare workers for the future of work.

• AI and technology adoption: By offering consultations on the implementation of AI and digital solutions, the hubs help SMEs identify and integrate appropriate technologies to improve productivity, innovation and competitiveness. They offer a “low-threshold” entry to digital transformation, making advanced technology accessible even to smaller organisations.

• Inclusive transition support: The hubs place a strong emphasis on inclusive digital transformation, ensuring that workers of all ages, skill levels and backgrounds can benefit. This aligns with Germany’s commitment to socially responsible innovation, where the workforce’s diverse needs are taken into account.

• Regional collaboration hubs: Located across Germany, there are several regional hubs for collaboration, bringing together industry experts, researchers, business leaders and employees. This network facilitates the exchange of best practices, success stories and innovative approaches to digital challenges.

• Future-oriented research: In addition to training and advisory services, the hubs engage in research to anticipate future labour trends and technology developments. They contribute to Germany’s long-term strategies on employment, providing data and insights that guide policy-making.

Source: Zukunftszentren (2024[32]), Homepage, https://zukunftszentren.de/, accessed on 15 November 2024.

Table 3. Ensure AI technologies work for people: Key initiatives

Name	Start year	Short description (main goals)	Funding (including EU funding use)
AI Studios (KI‑Studios)	2023	AI Studios, a BMAS project, empower workers and their representatives to actively engage with AI and shape its applications in their workplaces. Through interactive AI demonstrators and 350 accessible workshops nationwide, participants experience realistic work scenarios with AI applications to learn about the technology’s impact, opportunities and risks (KI-Studios, 2024[33]).	EUR 6.37 million
Civic Innovation Platform (CIP)	2020	Established in 2020 by the BMAS, the CIP focuses on promoting socially responsible and participatory approaches to AI development. It explores a range of tools to support collaborative and participatory social innovation processes. The CIP is also a key component of the Civic Coding – Innovation Network AI for the Common Good, an interdepartmental initiative involving the BMAS, the Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection (BMUV), and the Federal Ministry for Family Affairs, Senior Citizens, Women and Youth (BMFSFJ) (Civic Innovation Platform, 2025[34]).	EUR 7.35 million
Competence Centres for Digital and Digitally Supported Teaching in Schools and Continuing Education (Kompetenzzentren für digitales und digital gestütztes Unterrichten in Schule und Weiterbildung)	2023	Initiated by the BMBF as part of the EU Recovery and Resilience Facility (RRF), these centres focus on the quality development of digitalisation-related teacher training through research, innovation and transfer activities until the end of 2026. As one of many aspects, this also includes the pedagogically precise use of AI‑supported systems in schools and teaching (BMBF, 2025[35]).	Up to EUR 205 million (RRF)
Digital Pact for Schools (DigitalPakt Schule)	Not reported	The Digital Pact for Schools empowers federal states to integrate AI technologies into diverse educational projects, facilitating the use of digital learning materials, adaptive learning systems and targeted student support. By doing so, it establishes essential technical foundations that enable both teachers and students to develop digital and AI-related skills effectively. The initiative allocates EUR 92 million to enhance AI-related educational media infrastructure across 9 cross-state projects (BMBF, 2024[36]).	EUR 92 million
Funding Programme for Female AI Junior Scientists (KI‑Nachwuchswissenschaftlerinnen)	2019	This BMBF programme supports female-led junior research groups in AI, aiming to increase the proportion of qualified women in leadership roles within German AI research. The initiative encourages innovative AI research topics and considers family-work balance conditions as part of the funding allocation criteria. In 2023, a new call for applications was issued to expand support for female AI scientists (BMBF, 2019[37]).	EUR 45.5 million across 2 calls
Konrad Zuse Schools of Excellence in Artificial Intelligence	2021	Funded by the BMBF through the German Academic Exchange Service (Deutscher Akademischer Austauschdienst, DAAD), the Konrad Zuse Schools of Excellence in Artificial Intelligence attract international talent at the master’s and doctoral levels. These schools offer English-language teaching and research programmes, connecting top scientists with industry fellows interested in innovative AI teaching and research (DAAD, 2024[38]).	EUR 42 million
Observatory on Artificial Intelligence in Work and Society (Observatorium Künstliche Intelligenz in Arbeit und Gesellschaft, also: KI-Observatorium)	2020	Established in 2020 within the BMAS, the Observatory examines the impact of AI on the world of work and advocates for a human-centred and responsible approach to AI adoption. It collaborates with businesses, labour unions, civil society, academia and international partners to develop guidelines and policy recommendations that ensure AI is used ethically and effectively (KI-Observatorium, 2025[39]).	EUR 28.5 million (2020-24)

Build strategic leadership in priority sectors

Germany is leveraging AI to drive digital transformation across key sectors. In climate and the environment, AI is being applied to improve resource efficiency, enhance environmental monitoring and optimise circular economy practices. Flagship initiatives include large-scale funding for AI-driven solutions in climate protection, waste management and biodiversity conservation, as well as targeted support for SMEs to integrate AI into sustainable business practices. The public sector is undergoing a structured AI adoption process, with initiatives to standardise AI governance, facilitate inter-ministerial collaboration and deploy AI solutions to improve administrative efficiency. A central advisory body and cross-government AI frameworks are ensuring that AI applications align with ethical standards and transparency principles. In mobility, AI-powered innovations are advancing autonomous driving, traffic management and multimodal transport integration. The focus is on developing safe, verifiable AI applications for next-generation mobility systems, with a particular emphasis on ensuring reliability and security. Agriculture, forestry and rural development benefit from AI-driven precision farming, data-driven food production and smart rural value chains, supported by substantial public investment.

State of AI in healthcare

Germany’s national AI strategy, introduced in 2018 and updated in 2020, has enhanced the conditions for integrating and advancing AI in healthcare, with a strong emphasis on robust health data governance. The framework focuses on three key areas: security, interoperability and accessibility (BMWi, 2018[40]; German Federal Government, 2018[41]). Data security has been a long-standing priority, with the introduction of the Guidelines on the Protection of Health Data in November 2018, followed by the Patient Data Protection Act (Patientendaten-Schutz-Gesetz, PDSG) in 2020. Despite these advancements, Germany faces challenges with balancing the heterogenous interpretation and implementation of general and sectorial EU-, federal- and state-level data protection rules and secondary data use, which currently still impedes access to comprehensive health data (OECD, 2024[3]). To facilitate access to health data, the BMBF launched a series of initiatives, including the Medical Informatics Initiative (MII) in 2016. The MII establishes the organisational and technical prerequisites to harmonise data from routine clinical care as well as biomedical research and to make them available for medical research in a data protection-compliant approach (MII, 2024[42]). The Network of University Medicine (NUM) and the Health Data Lab at the Federal Institute for Drugs and Medical Devices (BfArM) currently grant access to claims data (Netzwerk Universitätsmedizin, 2025[43]). From 2025, this will also include electronic patient record data, primarily for research purposes. In addition, the National Strategy for Genomic Medicine supports efforts to enhance genomic research and health data integration (TEDHAS, 2024[44]; BMG, 2024[45]).

Germany has further advanced healthcare interoperability through the Digital Act (DigiG), which expanded the Coordination Office for Interoperability into a competence centre. Supported by the Interop Council and expert working groups, it promotes technical, syntactic and semantic interoperability, ensuring a holistic, co‑ordinated approach to developing binding guidelines and standards. The Health Data Use Act came into force in March 2024, with the aim to improve data availability for health research and further public interest purposes, including development and validation of AI systems in healthcare, as preparation for implementing the European Health Data Space in Germany (OECD, 2024[3]). In addition to the MII, initiatives such as the National Research Data Infrastructure, launched in 2019 and funded at least through 2028, aims to ensure that data across different fields can be accessed, linked and used by researchers efficiently (DFG, 2024[46]). In the health sector, Germany is accelerating innovation through initiatives such as NFDI4Health, which aims to facilitate collaboration and make health data accessible to researchers, innovators, including AI developers (NFDI4Health, 2024[47]). These initiatives collectively aim to establish a secure, interoperable and accessible health data infrastructure to support AI integration.

Germany has demonstrated significant investment in AI in health, funding 38 AI healthcare projects between 2020 and 2025, focusing on areas like smart sensors, smart data use, smart algorithms and expert systems, as well as smart communication. Funded projects ranged from diagnostic support through AI-enhanced skin cancer detection, to using smart sensors for decubitus prevention and administrative support through AI scribes for trauma care (BMG, 2023[48]; 2023[49]; 2024[50]). Furthermore, the BMBF is funding R&D projects that explore the use of AI in care, clinical processes and precision surgery for oncology (BMBF, 2021[51]; 2024[52]). Additionally, several funding measures, such as Optimal Therapies through Data-Driven Decision and Support Systems, aim to enable companies to establish leadership in specific areas of AI healthcare solutions (BMBF, 2023[53]). SMEs can leverage AI solutions and other innovative ideas through the BMBF initiative SMEs Innovative: Medical Technology (BMBF, 2024[54]). Moving forward, Germany plans to equip every statutory insured person with the electronic patient record by 2025 (unless they opt out), furthering the creation and regulation of a digital healthcare platform for secure data exchange. With the entry in force of the Health Data Use Act, Germany has advanced beyond using health data solely for research purposes and has established a governance framework for the secure use of health data in testing and training AI systems. This legislation is essential for AI development, ensuring privacy, ethical use and the creation of accurate, data-driven algorithms (BMG, 2023[55]; 2025[56]).

Table 4. Build strategic leadership in priority sectors: key initiatives

Name	Start year	Short description (main goals)	Funding (including EU funding use)
Climate and environment
AI Idea Workshop for Environmental Protection	2023	The initiative aims to support the development of AI applications for environmental protection by non-governmental organisations, civil society initiatives, researchers, start-ups and private individuals. Its goal is to advance AI-driven solutions for environmental protection through a strong civil society engagement. The initiative offers technical expertise, networking opportunities and an accessible funding programme, structured around five key modules: AI workshop, pilot projects, environmental data workshop, mobile workshops and network building (KI-Ideenwerkstatt, 2025[57]). The AI Idea Workshop is part of the Civic Coding initiative (Civic Coding, 2025[58]).	EUR 8.3 million (funded until 2025)
AI Lighthouses for Environment, Climate, Nature and Resources	2019	The programme provides funding for AI-driven solutions aimed at addressing environmental challenges and strategically advancing AI applications for environmental and climate protection. This includes areas such as energy efficiency, resource efficiency, biodiversity conservation, nature protection, species preservation, water management, sustainable consumption and eco-friendly mobility. The focus is on application-oriented R&D projects, which can receive funding for up to 3 years, with a maximum grant of EUR 3 million per project (BMUV, 2024[59]).	EUR 150.9 million
Application Hub for a Circular Economy for Plastic Packaging through AI Methods	2021	Financed by the BMBF, this application hub focuses on developing AI methods to enhance circular economy practices for plastic packaging. It supports research and innovation to reduce waste and improve recycling efficiency in Germany (AI Hub Plastic Packaging, 2024[60]).	EUR 30 million until 2025
Application Lab for AI and Big Data	2022	Managed by the German Environment Agency (UBA), this laboratory specialises in leveraging AI and big data to advance environmental enforcement, research and the sustainable use of AI technologies. As part of the Federal Government’s economic stimulus and future technologies package, it is funded until 2025. The lab generates data-driven insights to inform policy decisions and raise public awareness on environmental issues, while also promoting a modern and efficient approach to public administration (UBA, 2024[61]).	EUR 26.4 million (funded until 2025)
Green AI Hub Mittelstand	2023	The Green AI Hub Mittelstand is an initiative launched by the BMUV to support German SMEs in adopting AI technologies for environmental protection and climate action. The hub aims to empower SMEs to integrate AI solutions that enhance energy efficiency, reduce resource consumption and minimise environmental impact. It offers a range of resources, including technical guidance, funding access and training opportunities to facilitate the development and implementation of sustainable AI-driven projects. Additionally, the hub fosters collaboration by providing networking opportunities, bringing together SMEs, research institutions and environmental organisations to create a supportive ecosystem for sustainable AI innovation (BMUV, 2024[62]).	EUR 15.2 million (funded until 2025)
Health
Centre for Artificial Intelligence in Public Health Research (ZKI-PH)	2021	The ZKI-PH is responsible for the strategic support of advances in the field of public health research using the latest AI-based technologies at Germany’s Robert Koch Institute. At the ZKI-PH, the topics of bioinformatics, computational epidemiology, modern data visualisation as well as big data and systems analysis are combined with the central methodological building blocks of machine learning, AI, decision‑making research as well as the development of realistic computer simulations in the field of public health research (RKI, 2025[63]).	Not reported
Health Data Use Act (GDNG)	2024	The GDNG is a key enabler to facilitate the access to healthcare data for secondary use. Its measures include procedural simplifications on re-using health data across multiple states (Länder). It further provides a legal basis for healthcare institutions to re-use their patients‘ data for research, patient safety and quality assurance, and enables statutory health insurance funds to utilise data to improve the quality of care and to support AI applications (BMG, 2025[56]).	Not reported
AI-assisted precision surgery in oncology (KI‑gestützte Präzisionschirurgie in der Onkologie)	2024	Surgical interventions are an essential component of curative multimodal treatment strategies for solid cancers and remain a fundamental pillar of modern cancer medicine. AI can make a decisive contribution to personalised precision oncology approaches both before, during and after surgery. The aim of the funding measure is to improve the precision of surgical treatment of oncological diseases with the aid of interactive AI technologies (BMBF, 2024[52]).	Approximately EUR 17.5 million
AI-based assistance systems for in-process healthcare applications (KI‑basierte Assistenzsysteme für prozessbegleitende Gesundheitsanwendungen)	2021	In addition to the much-discussed potential in diagnostics, AI-based interactive systems can very effectively support processes in hospitals and comparable healthcare facilities and thus contribute to the improvement of medical, organisational and administrative processes. The aim of the projects in this funding measure is to research and develop AI-based assistance systems that lead to quantifiable and measurable improvements in clinical processes (BMBF, 2021[64]).	EUR 19.5 million
Health Data Lab (HDL) (Forschungsdatenzentrum [FDZ] Gesundheit)	Not reported	The HDL at the BfArM makes pseudonymised claims for data from people insured in the statutory health system and available for research purposes and other legally defined public interest purposes, including AI development. The lab makes an important contribution towards better and safer healthcare. With the Health Data Use Act, the Social Security Code – Book V (SGB V) has been amended to explicitly enable the development of AI systems on health data accessible through the HDL (§303e II Nr. 9 SGB V).	Not reported
Health IT Interoperability Governance Ordinance (GIGV) Competence Centre	2024	Germany has advanced healthcare interoperability through the Digital Act, which expanded the Coordination Office for Interoperability into a competence centre. Supported by the Interop Council and expert working groups, it promotes technical, syntactic and semantic interoperability, with the Health IT Interoperability Governance Ordinance (GIGV) ensuring a holistic, co‑ordinated approach to developing binding guidelines and standards (BMG, 2024[65]; BMJ, 2024[66]).	Not reported
Making repositories and AI systems usable in everyday nursing care (Repositorien und KI-Systeme im Pflegealltag nutzbar machen)	2021	This funding measure aims to support caregivers as well as caregiving relatives and to improve the self-determination and quality of life of people in need of care through innovative AI applications. Funded projects develop long-term usable data and software repositories as well as AI systems for use in everyday care (BMBF, 2021[51]).	EUR 15.9 million
Optimal therapies through data-driven decision and support systems (Optimale Therapien durch datengetriebene Entscheidungs- und Unterstützungssysteme)	2023	In many diseases, choosing the appropriate therapy forms the basis for the subsequent course and success of the treatment. The goal of the funding is to optimise patient care through medical technology solutions in the form of innovative decision and support systems. Data‑driven approaches should support healthcare providers at all stages of the care process to achieve better healing or a reduction in side effects. Projects should primarily use data-driven approaches, such as those typically found in AI or machine learning techniques beside rule-based methods (BMBF, 2023[53]).	EUR 25 million
SMEs Innovative: Medical Technology (KMU‑innovativ: Medizintechnik)	2018	Medical technology plays an indispensable role in healthcare. The German medical technology sector is primarily made up of SMEs, which account for over 90% of the companies in the field. These SMEs are the innovative backbone of the industry, operating in a highly dynamic environment and under stringent regulatory requirements for medical products, which significantly increase the investment risks in R&D. To strengthen the innovative capacity of Made in Germany medical technology, the BMBF supports SMEs in their research on innovative medical products, in-vitro diagnostics and digital medical technology solutions. This funding aims to initiate additional R&D activities, boost medical technology research in Germany, enhance networking between SMEs and partners in science and healthcare, and strengthen the competitive position of the German medical technology sector.	EUR 30 million per annum
New Section 393 SGB V (Social Security Code – Book V) enacted with the recent Digital Act	2024	Germany established uniform and transparent standards for the use of cloud-computing services for processing health data, protecting sensitive health information from unauthorised access, manipulation or loss. This regulation can positively impact AI use and research by providing a secure and standardised framework for handling sensitive health data, fostering trust and enabling more robust, compliant AI‑driven innovations in healthcare (BMG, 2024[67]).	Not reported
Public sector
AI Advisory Centre (Beratungszentrum für Künstliche Intelligenz, BeKI)	In Development	The Federal Ministry of the Interior and Community (Bundesministerium des Innern und für Heimat, BMI) BeKI initiative is creating a central advisory and co‑ordination hub for AI in the federal administration. It aims to standardise AI initiatives across federal agencies by offering guidance on legal, ethical and technical aspects of AI use. BeKI also collaborates with other specialised centres, like the Federal Ministry of Finance’s AI Competence Centre, to support AI competency within the government (BMI, 2024[68]).	EUR 9.18 million in budget funds provided to date (includes all initiatives connected to BeKI, i.e. MaKI, KIPITZ, AI guiding statements and AI guidelines)
AI framework guiding statements (KI-Leitbild)	2024	Launched by the BMI, this framework focuses on an opportunity-oriented and responsible approach to AI within the ministry and its affiliates. It outlines guiding principles, such as human-centred design, transparency and fairness, and identifies critical factors along the AI value chain that contribute to successful AI use in public administration (BMI, 2024[69]). Similarly, the Federal Foreign Office (AA) has adopted an AI charter (Auswärtiges Amt, 2025[70]).	See BeKI
AI cuidelines (KI-Leitlinien)	2025	Co‑ordinated by the AI Advisory Centre (BeKI), AI guidelines are being developed to ensure a harmonised inter-ministerial approach to the use of AI in public administration. These guidelines promote a value-based approach to AI deployment and offer practical guidance for both employees utilising AI systems and the respective administrative units responsible for providing these systems (BMI, 2024[69]).	See BeKI
AI Marketplace for Opportunities (Marktplatz der KI-Möglichkeiten)	In development	As a pilot project under BeKI, this marketplace will connect ministries and agencies with AI solutions that meet their needs. It will improve transparency and collaboration by cataloguing AI applications and experiences within government departments. The project is currently being developed with the BMI Data Lab, ITZBund and other ministries, with plans to launch publicly by late 2024 (BMI, 2024[68]).	See BeKI
KIPITZ AI Plattform	2024	Jointly managed by BeKI, the BMF and the Federal Chancellery’s Data Lab, KIPITZ is an overarching AI infrastructure supporting LLMs for the federal administration. The platform, built by ITZBund with open-source components, allows cross-departmental testing and deployment of generative AI tools, fostering innovation and digital sovereignty in the public sector (BMI, 2024[68]).	See BeKI
Datalabs (Datenlabore)	2021	Since 2021, the Federal Government’s data labs have recruited experts in data science and AI from academia, civil society and the private sector to support the federal administration. These experts help develop and implement AI-driven solutions within government agencies, making data and AI more useful in decision making and public services. Through exploring and testing new AI applications, the data labs help to modernise administrative processes and promote AI technologies in the public sector.	Not reported
Guidelines for the Use of AI in the Administrative Work of the Employment and Social Protection Services (Selbstverpflichtende Leitlinien für den KI‑Einsatz in der behördlichen Praxis der Arbeits- und Sozialverwaltung)	2021	Co‑ordinated by the Policy Lab Digital, Work and Society at the BMAS, these guidelines were developed to ensure responsible, human-centred and non-discriminatory AI deployment in employment and social protection services. Created through a participatory, bottom-up process, these guidelines aim to benefit both employees and citizens (BMAS, 2022[71]).	EUR 920 000 (2021‑23)
Mobility
AI applications for connected and automated driving	2020	The funding guidelines entitled Ensuring a Viable and Sustainable Mobility System through Automated Driving and Connectivity aim to support the development of approaches in the fields of automated and connected driving as integral components of the future mobility system. They are particularly focused on higher levels of automation, extending to fully autonomous (driverless) driving, as well as connectivity in road transport, including interfaces with other modes of transport in complex use cases incorporating AI methods. In 2020, the BMDV launched research funding to promote a viable and sustainable mobility system through automation and connectivity, with a strong emphasis on AI applications. Several projects were funded by the BMDV to address various objectives, including: AI-based optimisation of security and comfort for people with mobility restrictions in non-motorised private transport; AI-driven regular operation of autonomous on-demand transport; and the development of a safety-oriented and standardised reference model for integrating autonomous vehicles (from Autonomy Level 4) into public transport, among others (BMDV, 2018[72]; 2021[73]).	EUR 47.2 million
AI applications in mobility and logistics	Not reported	The BMDV supports AI-based analysis, forecasting and information systems, as well as highly transferable concepts that enhance the safety, efficiency, resource sustainability and convenience of mobility and logistics (BMDV, 2018[72]).	EUR 75.08 million
AIAMO Mobility Data Hub and Services	Not reported	This initiative, led by the BMDV, addresses the challenge of ensuring reliable mobility options while prioritising climate protection. The AIAMO aims to create a data-sovereign platform that integrates various mobility services, providing an accessible solution for SMEs and smaller cities. By simplifying data collection in the mobility sector, the project enables insights into environmentally friendly and multimodal traffic management. Through an interconnected integration zone, trusted AI applications will provide research findings and support easy market access for SMEs and numerous cities (BMDV, 2023[74]).	EUR 22.29 million
Mobility Data Space (MDS°	2020	The BMDV is funding the MDS, a platform designed to facilitate the legally secure exchange of sensitive data. Within this space, private sector data can be voluntarily shared and traded while ensuring full respect for data sovereignty. It operates as a non-profit joint venture and is managed by Datenraum Mobilität GmbH, established in May 2021. Unlike traditional data platforms, the MDS does not host data themselves; instead, all data remain with the original holders. The MDS is intended to extend beyond Germany, aligning with the EU data strategy by ensuring interoperability with other initiatives and data spaces at the regional, national and EU levels. A key objective is to facilitate AI applications by providing controlled access to non-public data, thereby unlocking new possibilities for innovation in mobility (MDS, 2025[75]).	EUR 13.76 million
nxtAIM	2024	Funded by the BMWK as part of the New Vehicle and System Technologies programme, this joint project aims to develop and train generative AI methods for autonomous driving. These are designed to overcome key barriers to the deployment of automated and autonomous vehicles. Notably, all participating companies are, for the first time, making their proprietary datasets available to facilitate the joint training of foundation models (nxtAIM, 2025[76]).	EUR 27 million
Safe AI Engineering	2025	The programme, funded by the BMWK under the New Vehicle and System Technologies programme (BMWK, 2023[77]), aims to enable comprehensive verification of AI safety for autonomous vehicles, paving the way for their reliable and secure use.	EUR 17.2 million
Silicon Economy Ecosystem	Not reported	The Silicon Economy Ecosystem research project, funded by the German Federal Ministry for Digital and Transport (Bundesministerium für Digitales und Verkehr, BMDV), developed data models, interfaces and AI-based hardware and software components that enable logistics companies of all sizes to intelligently automate their business processes along the supply chain. All components are made available to companies free of charge and open source (Silicon Economy, 2025[78]).	EUR 33.77 million
Agriculture/forestry/rural development
AI and Data Accelerator in the Field of Food and Agriculture (KI- & Daten-Akzelerator im Bereich Ernährung und Landwirtschaft, KIDA)	2021	As part of the German AI strategy, KIDA serves as a cross-institutional service centre for AI use cases in the agri-food sector. Led by the Federal Ministry of Food and Agriculture (Bundesministerium für Ernährung und Landwirtschaft, BMEL), it enables AI and big data applications in agriculture, supporting subordinate authorities in handling AI and data cases (KIDA, 2024[79]).	EUR 40 million
Announcement on the Promotion of Artificial Intelligence (AI) in Agriculture, the Food Chain, Health Nutrition and Rural Areas (Bekanntmachung zur Förderung der Künstlichen Intelligenz (KI) in der Landwirtschaft, der Lebensmittelkette, der gesundheitlichen Ernährung und den Ländlichen Räumen)	2020	This initiative supports 36 projects across the agri-food sector. For agriculture, 24 projects focus on plant production topics like crop breeding, yield protection, plant health, weed control and connected farming technology, all through AI-driven methods like robotics, drones and smart sensors. The four projects in animal husbandry focus on animal welfare and health, leveraging AI to improve farming practices and promote sustainability (BMEL, 2020[80]). In the fields of food supply chains and healthy nutrition, a total of five projects are investigating how AI can improve food safety and quality, enhance transparency and promote sustainable, health-conscious consumer behaviour. Notably, the most recent three projects focus on rural areas, aiming to strengthen regional value chains, support the marketing of local products and boost innovation capacity in rural regions.	EUR 44.2 million
FAIR Forward Open Data for Agriculture	2023	The Federal Ministry for Economic Cooperation and Development (Bundesministerium für wirtschaftliche Zusammenarbeit und Entwicklung, BMZ) promotes environmental sustainability and AI with the FAIR Forward project. It provides partner countries in the Global South with access to climate-smart agricultural advice and includes a practitioner’s guide to green data centres, developed in collaboration with the World Bank, International Telecommunications Union and federal enterprise GIZ (BMZ, 2024[81]).	EUR 35.3 million
Optimisation of Data Collection and Control Technology for Biomass Combustion Systems (Optimierung von Datenerfassung und Steuerungstechnik für Biomassefeuerungen, DigitalFire)	2019	DigitalFire aims to improve biomass combustion systems by using advanced data collection, machine learning and predictive maintenance. The project looks to enhance efficiency and reliability, providing cost-effective solutions for manufacturers and operators (FNR, 2024[82]).	EUR 90 000
T2O2 Regulation (T2O2‑Regelung)	2020	This project focuses on creating a biomass-based combustion control system to reduce pollutants in free-standing room heaters. Developed with industry partners, the T2O2 system applies the energy balance method and aims for market readiness after further optimisation (FNR, 2024[83]).	EUR 303 000

References

[12] 8ra (2024), The Future of Europe’s Digital Infrastructure, 8ra Cloud-Edge Continuum, https://www.8ra.com/ (accessed on 15 November 2024).

[60] AI Hub Plastic Packaging (2024), AI Application Hub on Plastic Packaging, https://ki-hub-kunststoffverpackungen.de/en/ai-hub/about (accessed on 15 November 2024).

[70] Auswärtiges Amt (2025), Für einen modernen Auswärtigen Dienst - das Auswärtige Amt gibt sich eine KI-Charta, https://www.auswaertiges-amt.de/de/aussenpolitik/sicherheitspolitik/cyber-aussenpolitik/ki-charta-2698666 (accessed on 4 March 2025).

[4] BAIOSPHERE (2024), Der Bayerische KI-Rat, https://baiosphere.org/ai-council/ (accessed on 15 November 2024).

[21] BMAS (2024), “Lern- und Experimentierräume”, German Federal Ministry of Labour and Social Affairs, https://www.bmas.de/DE/Arbeit/Digitalisierung-der-Arbeitswelt/Austausch-mit-der-betrieblichen-Praxis/Lern-und-Experimentierraeume/lern-und-experimentierraeume.html (accessed on 15 November 2024).

[71] BMAS (2022), Selbstverpflichtende Leitlinien für den KI-Einsatz in der behördlichen Praxis der Arbeits- und Sozialverwaltung, German Federal Ministry of Labour and Social Affairs, https://www.denkfabrik-bmas.de/fileadmin/Downloads/Publikationen/Guidelines_for_the_use_of_ai_in_the_administrative_work_of_employment_and_social_protection_services.pdf (accessed on 15 November 2024).

[35] BMBF (2025), Kompetenzzentren für digitales Unterrichten, German Federal Ministry of Research, Technology and Space, https://www.bmbf.de/DE/Bildung/Schule/Digitalisierung/KompetenzzentrenFuerDigitalesUnterrichten/kompetenzzentrenfuerdigitalesunterrichten_node.html (accessed on 3 March 2025).

[36] BMBF (2024), DigitalPakt Schule, German Federal Ministry of Education and Research, https://www.digitalpaktschule.de/ (accessed on 15 November 2024).

[52] BMBF (2024), Richtlinie zur Förderung von Projekten zum Thema „KI-gestützte Präzisionschirurgie in der Onkologie“, German Federal Ministry of Research, Technology and Space, https://www.bmbf.de/SharedDocs/Bekanntmachungen/DE/2024/08/2024-08-07-Bekanntmachung-Pr%C3%A4zisionschirurgie.html (accessed on 7 March 2025).

[54] BMBF (2024), Richtlinie zur Förderung von Vorhaben zum Themenfeld „KMU-innovativ: Medizintechnik, German Federal Ministry of Research, Technology and Space, https://www.bmbf.de/SharedDocs/Bekanntmachungen/DE/2024/08/2024-08-09-Bekanntmachung-Medizintechnik.htm (accessed on 10 March 2025).

[53] BMBF (2023), Richtlinie zur Förderung von Projekten zum Thema „Optimale Therapien durch datengetriebene Entscheidungs- und Unterstützungssysteme“, German Federal Ministry of Research, Technology and Space, https://www.bmbf.de/SharedDocs/Bekanntmachungen/DE/2023/10/2023-10-04-Bekanntmachung-Unterst%C3%BCtzungssysteme.html (accessed on 10 March 2025).

[19] BMBF (2022), Förderung von vier KI-Servicezentren gestartet, German Federal Ministry of Education and Research, https://bmbf-test41.gsb.itzbund.de/bmbf/shareddocs/kurzmeldungen/de/2022/11/foerderung-von-4-ki-zentren-gestartet.html (accessed on 15 November 2024).

[18] BMBF (2022), “Stark-Watzinger: 100. zusätzliche KI-Professur wurde besetzt”, German Federal Ministry of Research, Technology and Space, https://www.bmbf.de/bmbf/shareddocs/pressemitteilungen/de/2022/05/030522-KI-Professoren.html (accessed on 15 November 2024).

[10] BMBF (2021), Bekanntmachung der Richtlinie zur Förderung von Verbundprojekten auf dem Gebiet „Neue Methoden und Technologien für das Exascale-Höchstleistungsrechnen“ (SCALEXA), German Federal Ministry of Research, Technology and Space, https://www.bmbf.de/bmbf/shareddocs/bekanntmachungen/de/2021/08/2021-08-26-Bekanntmachung-SCALEXA.html (accessed on 15 November 2024).

[11] BMBF (2021), Bekanntmachung der Richtlinie zur Förderung von Verbundprojekten auf dem Gebiet des energieeffizienten High-Performance Computings (GreenHPC), German Federal Ministry of Research, Technology and Space, https://www.bmbf.de/bmbf/shareddocs/bekanntmachungen/de/2021/05/3621_bekanntmachung.htm (accessed on 15 November 2024).

[7] BMBF (2021), Microelectronics - Trustworthy and Sustainable - For Germany und Europe, German Federal Minister of Education and Research, https://www.bmbf.de/SharedDocs/Publikationen/de/bmbf/FS/31646_Mikroelektronik_Vertrauenswuerdig_und_nachhaltig_en.pdf?__blob=publicationFile&v=6 (accessed on 15 November 2024).

[51] BMBF (2021), Richtlinie zur Förderung von Forschung und Entwicklung auf dem Gebiet „Repositorien und KI-Systeme im Pflegealltag nutzbar machen“, German Federal Ministry of Research, Technology and Space, https://www.bmbf.de/SharedDocs/Bekanntmachungen/DE/2021/01/3298_bekanntmachung.html (accessed on 7 March 2025).

[64] BMBF (2021), Richtlinie zur Förderung von Projekten zum Thema „KI-basierte Assistenzsysteme für prozessbegleitende Gesundheitsanwendungen“, German Federal Ministry of Research, Technology and Space, https://www.bmbf.de/SharedDocs/Bekanntmachungen/DE/2021/07/3690_bekanntmachung.html (accessed on 7 March 2025).

[16] BMBF (2020), Bekanntmachung der Richtlinie zur Förderung von Projekten zum Thema „Erforschung, Entwicklung und Nutzung von Methoden der Künstlichen Intelligenz in KMU“, German Federal Ministry of Research, Technology and Space, https://www.bmbf.de/bmbf/shareddocs/bekanntmachungen/de/2020/03/2876_bekanntmachung.html (accessed on 15 November 2024).

[37] BMBF (2019), Bekanntmachung - Richtlinie zur Förderung von KI-Nachwuchswissenschaftlerinnen, German Federal Ministry of Research, Technology and Space, https://www.bmbf.de/bmbf/shareddocs/bekanntmachungen/de/2019/06/2502_bekanntmachung.html (accessed on 15 November 2024).

[74] BMDV (2023), Artificial Intelligence and Mobility - AIAMO, German Federal Ministry of Transport, https://bmdv.bund.de/SharedDocs/DE/Artikel/DG/KI-Projekte/aiamo.html (accessed on 15 November 2024).

[73] BMDV (2021), “Research funding for ensuring a viable and sustainable mobility system through automation and connectivity”, German Federal Ministry of Transport, https://bmdv.bund.de/SharedDocs/EN/Articles/DG/research-programme-on-automation-and-connectivity-in-road-transport.html (accessed on 17 March 2025).

[72] BMDV (2018), KI-Projekte des BMDV, German Federal Ministry of Transport, https://bmdv.bund.de/DE/Themen/Digitales/Kuenstliche-Intelligenz/KI-Projekte-in-der-Mobilitaet/aktionsplan.html (accessed on 17 March 2025).

[80] BMEL (2020), Bekanntmachung zur Förderung der KI in der Landwirtschaft, der Lebensmittelkette, der gesundheitlichen Ernährung und den Ländlichen Räumen, German Federal Ministry of Food and Agriculture, https://www.ble.de/SharedDocs/Downloads/DE/Projektfoerderung/Kuenstliche_Intelligenz/Bekanntmachung_KI.pdf?__blob=publicationFile&v=2 (accessed on 15 November 2024).

[56] BMG (2025), Gesundheitsdatennutzungsgesetz (GDNG), German Federal Ministry of Health, https://www.bundesgesundheitsministerium.de/service/gesetze-und-verordnungen/detail/gesundheitsdatennutzungsgesetz.html (accessed on 10 March 2025).

[50] BMG (2024), Entwicklung und Erprobung eines KI-basierten Spracherkennungssystems für die verbale Kommunikation in der Polytraumaversorgung (TraumAInterfaces), German Federal Ministry of Health, https://www.bundesgesundheitsministerium.de/ministerium/ressortforschung/handlungsfelder/forschungsschwerpunkte/digitale-innovation/modul-4-smarte-kommunikation/traumainterfaces.html (accessed on 10 March 2025).

[67] BMG (2024), “Entwurf eines Gesetzes zur Beschleunigung der Digitalisierung des Gesundheitswesens”, German Federal Ministry of Health, https://www.bundesgesundheitsministerium.de/fileadmin/Dateien/3_Downloads/Gesetze_und_Verordnungen/GuV/D/Kabinettvorlage_Digital-Gesetz-DigiG.pdf (accessed on 7 March 2025).

[45] BMG (2024), genomeDE – National Strategy for Genomic Medicine, German Federal Ministry of Health, https://www.bundesgesundheitsministerium.de/en/en/international/european-health-policy/genomde-en.html (accessed on 15 November 2024).

[65] BMG (2024), IOP-Governance-Verordnung (GIGV), German Federal Ministry of Health, https://www.bundesgesundheitsministerium.de/service/gesetze-und-verordnungen/detail/iop-governance-verordnung-gigv.html (accessed on 7 March 2025).

[55] BMG (2023), Digitalisation Strategy for Health and Care, German Federal Ministry of Health, https://www.bundesgesundheitsministerium.de/fileadmin/Dateien/3_Downloads/D/Digitalisierungsstrategie/Germany_s_Digitalisation_Strategy_for_Health_and_Care.pdf (accessed on 22).

[49] BMG (2023), Künstliche Intelligenz zur Vorbeugung von Wundliegegeschwüren (KIPRODE), German Federal Ministry of Health, https://www.bundesgesundheitsministerium.de/ministerium/ressortforschung/handlungsfelder/forschungsschwerpunkte/digitale-innovation/modul-1-smarte-sensorik/kiprode.html (accessed on 10 March 2025).

[48] BMG (2023), Skin Classification Project: Smarte Algorithmen zur Unterstützung in der Melanomdiagnostik (SCP2), German Federal Ministry of Health, https://www.bundesgesundheitsministerium.de/ministerium/ressortforschung/handlungsfelder/forschungsschwerpunkte/digitale-innovation/modul-3-smarte-algorithmen-und-expertensysteme/scp2.html (accessed on 10 March 2025).

[69] BMI (2024), “BMI stellt sein KI-Leitbild vor”, German Federal Ministry of the Interior, https://www.bmi.bund.de/SharedDocs/kurzmeldungen/DE/2024/06/KI-leitbild.html (accessed on 15 November 2024).

[68] BMI (2024), Künstliche Intelligenz in der Verwaltung, German Federal Ministry of the Interior, https://www.cio.bund.de/Webs/CIO/DE/digitale-loesungen/datenpolitik/daten-und-ki/daten-und-ki-node.html (accessed on 15 November 2024).

[66] BMJ (2024), Gesundheits-IT-Interoperabilitäts-Governance-Verordnung (IOP-Governance-Verordnung - GIGV), German Federal Law Gazette, https://www.recht.bund.de/bgbl/1/2024/279/VO.html (accessed on 7 March 2025).

[59] BMUV (2024), Künstliche Intelligenz für Umwelt und Klima, Geman Federal Ministry for the Environment, Climate Action, Nature Conservation and Nuclear Safety, https://www.bmuv.de/themen/digitalisierung/kuenstliche-intelligenz/kuenstliche-intelligenz-fuer-umwelt-und-klima (accessed on 15 November 2024).

[62] BMUV (2024), Unsere Initiative “Green-AI Hub Mittelstand”, German Federal Ministry for the Environment, Climate Action, Nature Conservation and Nuclear Safety, https://www.bmuv.de/themen/digitalisierung/kuenstliche-intelligenz/kuenstliche-intelligenz-fuer-umwelt-und-klima/unsere-initiative-green-ai-hub-mittelstand (accessed on 15 November 2024).

[14] BMV (2023), Driving Progress with Data, German Federal Ministry of Transport, https://bmdv.bund.de/SharedDocs/DE/Anlage/K/driving-progress-with-data.pdf?__blob=publicationFile (accessed on 15 November 2024).

[15] BMV (2022), Digital Strategy - Creating Digital Values Together, German Federal Ministry for Digital and Transport, https://www.bmv.de/SharedDocs/EN/Documents/Press/pm-063-en-long-version.pdf?__blob=publicationFile (accessed on 15 November 2024).

[40] BMWi (2018), Guidance on Health Data Protection (Orientierungshilfe zum Gesundheits datenschutz), German Federal Ministry for Economic Affairs and Energy, https://www.bmwk.de/Redaktion/DE/Downloads/M-O/orientierungshilfe-gesundheitsdatenschutz.pdf?__blob=publicationFile&v=1 (accessed on 22 November 2024).

[17] BMWK (2025), AI Innovation Competition, German Federal Ministry for Economic Affairs and Energy, https://www.digitale-technologien.de/DT/Navigation/EN/ProgrammeProjekte/AktuelleTechnologieprogramme/Kuenstliche_Intelligenz/ai.html (accessed on 3 March 2025).

[26] BMWK (2025), KI-Innovationswettbewerb – Generative KI für den Mittelstand, German Federal Ministry for Economic Affairs and Energy, https://www.digitale-technologien.de/DT/Navigation/DE/Foerderaufrufe/KI-Innovationswettbewerb/ki-innovationswettbewerb.html (accessed on 3 March 2025).

[29] BMWK (2024), “European Digital Innovation Hubs in Deutschland”, https://www.mittelstand-digital.de/MD/Redaktion/DE/Artikel/Blog/blog-beitrag-43-die-european-digital-innovation-hubs.html (accessed on 3 March 2025).

[13] BMWK (2023), IPCEI Next Generation Cloud Infrastructure and Services, German Federal Ministry for Economic Affairs and Energy, https://www.bmwk.de/Redaktion/EN/Artikel/Industry/ipcei-cis.html (accessed on 14 November 2024).

[77] BMWK (2023), The Federal Government’s Lightweighting Strategy, German Federal Ministry for Economic Affairs and Climate Action, https://www.bmwk.de/Redaktion/EN/Publikationen/Schluesseltechnologien/the-federal-governments-lightweighting-strategy.pdf?__blob=publicationFile&v=3 (accessed on 4 March 2025).

[81] BMZ (2024), FAIR Forward – Künstliche Intelligenz für alle, German Federal Ministry for Economic Cooperation and Development, https://www.bmz.de/de/themen/digitalisierung/digitale-oeffentliche-gueter-und-infrastruktur/fair-forward-208812 (accessed on 15 November 2024).

[58] Civic Coding (2025), Civic Coding - Innovationsnetz KI für das Gemeinwohl, https://www.civic-coding.de/ (accessed on 4 March 2025).

[34] Civic Innovation Platform (2025), Über uns, https://www.civic-innovation.de/start (accessed on 4 March 2025).

[38] DAAD (2024), Konrad Zuse Schools of Excellence in Artificial Intelligence, Deutscher Akademischer Austauschdienst e.V., https://www.daad.de/en/the-daad/zuse-schools/ (accessed on 15 November 2024).

[46] DFG (2024), National Research Data Infrastructure, Deutsche Forschungsgemeinschaft, https://www.dfg.de/en/research-funding/funding-initiative/nfdi.

[30] DFKI (2024), Netzwerk der Deutschen Kompetenzzentren für Forschung zu Künstlicher Intelligenz, German Research Center for Artificial Intelligence, https://www.dfki.de/web/qualifizierung-vernetzung/netzwerke-initiativen/ki-kompetenzzentren (accessed on 15 November 2024).

[83] FNR (2024), T2O2-Regelung - Entwicklung und Dauererprobung einer vermarktungsfähigen Verbrennungsregelung zur Schadstoffminderung und Effizienzerhöhung in freistehenden Raumheizern nach DIN EN 13240 - Akronym: T2O2-Regelung, Fachagentur Nachwachsende Rohstoffe e. V., https://digitalisierung.fnr.de/projekte/projektuebersicht/projektuebersicht-details?fkz=22042318&cHash=8b0781c3b925e4c531d62f3b0a36640c (accessed on 15 November 2024).

[82] FNR (2024), Verbundvorhaben: Optimierung von Datenerfassung und Steuerungstechnik für Biomassefeuerungen; Teilvorhaben 2: technische Unterstützung und Softwareentwicklung - Akronym: DigitalF, Fachagentur Nachwachsende Rohstoffe e. V., https://www.fnr.de/index.php?id=11150&fkz=2219NR037 (accessed on 15 November 2024).

[22] Fraunhofer (2024), About Fraunhofer, https://www.fraunhofer.de/en/about-fraunhofer.html (accessed on 15 November 2024).

[23] Fraunhofer IAIS (2024), Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS, https://www.iais.fraunhofer.de/en.html (accessed on 15 November 2024).

[25] Fraunhofer IAO (2024), Fraunhofer Institute for Industrial Engineering IAO, https://www.iao.fraunhofer.de/en.html (accessed on 15 November 2024).

[24] Fraunhofer IPA (2024), Fraunhofer Institute for Manufacturing Engineering and Automation IPA, https://www.ipa.fraunhofer.de/en.html (accessed on 15 November 2024).

[8] Gaia-X (2024), About Gaia-X, https://gaia-x.eu/about/ (accessed on 15 November 2024).

[9] GCS (2024), About Us, Gauss Centre for Supercomputing, https://www.gauss-centre.eu/about-us (accessed on 15 November 2024).

[2] German Federal Government (2020), “Economic stimulus package: “An ambitious programme””, https://www.bundesregierung.de/breg-de/aktuelles/konjunkturpaket-1757482 (accessed on 15 November 2024).

[1] German Federal Government (2020), Strategie Künstliche Intelligenz der Bundesregierung - Fortschreibung 2020, https://www.ki-strategie-deutschland.de/files/downloads/201201_Fortschreibung_KI-Strategie.pdf (accessed on 15 November 2024).

[41] German Federal Government (2018), Artificial Intelligence Strategy of the Federal Government (Strategie Künstliche Intelligenz der Bundesregierung), https://www.bundesregierung.de/resource/blob/997532/1550276/3f7d3c41c6e05695741273e78b8039f2/2018-11-15-ki-strategie-data.pdf (accessed on 22 November 2024).

[5] hessian.AI (2024), About Us, Hessian Center for Artificial Intelligence, https://hessian.ai/about/ (accessed on 15 November 2024).

[20] INQA (2024), About INQA, Initiative New Quality of Work, https://www.inqa.de/DE/service/english/english.html (accessed on 25 November 2024).

[6] IT-Planungsrat (2020), Deutsche Verwaltungscloud-Strategie, https://www.cio.bund.de/SharedDocs/downloads/Webs/CIO/DE/digitale-loesungen/Deutsche_Verwaltungscloud_Strategie.pdf;jsessionid=8D437C431327CA597EF1410178BD36E2.live861?__blob=publicationFile&v=2 (accessed on 15 November 2024).

[79] KIDA (2024), KI- & Daten-Akzelerator, https://www.kida-bmel.de/ (accessed on 15 November 2024).

[57] KI-Ideenwerkstatt (2025), KI-Ideenwerkstatt für Umweltschutz, https://www.ki-ideenwerkstatt.de/ (accessed on 4 March 2025).

[39] KI-Observatorium (2025), Homepage, https://www.ki-observatorium.de/ (accessed on 4 March 2025).

[33] KI-Studios (2024), KI-Studios - Gemeinsam gestalten wir die Zukunft der Arbeit, https://www.ki-studios.ai/ (accessed on 15 November 2024).

[75] MDS (2025), Homepage, Mobility Data Space, https://mobility-dataspace.eu/de/ (accessed on 17 March 2025).

[42] MII (2024), Medical Informatics Initiative: Strengthening Research and Advancing Healthcare, Medical Informatics Initiative, https://www.medizininformatik-initiative.de/en/start (accessed on 22 November 2024).

[27] Mission KI (n.d.), Homepage, National Initiative for Artificial Intelligence and Data Economy, https://mission-ki.de/de.

[43] Netzwerk Universitätsmedizin (2025), The Network of University Medicine (NUM), https://www.netzwerk-universitaetsmedizin.de/en/about-us/network-of-university-medicine (accessed on 10 March 2025).

[47] NFDI4Health (2024), NFDI4Health National Research Data Infrastructure for Personal Health Data, https://www.nfdi4health.de/en/ (accessed on  `).

[28] NHR (2024), Nationales Hochleistungsrechnen, https://www.nhr-verein.de/ (accessed on 15 November 2024).

[76] nxtAIM (2025), Generative Methoden für Perzeption, Prädiktion und Planung, https://nxtaim.de/ (accessed on 4 March 2025).

[3] OECD (2024), OECD Artificial Intelligence Review of Germany, OECD Publishing, Paris, https://doi.org/10.1787/609808d6-en (accessed on 15 November 2024).

[31] Plattform Lernende Systeme (2024), Homepage, https://www.plattform-lernende-systeme.de/home-en.html (accessed on 15 November 2024).

[63] RKI (2025), Centre for Artificial Intelligence in Public Health Research, Robert Koch Institute, https://www.rki.de/EN/Institute/Organisation/Departments/ZKI-PH/zki-ph-centre-for-artificial-intelligence-in-public-health-research-node.html (accessed on 10 March 2025).

[78] Silicon Economy (2025), Homepage, https://www.silicon-economy.com/ (accessed on 17 March 2025).

[44] TEDHAS (2024), Country Visit – Germany, Towards European Health Data Space, https://tehdas.eu/app/uploads/2023/03/germany-country-visit-factsheet-final.pdf.

[61] UBA (2024), UBA Application Lab for AI and Big Data - The AI Lab at the German Environment Agency, German Environmental Agency, https://www.umweltbundesamt.de/en/topics/digitalisation/uba-application-lab-for-ai-big-data (accessed on 15 November 2024).

[32] Zukunftszentren (2024), Homepage, https://zukunftszentren.de/ (accessed on 15 November 2024).

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