Funding

Funding by the Federal Government

Sufficient public funding for AI promotion measures is necessary to continue establishing Germany as a location where AI is researched, applied and transferred. To this end, additional financial resources have been made available since 2019, particularly as part of the German government's AI strategy. The German Federal Government has invested an additional €3.01 billion in specific AI projects in Germany. Of this amount, €1.97 billion have already been spent on the projects that for the most part are perennial.

Additional investment in AI funding by the Federal Government since 2019 (as of January 2024)

Source & data collection: Data provided by the Federal Ministry of Education and Research (BMBF).

Presented by Plattform Lernende Systeme

Research | Skills

Professorships funded by Federal Government

The funding of 150 additional professorships on AI in Germany secures and institutionalizes research and teaching on AI in the academic landscape. The establishment of the professorships is part of the German Federal Government's AI strategy.

150 additional professorships on AI funded (since 2019); of these, 38 filled by women & 54 appointed from abroad (as of July 2024)

  • Distribution of professorships on AI
  • 18 Alexander von Humboldt professorships
  • 24 professorships at the 5 German Centres of Excellence for AI Research
  • 85 professorships via the Tenure-Track programme
  • 8 professorships via German Research Foundation (DFG) programs
  • 15 professorships in cooperations between non-university research institutions and universities

Sponsored by the Federal Ministry of Education and Research (BMBF)

Distribution of the 150 professorships on AI among 49 German universities

Source & data collection: Researched and presented by Plattform Lernende Systeme

Research

Publications and citations

When assessing Germany as a research location, the number of scientific articles published on AI by researchers at German universities and institutes is crucial. Furthermore, it is also important how often other researchers worldwide cite from these publications. This reveals not only the relevance of the research location, but also its interconnectedness in an international context.

Scientific articles on AI

  • Total number

  • Per 10 million inhabitants

Number of articles

Number of articles

From which countries/regions do scientific articles on AI come from that researchers worldwide cite the most?

Article origin (in percent)

Source & data collection: OECD AI Index; based on data from Elsevier (Scopus).

Scientific articles published by authors in the respective country are measured. In the case of co-authorship from different countries/regions, the articles are counted proportionally. To improve international comparability, the number of articles is set in relation to the population (articles per 10 million inhabitants). Citations are measured by the extent to which AI publications from the respective states/regions are cited by other researchers. The given year indicates the year of publication of the article, not the year of citation. Figures are rounded; calculated and presented by Plattform Lernende Systeme.

Figures are rounded; calculated and presented by Plattform Lernende Systeme

Research

German Centres of Excellence for AI Research

In addition to numerous institutions conducting research on AI, to strengthen the exchange between scientists in Germany, there exists a nationwide network of six leading AI research institutions at eleven locations. The resulting cooperation leverages synergies and increases international visibility. This network of cutting-edge research constitutes a cornerstone for the development of AI-technologies. The German Centres of Excellence for AI Research are funded by the German Federal Government and the federal states.

Nationwide network of six German Centres of Excellence for AI Research at eleven locations

Source & data collection: Researched and presented by Plattform Lernende Systeme

Skills

Learning opportunities at high schools

In Computer Science lessons at school, young people can learn about the basics of digital transmission and processing of data. A fundamental understanding of Computer Science at a young age can be a foundation for later involvement (in studies, research, and work) with AI. Thus, the teaching of relevant material at school is central to the dissemination of AI skills in society and economy.

Computer Science as a subject in German high schools (as of 2024)

Source & data collection: Informatik-Monitor by German Informatics Society.

Only grade 5 and higher grades are taken into account; no Computer Science classes are offered below this grade level in Germany.

Presented by Plattform Lernende Systeme

Transfer

Grant programs for SMEs

In order to support the transfer from AI research to AI application, the German Federal Government and the federal states have set up 44 different programs. Small and medium-sized enterprises (SMEs) in Germany have access to a variety of public programs giving advice on the application of AI. This interlinkage of science and economy is particularly relevant for the successful implementation of AI technologies.

Promotion of AI transfer in SMEs through 39 grant programs nationwide (as of July 2024)

  • 23 programs of the Federal Government

  • 16 programs of the federal states

  • Funding programs
  • Funded by
  • Duration
  • Link
  • Technology Transfer Program Lightweight Construction (TTP LB) - Funding for research, development and innovation
  • Federal Ministry for Economic Affairs and Climate Action (BMWK)
  • 10/01/2027
  • KMU-innovativ: Electronics and autonomous driving/high performance computing
  • Federal Ministry of Education and Research (BMBF)
  • 06/30/2027
  • Secure future technologies in a hyper-connected world: Artificial Intelligence
  • Federal Ministry of Education and Research (BMBF)
  • 06/30/2027
  • KMU-innovativ: Biomedicine
  • Federal Ministry of Education and Research (BMBF)
  • 06/30/2027
  • Funding for microelectronics research by joint venture partners within the KDT framework
  • Federal Ministry of Education and Research (BMBF)
  • 06/30/2027
  • KMU-innovativ: Information and communication technology (ICT) - communication systems and IT security (CIS)
  • Federal Ministry of Education and Research (BMBF)
  • 10/15/2025
  • ICT for Electromobility: economical e-utility vehicle applications and infrastructures
  • Federal Ministry for Economic Affairs and Climate Action (BMWK)
  • 06/30/2026
  • Transformation cluster Social innovations for sustainable cities
  • Federal Ministry of Education and Research (BMBF)
  • 06/30/2027
  • "Computational Life Sciences - Digital methods for researching post-acute infection syndromes"
  • Federal Ministry of Education and Research (BMBF)
  • 06/30/2027
  • Projects within the European EUREKA cluster
  • Federal Ministry of Education and Research (BMBF)
  • 06/30/2024
  • mFund
  • Federal Ministry for Digital and Transport (BMDV)
  • 12/31/2022
  • Future centers - supporting small and medium-sized enterprises and employees in the (further) development and implementation of innovative design approaches to master the digital transformation
  • Federal Ministry for Labour and Social Affairs (BMBF)
  • 12/31/2027
  • Horizon Europe - Framework Program for Research and Innovation (2021-2027)
  • EU-Büro des BMBF
  • 12/31/2027
  • InvestEU (2021–2027)
  • European Commission
  • 12/31/2027
  • Go-digital
  • Federal Ministry for Economic Affairs and Climate Action (BMWK)
  • 12/30/2024
  • ERP Digitisation and Innovation Loan
  • Kreditanstalt für Wiederaufbau (KfW)
  • Unlimited for now
  • Artificial Intelligence for the public welfare
  • Federal Ministry of Family Affairs, Senior Citizens, Women and Youth (BMFSFJ)
  • 12/31/2025
  • Digital Europe Programme
  • European Commission
  • 12/31/2026
  • Development of digital technologies
  • Federal Ministry for Economic Affairs and Climate Action (BMWK)
  • 06/30/2026
  • Autonomous and connected driving in public transport systems
  • Federal Ministry for Digital and Transport (BMDV)
  • 12/31/2026
  • KMU-innovativ: Information and communication technology (ICT) - software-intensive systems (SWS)
  • Federal Ministry of Education and Research (BMBF)
  • 06/30/2027
  • DeepTech & Climate Fonds (DTCF)
  • Future Fund / Various
  • 12/31/2029
  • Artificial Intelligence for a more sustainable agriculture
  • Federal Ministry of Food and Agriculture (BMEL)
  • 12/31/2023
  • Funding programs
  • Funded by
  • Duration
  • Link
  • Invest BW – Innovation II
  • Baden-Württemberg
  • 12/31/2027
  • Digitisation Bonus Plus - Loan option
  • Ministerium für Wirtschaft, Arbeit und Tourismus Baden-Württemberg & L-Bank
  • 12/31/231
  • ProDigital
  • Ministerium für Wirtschaft, Wissenschaft und Digitale Gesellschaft Thüringen
  • 12/31/2024
  • Digitisation & ultra efficiency
  • Ministerium für Umwelt, Klima und Energiewirtschaft Baden-Württemberg
  • 12/31/2024
  • DigiBoost
  • Investitions- und Strukturbank Rheinland-Pfalz
  • 12/31/2024
  • Games BW
  • MFG Baden-Württemberg
  • 06/30/2025
  • Bavarian Collaborative Research Program (BayVFP) - Digitization
  • Bayern Innovativ – Bayerische Gesellschaft für Innovation und Wissenstransfer mbH
  • 12/31/2025
  • Potential consultation
  • Ministerium für Arbeit, Gesundheit und Soziales Nordrhein-Westfalen
  • 12/31/2027
  • NEXT.IN.NRW - Innovative ideas, services and products from culture, media, creative industries, AI and ICT
  • Bavarian Ministry of Economic Affairs, Regional Development and Energy
  • 2027
  • Promoting sustainable regional development through innovation systems and sustainability (EFRE - RegioWIN2030)
  • L-Bank Staatsbank für Baden-Württemberg
  • 12/31/2029
  • Promotion the expansion of business-related research infrastructure and technology transfer, validation of research results and of business start-ups (EVI PLUS 2021-2027)
  • L-Bank Staatsbank für Baden-Württemberg
  • 12/31/2029
  • SME Innovative and Digital (MID) - Vouchers
  • North Rhine-Westphalia
  • Unlimited for now
  • Distr@l - Strengthening digitisation, living the transfer: Feasibility studies
  • Hamburgische Investitions- und Förderbank
  • Unlimited for now
  • Distr@l - Strengthening digitisation, living the transfer: Digital innovation projects
  • Hamburgische Investitions- und Förderbank
  • Unlimited for now
  • Distr@l - Strengthening Digitisation, living the transfer: Knowledge and transfer projects on digitisation
  • Hamburgische Investitions- und Förderbank
  • Unlimited for now
  • Distr@l - Strengthening digitisation, living the transfer
  • Hamburgische Investitions- und Förderbank
  • Unlimited for now

In order to support the transfer from AI research to AI application, the German Federal Government and the federal states have set up different programs. Small and medium-sized enterprises (SMEs) in Germany have access to a variety of public programs giving advice on the application of AI. This interlinkage of science and economy is particularly relevant for the successful implementation of AI technologies.

Source & data collection: This list covers active grant programmes for SMEs. Their application deadline may have already expired. Also covered are digitisation programmes under which SMEs can apply with AI projects.

Researched and presented by Plattform Lernende Systeme

Transfer

AI patents

AI patents are both the foundation and the consequence of successful research and application of AI technologies. The number of new patents filed worldwide by scientists from Germany is directly indicative for the country as a location of innovation and for the know-how generated there.

Newly filed AI patents

  • Total number

  • Per 10 million inhabitants

Newly filed AI patents

Newly filed AI patents

Source & data collection: Fraunhofer Institute for Systems and Innovation Research; based on data from the World Patents Index; also: Federal Statistical Office of Germany.

AI patents newly filed by scientists working in the respective countries or regions are taken into account. Since new filings are published with a delay of up to 18 months, data can only be presented with a corresponding delay. Second filings are not counted. To improve international comparability, the number of patent filings is set in relation to the population (patent filings per 10 million inhabitants).

Figures are rounded; calculated and presented by Plattform Lernende Systeme

Transfer

Publicly funded Transfer Hubs

Numerous institutions in Germany support the transfer of AI innovations from research to application. These Transfer Hubs offer companies of different sizes tailor-made consulting, support in AI application and a networking with the scientific community. This interlinkage of science and economy is particularly relevant for the successful implementation of AI technologies.

125 publicly funded transfer hubs on AI in Germany (as of 2024)

  • Transfer Hubs
  • Focus
  • Funding
  • 20 Mittelstand-Digital Innovation Hubs
  • Digitisation, SMEs
  • BMWK
  • 14 Zukunftszentren
  • Competencies, employees, self-employees
  • BMAS
  • 12 Digital Hubs
  • Startups, investors
  • BMWK
  • 8 Regional Competence Centres for Labour Research
  • Labour, technological development
  • BMBF
  • 6 Digital Hubs on Health
  • Health, data
  • BMBF
  • 3 International Labs on AI
  • Internationalisation
  • BMBF
  • 4 AI Service Centres
  • Competencies, IT infrastructure
  • BMBF
  • AI Application Hub on Plastic Packaging
  • Sustainability, circular economy
  • BMBF
  • 57 other Transfer Hubs
  • Digitisation, SMEs
  • Federal Government, federal states, EU

Source & data collection: researched and presented by Plattform Lernende Systeme

Research | Skills

Junior research groups on AI

To strengthen young scientists in AI research, the German Federal Ministry of Education and Research (BMBF) and the German Research Foundation (DFG) are funding 56 Junior Research Groups across Germany. These consist of young researchers. The Junior Research Groups focus on novel and innovative AI topics. In addition, the scientists in these groups have the opportunity to expand their research profile and their scientific visibility.

Overview of the 56 Junior Research Groups on AI (as of July 2024)

  • 41 BMBF-funded Junior Research Groups

  • 15 DFG-funded Junior Research Groups

  • Junior Research Group/Project
  • Project coordination
  • AI for eye tracking data (AEye)
  • University of Potsdam
  • Computer-assisted rhetoric in social media and law (CAROLL)
  • University of Passau
  • Data driven methods in control engineering (DART)
  • Paderborn University
  • Dynamical processing of natural language for discourse analysis (DynSoDa)
  • Philipps-Universität Marburg
  • Digital deliberation processes (E-DELIB)
  • University of Stuttgart
  • Empathic AI (EKI)
  • Hasso-Plattner-Institut für Digital Engineering Potsdam
  • AI-assisted decision making for business management processes (EP-KI)
  • Fraunhofer Institute for Industrial Mathematics Kaiserslautern
  • Transparency and efficiency through AI (Explaining 4.0)
  • Technische Universität Berlin
  • Graphs in neuronal networks (GAIN)
  • University of Kassel
  • Hybridisation of intelligence in knowledge work (HyMeKI)
  • Universität Hamburg
  • Interactive AI (IKIDA)
  • Technical University of Darmstadt
  • AI in biodiversity research (KI4Biodiv)
  • Max Planck Institute for Biogeochemistry Jena & Technische Universität Ilmenau
  • Intelligent spectrum sharing (MABISS)
  • Technische Universität Berlin
  • Model-based Deep Learning for computer vision problems (MoDL)
  • Fraunhofer Institut for Telecommunication Berlin
  • Navigation approaches to answer sets (NAVAS)
  • Technische Universität Dresden
  • Public interest AI (PI-AI)
  • Alexander von Humboldt Institute for Internet and Society Berlin
  • Quantitative video displaying for behavioural studies (QuantVID)
  • University of Cologne
  • Seismology and AI (SAI)
  • Frankfurt Institute for Advanced Studies
  • Fast algorithms for transparent recommendation systems (SAIE)
  • University of Technology Chemnitz & Technische Universität Berlin
  • Distinguishing between style and theme in text data (SeDis)
  • Johannes Gutenberg University Mainz
  • Extraction of knowledge from scientific publications (SCINEXT)
  • University Library Hannover
  • Hybrid AI architecture in critical infrastructures (ARL)
  • Carl von Ossietzky University of Oldenburg
  • Machine learning in complex systems under uncertainty (FEAT)
  • Eberhard Karls University of Tübingen
  • Self-learning dynamic moving of mobile robots (DynaFoRo)
  • Fraunhofer Institute for Material Flow and Logistics
  • Transparent decision making support through interpretable AI models (White-Box-AI)
  • Friedrich-Alexander-Universität Erlangen-Nürnberg
  • Scaling the inverse approach to image analysis (IRRW)
  • Friedrich-Alexander-Universität Erlangen-Nürnberg
  • Artificial cognitive imaging (ACONITE)
  • Max Planck Institute for Human Cognitive and Brain Sciences Leipzig
  • Bioacoustic monitoring for the protection of animal species and habitats (BirdNET-Plus)
  • Chemnitz University of Technology
  • Quantification of uncertainties in the forecasting of time series (EQUIPE)
  • Karlsruhe Institute of Technology
  • Platform based on fanned out feature spaces (FFS-AI)
  • University of Potsdam
  • Generative precision networks for particle physics (GPN42P)
  • Heidelberg University
  • Multimodal tutoring system in distance education and training (HyTea)
  • Leibniz Institute for Research and Information in Education Frankfurt am Main
  • Evaluation metrics for text generation systems (Metrics4NLG)
  • Bielefeld University
  • Automated modelling and validation of dynamic systems (ML-Expert)
  • Paderborn University
  • Multicriteria Machine Learning (MultiML)
  • Paderborn University
  • Generation and pedagogical use of natural language (Polke)
  • University of Tübingen
  • Learning algorithms for a smart energy system (RL4CES)
  • University of Kassel
  • Self-learning composition of spatio-temporal information (STCL)
  • Goethe University Frankfurt am Main
  • Understanding and modelling complex systems (Themis)
  • University of Rostock
  • Learning adaptive skills for intelligent autonomous agents (TriFORCE)
  • Technical University of Darmstadt
  • Uncertainty quantification and efficient annotation processes (UnrEAL)
  • University of Wuppertal
  • Junior Research Group/Project
  • Project coordination
  • Harmonic AI based on linear operators
  • Technical University of Munich
  • Robust computer vision with 3D-aware network architecture
  • University of Freiburg
  • Theory and practice of graph embedding
  • RWTH Aachen University
  • Trustworthy reinforcement learning for multi-agent systems
  • Max Planck Institute for Software Systems Saarbrücken
  • Robot autonomy in human-centered environments
  • University of Freiburg
  • Foundations of lifelong reinforcement learning
  • University of Tübingen
  • Eidetic representations of natural language
  • Humboldt-Universität Berlin
  • Resource-efficient Machine Learning
  • University of Tübingen
  • Response consistency for machine vision
  • University of Tübingen
  • Mobile manipulation for intelligent assistance
  • Technical University of Darmstadt
  • Motion coordination for heterogeneous aerial swarms
  • Technische Universität Berlin
  • Intuitive robot intelligence
  • Karlsruhe Institute of Technology (KIT)
  • Decision making based on physics knowledge
  • University of California Berkeley
  • Approximation algorithms for geometric data analysis
  • Heinrich-Heine-Universität Düsseldorf
  • Stability and solvability in Deep Learning
  • Catholic University of Eichstätt-Ingolstadt

Source & data collection: Researched and presented by Plattform Lernende Systeme

Skills

Study programs related to AI

A wide selection of study programs that focus primarily or at least in several modules on AI or Data Science allows interested students in Germany to receive scientific training in these fields. They are the next generation of AI research and AI application.

Source & data collection: Map on AI by Plattform Lernende Systeme; based on data from the Higher Education Compass offered by German Rectors' Conference (HRK) & on research by Plattform Lernende Systeme.

The analysis includes study programs that fully or partially focus on AI or on Data Science. Only state or state recognized universities are listed. The data is continuously updated by reviewing relevant publications. Due to deviations in analysis and its frequency, the number of study programs listed may differ from numbers in HRK's Higher Education Compass.

Presented by Plattform Lernende Systeme

Skills

Professionals' AI skills

For AI to be successfully applied in German companies, an important prerequisite is that the companies’ employees have a basic understanding of AI. The dissemination of AI skills is therefore relevant both for the individual training level of employees and for the companies’ ability to compete nationally and internationally.

Proportion of employees with AI Skills

Proportion of employees (in percent)

Source & data collection: OECD AI Index; based on the LinkedIn Economic Graph.

Here, the prevalence of AI skills among employees is measured. The index is based on information provided by useres of the social network LinkedIn on AI skills or on their employment at respective companies. The index shows the ratio of LinkedIn users with AI skills to all LinkedIn users in a certain country.

Figures are rounded; presented by Plattform Lernende Systeme

Transfer

AI startups

The number of new AI startups and the investment in them are indicators when observing the AI startup scene in Germany. The relevance of AI for the business models of young companies and the crucial role of startups in the application of AI is made visible. The performance of startups and the level of trust in them can be measured based on the private investment in young companies in the AI sector. In Germany, 502 AI startups have been founded in the past ten years. Private investment in young AI companies amounted to $2,16 billion in 2023.

Newly founded AI startups and private investment in AI startups (since 2013)

  • Newly founded AI startups in Germany

  • Private investment in German AI startups

Newly founded AI start-ups

Investment (in Mio. Dollar)

Source & data collection: OECD AI Index; based on data by Preqin

The German AI Startup Landscape records newly founded startups in Germany whose activities are related to Machine Learning. Primarily, startups are inlcuded that apply and/or develop AI. Startups newly founded in the most current year may be underrepresented and will be leveled in follow-up surveys. The Stanford AI Index measures the private investment in German AI startups.

Figures are rounded; presented by Plattform Lernende Systeme