The OECD review of Germany's AI ecosystem evaluates its strengths, weaknesses, opportunities, and threats, highlighting successes in attracting AI talent and maintaining a strong research base, while noting challenges in AI adoption among firms. Recommendations include updating the national AI strategy, leveraging AI for public sector efficiency and environmental goals, and enhancing data access and entrepreneurial support. The report calls for improved training and consultation on AI skills to address workforce demands and barriers to adoption.

1. OECD Artificial Intelligence
Review of Germany
11 June 2024
Jerry Sheehan,
STI Director
Stefano Scarpetta,
ELS Director

2. Overview and methodology
• Provide an international
benchmarking of the German AI
ecosystem and discuss
implementation of the national AI
strategy
• Data from OECD.AI Policy
Observatory, AI-WIPS, over 90
interviews
• Analysis along the pillars of the
national AI strategy
• Three sector spotlights on AI in the
public sector, AI and environmental
sustainability and AI and healthcare.
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3. Where does Germany stand today in AI?
S W
O T
Germany’s AI
ecosystem
3

4. Strengths
4

5. Capacity to attract international AI talent in business
and academia
German companies
have been able to
attract and retain
workers with AI skills
internationally in recent
years: more
AI-skilled workers are
coming into the country
than are leaving it.
The target included in
the national AI strategy
to attract academic
talent was achieved
ahead of the set
timeline: 150 additional
professorships on AI
were funded by 2023.
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6. Strong research base in AI
Germany ranks fifth
internationally in number
of AI publications, fourth
when considering
publication quality.
Public and private
German institutions rank
in top positions for the
quality of
their AI research: the Max
Planck Society ranks
second worldwide
alongside the University
of California
Berkeley, while Siemens
ranks seventh among
leading global companies
producing AI research.
Source: OECD.AI (2023), AI Research Publications Time Series by Country, visualization powered by JSI, using data from OpenAlex,
www.oecd.ai.
Figure 3.1 AI research publications by country
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7. Solid AI compute capacity in the research sector
Source: Figure produced using data from TOP500 (2023), The List, https://www.top500.org/ (accessed on 15 November 2023).
Germany ranks high in
terms of national
supercomputing capacity,
namely for computing
applications in science,
research, and academia.
The Gauss Centre for
Supercomputing – also
part of EuroHPC -
combines the three
largest national
supercomputing centres
in
Germany into the
country’s leading
supercomputing
institution.
Figure 4.10 Number of supercomputers by country
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8. Weaknesses
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9. AI use by firms lower than in EU frontrunners
In 2023, 12% of
German firms used
AI, above the EU27
average of 8%, but
below EU countries at
the forefront in AI
adoption, including
for large firms.
Challenges reported
by firms for wider
adoption include skill
shortages, data
protection concerns,
low digitalisation, and
limited awareness of
AI use cases.
Source: Eurostat (2023[2]), Digital Economy and Society Database, https://ec.europa.eu/eurostat/databrowser/explore/all/science?lang=en&su
btheme=isoc&display=list&sort=category.
Figure 4.1 Firms using at least one AI system in EU selected countries
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10. Limited availability of open government data
Germany lags
considerably in open
government data
availability and support
to data re-use, even
though data
accessibility is
relatively high.
Industrial data are also
reported to be largely
underutilized.
Source: OECD (2023[36]), 2023 OECD Open, Useful and Re-usable data (OURdata) Index: Results and key findings,
https://doi.org/10.1787/a37f51c3-en..
Figure 8.1 Open government data availability, re-use and accessibility in OECD countries
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11. Limited availability of risk capital
The number of AI start-
ups in Germany has
increased significantly in
the past 15 years, with
41.5% of them originating
in academia.
Despite increase in VC
investments in recent
years, Germany still lags
significantly behind
leading countries. The
country is relatively well
positioned in the EU27,
but the UK, Israel and
India attract higher VC
investments in AI. Source: OECD.AI (2023), Worldwide VC Investments in AI, visualisations powered by JSI using data from Preqin, www.oecd.ai.
Figure 4.10 Venture Capital investments in AI start-ups in selected countries
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12. Opportunities
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13. A turning point in AI adoption?
Source: ifo Institute (2023), “Artificial intelligence in use at 13.3% of companies in Germany”, https://www.ifo.de/en/facts/2023-08-
02/artificial-intelligence-use-companies.
Recent national
surveys show
that German
firms increasingly
use or plan to use
AI solutions,
including in the
manufacturing
sector, possibly
due to
developments in
generative AI and
to labour
shortages.
Figure 4.3. AI current and planned use in German firms
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14. AI can support rapid decarbonisation in key sectors
Several initiatives in the German AI ecosystem leverage AI for rapid decarbonization across sectors
Figure 9.1
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15. Threats
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16. The economic, geopolitical and technological
context has radically changed
• The United States and China are the worldwide AI powerhouses
and India is quickly catching up on AI research.
• Heightened types of ethical concerns related to AI with the
potential to threaten people’s trust in AI.
• Risk of insufficiently exploiting AI's potential for Germany's
international competitiveness, prosperity, and social cohesion.
• AI has considerable environmental impacts, such as energy
consumption and water use.
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17. Key recommendations
Keep sight of the bigger picture: Germany’s national AI strategy could be
updated to target sectors where AI is expected to have the strongest impact.
Leverage AI to cut red tape in the public sector, reach healthcare and
environmental objectives, and secure industrial competitiveness.
Secure buy-in at the highest political level and harmonise policy efforts in
adjacent areas.
Involve and inform citizens and workers.
Attention should focus on three strategic enablers:
Widen access to data.
Nurture the next generation of AI entrepreneurs.
Build and scale a globally competitive computing infrastructure.
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18. AI and the World of Work
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19. Where does Germany stand today in AI and work?
S W
O T
World of
Work
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• Positive attitude towards
AI in the workplace
• Talent bottlenecks
• Expanding consultation for
more inclusive policy
• Risks for the safety and
rights of workers

20. Demand for AI skills in Germany is relatively low
but growing
20
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Mean (2019 to 2022) 2019 2022
Percentage of online vacancies advertising positions requiring AI skills, by country
Notes: The figure shows the total number of online vacancies requiring AI skills relative to all vacancies advertised in a country. Vacancies requiring AI skills are vacancies in which at
least two generic AI skills or at least one AI-specific skill were required on generic and specific skills). Countries are sorted in descending order by the highest average share across
2019 to 2022 of vacancies requiring AI skills. Average refers to the average across countries with available data.
Source: Borgonovi, F. et al. (2023[13]), “Emerging Trends in AI Skill Demand Across 14 OECD Countries”, https://doi.org/10.1787/7c691b9a-en.

21. Note: Data based on the following question to employers : “I’m going to list a few potential barriers to the adoption of artificial intelligence. In each case, please tell me whether it has ever
been a barrier to adopting artificial intelligence in your company: High costs/Lack of skills to adopt artificial intelligence/Government regulation/Not convinced by the technology/Any other
barriers not previously mentioned”. Source: Lane, M., M. Williams and S. Broecke (2023[2]), “The impact of AI on the workplace: Main findings from the OECD AI surveys of employers and
workers”, https://doi.org/10.1787/ea0a0fe1-en
Lack of skills is a key barrier to AI adoption
21
0
10
20
30
40
50
60
70
UK France Canada Ireland Austria Germany USA
Lack of skills Cost Government Regulation Not convinced by technology
Share of employers who cite the following reasons as barriers to the adoption of AI, 2022

22. 0
10
20
30
40
50
60
70
Productivity Satisfaction Management Health and
safety
%
Consultation (↘) No consultation
B. Positive impact of AI on selected outcomes
% of employers, by consultation
0
10
20
30
40
50
60
70
80
90
100
UK Ireland Germany Average Canada Austria US France
% Consultation (↘) No consultation Don't know
A. Consultation with workers or worker representatives
% of employers that have adopted AI, by country
The positive impact of workers' consultation
22

23. Recommendations
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• Strengthen information collection on the supply and demand of AI skills
• Promote education and training opportunities in AI through PES and career guidance
• Increase flexibility and modularity of adult learning
• Incentive for employers to provide AI-related training
• Encourage co-creation, consultation and co-operation with social partners, works councils
and employees
• Foster AI-related knowledge in the workplace and secure external expertise when relevant
• Monitor and fill policy gaps for a trustworthy use of AI in the workplace

24. Learn more
Read the report – English
Den Bericht lesen – Deutsch
https://oecd.ai/
Follow us on LinkedIn @OECD.AI
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