Focus Indicators

SMEs: small and medium-sized enterprises, i.e. enterprises with fewer than 250 employees

Large enterprises: enterprises with 250 or more employees

Figures expressed as a percentage of all innovation-active SMEs or all innovation-active large enterprises

Partners in the science and R&D sector:

• Higher education institutions: public and private universities, universities of applied sciences and other higher education institutions
• Non-university research institutions: research institutions receiving core funding from the state or institutional funding, such as Helmholtz Centres, Fraunhofer Institutes, Max Planck Institutes, Leibniz Institutes, and federal and state research institutions
• Consultants, private R&D service providers: enterprises offering scientific and technical services

Figures expressed as a percentage of all enterprises engaged in innovation cooperations

Partners along the value chain:

• Customers: private or public customers or end-users of the enterprise's products
• Suppliers: enterprises and organisations that supply goods or services
• Competitors: enterprises operating in the same sales market or sector

Figures shown as a percentage of all enterprises engaged in innovation cooperations

Support for innovation:

financial support for innovation activities (including R&D activities) provided by the public sector, e.g. through grants, subsidies, loans, subsidy payments, equity investments or loan guarantees, including support provided by commissioned institutions (project management organisations, development banks), but excluding tax incentives such as the research allowance. The routine payment of contracts by public contracting authorities is not regarded as public funding.

Expressed as a percentage of all enterprises engaged in innovation

Funding bodies:

• State: State ministries and bodies commissioned by state governments, such as state banks
• Federal: Federal ministries and bodies commissioned by the Federal Government, including KfW
• EU: EU funding programmes (e.g. Horizon) and other European programmes (e.g. Structural Funds programmes, ESA)

Figures given as a percentage of all enterprises receiving public financial support

SMEs: small and medium-sized enterprises, i.e. enterprises with fewer than 250 employees

Large enterprises: enterprises with 250 or more employees

Data collected only for the reporting years 2008, 2014, 2020, 2022 and 2024.

Figures are expressed as a percentage of all SMEs or all large enterprises

Environmental innovations in process areas (selection):

• Reduction in energy consumption: 
  Reduction in energy input per unit produced or per service operation
• Reduction in material consumption: 
  Reduction in material input per unit produced or per service operation
• Reduction in CO₂ emissions: 
  Reduction in CO₂ emissions per unit produced or per service operation

Data collected only for the reporting years 2008, 2014, 2020, 2022 and 2024.

Figures given as a percentage of all enterprises

Environmental innovations in product areas (selection):

• Improvement in energy efficiency/overall CO₂ footprint: products with lower specific energy consumption, products with lower CO₂ emissions over their entire life cycle (manufacture, use, disposal)
• Improvement in recyclability: improvement in the reusability and suitability for the circular economy of products
• Increasing service life/durability: Extending the service life of products; reducing the need for product repairs

Data collected only for the reporting years 2008, 2014, 2020, 2022 and 2024.

Figures given as a percentage of all enterprises

Financing-Related Obstacles to Innovation: 

• Excessive risk associated with the innovation project
• Excessive costs of the innovation project
• Lack of internal funding for innovation projects
• Lack of external funding for innovation projects

Data collected only for the reporting years 2006, 2010, 2014, 2018 and 2022.

Figures given as a percentage of all enterprises

Personnel- and Organisation-Related Obstacles to Innovation: 

• Internal resistance to innovation projects
• Organisational problems in the implementation and execution of innovation projects
• Shortage of qualified staff to implement innovation projects

Data collected only for the reporting years 2006, 2010, 2014, 2018 and 2022.

Figures given as a percentage of all enterprises

Market-Related Obstacles to Innovation: 

• A lack of technological information required to implement innovation projects
• A lack of market information required to implement innovation projects
• A lack of demand or insufficient customer acceptance of the results of innovation projects
• Market dominance by established companies hinders the adoption or implementation of innovation projects

Collected only for the reporting years 2006, 2010, 2014, 2018 and 2022.
* Not collected for 2018

Figures given as a percentage of all enterprises

Legal or Administrative Obstacles to Innovation: 

• Laws and regulations
• Lengthy administrative procedures
• Standards and norms
• Lack of access to intellectual property rights

Data collected only for the reporting years 2006, 2010, 2014, 2018 and 2022.
* For 2018, the question was phrased differently

** Not collected for 2006

Figures shown as a percentage of all enterprises

AI techniques used:

• Speech recognition, text generation
• Image/pattern recognition, image processing
• Machine learning for data analysis
• Automation, autonomous systems
• Knowledge-based systems, decision support

* Not surveyed for 2019 and 2021

Figures given as a percentage of all enterprises using AI

Area of application:

• Products and services
• Processes (production, service delivery) and logistics
• Sales, marketing (including customer communication)
• IT systems, administration
• Other areas

* Not surveyed for 2019

Figures shown as a percentage of all enterprises using AI

AI developers:

• Primarily the company using the AI itself
• Primarily third parties, such as software enterprises or providers of AI solutions
• Both the company itself and third parties, either through cooperation or because certain AI used by the company was developed in-house whilst other AI used was developed by third parties

Not surveyed for 2021

Figures as a percentage of all companies using AI

Use of generative AI:

The use of AI models to generate new content based on data from which the models have been trained. Enterprises can use generative AI as part of their wider AI deployment in products and processes, or independently of this, for example through employees’ independent use of generative AI.

Percentage of all enterprises

Protection Rights for Intellectual Property:

• Patents
• Utility models
• Designs
• Trade marks
• Copyright
• Protection of trade secrets

Data collected only for the reporting years 2014, 2020 and 2024

Figures shown as a percentage of all enterprises