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AI in the High-Tech Agenda Germany

Download of the HTAD (German)

Through the High-Tech Agenda Germany (HTAD), the German government is bringing its research and innovation policies together. Artificial intelligence is one of six key technologies and plays a central role in competitiveness and sovereignty. Plattform Lernende Systeme demonstrates what this means in practice.

  • Context:
    High-Tech Agenda Germany

  • Objectives of the High-Tech Agenda in the field of AI

  • Strengths, weaknesses, opportunities and risks

  • Key measures and funding instruments

  • Implementation of the AI focus areas

  • AI and other key technologies

The High-Tech Agenda Germany (HTAD) is the German Government’s central strategic framework for research and innovation policy.

The HTAD, adopted in July 2025, sets out the guidelines according to which Germany will shape its technological future. It addresses three key questions:

  1. In which areas should Germany be a technological leader?
  2. How can competitiveness be secured in the long term?
  3. And how can the country maintain its autonomy in key technologies?

Artificial intelligence is one of six key technologies anchored in the HTAD. As a cross-cutting technology, AI permeates almost all sectors, from industrial production and healthcare to mobility and public administration.

The High-Tech Agenda for Germany builds on and further implements the overarching objectives previously set out in the Federal Government’s National AI Strategy.

The HTAD has set itself ambitious goals for AI in the fields of business, technology and society. At the heart of this is a clear objective:

Objective 1

By 2030, around 10 percent of Germany’s economic output is set to be supported by or directly generated through AI. Germany is set to become a leading centre for the development and application of AI. Labour productivity is set to increase, and artificial intelligence is set to become an important tool in key areas of research and application.

Objective 2

Science, research, business, public administration and society are to be given measurably better access to AI resources such as algorithms, data, computers, software tools and AI chips, so that they can make use of them. To this purpose, for instance, one of the European AI gigafactories is to be established in Germany.

Objective 3

Germany is set to become a key player in the next generation of AI and in global competition. Therefore, plans include strengthening and linking leading AI research centres and launching funding programmes.

Table presenting the strengths, weaknesses, opportunities and risks in English

The HTAD brings together initiatives designed to take AI from the research stage to practical application. To achieve its goals in the field of AI, the High-Tech Agenda brings together a range of measures and funding instruments, ranging from the development of new AI models to support for start-ups.

Key priorities include:

Next-generation AI models

Research networks are developing high-performance AI models tailored to European requirements that drive research forward, for example in the areas of data protection, security and energy efficiency. A key focus is on secure, explainable and resource-efficient systems.

Data and
computing infrastructure

National data centres and cloud capacities are being expanded and made more accessible. To achieve this, one of the European AI gigafactories is set to be established in Germany. A planned Research Data Act is intended to regulate how data can be shared and used responsibly.

Cooperation and transfer

The HTAD supports collaborative projects between universities, non-university research institutes, start-ups, businesses and public sector organisations. Funding is provided for technology transfer projects and AI pilot applications, particularly in key sectors.

Support for SMEs

SMEs should be supported in their use of AI, including through dedicated AI infrastructure such as AI service centres.

Start-up and
technology
transfer support

Start-ups from research will be given a helping hand, and funding opportunities for AI and deep tech start-ups will be expanded. This also includes improved framework conditions for financing, growth and scaling.

In order to achieve the HTAD’s objectives in the field of AI and to implement, further develop and supplement the measures outlined, a roadmapping process was launched in autumn 2025.

The aim is to work with stakeholders from academia, industry, politics, the federal states and civil society to develop milestones, timetables and appropriate indicators, which will be regularly reviewed and adjusted. A suitable monitoring system is being set up in conjunction with this.

AI is not an isolated field, but is closely linked to other key technologies (quantum technologies, microelectronics, biotechnology, fusion and climate-neutral energy generation, and technologies for climate-neutral mobility). The High-Tech Agenda consistently views AI as a cross-cutting technology. It strengthens other key technologies whilst simultaneously benefiting from their advances.

Advances, particularly in microelectronics, quantum technologies and the energy sector, are opening up new AI applications and enhancing their performance, security and efficiency. At the same time, AI is driving the development of these and other technologies, for example through automated analysis, pattern recognition or simulations.

Some examples:

Microelectronics

AI requires specialised hardware, energy-efficient chips and high-performance computers. European chip initiatives are laying the foundations for sovereign, scalable AI models, whilst in turn, AI optimises the design and manufacture of semiconductors.

Quantum technologies

Quantum computers can significantly speed up certain AI calculations. On the other hand, AI supports quantum research, for example in simulations and optimisation tasks. Together, they give rise to new applications, for example in materials research, logistics or cryptography.

Biotechnology and health

AI is central to personalised medicine, diagnostics, drug development and the analysis of large biomedical datasets. Advances in biotechnology provide the data basis; AI reveals complex patterns and supports clinical decision-making.

Climate-neutral energy & mobility

In the energy sector, AI helps to optimise grids, storage and consumption. In mobility, AI drives automated driving, traffic control and logistics. AI enables the intelligent control of complex energy and transport systems.

Aerospace

AI is used for autonomous navigation, image analysis and mission planning. Space exploration provides high-quality remote sensing data, which AI systems analyse for climate, environmental and security research.