We must make full use of the opportunity presented by Artificial Intelligence at TU Graz.
Horst Bischof, Rector of TU Graz
Guidelines and fundamental principles
TU Graz supports and promotes the responsible use of AI-based tools in teaching, research and administration. The fundamentals for safe handling of these tools are summarised as the AI-TU rule.
Furthermore, TU Graz adheres to the following frameworks:
- European Commission
- General Data Protection Regulation (GDPR)
- EU regulation laying down harmonised rules on artificial intelligence
- In German: Entwicklungsplan der TU Graz
- In German: Digitalisierungs- und IT-Strategie der TU Graz
- TU Graz Ethics Compass
- In German: Satzungsteil Wissenschaftliche und Künstlerische Integrität
Analyse the data!
Check whether the data entered is personal or confidential.
- Check for “personal”: Is any of this personal data or data of third parties that is not already public and is being used without consent?
- Check for “confidential”: Would it be a problem if this data were freely available on the internet, or does it include confidential or trade‑secret material?
Interpret the results critically!
Never use AI-generated results as your sole source of information, especially for decisions that may have legal, medical or financial implications. You (and not the AI) are responsible for the use of the results.
Truth-check the results!
Before reusing the information generated by AI, verify that it is accurate. Only you, for example as the author of a text, can take responsibility and critically review AI-generated results. AI applications are prone to bias, to producing false information ("hallucinations") and to other errors.
Use the results responsibly!
Before using AI-generated results, check the intended use. If the output generated by AI is for your own use only and will not be shared, you may use it. If the output will be shared, additional steps/measures may be required. You are obliged to indicate the use of AI if you have not revised or reworded the results accordingly.
AI in Education
AI-related degree progammes
AI in Continuing Education
TU Graz Life Long Learning is our educational interface with the business world and offers AI-related skills development programmes for graduates and companies:
- AI Essentials: Fundamentals and Practical Application of AI and Generative AI
- Development and Evaluation of AI Use Cases
- Low and No-Code Machine Learning with KNIME
- Executive MBA Digital Leadership – Green Microelectronics
- MBA Leadership in Digital Transformation
Other AI-related offers (free and open to everyone)
- TU Graz prompting.school
Free prompt engineering courses in German - TU Graz MOOCs
Introductory courses on Generative AI (self-study) in German
The Vice Rectorate for Academic Affairs provides information and support on the use of AI for both students and teaching staff through guidelines, regulations and numerous resources. Explore them here: AI in Teaching
- Vice Rectorate for Academic Affairs: vr-lehre@tugraz.at
- Educational Technology: elearning@tugraz.at
- Life Long Learning: lifelong.learning@tugraz.at
AI in Research
Artificial Intelligence is an integral part of almost all research activities at TU Graz and, at the same time, an independent field of research.
Strategically, the main areas of research in the field of AI are reflected both in the broad Fields of Expertise (FoEs) – such as the FoE Information, Communication & Computing – and in the specialised Research Centers (RCs), such as the RC GraML (Graz Center for Machine Learning), as well as in the COMET competence centres, such as the Know-Center or Pro2Future ("Products and Production Systems of the Future").
AI research at TU Graz ranges from basic research – TU Graz is, for example, a partner in the Cluster of Excellence Bilateral AI – to application-oriented research within the framework of highly competitive national and European programmes, and innovative, specialised start-ups emerging from this environment.
TU Graz has created a framework for innovative and high-quality research with AI, supporting researchers with various services and offers:
- Research Data Management: rdmteam@tugraz.at
- Research and Technology House: forschung@tugraz.at
- TU Graz Library: service.bibliothek@tugraz.at
- High Performance Computing: it-support@tugraz.at
FAQ on AI at TU Graz
TU Graz supports and promotes the responsible use of AI-based tools in teaching, research and administration. To remain competitive, it is important that researchers at TU Graz are empowered to actively utilise the new possibilities of AI in their research processes. In teaching, staff may decide individually on the use of AI in their courses.
Details can be found in the guideline for use of AI supported tools in teaching as well as the AI Guide for Researchers at TU Graz.
TU Graz’s AI strategy is an integral part of our digitalisation and IT strategy and is being implemented through corresponding measures. This integration is an ongoing process.
The use of AI tools depends on the specific requirements of each course. Teaching staff must inform students about whether and to what extent AI tools may be used before the start of the semester. Spell check and translation tools are generally permitted.
Teaching staff can find further details in the guideline for use of AI supported tools in teaching and the document Designing performance review in the context of the availability of AI-supported tools.
The use of AI must be made transparent in accordance with the AI-TU principles, and, where appropriate, labelled as such. The use of AI and related labelling requirements are outlined in the below guidelines.
- For teaching staff: guideline for use of AI supported tools in teaching
- For researchers: AI Guide for Researchers at TU Graz
For TU Graz, in addition to the EU regulation on AI (EU AI-ACT) and the General Data Protection Regulation (GDPR), Austrian laws and university regulations also apply.
When entering personal data into AI applications, first consider anonymising the information. If full anonymisation is not possible, only pseudonymised data (i.e., data replaced with fictitious data) should be used. The principle of data minimisation is applicable in this regard: only data that is absolutely necessary may be processed.
Textual information
- Safe to enter: information already publicly available, published or ready for publishing; publication in progress
- Never enter: trade secrets, ideas for new technologies or projects, confidential information
Personal data
- Safe to enter: your own personal data; personal data of people who have given you their explicit consent for publication of their personal data
Third party data
- Safe to enter: data already publicly available from third parties; third party data of those who have given you their explicit consent for publication of their data
- Must be reviewed on a case-by-case basis: publicly available but personal data from third parties for which no consent has been obtained
- Never enter: any data protected by a confidentiality agreement/NDA
Software, code, algorithms, datasets
- Safe to enter: software/code that is publicly available, has already been published or is ready for publication
- Never enter: trade secrets, confidential software/code
Inventions
- Safe to enter: patented inventions or inventions pending patent approval
- Never enter: inventions pending patent application
- Academic AI
The Academic AI is available to all TU Graz employees. The goal of this initiative is to create a secure environment for using AI while respecting data protection and information security. - High Performance Computing at the Austrian Scientific Computing (ASC)
National network connection to HPC (High Performance Computing) - Projekt Multi-Site Computer Austria (MUSICA)
From 2026 onwards, the Austrian supercomputing infrastructure “Multi-Site Computer Austria” (MUSICA) aims to provide an experimental, open-source environment. This environment will be used to train AI models with specific use cases and develop innovative, AI-based services for teaching, research and administration. - University cloud services
- Specialised AI hardware at institutes
In addition to the freely available resources offered by TU Graz, there are specific tools and further training opportunities available for TU Graz employees:
- Academic AI
Academic AI is a language model developed for the Austrian higher education sector and operated by ACOmarket. It provides all TU Graz employees with data protection-compliant AI services. - Future Skills Initiative of TU Graz
The Future Skills Initiative of the Human Resource Development department at TU Graz support employees in confidently developing their AI skills as well as other numerous future-oriented competencies. In addition, the self-learning platform Future Skills to go provides opportunities to engage flexibly and practically with topics related to AI and other digital skill fields – at any time and at your own pace. - In-House Training at TU Graz
The in-house training programme at TU Graz offers courses for all TU Graz employees to further their skills in working with AI. - Teaching Academy Programme
The Teaching Academy offers specific workshops on the topic of AI in teaching, for example: “KI in Lehre Integrieren” (Integrating AI into Teaching), “Technology-Enhanced Learning (TEL)” and TEL coaching. - TU Graz prompting.school
The organisational unit Educational Technology offers free prompt engineering courses for all TU Graz employees. The AI Campus and the Hochschulforum Digitalisierung (HFD) also offer an open prompt catalogue for teaching staff. - MOOCs of TU Graz
The Austrian MOOC platform iMooX offers self-study introductory courses on generative AI. The catalogue of open online courses is continuously expanded and is accessible to anyone. - Digital competence
Human Resource Development has compiled a variety of resources for self-study on TU4U – from e-learning courses to videos, podcasts, articles and programming tutorials.
- High Performance Computing at the Austrian Scientific Computing (ASC)
TU Graz is an ASC project partner with a national network connection to HPC (High Performance Computing) - Multi-Site Computer Austria (MUSICA) project
Austria’s national supercomputing infrastructure, scheduled to go online in 2026 - AI Factory Austria (AI:AT) - Training
- AI in Literature Search
- scite_AI for Resarch (TU Graz Library)
- Consultation with the TU Graz Data Stewards
- Tools für AI-ready data
- Consultation and support with research funding (Research & Technology House)
