Strengthen AI competences and knowledge transfer at universities through community work

Artificial Intelligence is changing universities not only through new technologies. What matters is sharing experiences and transferring successful approaches. The BMFTR project “Strengthening AI competences at universities” connects regional, nationwide and European communities for this purpose.

Generative AI has long since arrived in everyday university life: students use language models for learning and writing, teaching staff develop new teaching and learning scenarios, central units design professional development opportunities, and university management teams address governance, infrastructure and legal frameworks.

In doing so, many universities face similar questions: Which competences do the various status groups need? How can opportunities be institutionally embedded? And how can good solutions be disseminated beyond individual projects and committed individuals? These questions are addressed by the project “Strengthening AI competences at universities”, funded by the Federal Ministry of Research, Technology and Space (BMFTR). The collaborative project develops open learning opportunities, educational resources and tools to strengthen AI competences, pilots them at universities and makes them available for reuse. Nine consortium partners and additional universities as associated partners are involved in this strongly cooperation-oriented initiative. The resulting opportunities feed into the AI Campus, where they are openly licensed and available free of charge.

Transfer is not understood here as the final dissemination of finished results, but as part of a continuous development process based on exchange with the community: university members contribute needs relating to strengthening AI competences at universities, trial jointly developed approaches and feed the insights gained back into their institutions and networks.

The AI Campus benefits from both cross-institutional approaches and direct feedback that contributes to improvement; universities benefit early on from learning opportunities tailored to them.

Within the project, the “Transfer and Community” focus pursues interconnected objectives at various levels: project insights are to be transferred into the university community. At the same time, regional, nationwide and European synergies are to emerge.

Three examples are representative of these different transfer pathways through which the AI Campus achieves these goals: (1) the AI Campus Hub NRW, (2) the cooperation between Hochschulforum Digitalisierung and AI Campus and (3) the further development of a European AI Literacy Framework.
 

Example 1: AI Campus Hub NRW – strengthening AI competences in the federal states

With the AI Campus Hub NRW, FernUniversität in Hagen, as a consortium partner in the BMFTR project, is establishing a regional point of contact for AI competences in higher education. The aim is also to reach universities and educational institutions where AI has so far been less firmly embedded institutionally. Through its advisory services, the hub shows the opportunities that the use of the AI Campus offers for universities. Application scenarios are conveyed and illustrated by way of example, along with how opportunities can be implemented in curricula. The prerequisite for this is the consistent OER approach under which all opportunities on the AI Campus are made available. This creates a low threshold for getting started and immediate access. 

Since 2026, the AI Campus Hub NRW has served as a central interface to the KI:Expertisezentrum.nrw. FernUniversität in Hagen is one of the project partners in this NRW state-funded project. The centre builds AI competences and passes them on, provides training, advice and networking, particularly within the federal state. The programming and operation of applications are also objectives of the centre, for which a shared hardware infrastructure is operated. The AI Campus complements this offering and appears as a supra-regional network partner at local networking events (e.g. AI Symposium of FernUniversität Hagen, Learning AID at Ruhr University Bochum).

Further AI Campus hubs are located in Berlin (AI Campus Hub Berlin) and Heilbronn (AI Campus Hub Baden-Württemberg).
 

Example 2: Cooperation between AI Campus and Hochschulforum Digitalisierung – strengthening AI competences together nationwide

The AI Campus has been cooperating with Hochschulforum Digitalisierung (HFD) for years. Both initiatives receive federal funding under the Hightech Agenda Deutschland. In the project “Strengthening AI competences at universities”, the HFD community initially supported, in particular, the clarification of the target groups’ needs at universities. As the project progressed, the HFD created direct access and contact to key actors and multipliers within the higher education community.

• Bot-Camp: How community, professional development and practical development can work together beyond traditional self-study courses is shown by the Bot-Camp run in May 2026 by HFD and the AI Campus. Almost 400 participants from the DACH region engaged with knowledge-based AI assistants and their possible uses at universities. The Bot-Camp combined two online events with an experimentation phase. Based on specific use cases, participants developed their own prototypes. An environment provided by RWTH Aachen enabled the technical implementation. In a final peer-to-peer workshop, the results were jointly reflected on and further developed. The format thus focused on informed experimentation: specialist input creates a shared foundation, work on participants’ own use case establishes the connection to their respective institution, and collegial reflection makes experiences transferable.
• Prompt Lab: Generative AI in higher education teaching: Since 2023, HFD and AI Campus have also jointly been developing the professional development programme “Prompt Lab: Generative AI in higher education teaching”, in which teaching staff make key AI topics for higher education teaching tangible in a practical way. With synchronous live sessions, one hundred higher education teachers were reached. At the same time, the asynchronous learning opportunities developed within the community in the AI Campus Moodle learning ecosystem had already recorded over 12,000 course enrolments by mid-2026.
• University:Future Festival: At the University:Future Festival organised by HFD (May 2026), the AI Campus presented itself as a long-standing partner in various formats and contexts. In 2026, the focus was a community meetup at which the partners of the project “Strengthening AI competences at universities” introduced themselves to festival participants, explained the project objectives and responded directly to questions and cooperation ideas. The event’s wide reach made it possible to raise targeted awareness of the AI Campus offerings in the DACH region and to win people and institutions for engagement in the AI Campus community. In concrete terms, new associated partnerships were also initiated through these personal contacts. At the same time, the festival also served the AI Campus for focused thematic positioning on the future topic of “agentic AI”, for example with the session When AI doesn’t just answer, but acts: agents at universities and the workshop New actors in higher education transformation: AI agents in action.
• Agora [Future]: The event Agora [Future], also hosted by HFD (September 2026), centred in 2026 on the topics of AI strategies, AI literacy, digital sovereignty and innovative teaching. With the Agora, HFD offers “an innovative space for thinking and mutual understanding in which pressing challenges and promising approaches to digital transformation in higher education are made visible, jointly contextualised and developed further.” Here too, the AI Campus, as a network partner on the focus topic of AI literacy, was able to make an important contribution to networking and exchange, and also benefit directly from the exchange itself. Focus questions in the thematic track and in the accompanying workshops were: What structures and offerings are needed for competence development among staff and teachers or students? How can successful formats for building AI competences be demonstrably promoted and scaled? How do you implement an AI literacy framework that fits the university profile within institutional development?

Outlook: From November 2026, in the digital “Teaching Staff Lounge”, teaching staff will be able to present once a month who have already successfully implemented innovative teaching concepts on AI topics with the AI Campus. Digital learning opportunities, didactic approaches and exciting specialist questions will take centre stage. To implement the format, we are continually seeking interested teaching staff via a Call for Participation who would like to provide a short input for the Teaching Staff Lounge.
 

Example 3: AI literacy at European level

The question of AI competences acquired a European dimension well before the EU AI Act. The AI Campus also acts at this level as a community actor and seeks to bring different perspectives together in such a way that ideas and frameworks for lived educational practice can emerge, and numerous consortium partners contribute overarching experience from European higher education networks (such as the OpenEU network).

Among the specific starting points for the project “Strengthening AI competences at universities” were the requirements from Article 4 of the AI Act. The project relies on a continuous exchange with European stakeholders on AI competence requirements.

A key basis for engaging with AI competences is the AI Literacy Framework published in June 2026 by the European Commission and the Organisation for Economic Co-operation and Development (OECD), which is structured along four competence areas: “Engage with AI consciously”, “Apply AI creatively”, “Use AI purposefully” and “Actively shape AI”. Stifterverband was represented in the expert group that developed the framework, coordinated a task force of German education stakeholders and was responsible for the German translation. Building on this, the AI Campus, together with education partners, is developing digital learning opportunities, initially for the school sector, which are also directly relevant for teacher training programmes. In a next step, a higher-education-specific competence framework is to be derived within the project consortium on this existing European basis.
 

Conditions for success for community work and transfer

From the activities presented by way of example, conditions for success for effective transfer and community work can be derived:

• Community work must always consider different levels of actors. Education in Germany is the responsibility of the federal states, but at the same time it is also part of a European education and higher education area. And nationwide initiatives can help to bring actors together even better.
• Different target groups require different forms of access. University leadership needs strategic guidance, staff in support structures need professional exchange, and teaching staff and students need protected spaces for experimentation. Teaching staff, employees from support structures and from higher education development, as well as student representatives, bring different perspectives, all of which are important. At the same time, collaboration creates relationships through which new approaches reach faculties, central units and inter-university networks.
• Transfer begins as early as development and needs practice. If members of the university are involved early on, provision is created that is more closely aligned with real needs. At the same time, willingness to use results within one’s own structures increases. In addition, the following applies: the value of exchange grows with the wealth of practical experience contributed by those involved. One key insight: transfer works better when the target groups are not viewed merely as passive recipients, but when they are directly involved in the creation of transfer formats.
• Continuity is just as important as visibility. Individual events can generate attention. However, lasting change requires recurring opportunities for exchange, reliable contacts and spaces in which unfinished ideas and difficulties can also be discussed.
• Open materials create transfer mechanisms. Because the provision is open, community members can take it up without barriers, try it out and develop it further in their own contexts – and in turn feed their adaptations back into the community. Openness thus itself becomes a transfer mechanism: it enables experiences and further developments from individual universities to flow back to other locations and networks, rather than remaining within a single institution.
   

Conclusion: transfer is a collective task

Strengthening AI competences is not solely a question of good learning content. Universities need social and organisational structures in which experiences circulate, questions are worked on jointly and solutions are adapted to different contexts. This requires spaces, relationships and shared practice. Community work is therefore not merely accompanying communication, but a social infrastructure for change. In essence, AI Campus does not build this itself, but benefits—especially in the project “Strengthening AI competences at universities”—from existing initiatives, alliances and actors who actively include us in their communities. The aim is always partnerships on an equal footing that create added value for everyone involved.

For us, collaboration is an important prerequisite for gaining access to networks, building trust and establishing sustainable structures for exchange.

Through joint event and qualification formats such as the Prompt Lab or the Bot Camp, new trend topics are not only made tangible and directly experienceable for many teaching staff. They also create the basis for supra-regional networking, cooperation, exchange of experience and also qualification across institutions and federal states.

In the coming project phases, regional communities are to be further strengthened, nationwide networks integrated more systematically and European mechanisms for exchange expanded.

Already it is apparent that successful transfer requires, in particular, strong cooperation that can adapt approaches and ideas to their respective contexts, needs and challenges, while at the same time also bringing new impetus to our work.