In a blog post, two project managers of the Hochschulforum Digitalisierung (CHE) give universities five recommendations for institutionalising AI, drawn from a workshop with 36 participants at the Learning AID conference and from HFD’s own advisory work. The post contains observations and opinion, not systematic data or a study of learning outcomes.
How this is computed
- Key claims supported: 2 of 6
- Type of source: Institution on its own work
- Independent confirmation: None
Rates the source, not the topic and not our analysis.
Why it matters
Our reading: The post illustrates how the higher-education debate may be moving from whether to use AI towards who runs and funds it over time. Its value lies in naming governance problems such as unclear responsibility; whether these problems are widespread is not measured.
What the source says
- Conditionally supported HFD authors Westermann and Tobor say the initially dismissive attitude at universities has given way to constructive engagement, with guidelines, tool licences, institutional AI access and pilot projects in place at many institutions. They base this on their own consulting and publications, without giving figures.
- Conditionally supported The authors describe AI use among students as factually widespread and cite Horstmann et al. 2026; the post does not give that study’s method, sample or results.
- Vendor claim only According to the organisers, 36 participants worked in four thematic groups and a plenary at the workshop on 1 September. This is a small, self-selected group.
- Unverifiable The authors warn that AI pilots can quietly become permanent project-based services without clarified staffing, funding and responsibility, and that good solutions may then disappear. They cite no cases.
- Unverifiable The authors say the EU AI Act requires AI inventories to be set up and maintained, which could prompt universities to survey the AI tools they use. They do not name a specific provision.
- Vendor claim only According to the authors’ summary of the workshop discussions, the governance problem is often unclear handovers of responsibility and stalled information flows rather than a complete absence of structures.
The key caveat
The recommendations rest on a single workshop with a self-selected group and on HFD’s own advisory work, which the post names but does not quantify. They are not representative of universities and are not an independent evaluation.
Open questions
- What do Horstmann et al. 2026 actually measure about student AI use, and with which sample and method?
- Which provision of the AI Act would require AI inventories, and does it apply to universities?
- How many universities have pilot AI services without clarified long-term staffing and funding?
Source: Hochschulforum Digitalisierung, 15 October 2026: 5 Impulse zur KI-Transformation von der Learning AID
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