8 June 2026 – We owe the survey “Generative AI in University Communications”[1] (in German) conducted by the Institute for Higher Education Research at Martin Luther University Halle-Wittenberg for providing rare and up-to-date data on the use of AI tools in academic communications. No fewer than 64 senior communications officers at public, private and church-affiliated universities in Germany provided insight into the current state of their teams’ work. The authors of the study report that AI tools are increasingly being used for specific tasks and as assistive technologies: tools for text generation, translation, proofreading and language enhancement, followed by those for document analysis, image generation and the transcription of audio and video.
Communicators aim to carry out existing tasks more quickly and with fewer resources. The use of tools to automate multi-step workflows and of AI agents is still in its infancy. In line with typical patterns of innovation adoption, at the time of the survey, generative AI was being used little or not at all for analysing target audiences, defining communication objectives, analysing communication impacts, or planning communications. Respondents primarily cite data protection concerns, worries about factual accuracy and reliability, and ethical concerns as barriers to the wider use of AI tools. A professional commitment to producing authentic, high-quality content in an original and creative manner, a lack of internal guidelines, coupled with insufficient budgets, are further key reasons why communicators are hesitant to use current AI tools.
Strategic context for achieving impact
The authors of the study conclude that a “transition from an experimental phase (2023) via a pragmatic consolidation (2024) towards a structural embedding of generative AI in German higher education communication” is taking place. This is certainly accurate, albeit from a bird’s-eye view of the diverse and heterogeneous science communication practised by the more than 400 higher education institutions in Germany. Structural integration presents a technical, organisational and strategic challenge. It is best tackled not by communications departments alone, but across the board and in close collaboration with institute management, IT teams and other functions within teaching and research organisations that also benefit from integrated and consistently used AI tools, or whose expertise and buy-in is crucial. However, communications teams still have the opportunity to be the drivers of this innovation within their organisations. High internal expectations, but also the fascination that AI tools can generate among users and target groups, usually lead to isolated or individual use, the usefulness of which remains limited.
Particularly when time is of the essence, it is helpful to step back and consider the institution’s overall strategy, which underpins the communication strategy in general and the strategy for using generative AI in communication in particular. This strategy provides a framework for the selection, use and mastery of AI tools within the organisation, depending on its objectives, structure and workflows, skills and resources. If work is taking place in parallel at technical, organisational and strategic levels, it should primarily be guided by established or developed strategic directions in order to be successful. This process can be facilitated and driven by communicators, who are ideally suited to this role as they typically work in a generalist capacity, across organisational boundaries and with a focus on target audiences. This strategic orientation helps to make AI-supported communication – like any form of communication – more effective and efficient for the organisation.
[1] [1] Justus Henke und Matthias Begenat, Generative KI in der Hochschulkommunikation, 135, Ergebnisse der 3. Welle – 2025 (in German), https://hof.uni-halle.de/publikation/ki-in-der-hochschulkommunikation-2025/ (accessed on 12 May 2026)