There was a genuine sense of curiosity around our newly rebranded Hivve exhibition stand at this year’s ARMA. Following a steady stream of inquisitive visitors, word quickly spread that we were delivering live, back-to-back demonstrations of our newly launched AI Impact Case Study Generator throughout the conference.
Rather than relying on a conventional product presentation, we wanted attendees to see the platform working in real time with genuine project information. During each demonstration, Laura (our CEO) and I showed how research and impact evidence could be transformed into a structured first draft of an impact case study within minutes.
This meant that visitors were not simply being told what the technology could do. They were able to watch the process unfold and, shortly afterwards, examine a generated case study based on a project they already understood. The response was overwhelmingly positive.
I spoke with research managers, impact officers and one or two academics who were genuinely excited by what they saw. Many were particularly interested in the speed at which the Generator could organise complex information, identify a coherent impact narrative and produce a substantial draft for further development.
What appeared to resonate most strongly was not simply the speed of the process, but the opportunity to begin with a meaningful and well-structured draft rather than a blank page.
Preparing an impact case study can often require weeks of gathering information, identifying the central narrative, checking evidence and repeatedly refining the wording. The AI Impact Case Study Generator is designed to help accelerate those early stages while preserving the essential role of human expertise, critical judgement and institutional oversight.
In my view, the technology is most valuable to support experts, it should never be thought as a way to replace them. It provides a strong starting point that researchers and research support professionals can review, challenge, verify and improve.
Generating an Impact Case Study Live
I also had the opportunity to deliver the session: “Accelerating Impact: Using AI to Generate Funder-Ready Case Studies in Hours, Not Weeks.”
During the session, I took the audience through the creation of an impact case study in real time. I demonstrated how project information, research findings, stakeholder engagement and supporting evidence could be developed into a clear narrative focused on the research and the resulting change.
The live demonstration provided a practical opportunity to look beneath the surface of the technology. Rather than presenting a carefully prepared final example, I was able to show the audience how the case study was produced in real time.
This allowed me to talk about how the AI Impact Case Study Generator works, the quality and consistency of its outputs and the practical ways in which it could support organisational preparedness.
The discussion explored questions such as:
- How can institutions identify promising impact stories earlier?
- Where should human review and subject expertise remain central?
- How could the platform support REF and funder reporting processes?
- How can institutions develop a more consistent approach across multiple case studies?
- How might artificial intelligence reduce administrative effort without weakening quality or accountability?
One of my main reflections from the session was the level of interest in using artificial intelligence as part of a wider impact development process, rather than simply as a writing tool.
Attendees were interested not only in generating a draft, but also in how the technology might help institutions recognise evidence gaps, strengthen narratives and prepare more consistently across departments, faculties and research portfolios.
Supporting Impact Teams Beyond the First Draft
The AI Impact Case Study Generator is available alongside Hivve Impact Tracker, allowing organisations to connect the longer-term process of capturing and managing impact evidence with the development of structured case study narratives.
Together, the tools are intended to help research and impact teams move from fragmented information towards clearer, stronger and more evidence-led accounts of change.
For me, this connection is particularly important. Strong impact case studies rarely begin at the point when someone is asked to write them. They develop through the ongoing collection of evidence, engagement with stakeholders and careful documentation of how research contributes to change.
By connecting evidence management with case study development, institutions can reduce the pressure of last-minute preparation and build a more sustainable approach to impact reporting.
The conversations reinforced my belief that, when combined with expert judgement and good evidence, artificial intelligence can help institutions spend less time wrestling with the first draft and more time strengthening the story of the change their research has created.
To request further information or arrange a demonstration, contact us at hello@hivveimpact.com or visit www.hivveimpact.com.
