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AIRON Use Case Library – Submission Form

Thank you for contributing your project to the AIRON Use Case Library.

The Hub exists to make visible how AI is being used across research operations — grounded in real needs, real constraints, and real people. By sharing your use case, you are helping colleagues across institutions learn from lived experience, reduce duplication of effort, and move toward more responsible, human-centred AI adoption.

This form welcomes early ideas, prototypes, paused projects, lesson learned, not just finished solutions.

Please complete the form below with as much detail as you feel comfortable sharing.
Your submission will be reviewed and added to the Use Case Hub according to your sharing preferences.

First name

Last name

Email address

LinkedIn

Role

Institution

Country

Project Title

Describe your project in 3-5 sentences. (What problem were you aiming to solve, and why is it important in your institutional context?

What triggered this use case? (Select all that apply)

What triggered this use case? (Select all that apply)

Other

Which part(s) of research operations does this use case relate to most closely? (Select all that apply)

Which part(s) of research operations does this use case relate to most closely? (Select all that apply)

Other

How many people are working on this project

How many people are working on this project
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B
C
D
E

Other

Please describe the roles involved in your project team.
(e.g., Research Manager, Librarian, Developer, Data Analyst, Academic Lead, etc.)

How much time does each team member contribute? Please enter in this format: Role — FTE or hours per week — Notes (e.g. Data Analyst) — 0.2 FTE — Working on dashboards)

What stage is your project currently at?

What stage is your project currently at?
A
B
C
D
E

What is the estimated duration of your project?

What is the estimated duration of your project?
A
B
C
D

Please add your planned start and end dates:

Have you received any approvals needed to move forward?

Have you received any approvals needed to move forward?

How did you approach trust, transparency, or risk in this use case?
(For example: communicating clearly what AI does and does not do, involving staff early, limiting scope, anonymisation, human review, etc.)

Were there any concerns, hesitations, or resistance — and how were they addressed (if at all)?

Have you requested or secured funding for this project?

Have you requested or secured funding for this project?
A
B
C
D

Please provide details about funding (amount, source, purpose).

What was your core approach or method, and what technology did you use? (e.g., agent, dashboard, automation, workflow redesign, model comparison, AI platform)

Which technology, company, or platform did you use in this project? Please list any models, tools, or platforms (e.g., Microsoft Copilot, Copilot Studio, OpenAI, Google Gemini, Lovable, Power BI, etc.)

If you built or tested something, please share a link.

What are your next steps for developing or implementing this project?

What benefits has this use case created so far — or what do you expect it to create? (e.g. time saved, improved service quality, reduced workload, increased consistency, better access, fewer errors, etc.)

How do you plan to reinvest these benefits? (For example: redeploying staff time, improving researcher support, addressing backlogs, focusing on higher-value work, etc.)

What has surprised you most during this project?

If you were starting again, what would you do differently?

Please provide 3–8 hashtags that describe your project (#FundingMatchmaking, #LibrariesAI)

How would you like your project to be shared in the AIRON Use Case Hub?

How would you like your project to be shared in the AIRON Use Case Hub?
A
B
C