Can AI turn a reporting policy into checks for your Research Office?
A report moves from preparation to certification and submission. Can AI turn the reporting policy into checks that show who does each step, without blurring the hand-off?
PRACTICAL APPLICATIONS
The problem
When you prepare a reporting checklist, “submit the report” is too broad. Submit it to whom, and by which role?
You need the preparation and Research Office steps kept separate.
A source-linked table gives the reviewer a way to check those responsibilities against the policy, rather than relying on a tidy summary.
What's real
ARC's Final Report guidance says the lead investigator completes and submits the report to the Research Office, the Research Office certifies and submits it to ARC [1]. Vendor guides document working with uploaded documents and asking questions about them [2–4], with a separate licensed work-data route [5]. AI can omit or misassign a step, so source checking remains essential. OAIC recommends testing and human oversight [6].
Practical use
Pick your text. Use the ARC's Final Report page [1]. It's short, so copy its main text. Or use your own reporting procedure in an approved tool.
Keep the original beside you. You'll check every row against it.
Ask for actions, not a summary. Use columns for action, policy section, who does it, by when, conditions or exceptions, and anything unclear. Keep preparation, hand-off, certification and submission as separate rows.
Keep the gaps honest. The ARC page names who does each step, but it gives no due dates. Every “by when” should say “not stated”, not borrow a deadline from memory. Your grant agreement and local procedure set the dates.
Check both ways. Match every row to the page, then read the page against the table. Pay particular attention to where each step sends the report.
Before anyone uses it: if it's your own procedure, the reporting owner resolves unclear wording and approves the checks. If it's the ARC page, treat the table as practice; other funders work differently.
Test it and report back
Try it this week. Did it work? If not, why do you think? If it did, what did it solve?
Tell us how it went on our LinkedIn post LinkedIn post link: did the roles, destinations and missing deadlines stay clear?
Prefer to keep it private? Send us an email at hello@25hours.ai.
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Exercise Block
Use an AI tool your organisation has approved, such as Microsoft 365 Copilot, ChatGPT or Claude.
No procedure handy? Use our public example: the ARC's Final Report page. It's public and short, so you can paste its main text into any tool, including free ones.
Using your own organisation's policy? Only use a tool your organisation has approved for internal documents (usually a licensed workplace tool, not a free personal account), and follow your organisation's AI, privacy and information security policies. If you're not sure, check with your IT or privacy team first, or use the public example.
Whatever you use, check the output against the original before you rely on it. This exercise is for practice, not legal or compliance advice.
Free: ChatGPT / Microsoft Copilot / Claude:
“Turn the policy text below into a checklist table with these columns: action, policy section, who does it, by when, conditions or exceptions, anything unclear. Use only the text below. If the text doesn't say who or when, write ‘not stated’. Keep preparation, hand-off, certification and submission as separate rows, and say where each step sends the report. Quote any timing words exactly; don't turn them into dates.” [paste the text]
Microsoft 365 Copilot (licensed):
Same prompt as above. To use your own policy, type / and select the file from SharePoint or OneDrive instead of pasting.
ChatGPT / Claude paid plans:
Same prompt as above. If your organisation allows it, you can upload your policy file instead of pasting.
Agent tools:
An agent could extract checks from an approved reporting procedure and send the table to the reporting owner, leaving certification and submission with the people named in it. If you'd like to see this set up for your team, book a catch-up.
What a good table shows (ARC example)
Lead investigator: completes the Final Report and submits it to the Research Office.
Research Office: certifies completed Final Reports and submits them to the ARC.
Questions about Final Reports go to the Research Office.
“By when” is “not stated” on every row: the page gives no due dates.
Why it works
Separate rows expose the hand-off rather than hiding it under “submit”.
The policy section column lets the reviewer check roles and destinations directly.
“Not stated” makes missing deadlines visible, so nobody fills them in from memory.
If it doesn't work (Troubleshooting)
If the tool tries to open the link, or says it can't, paste the text instead.
If it cuts off or drops details, paste a smaller section.
If it adds a role, deadline or action, ask it to quote the source sentence for that row. If it can't, delete the row.
Keep real grant, student and confidential research information out of free tools. The ARC page shows one funder's process; your grant agreement and local procedure set the dates.
Data-handling note
Before you try this: free and personal AI tools may use what you paste to improve their models, depending on your settings. Don't paste personal, health, student, resident or client information. Use a de-identified sample, or your organisation's licensed tool if it has one
Sources
Australian Research Council — Final Report; undated. arc.gov.au
OpenAI — Uploading files and audio to ChatGPT; undated. help.openai.com
Microsoft — File upload in Microsoft Copilot; undated. support.microsoft.com
Anthropic — Upload files to Claude; 23/07/2026. support.claude.com
Microsoft — How Copilot Chat works with and without a Microsoft 365 Copilot licence; undated. support.microsoft.com
OAIC — Guidance on privacy and the use of commercially available AI products; updated 17/01/2025. oaic.gov.au
Disclosure: This blog was conceptualised and planned by the 25 hours AI team and then researched and drafted with AI assistance. Once the structure, content, and resources were reviewed, verified and tested, the team finalised and publishes the content. Images that were generated with AI were conceptualised and sketched by the team prior to AI generation.