How Research Organisations Get Their Work Cited by AI Assistants

Research gets cited by AI assistants when its findings are publicly accessible, summarised in plain language, clearly attributed to named authors and institutions, and discussed by other credible sources. Many valuable studies sit in PDFs behind paywalls or in technical language that is hard to quote. A few changes in how you publish and present research can make it much easier for assistants to find and describe your work accurately.

Who This Is For

Universities and research centres, think tanks, industry associations publishing reports, market research firms, NGOs with field studies, and corporate research teams. The questions people ask AI that touch your work might be “what does research say about four-day work weeks?”, “how many bees are lost each winter in Europe?” or “is intermittent fasting effective for weight loss?”.

Common Barriers to AI Citation

• Paywalls and logins: if a crawler cannot read the content, it cannot use it.
• PDF-only publishing: PDFs can be read by some systems, but HTML pages with clear headings are usually easier to process and link to.
• No plain-language summary: abstracts written for specialists may not match how the public asks questions.
• Scattered versions: preprint, journal version, press release and report all saying slightly different things.

Step 1: Publish an HTML Summary Page for Each Study

Create one page per study or report with:

1. A title that states the finding, not just the project name.
2. A three-sentence plain-language summary of what was found.
3. Key numbers with their context (sample size, period, region).
4. Limitations stated honestly.
5. Authors, institution, publication date and a link to the full paper or DOI.

Accurate limitations matter. They help assistants avoid overstating your results.

Step 2: Use Open Access Where You Can

If your funding and publisher allow it, deposit the accepted manuscript in an institutional repository. Open versions can be read by more systems and people.

Step 3: Add Scholarly Metadata

Use structured data such as ScholarlyArticle or Dataset from schema.org, include DOIs, and keep author identifiers like ORCID linked from author pages. This helps machines connect findings, authors and institutions.

Step 4: Publish Data, Not Only Conclusions

Where possible, share datasets with clear documentation. Journalists, analysts and other researchers then cite and reuse your data, which creates more independent mentions. See whitepapers and research for AI for formats that work well.

Step 5: Communicate Beyond the Journal

Press releases, explainer articles, expert commentary in the media and talks at public events all spread your findings in everyday language. These are the sources many AI answers draw on for general questions.

Correcting Misrepresentation

If an assistant misstates your findings, check which sources it seems to rely on. Often it is a secondary article that simplified the result. Publishing a clear summary and asking the author of the secondary article for a correction is usually the most effective fix. Keep a short public FAQ for each major study that answers the questions people most often get wrong, such as what the study did not measure.

Measure Over Time

Pick a handful of questions related to your main findings and ask them in several assistants every few months. Note whether your institution or authors are named, whether the findings are described accurately, and which sources appear. This gives your communications team a simple way to see whether public understanding of your work is improving.

How Keboost Helps

Keboost tracks the questions people ask about your research topics across ChatGPT, Gemini, Claude, Perplexity and Copilot, shows which sources are cited instead of yours, and creates focused, accessible content that presents your findings clearly. Run a free AI visibility check for your organisation.