Expert Session

How to Use AI for Research Grant Writing and Evidence Development

Speaker

Prof. Benita Oliver

Quick answer

Use SciSpace in grant writing to organize requirements and evidence, not to invent funder rules, preliminary data, or citations. Build a compliance matrix from the call, map each aim to a documented need and method, test the logic model, anticipate reviewer questions, and verify every factual and bibliographic claim before submission.

About this session

Prof. Benita Oliver discusses using the SciSpace platform to streamline grant writing workflows [L5]. The session highlights strategies for organizing grant requirements and evidence effectively, emphasizing the importance of early preparation and increasing submission quality to overcome low funding success rates while managing long-term research proposal timelines [L5].

A competitive grant is not improved by generic persuasive language alone. It needs a credible problem, a well-supported gap, clear funder fit, a defensible method, and evidence that the team can deliver. This session focuses on the research work behind stronger proposal sections rather than treating AI as a grant-writing shortcut.

What this tutorial covers

Translate a funding call into eligibility, priority, evaluation, and evidence requirements.
Build a source-backed case for significance, need, novelty, and expected impact.
Map claims in the proposal to primary studies, reviews, datasets, policies, or preliminary findings.
Use AI to identify reviewer objections, missing evidence, feasibility risks, and weak logic.

Key concepts explained

Funder fit: A strong idea must directly answer the call’s scope and assessment criteria.
Evidence architecture: Each major proposal claim should have an appropriate type of support.
Gap validation: Novelty requires showing what prior work has and has not resolved.
Reviewer simulation: Critical review can reveal assumptions, overclaiming, and unclear work packages.

How to try it in SciSpace

1
Upload or summarize the call, guidance, scoring criteria, and organizational constraints.
Convert the funding call into a compliance matrix with eligibility, required sections, scoring criteria, page limits, dates, and organizational constraints. Verify each item in the original call.
2
Ask SciSpace to create a compliance and evidence matrix for every required section.
Create an evidence matrix for significance, gap, approach, innovation, feasibility, impact, and team capability. Mark where evidence or preliminary work is still missing.
3
Search for literature and data that support the problem, gap, approach, and impact pathway.
Search for literature and data that support the problem and proposed pathway, then verify the sources. Do not use AI-generated statistics or funder priorities without an authoritative reference.
4
Draft section outlines linked to verified evidence rather than generating the whole proposal at once.
Draft section outlines linked to the matrix before writing prose. Keep aims, methods, milestones, evaluation, and risks aligned across the whole proposal.
5
Run a reviewer-style critique and revise claims, risks, milestones, and citations.
Run a reviewer-style critique against the scoring criteria and revise unsupported claims, feasibility gaps, citations, milestones, and compliance issues before submission.

Worked example

A team prepares a grant proposal for an adolescent sleep intervention. In SciSpace, it turns the funding call into a compliance table, maps the evidence supporting the problem, and links each specific aim to a method, measure, and expected output. A draft significance section contains an unsupported prevalence claim, so the team replaces it with a verified statistic. The final proposal keeps preliminary findings, planned research, and external evidence clearly separated.

Practice prompt

Analyze this funding call and my project concept. Create a matrix of eligibility, priorities, review criteria, required sections, evidence needed, and potential weaknesses. Then identify literature that supports the need, gap, approach, feasibility, and expected impact. Do not invent preliminary data.

Key takeaway

Use SciSpace to strengthen the evidentiary spine of a grant; the scientific vision, partnerships, commitments, and truth of the proposal remain the applicants’ responsibility.