This Simple AI Process Gets Grants Approved

Grant Application with AI: A Detailed Summary

Key Concepts: Grant Writing, AI Tools (Sispace, Thesify, Grantable, ChatGPT, Gemini, Claude, Elicit, Consensus, Litmaps, Research Rabbit, Connected Papers), Literature Review, Peer Review Guidelines, ARC Grants (Australian Research Council), Grant Databases, Research Impact, Grant Assessors.

1. Finding Grants: Identifying Funding Opportunities

The initial stage of securing research funding involves identifying suitable grants. Traditional methods are often cumbersome, but AI tools can streamline this process. Two primary recommendations are:

• Sispace: A platform offering a gallery of pre-built “agents” designed for academic tasks. Specifically, agents labeled “grantable,” “find grants,” and “AI grant writer” can be utilized to search for relevant opportunities. While offering free access with limitations, it provides a starting point for grant discovery.
• Thesify: This tool excels at providing contextually relevant grant suggestions. By uploading a research paper, Thesify analyzes its themes and identifies grants with a high degree of applicability. For example, a paper analyzed yielded a 76% match to a specific grant, displaying opening and closing dates. The speaker notes Thesify is particularly valuable for academic research.
• Traditional Databases: While AI tools offer a new avenue, utilizing established grant databases remains crucial.

2. Drafting the Grant: Leveraging AI for Content Generation

Grant applications are complex, encompassing sections on the applicant, institution, project, funding requirements, timeline, and expected outputs. AI can significantly simplify the drafting process.

• Sispace (again) & Grantable: These platforms offer AI-powered grant writing capabilities. The speaker demonstrated Sispace’s agent, prompting it to create a grant application for an ARC grant, incorporating the researcher’s credentials (identified via Google Scholar). The agent generated a substantial draft (8,500 words) including sections like executive summary, background, research objectives, risk management, and budget justification. While requiring refinement, it provides a robust starting point.
• Grantable: Positioned as a more science-focused AI grant application tool, Grantable offers features like building, researching, refining, and adding sources. It provides quick actions for letters of intent, budgets, and narratives. It's noted as a relatively affordable option at approximately $25/month.
• Literature Review Integration: AI tools like SciSpace, Elicit, Consensus, Litmaps, Research Rabbit, Connected Papers, and Google Scholar (with its AI Labs) are essential for efficiently generating a literature review, a critical component of any grant application. A separate video on AI-powered literature reviews is recommended for further detail.

3. Reviewing the Grant: Optimizing for Acceptance with Peer Review Insights

The final stage involves refining the draft to maximize its chances of acceptance. A key strategy involves utilizing peer review guidelines.

• Peer Reviewer/Assessor Guides: Most grant applications include detailed guidelines for reviewers. The speaker advocates for inputting these guidelines into large language models (LLMs) like ChatGPT, NotebookLM, Claude, or Gemini alongside the grant draft.
• LLM Prompting: By asking the LLM if the grant application satisfies the criteria outlined in the reviewer guide, researchers can identify areas for improvement and ensure they are directly addressing the points assessors prioritize. This approach aims to make the reviewer’s task easier, increasing the likelihood of a positive evaluation.
• Strategic Alignment: The speaker emphasizes the importance of explicitly addressing key definitions and types of research impact as outlined in the reviewer guidelines, aiming for a “leadership score of five” – indicating excellence.
• Anecdotal Evidence: The speaker cites a recent conversation with a researcher who successfully secured funding by employing this strategy, providing a “proof of one” for its effectiveness.

4. Technical Terms & Concepts

• ARC Grants: Australian Research Council grants, a common funding source for researchers in Australia.
• OPV (Organic Photovoltaic): A type of solar cell based on organic materials.
• Nanomaterials: Materials with structures at the nanoscale (one billionth of a meter).
• LLM (Large Language Model): A type of artificial intelligence model capable of understanding and generating human-like text (e.g., ChatGPT, Gemini).
• Google Scholar: A freely accessible web search engine that indexes scholarly literature.
• Peer Review: The process of subjecting an author's work to the scrutiny of other experts in the same field.

5. Logical Connections & Flow

The video follows a logical progression: identifying funding opportunities, drafting the application, and then refining it for review. Each section builds upon the previous one, demonstrating how AI can be integrated into each stage of the grant writing process. The speaker consistently emphasizes the iterative nature of grant writing, highlighting how AI can accelerate the initial drafting phase, allowing researchers to focus their expertise on refinement and strategic alignment.

6. Data & Statistics

• Thesify Match Percentage: The example provided showed a 76% match between a research paper and a relevant grant.
• Grant Draft Length: The Sispace-generated grant draft was 8,500 words long.
• Grantable Pricing: Approximately $25/month.

7. Notable Quotes

• “To be able to do research, you need to beg for money. This academic panhandling is called applying for grants.”
• “It’s not perfect, clearly couldn’t use this [Sispace draft], but it gives you a great starting point.”
• “You can start actually working with real things and use that meat brain for better things.”
• “If you make it easy for [the reviewer], it’s going to be to your benefit.”

Conclusion:

This video provides a practical guide to leveraging AI tools throughout the grant application process. From identifying funding opportunities with Sispace and Thesify to generating initial drafts with Sispace and Grantable, and ultimately optimizing the application using peer review guidelines and LLMs, the speaker demonstrates how AI can significantly enhance efficiency and increase the likelihood of securing research funding. The key takeaway is that AI should be viewed as a powerful assistant, freeing researchers to focus on the strategic and creative aspects of their work.