The Researcher’s Guide to Using Generative AI in Research Grant Development

Overview

This guide aims to provide researchers with the essential, grant-specific knowledge and tools to effectively use Generative AI (Gen AI) in developing research grant proposals.

In alignment with the Framework for the Responsible Use of AI at the University of Alberta, Gen AI should be an augmentative tool that complements human expertise. Human oversight is crucial to ensure integrity and success.

For comprehensive information on fundamental concepts like AI Literacy, Definitions (AI, Gen AI, LLMs), and general guidelines on using Gen AI for research and other purposes, please refer to the main University of Alberta Library website: Using Generative AI.

The Research Development Services (RDS) portfolio of the Office of the Vice-President Research will offer a series of workshops and training sessions on Gen AI and research grant development. Kindly send an email to vprai@ualberta.ca if there are topics you would like to see addressed.

Role of Generative AI in Research Grant Development

Research Grant Development is the process of developing proposals to acquire funding. Gen AI tools, particularly Large Language Models (LLMs), can enhance efficiency by managing high-volume, repetitive, or initial-drafting tasks across various stages of grant development. Below are examples of how LLMs can assist in key activities related to research grant development. 

Activity	How Gen AI can Help
Identifying funding opportunity	Brainstorming funding sources. Analyzing and summarizing funding announcements for key requirements and deadlines. Matching researcher expertise to opportunities.
Proposal Development	Supporting ideation, literature review and synthesis. Drafting non-substantive sections (bios, institutional overviews). Editing (grammar, clarity, translation of complex language), and reformatting for compliance,  Aiding in budget preparation by drafting justifications and identifying missing costs. Generating figures.
Institutional Approval	Pre-screening proposals for compliance issues (e.g., flagging conflicts with institutional policies or comparing funding agency rules against institutional standards). Generating tailored checklists, and reviewing draft proposals against funders’ assessment criteria.

AI Literacy for Research Grant Development

In the context of academic research grant development, AI literacy equips all researchers and administrators to become informed, critical, and responsible participants in AI, enabling them to leverage its advantages while addressing potential risks.

The key components of AI literacy and their relevance to researchers are summarized below:

Component	Description	Relevance to Researchers
Foundational Knowledge	Understanding the basic concepts of and knowing the core functions of specific models.	Understanding the difference between Large Language Models and their applications to proposal development, including how to select the right tool for a task.
Effective Prompting	Knowing how to communicate effectively with Gen AI systems to achieve high-quality, relevant outcomes.	Crafting detailed prompts (Role, Task, Context, Constraint) to support proposal development
Critical Evaluation	The ability to recognize the limitations, risks, and potential errors (e.g., hallucinations, bias) inherent in AI output.	Understanding the need for rigorous verification of all facts, citations, and methodologies generated by Gen AI.
Ethical and Societal Understanding	Recognizing the ethical, legal, and social implications of GenAI, including issues with  privacy, accountability, and Intellectual Property (IP).	Adhering to institutional policies on data security

Adapted from the AI Literacy Lab (the AI Literacy Framework for Higher Education), Zachariah et al., 2025 (AI Literacy in Postsecondary Education) and Lo, L.S., 2025 (AI Literacy: A Guide for Academic Libraries).

AI Disclosure: Portions of this website’s content were developed with the assistance of Google Gemini. We utilize generative AI to synthesize and summarize publicly available information. All AI-generated drafts are rigorously reviewed, edited, and verified by human experts for accuracy.