AUTOMATION OF GRANT APPLICATION WRITING WITH THE USE OF CHATGPT

Purpose: This paper examines the integration of generative AI, specifically ChatGPT, into grant application writing, evaluating its impact on efficiency, quality, and equity in research funding. The study aims to address systemic challenges in grant writing, such as high time investment, low success rates, and inherent biases against underrepresented groups. Design/methodology/approach: The research analyzes the development and submission of four grant proposals to public and private funding bodies in the U.S. and EU. ChatGPT was employed to automate key components of the process, including generating proposal structures, drafting content, and formatting team qualifications. The outcomes were compared in terms of time efficiency, success rates, and the quality of applications. Findings: The use of ChatGPT reduced the average grant preparation time from 30-50 days to 3-5 days while achieving a 50% success rate, significantly exceeding typical success rates of 10-20%. The findings highlight ChatGPT’s potential to enhance the inclusivity of funding processes by mitigating biases and lowering entry barriers for junior faculty and underrepresented groups. Research limitations/implications: The study is limited by the small sample size of four grant applications and the inherent variability of AI-generated outputs. Future research should explore scalability, reproducibility, and the ethical implications of AI use in academic and professional settings. Practical implications: The adoption of AI in grant writing can streamline the application process, allowing researchers to focus on substantive project development. Funding bodies are encouraged to adapt evaluation standards to distinguish between human-authored and AI-generated content, ensuring fair assessments. Social implications: By reducing biases and increasing accessibility, AI-driven grant writing can democratize research funding opportunities, fostering greater equity and diversity in academic and scientific communities. Originality/value: This study provides the first empirical evaluation of ChatGPT’s application in grant writing, offering insights into its transformative potential for academia, policy, and research funding practices. It is valuable to researchers, funding organizations, and policymakers seeking to leverage AI for more inclusive and efficient grant processes.

Authors

Publication Details

Journal
Scientific Papers of Silesian University of Technology Organization and Management Series
Published
2025-01-01
DOI
https://doi.org/10.29119/1641-3466.2025.216.30
Citations
1
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
4.17
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article

AUTOMATION OF GRANT APPLICATION WRITING WITH THE USE OF CHATGPT

Krzysztof Rybiński
1 citations
Scientific Papers of Silesian University of Technology Organization and Management Series
Scientific Computing and Data Management
4.17
article

AUTOMATION OF GRANT APPLICATION WRITING WITH THE USE OF CHATGPT

Krzysztof Rybiński
article en
1 citations

Abstract

Purpose: This paper examines the integration of generative AI, specifically ChatGPT, into grant application writing, evaluating its impact on efficiency, quality, and equity in research funding. The study aims to address systemic challenges in grant writing, such as high time investment, low success rates, and inherent biases against underrepresented groups. Design/methodology/approach: The research analyzes the development and submission of four grant proposals to public and private funding bodies in the U.S. and EU. ChatGPT was employed to automate key components of the process, including generating proposal structures, drafting content, and formatting team qualifications. The outcomes were compared in terms of time efficiency, success rates, and the quality of applications. Findings: The use of ChatGPT reduced the average grant preparation time from 30-50 days to 3-5 days while achieving a 50% success rate, significantly exceeding typical success rates of 10-20%. The findings highlight ChatGPT’s potential to enhance the inclusivity of funding processes by mitigating biases and lowering entry barriers for junior faculty and underrepresented groups. Research limitations/implications: The study is limited by the small sample size of four grant applications and the inherent variability of AI-generated outputs. Future research should explore scalability, reproducibility, and the ethical implications of AI use in academic and professional settings. Practical implications: The adoption of AI in grant writing can streamline the application process, allowing researchers to focus on substantive project development. Funding bodies are encouraged to adapt evaluation standards to distinguish between human-authored and AI-generated content, ensuring fair assessments. Social implications: By reducing biases and increasing accessibility, AI-driven grant writing can democratize research funding opportunities, fostering greater equity and diversity in academic and scientific communities. Originality/value: This study provides the first empirical evaluation of ChatGPT’s application in grant writing, offering insights into its transformative potential for academia, policy, and research funding practices. It is valuable to researchers, funding organizations, and policymakers seeking to leverage AI for more inclusive and efficient grant processes.

Scientific Papers of Silesian University of Technology Organization and Management SeriesVol. 2025(216)
Openalex Percentile: Top 7%
Scientific Computing and Data Management
4.17
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