How effectively can ChatGPT-4 draft data transfer agreements for health research?

Donrich Thaldar ()
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Donrich Thaldar: University of KwaZulu-Natal

Palgrave Communications, 2025, vol. 12, issue 1, 1-7

Abstract: Abstract The rapid advancement of generative artificial intelligence (AI), such as ChatGPT-4, is reshaping legal drafting, offering significant potential for streamlining the creation of complex legal documents. However, there is limited scholarly research on how effectively AI can draft specialised contracts, such as data transfer agreements (DTAs) for health research. Unlike common consumer contracts, DTAs are highly specialised and less prevalent in the public data used to train generative AI models, making them a more challenging test of AI’s drafting capabilities. This article fills this gap by critically assessing ChatGPT-4’s ability to draft DTAs for health research. The study uses a two-stage methodology: first, an iterative process to develop a comprehensive outline, and second, a detailed refinement of each clause. This methodology produced a comprehensive DTA of 6847 words. While this DTA includes all the standard headings, the quality of the clause content varies in terms of clarity and legal precision. Additionally, its alignment with data protection best practices requires further refinement. The findings suggest that although generative AI is a valuable tool for legal drafting, it cannot yet replace the essential role of human legal expertise.

Date: 2025
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DOI: 10.1057/s41599-025-04643-z

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