How effectively can ChatGPT-4 draft data transfer agreements for health research?
1School of Law, University of KwaZulu-Natal, Durban, South Africa.
Humanities & Social Sciences Communications
|February 5, 2026
Summary
Generative artificial intelligence (AI) shows promise in drafting specialized health research data transfer agreements (DTAs). However, current AI models require human legal expertise for accuracy and data protection compliance.
Area of Science:
- Legal Technology
- Artificial Intelligence in Law
- Health Law
Background:
- Generative AI, like ChatGPT-4, is advancing rapidly, impacting legal drafting.
- Limited research exists on AI's effectiveness in drafting specialized contracts, such as health research data transfer agreements (DTAs).
- DTAs are complex and less common in AI training data, posing a unique challenge.
Purpose of the Study:
- To critically assess ChatGPT-4's capability in drafting data transfer agreements (DTAs) for health research.
- To identify limitations and areas for improvement in AI-generated legal contracts.
Main Methods:
- A two-stage methodology was employed: iterative outline development followed by detailed clause refinement.
- The process resulted in a comprehensive DTA of 6847 words.
Main Results:
- The AI-generated DTA included standard headings but varied in clause clarity and legal precision.
- Alignment with data protection best practices requires further refinement.
- The AI-generated DTA was a valuable starting point but not a complete substitute for human legal input.
Conclusions:
- Generative AI is a useful tool for legal drafting, particularly for complex documents like DTAs.
- Human legal expertise remains indispensable for ensuring accuracy, precision, and compliance in specialized legal drafting.
- Further development is needed for AI to fully meet the demands of specialized legal contract generation.
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