Using Large Language Models to Transform Estate Planning

Background: Advancements in generative artificial intelligence (AI) and large language models (LLMs) have introduced new possibilities in democratizing access to professional services. Malaysia's non-Muslims can rely on AI-driven tools to draft their wills without legal assistance, but empirical evaluations of LLM chatbots' reliability are absent. Methods: Grounded in the Technology Acceptance Model, this study assesses the accuracy, legal validity, comprehensibility, and reliability of five prominent LLM chatbots, namely ChatGPT 3.5, ChatGPT 4.0, Claude Sonnet, Gemini Pro, and Microsoft Copilot. Results: ChatGPT 4.0 consistently outperformed other models across all complexity levels in succession and drafting-related question tasks, showing the highest reliability and accuracy. Gemini Pro performed well for introductory and intermediate queries, particularly in drafting simple wills. In contrast, Copilot and Claude Sonnet exhibited high variability and struggled with complex queries. Across all chatbots, performance declined significantly with increased query complexity. Qualitative assessment reveals inconsistencies, misinterpretations, and occasional legal inaccuracies, particularly when prompts contain incomplete information. Conclusion: While specific LLM chatbots, particularly ChatGPT 4.0, demonstrate potential as reliable tools for basic estate planning, their limitations in handling complex legal instructions underscore the need for caution. By shedding light on the role of AI in legal contexts, this research significantly enriched both scholarly and practical dialogues, enhancing our understanding of AI’s potential to revolutionize the legal landscape, particularly in estate planning.

Authors

Institutions

Publication Details

Journal
Recoletos Multidisciplinary Research Journal
Published
2025-04-12
DOI
https://doi.org/10.32871/rmrj2513.01.15
Primary Topic
BIM and Construction Integration
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Using Large Language Models to Transform Estate Planning

Richard Yeaw Chong Seow
Recoletos Multidisciplinary Research Journal
BIM and Construction Integration
article

Using Large Language Models to Transform Estate Planning

Richard Yeaw Chong Seow
article en

Abstract

Background: Advancements in generative artificial intelligence (AI) and large language models (LLMs) have introduced new possibilities in democratizing access to professional services. Malaysia's non-Muslims can rely on AI-driven tools to draft their wills without legal assistance, but empirical evaluations of LLM chatbots' reliability are absent. Methods: Grounded in the Technology Acceptance Model, this study assesses the accuracy, legal validity, comprehensibility, and reliability of five prominent LLM chatbots, namely ChatGPT 3.5, ChatGPT 4.0, Claude Sonnet, Gemini Pro, and Microsoft Copilot. Results: ChatGPT 4.0 consistently outperformed other models across all complexity levels in succession and drafting-related question tasks, showing the highest reliability and accuracy. Gemini Pro performed well for introductory and intermediate queries, particularly in drafting simple wills. In contrast, Copilot and Claude Sonnet exhibited high variability and struggled with complex queries. Across all chatbots, performance declined significantly with increased query complexity. Qualitative assessment reveals inconsistencies, misinterpretations, and occasional legal inaccuracies, particularly when prompts contain incomplete information. Conclusion: While specific LLM chatbots, particularly ChatGPT 4.0, demonstrate potential as reliable tools for basic estate planning, their limitations in handling complex legal instructions underscore the need for caution. By shedding light on the role of AI in legal contexts, this research significantly enriched both scholarly and practical dialogues, enhancing our understanding of AI’s potential to revolutionize the legal landscape, particularly in estate planning.

Recoletos Multidisciplinary Research JournalVol. 13(1)
Paris School of Business (FR)
Openalex Percentile: Top 84%
BIM and Construction Integration
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.