Abstract

Statistical surveys are the core foundation of robust, evidence-based decision-making Considering that the quality of the final data is fundamentally determined during the questionnaire design phase, achieving the highest levels of accuracy and effectiveness in data collection is paramount , Consequently, in response to the rapid acceleration of digital transformation, Consequently in response to the rapid acceleration of digital transformation, NSOs and research institutions must prioritize the urgent modernization of traditional practices by adopting cutting-edge technological tools, particularly Artificial Intelligence (AI), to enhance operational efficiency and safeguard data integrity..
In this context, Generative AI tools like ChatGPT and Large Language Models (LLMs (emerge as powerful instruments to address linguistic and logical challenges. Leveraging its text generation capabilities, ChatGPT acts as an efficient methodological assistant, analyzing complex statistical wordings, proposing alternatives to reduce bias, and generating consistent Skip Logic. This represents a paradigm shift from manual scrutiny to advanced automated support in survey design.
Building on this capability, this paper presents an applied case study focusing on the design of the "Trends of Egyptian Households Towards Internal Migration due to Climate Change" survey, specifically it investigates how ChatGPT enhances crucial design stages, including generating nuanced wordings for sensitive items and standardizing terminology across diverse respondent groups (household head, youth, and children).
Furthermore, this paper analyzes the practical benefits and identifies the key operational challenges that NSOs must navigate when implementing this innovative methodology to fortify the quality of their measurement instruments before fieldwork begins.