This paper explores the impact of GEN AI in research projects, highlighting real-world applications and insights. It covers questionnaire development, dynamic surveys, data quality management, and text analytics. Key findings include the effectiveness of AI-generated questionnaires, the advantages of dynamic surveys in capturing respondent sentiment, and the potential of fine-tuned models for data quality management. Additionally, machine-driven text analytics shows promise in sentiment analysis and theme identification, achieving near human-level performance on larger datasets.
