# How Is Generative AI Used for Persona Development?: A Systematic Review of 52 Research Articles

**Authors:** Danial Amin, Joni Salminen, Farhan Ahmed, Sonja M. H. Tervola, Sankalp Sethi, Bernard J. Jansen  
**arXiv:** [2504.04927](https://arxiv.org/abs/2504.04927)  
**Date:** 2025-04-07  
**Summary page:** https://www.summarizepaper.com/en/arxiv-id/2504.04927v1/

## Key points

- The field of AI-generated personas is rapidly evolving, emphasizing the need to balance technical innovation with methodological rigor.
- Closed commercial models dominate persona development, leading to a lack of diversity.
- Generative AI (GenAI) is crucial in various stages of persona development but lacks comprehensive evaluation compared to traditional techniques.
- Human-AI collaboration models require further refinement for maintaining ethical standards.
- Collaborative efforts between academia and industry are essential for realizing the benefits of AI-generated personas.
- Future research should focus on developing standardized evaluation frameworks, enhancing transparency and reproducibility, expanding applications into underserved domains, and refining human-AI collaboration models.
- Delving deeper into specific aspects like the use of Large Language Models (LLMs) in persona development and incorporating additional variables can further improve AI-generated personas.
- Embracing interdisciplinary perspectives from fields like Human-Computer Interaction (HCI) and Natural Language Processing (NLP) can contribute to the evolution of AI-generated personas towards greater maturity and societal impact.

## Summary

The field of  is rapidly evolving and there is a pressing need to balance technical innovation with methodological rigor. A recent  of 52 articles from 2022-2024 sheds light on key findings and challenges in this area. The review highlights that closed commercial models dominate persona development, leading to a lack of  Additionally, Generative AI (GenAI) plays a crucial role in various stages of persona development, including data collection, segmentation, enrichment, and evaluation. Despite the potential of AI-generated personas, there are significant gaps in their evaluation compared to traditional quantitative persona development techniques. Human-AI collaboration models also require further refinement to ensure ethical standards are maintained. The review underscores the importance of collaborative efforts between academia and industry to fully realize the benefits of AI-generated personas. Moving forward, future research should prioritize developing standardized evaluation frameworks, enhancing transparency and reproducibility, expanding applications into underserved domains, and refining human-AI collaboration models. By drawing inspiration from established quantitative persona science principles and exploring new frontiers beyond software development and marketing, AI-generated personas can transition from a technological novelty to a robust and socially beneficial research paradigm. Furthermore, it is suggested that future research could delve deeper into specific aspects such as the use of Large Language Models (LLMs) in different stages of persona development and incorporate additional variables like the number of personas generated and the framework used for evaluation. By addressing these areas for improvement and embracing interdisciplinary perspectives from fields like Human-Computer Interaction (HCI) and Natural Language Processing (NLP), the field of AI-generated personas can continue to evolve towards greater maturity and societal impact.