Aim/Purpose
The purpose of this study is to address the gap in methodologies, data sources, and validation frameworks for interactive persona systems as they evolve from static design artifacts to AI-driven simulators.

Background
Research on personas has traditionally focused on their use as static tools for communicating user requirements to designers. However, the evolution of Artificial Intelligence has transformed these narratives into dynamic systems that simulate real user behavior.

Methodology
The systematic search resulted in 1096 records, of which 985 abstracts were screened, reducing the relevant citations to 65 full-text papers assessed for eligibility. Ultimately, 42 studies met our inclusion criteria. They were analyzed for creation methods, domains, and interaction types, and graded using the Technology Readiness Level (TRL) assessment, a nine-point scale measuring system maturity from concept to deployment.

Contribution
This paper presents the first comprehensive mapping of the design space for interactive persona systems. To support applied settings, it introduces a Practitioner’s Toolkit, featuring a Design Framework and a decision matrix, that provides a structured, evidence-based path to select, build, and validate interactive persona systems based on specific project constraints. Furthermore, the review maps four core system types (Behavioral Simulation, Persona Management, Autonomous Personas, and Interface Personas) to distinct use cases and validation goals, providing guidelines to build personas that serve as a fundamental bridge for human-AI alignment.

Findings
The technology readiness assessment revealed that the field is still in develop-mental stages, with only 8.6% of systems achieving high and operational maturity levels (TRL 6-9). A critical gap was noted regarding empirical validation: 52% of systems lack any empirical validation. Interactive personas are most prominently applied in UX research, education, gaming, and social simulation, with web applications representing the dominant mode of user interaction. This validation gap directly undermines the reliability of human-AI alignment in design, as systems that have not been empirically tested against real users cannot be assumed to faithfully represent human behavior.

Recommendations for Practitioners
Practitioners are advised to utilize personas to humanize AI systems in human-AI collaboration, integrate personas as core interface components, and leverage them to advance Human-AI alignment.

Recommendations for Researchers
Researchers are urged to develop standardized validation frameworks to assess persona alignment with real users to advance Human-AI alignment.

Impact on Society
Interactive personas advance computing for social good, such as training and advocacy, by providing safe simulation environments. They enable privacy-preserving research through anonymized, aggregated population models.

Future Research
Future work must balance empirical validity with cost constraints and establish ethical metrics to ensure interactive persona systems authentically represent human behavior.
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