PersoPilot: An Adaptive AI-Copilot for Transparent Contextualized Persona Classification and Personalized Response Generation
Saleh Afzoon, Amin Beheshti, Usman Naseem

TL;DR
PersoPilot is an adaptive AI system that combines persona understanding with contextual analysis to enable transparent, personalized interactions and insights for users and analysts, improving service personalization.
Contribution
It introduces PersoPilot, a novel AI-Copilot that integrates persona and context for adaptive, explainable personalization and active learning-based classification.
Findings
Supports natural language preferences and recommendations
Provides transparent, reasoning-powered labeling for analysts
Adapts over time with new labeled data
Abstract
Understanding and classifying user personas is critical for delivering effective personalization. While persona information offers valuable insights, its full potential is realized only when contextualized, linking user characteristics with situational context to enable more precise and meaningful service provision. Existing systems often treat persona and context as separate inputs, limiting their ability to generate nuanced, adaptive interactions. To address this gap, we present PersoPilot, an agentic AI-Copilot that integrates persona understanding with contextual analysis to support both end users and analysts. End users interact through a transparent, explainable chat interface, where they can express preferences in natural language, request recommendations, and receive information tailored to their immediate task. On the analyst side, PersoPilot delivers a transparent,…
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Taxonomy
TopicsPersona Design and Applications · AI in Service Interactions · Innovative Human-Technology Interaction
