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Conversational AI agents are proliferating, embodying a range of devices suchas smart speakers, smart displays, robots, cars, and more. We can envision afuture where a personal conversational agent could migrate across differentform factors and environments to always accompany and assist its user tosupport a far more continuous, personalized, and collaborative experience. Thisopens the question of what properties of a conversational AI agent migratesacross forms, and how it would impact user perception. To explore this, wedeveloped a Migratable AI system where a user's information and/or the agent'sidentity can be preserved as it migrates across form factors to help its userwith a task. We designed a 2x2 between-subjects study to explore the effects ofinformation migration and identity migration on user perceptions of trust,competence, likeability, and social presence. Our results suggest that identitymigration had a positive effect on trust, competence, and social presence,while information migration had a positive effect on trust, competence, andlikeability. Overall, users report the highest trust, competence, likeability,and social presence towards the conversational agent when both identity andinformation were migrated across embodiments.

Migratable AI: Effect of identity and information migration on users perception of conversational AI agents