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