The Shape of My-AI: How Multimodality Shapes Trust and Persuasion in Interactions with an AI-Generated Future Self

AI-generated future selves allow people to engage in dialogue with a personalized digital representation of themselves decades ahead, yet it remains unclear how presentation modality shapes their psychological impact. We report a randomized between-subjects study (n=92) comparing three modalities of an AI-generated future self—text, voice, and a photorealistic talking avatar—against a neutral voice control. After evaluating multiple large language models for conversational quality, we implemented Claude 4 and integrated age progression, voice cloning, and facial animation. All personalized modalities significantly increased future self-continuity, particularly vividness and positivity, relative to control, with no reliable differences across text, voice, and avatar conditions. Although the avatar produced the largest vividness gain, effects were comparable across modalities. Instead, subjective interaction quality, especially perceived persuasiveness, realism, and engagement, strongly predicted gains in future self-continuity and affect, indicating that experiential quality matters more than interface form. Conversation analysis revealed modality-specific patterns, with text emphasizing instrumental career planning and voice-based interactions eliciting more existential reflection. These findings suggest that future-self interventions can scale through lightweight conversational formats when optimized for personalization and behavioral authenticity, while underscoring ethical considerations around persuasive influence and narrative authorship in self-referential AI systems.