Summon: Integrating an Emotion-Aware AI Companion into Everyday Productivity

Purpose — This research explores whether a productivity application can meaningfully support user motivation and emotional wellbeing by combining task management with an AI companion character, voice-first task capture, mood-aware adaptation, and gamified progress feedback. The study responds to a persistent gap in existing productivity tools between organising tasks and helping people actually begin them. Design/methodology/approach — A human-centred design approach was used to conceptualise Summon, a productivity companion in which users select a personality-driven AI character during onboarding. Task creation was designed around natural voice input processed through speech recognition and natural-language understanding, with AI-suggested task structures always confirmed by the user before being saved. A lightweight, optional mood check-in was layered onto the daily flow so that interface tone and task suggestions could adapt without removing user control. Progress feedback was reframed through narrative and gamification patterns rather than flat completion states. Findings — Six interaction patterns emerged as central to the concept: character-based motivational framing, voice-first task capture with mandatory user confirmation, mood-adaptive rather than diagnostic tone-shifting, narrative-based progress feedback, a deliberately narrow information architecture, and privacy-by-design handling of behavioural and emotional data. Practical implications — The findings suggest that productivity interfaces can reduce the gap between intention and action by treating motivation, and not only organisation, as a first-class design problem, while remaining accountable for emotional-data collection, AI error correction, and user autonomy.