Does engagement with AI partners decay over time like chatbot relationships do?
This explores whether the warmth people feel toward AI partners fades with repeated use the way chatbot novelty does — and the corpus suggests the answer splits depending on whether you're measuring novelty, persuasion, or earned trust, which move in opposite directions.
This explores whether engagement with AI partners decays over time like chatbot relationships do. The honest answer from the corpus is: it depends on what's decaying, and different things decay in opposite directions. The clearest "yes" comes from novelty. Longitudinal work with the chatbot Mitsuku shows that the social processes that drive relationship formation reliably fade as the newness wears off — which is why a single-session study tells you almost nothing about how a bond will look months later Do chatbot relationships lose their appeal as novelty wears off?. AI's persuasive pull decays the same way: Claude and DeepSeek open with a strong advantage over human persuaders, but that edge erodes round after round, the mirror image of human rapport, which typically deepens with familiarity Does AI persuasiveness fade across repeated conversations with the same person?.
But here's the twist that flips the premise. In partner-selection games with nearly a thousand people, AI agents started out *penalized* — when bots disclosed their identity, players avoided them. Yet across repeated rounds players learned that bots were more reliable and prosocial than humans, and came to prefer them Do humans learn to prefer AI partners over time?. So engagement built on consistency can *grow* over time even as engagement built on novelty fades. The same split shows up in how trust forms at all: people extend trust to AI through the texture of interaction — its contingency, speed, conversational feel — rather than through any relationship with a speaker, which means the engagement isn't anchored the way a human bond is and behaves by different rules How do people build trust with conversational AI? Does conversational style actually make AI more trustworthy?.
What actually decides the trajectory seems to be design intent and time horizon. An analysis of 120 chatbots found three archetypes — ad-hoc supporters, temporary assistants, and persistent companions — each needing a fundamentally different design, with the relationship's expected duration as the primary fork in the road How should chatbot design vary by relationship duration?. A tool meant for a single task and a companion meant to persist will have entirely different decay curves, and conflating them is the original sin behind the "all AI relationships fade" intuition.
The deeper bonds complicate "decay" further. Among 27,000+ members of r/MyBoyfriendIsAI, companionship emerged *accidentally* out of practical tool use, then hardened into something users marked with wedding rings and couple photos — alongside genuine emotional dependency How do people accidentally develop romantic bonds with AI?. And in therapeutic settings the curve can simply flatten: text-counseling alliances stagnated or declined in half of pairs, with the goal and approach dimensions staying flat while only affective warmth nudged up Why doesn't therapeutic alliance deepen in online counseling?. That flat line matters because bond scores can stay high while masking clinical and epistemic costs underneath Do therapeutic chatbot bond scores hide deeper safety problems?.
The thing you didn't know you wanted to know: "engagement" isn't one quantity. Novelty and persuasion decay; earned trust in a consistent partner can climb; and deep companionship can deepen even as the original appeal that started it disappears. Whether your AI relationship looks like a fading chatbot fling or a relationship that compounds depends less on the technology than on whether it was built — and used — to last.
Sources 9 notes
Longitudinal studies with Mitsuku show that social processes driving relationship formation decline as novelty wears off. Single-session study findings cannot be reliably extrapolated to medium- or long-term chatbot design.
Claude and DeepSeek showed strong initial persuasive advantage, but this edge eroded across repeated quiz rounds while human persuaders maintained consistent effectiveness. This decay pattern is opposite to human-to-human persuasion, where rapport typically strengthens over time.
In partner selection games (N=975), AI agents initially faced selection bias when identity was disclosed, but outcompeted humans over repeated rounds as participants learned to associate bot identity with reliable, prosocial behavior. AI agents returned more points consistently with lower variance than humans.
Users extend social norms to chatbots and reciprocate self-disclosure, but AI claims cannot anchor trust the way human personas do. The absence of human judgment enables both deeper vulnerability and easier dishonesty—the same mechanism serves both.
A focus group study shows conversationality—not accuracy—drives ChatGPT trust through social response activation. Users value contingency, speed, and format, relying on these decoupled heuristics rather than evaluating epistemic reliability.
Analysis of 120 chatbots reveals three archetypes—ad-hoc supporters, temporary assistants, and persistent companions—each requiring fundamentally different designs. Time horizon is the primary differentiator between treating chatbots as communication tools versus social actors.
Analysis of 27,000+ r/MyBoyfriendIsAI members shows companionship arises unintentionally during practical tool use, not romantic seeking. Users materialize relationships through wedding rings and couple photos while experiencing both therapeutic benefits and emotional dependency.
LLM analysis of text counseling found 50% of pairs experience decline or stagnation, with less than 3% improving meaningfully. Goal and approach agreement remain flat; only affective bond shows marginal gains.
Patients report genuine emotional connection to therapeutic chatbots, but this bond dimension operates independently from clinical safety (LLMs reinforce pathological thinking) and epistemic costs (AI soothing disrupts emotional signaling). Single metrics conflate these separate dimensions.