The spark of talking to a chatbot fades with use — how fast does that happen, and can we actually measure it?

This explores how fast the early spark of talking to a chatbot fades with repeated use. The short answer: the corpus doesn't give a precise decay curve, with a number of sessions or weeks. It does show that the fade is real and predictable, and that some parts of the relationship fade while others grow. Longitudinal work with the social chatbot Mitsuku found that the processes that drive relationship formation, like curiosity, liking and willingness to engage, decline steadily as the novelty wears off. The practical warning from that research is that findings from a single session can't be extrapolated to medium- or long-term use Do chatbot relationships lose their appeal as novelty wears off?. A large share of chatbot research consists of one-shot studies, so much of what we think we know about chatbot relationships may really describe a first date.

The most concrete evidence of speed comes from a nearby area: persuasion. Claude and DeepSeek started with a strong persuasive edge over human persuaders, but that edge wore down across a handful of repeated quiz rounds while the humans stayed steady Does AI persuasiveness fade across repeated conversations with the same person?. That reverses the usual human pattern, where rapport builds over time. It suggests that part of an AI's early influence is novelty in disguise, and that it can erode within a few interactions rather than over months.

Not everything decays, though. Personalization studies that follow users over time found that trust and the sense of the chatbot as human-like can increase with use. Expectations rise along with them, so each good interaction raises the bar and makes later failures more disappointing Does chatbot personalization build trust or expose privacy risks?. In partner-selection games, people started out biased against AI partners but came to prefer them over repeated rounds once the bots proved reliable Do humans learn to prefer AI partners over time?. The pattern looks less like simple decay and more like a handoff. Fascination with something new fades, and reliability-based trust either takes its place or doesn't.

That is why researchers treat the number of interactions as a design variable in its own right. One framework, adapted from ecological psychology, treats interaction count as its own layer (the 'chronosystem') that changes how users see the bot Why do users respond so differently to AI chatbots?. A review of 120 chatbots found that time horizon is the main thing separating one-off helpers, temporary assistants and long-term companions, and that each needs a different design How should chatbot design vary by relationship duration?. A companion bot that relies on first-session charm is built for the wrong time horizon.

What you may not have expected: the features that feel most 'relational' early on may not be what lasts. Users open up more to chatbots because there is no judgment Do chatbots help people disclose more intimate secrets?, and consistent emotional sharing from the bot draws deeper disclosure in return Do chatbots trigger human reciprocity norms around self-disclosure?. Both findings are mostly short-term. Whether they survive novelty decay is exactly the open question the corpus can't yet answer.