AI-Assisted Goal Setting Improves Goal Progress Through Social Accountability

TL;DR

This study shows that AI chatbots can enhance short-term goal progress by increasing social accountability, offering a scalable alternative to traditional coaching, with effects mediated by perceived accountability.

Contribution

It demonstrates that AI-assisted goal setting improves goal progress and highlights increased perceived social accountability as a key mechanism.

Findings

AI chatbot outperformed control in goal progress (d=0.33)

AI increased perceived social accountability

Accountability mediated the effect on goal progress

Abstract

Helping people identify and pursue personally meaningful career goals at scale remains a key challenge in applied psychology. Career coaching can improve goal quality and attainment, but its cost and limited availability restrict access. Large language model (LLM)-based chatbots offer a scalable alternative, yet the psychological mechanisms by which they might support goal pursuit remain untested. Here we report a preregistered three-arm randomised controlled trial (N = 517) comparing an AI career coach ("Leon," powered by Claude Sonnet), a matched structured written questionnaire covering closely matched reflective topics, and a no-support control on goal progress at a two-week follow-up. The AI chatbot produced significantly higher goal progress than the control (d = 0.33, p = .016). Compared with the written-reflection condition, the AI did not significantly improve overall goal progress, but it increased perceived social accountability. In the preregistered mediation model, perceived accountability mediated the AI-over-questionnaire effect on goal progress (indirect effect = 0.15, 95% CI [0.04, 0.31]), whereas self-concordance did not. These findings suggest that AI-assisted goal setting can improve short-term goal progress, and that its clearest added value over structured self-reflection lies in increasing felt accountability.