PurposeThe advent of ChatGPT has fundamentally changed the way people approach and access information. While we are encouraged to embrace the tool for its various benefits, it is yet to be known how to drive people to adopt this technology, especially to improve their life skills. Using implicit self-theories, the current research delineated the distinct way incremental (vs entity) theorists use ChatGPT, which in turn influences their attitude and hence the behavioural intention towards this technology.Design/methodology/approachThe research employed a between-subject experimental design with 100 prolific participants. The manipulation materials were also pre-tested (N = 50). No confound effects such as content clarity, personal interest, and cognitive load were found. For the mediating effect, PROCESS Model 4 with bootstraps 5,000 and CI 95% were employed.FindingsIndividuals who believed that human ability to use technological applications was malleable, i.e. incremental theorists, were more likely to use ChatGPT to improve their life skills. On the other hand, when people believed that such an ability was fixed, i.e. entity theorist, they were less likely to use this new technology. The reason was that through the implicit belief, attitude towards ChatGPT was (more vs less) positively influenced which in turn motivated the behavioural intention. Further, the effect held beyond the impact of demographic factors such as age, gender, occupation, and educational level.Originality/valueEven though implicit self-theories have received tremendous interest and empirical support, be it generic or domain-specific, the effect of implicit belief in technological applications was not clearly determined. The current research helps to extend the implicit self-theories into the technological domain, and in this case, the usage of ChatGPT. Moreover, the full mediating effect of attitude offers some thought about the revised models of technology acceptance. That is, perhaps it is the combination of (implicit) belief and attitude that may have better predictive power for technological adoption behaviour.