Trust in public institutions was challenged during the COVID-19 global pandemic, with widespread mistrust towards healthcare institutions as well as fellow public institutions. Concurrently, a new public institution or social tool, mass-market artificial intelligence (AI), more broadly emerged, which too may be a target of fluctuating public trust. Using national survey data from the United Kingdom’s Centre for Data Ethics and Innovation (survey year: 2022, N = 4320; survey year: 2023, N = 4232), we explore the level of trust in civic institutions (healthcare, non-healthcare, and AI) during and immediately after the COVID-19 pandemic in the United Kingdom using a naturalistic quasi-experimental design. At both waves (2022 and 2023), principal component analysis and structural equation modeling over thirteen public institutions and AI variables confirmed three factors (or domains) of public trust: trust in healthcare institutions, trust in fellow civic institutions other than healthcare, and trust in AI. Measurement invariance testing of mean levels of public trust along each distinct component revealed that as compared with 2022, in 2023, (1) trust in healthcare institutions and in fellow civic institutions other than healthcare significantly increased and (2) trust in AI remained approximately level. Next, latent profile modeling revealed four levels of a common public trust profile, with all three domains of public trust being normatively closely associated. Taken together, these results suggest that a psychological stance of public trust, PT, may increase after a societal crisis.