Abstract
Artificial intelligence is increasingly piloted in healthcare across Australia and New Zealand (AU/NZ), yet implementation remains uneven due to regulatory, environmental, societal, and technical challenges. This scoping review maps barriers and enablers of healthcare AI adoption, guided by the REST taxonomy (Regulatory, Environmental, Societal, Technical) and analysed using the Consolidated Framework for Implementation Research (CFIR). Literature published between 218 and April 225 was systematically searched across PubMed, Scopus, Google Scholar, and government sources, with 57 studies meeting inclusion criteria (38 from AU/NZ). Findings show societal concerns such as trust, equity, cultural safety, alongside technical issues of data quality and workflow integration, as the most frequently reported barriers; regulatory hurdles were persistent, while environmental impacts were rarely addressed. Few studies explicitly applied implementation frameworks. We present a REST–CFIR mapping that links challenges to practical enablers and propose a research agenda to guide equitable and sustainable healthcare AI deployment in AU/NZ.
Recommended Citation
Khoushmehr, Mina Ahmadiyan; Bajaj, Ruhi; HassanDoust, Farkhondeh; Beltran, Fernando; and Putra, Pragea, "Untangling the Barriers: A CFIR-Guided Scoping Review of AI
Implementation in Healthcare" (2025). ACIS 2025 Proceedings. 236.
https://aisel.aisnet.org/acis2025/236