Impacts of artificial intelligence on healthcare business models and outcomes

Purpose This study aims to identify what the interaction between artificial intelligence (AI) and business models (BMs) can have on healthcare (HC) outcomes and experience and also what the ethical considerations are for AI implementation in HC. The study proposes an exploratory method using data collected from HC professionals. It aims to fill the identified gaps and contribute to theory and practice. Design/Methodology/Approach This study used an exploratory methodology based on open-ended essay questions designed on prolific.co and collected data from 29 HC professionals. These include experts in the use of AI in HC, and a content analysis was used to analyze the data. Findings The results showed that using AI in HC can lead to the standardization of HC services, leading to improved access to quality care with reduced cost. It revealed that AI can increase HC efficiency by automating services and increasing innovations and discoveries. But there are some ethical concerns hindering the adoption of AI HC, including data privacy, bias in algorithms and liability issues. Research limitations/implications The sample size and the lack of including the opinions of patients are the major limitations of this study. Future studies are encouraged to improve in this direction. Practical implications This study will promote and facilitate the wider acceptance and implementation of AI in HC. It will also enable policy and decision-makers to address ethical issues hindering the adoption of AI in HC. Originality/Value This study has filled an important research gap by revealing how AI is impacting HC BMs and outcomes. The study will facilitate the adoption of AI in HC.