A Structural Analysis of AI Implementation Challenges in Healthcare

The incorporation of artificial intelligence (AI) into the healthcare system has been revolutionized, promising keyadvancements in diagnosis, treatment, patient care, administrative tasks, and operational efficiency.The implementation of artificial intelligence into the healthcare system has been very transformational, productive, and hopeful, with the potential to revolutionize diagnosis, treatment, patient care, administrative work, and operational efficiency. Using an in-depth analysis of the extensive amount of literature on artificial intelligence and how it could help the medical industry, this study identified the eleven barriers and challenges. An interpretative structural modelling (ISM) has been used as a methodological approach to find out the relationship between the extracted challenges and their dependency and driving powers. It resulted in a five-tiered model with introduction of innovative and new generation tools topping the chart as the most dependent challenge. Similarly Insufficient Data, Data Acquisition, Data Misuse and Missing Compassion being the key drivers. Thereby, during the implementation of artificial intelligence in medicine, there challenges should be considered.