Investigating the AI Drivers Integrating in Healthcare Systems

The study categorizes drivers that lead to the adoption of Artificial Intelligence (AI) in the healthcare services industry using ISM and MICMAC analysis. Systematically, the study categorizes and evaluates the major enablers and key success factors to reveal their interaction with one another as well as their level of hierarchy contrary to the situation in the layered technological infrastructure, legal frameworks, data management, organizational preparedness, and technological developments. The study reveals profound correlations, and although it shows that international comparisons have to be treated with caution as the existence of a correlation does not imply causation, it emphasizes the need to enhance various aspects such as data management and technological readiness to ensure successful AI implementation. Due to MICMAC analysis, several strategic focus areas are found, which highlights that the application of AI needs a systematic approach because it is a complex process to integrate and bring revolution in the industry. The method concludes the study offering the following practical findings; the authors suggest sound policies and frameworks to govern the employment of Artificial Intelligence, efficient technological platforms to support the employment of artificial intelligence, efficient education and training of the workforce, and an efficient ethical framework to govern the employments of artificial intelligence at workplaces.