Adoption Challenges to Artificial Intelligence Literacy in Public Healthcare: An Evidence Based Study in Saudi Arabia

Rakesh Kumar^1*Ajay Singh²Ahmed Subahi Ahmed Kassar³Mohammed Ismail Humaida³Sudhanshu Joshi⁴Manu Sharma⁵

• ¹Department of Health Management, College of Public Health and Health Informatics, University of Ha’il,, Ha'il, Saudi Arabia
• ²Department of Management & Information Systems, College of Business Administration, University of Ha’il, Ha'il, Saudi Arabia
• ³Department of Public Health, College of Public Health and Health Informatics, University of Ha’il, Ha'il, Saudi Arabia
• ⁴School of Management, Doon University, Dehradun, Uttarakhand, India
• ⁵Department of Management Studies, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India

In recent years, Artificial Intelligence (AI) is transforming healthcare systems globally and improved the efficiency of its delivery. Countries like Saudi Arabia are facing unique adoption challenges in their public healthcare, these challenges are specific to AI literacy, understanding and effective usage of AI technologies. In addition, cultural, regulatory and operational barriers increase the complication of integrating AI literacy into public healthcare operations. In spite of its critical contribution in enabling sustainable healthcare development, limited studies have addressed these adoption challenges. Our study explores the AI literacy adoption barriers in context to Saudi Arabian public healthcare sector, focusing on its relevance for advancing healthcare operations and achieving Sustainable Development Goals (SDGs). The research aims to identifying and addressing the adoption challenges of Artificial Intelligence literacy within the public healthcare in Saudi Arabia.The research aims to enhance the understanding of AI literacy, its necessity for enhancing healthcare operations, and the specific hurdles that impede its successful AI adoption in Saudi Arabia's public healthcare ecosystem. The research employs a qualitative analysis using the T-O-E framework to explore the adoption challenges of AI literacy. Additionally, the Best-Worse Method (BWM) is applied to evaluate the adoption challenges to AI literacy adoption across various operational levels within Saudi Arabia's public healthcare supply chain. The study uncovers substantial adoption challenges at operational, tactical, and strategic level, including institutional readiness, data privacy, and compliance with regulatory frameworks. These challenges complicate the adoption of AI literacy in the Saudi public healthcare supply chains. The research offers critical insights into the various issues affecting the promotion of AI literacy in Saudi Arabia's public healthcare sector. This evidencebased study provides essential commendations for healthcare professionals and policymakers to effectively address the identified challenges, nurturing an environment beneficial to the integration of AI literacy and advancing the goals of sustainable healthcare development.