Table 2.

The characterization of the articles included for the systematic review.

Authors	Title	Study type	Sample	Main findings
Abdelmaboud et al. (2022)	Blockchain for IoT applications: taxonomy, platforms, recent advances, challenges and future research directions.	Cross Sectional	27 participants in private facilities in Saudi Arabia.	The increasing use of IoT has led to the contextualization of AI based on sectorial approaches.
Abdullah and Fakieh (2020)	Health Care Employees’ Perceptions of the Use of Artificial Intelligence Applications.	Cross Sectional	100 employees in public hospitals in Riyadh, Saudi Arabia.	The healthcare employees indicate positive perceptions in the use of the AI in improving healthcare services
Aboalshamat et al. (2022)	Medical and Dental Professionals Readiness for Artificial Intelligence for Saudi Arabia Vision 2030.	Cross Sectional	200 employees from public and private healthcare sectors in Makkah, Saudi Arabia.	The study indicates that most medical professionals lacked the preparedness for integrating and working with the AI as part of developing healthcare strategy.
Alharthi (2018)	Healthcare predictive analytics: An overview with a focus on Saudi Arabia.	Experimental	300 participants from healthcare workers from public healthcare system in Saudi Arabia.	The development of predictive analytics enables the realization of the intended goals and roles in actualizing healthcare development.
Alotaibi and Alshehri (2023)	Prospers and Obstacles in Using Artificial Intelligence in Saudi Arabia Higher Education Institutions—The Potential of AI-Based Learning Outcomes.	Cross Sectional	15 institutions in Saudi Arabia.	The prospers have included increased investments, with the cultures and expectations from the patients creating the main obstacles.
Alowais et al. (2023)	Revolutionizing healthcare: the role of artificial intelligence in clinical practice.	Cross Sectional	220 participants from public healthcare in Saudi	The role of AI in clinical practices included diagnoses, interventions and developing follow ups.
Chikhaoui et al. (2022)	Artificial Intelligence Applications in Healthcare Sector: Ethical and Legal Challenges.	Cross Sectional	50 participants from private hospitals in Saudi	The ethical and legal challenges affect the commitments towards integrating AI, due to risks and vulnerabilities that affect the quality of the outcomes.
El-Sherif et al. (2022)	Telehealth and Artificial Intelligence insights into healthcare during the COVID-19 pandemic.	Cross Sectional	80 participants from public hospitals.	The COVID-19 pandemic has been instrumental in promoting the appreciation of the role of AI in promoting access to care.
Khafaji et al. (2022)	Artificial intelligence in radiology.	Cross Sectional	20 radiologists from private health facilities in Saudi Arabia.	The use of AI in radiology has enabled an improvement in the overall quality of care.
Nasseef et al. (2022)	Artificial intelligence-based public healthcare systems: G2G knowledge-based exchange to enhance the decision-making process.	Cross sectional	40 participants from public health facilities in Saudi Arabia.	Healthcare organizations have invested in the development of strategic criteria for developing healthcare through AI.
Pugliese et al. (2021)	Machine learning-based approach: Global trends, research directions, and regulatory standpoints	Quasi Experiment	18 participants from private hospitals.	The development and use of machine learning can help actualize the demands in healthcare.
Rong et al. (2020)	Artificial intelligence in healthcare: review and prediction case studies.	Case Study	11 case studies from Saudi’s healthcare system	The use of AI would increase in healthcare development due to the commitments made towards sustaining technological use.
Salah et al. (2019)	Machine learning applications in the diagnosis of leukemia: Current trends and future directions.	Cross Sectional	90 participants from private hospitals.	The concepts of machine learning can help in improving healthcare.