Аңдатпа
The digital transformation of healthcare and the rapid development of artificial intelligence technologies are creating new opportunities for healthcare delivery and managerial decision-making. This study assesses the prerequisites, application areas, and potential effects of artificial intelligence on the efficiency of healthcare system management in the Republic of Kazakhstan. The empirical base includes official statistical data for Kazakhstan for 2015–2025, materials of the Ministry of Healthcare of the Republic of Kazakhstan, national strategic and regulatory documents, and international research on the application of artificial intelligence in clinical and administrative healthcare processes. The study used dynamic, comparative, and structural analysis, document content analysis, a process-based approach, and systematisation of practical AI implementation cases. The findings show that the number of physicians increased from approximately 69.7 thousand in 2015 to 84.0 thousand in 2025, while the number of hospital organisations changed from 901 to 832. In 2025, more than 215 million healthcare services were provided, of which 190.8 million, or 88.6%, were delivered electronically. The development of the E-Densaulyq ecosystem, integration of fragmented information systems, and creation of a unified medical data repository establish a technological foundation for moving from digital record-keeping to data-driven, AI-supported management. The greatest managerial potential of AI is identified in patient-flow forecasting, resource planning, pharmaceutical supply management, quality control, clinical decision support, and anomaly detection. The study proposes an original AI-driven healthcare management framework that links digitalisation, data integration, AI applications, managerial processes, measurable efficiency outcomes, risk assessment, and evidence-based scaling. The study also shows that the independent macro-level effect of AI cannot yet be statistically separated from the broader impact of healthcare digitalisation because a sufficiently long and comparable national time series on AI adoption is lacking.