شناسایی ابعاد آمادگی سازمان‌های بهداشتی دولتی برای پذیرش سیستم‌های تصمیم‌گیری مبتنی بر هوش مصنوعی با تأکید بر ابعاد حکمرانی، داده و نیروی انسانی

آزاده تیموری; حمید رضا ملائی; صدیقه حسنی احمدیه; فاطمه السادات رباطی; محسن زاینده رودی

Authors

Azadeh Teimouri Ph.D. Student Department of Management, Ke.C., Kerman Branch, Islamic Azad University, Kerman, Iran Author https://orcid.org/0009-0002-8971-3471
Hamid Reza Mollai Department of Management, Ke.C., Islamic Azad University, Kerman, Iran https://orcid.org/0000-0003-0078-2236
Sedigheh Hasani Ahmadiye Department of Management, Kah.C., Islamic Azad University, Kahnuj, Iran Author https://orcid.org/0000-0001-6350-8942
Fatemeh Alsadat Robati Department of Educatioal Sciences, Raf.C., Islamic Azad University, Rafsanjan, Iran Author https://orcid.org/0000-0002-7043-6032
Mohsen Zayandeh-Roudi Department of Economy, Ke.C., Islamic Azad University, Kerman, Iran Author https://orcid.org/0000-0001-8109-0455

Keywords:

Organizational readiness, acceptance of decision-making systems, artificial intelligence, governance dimensions, human resources

Abstract

This study aimed to identify and explain the key dimensions and components of public healthcare organizations’ readiness to adopt artificial intelligence-based decision-making systems, with particular emphasis on governance, data, and human resources. This applied study employed a qualitative research design based on thematic analysis. Data were collected through a review of scientific literature, official reports, policy documents, and organizational records related to artificial intelligence and healthcare. Relevant sources published between 2018 and 2025 were retrieved from national and international scientific databases using combinations of keywords such as organizational readiness, artificial intelligence, data governance, human resources, and decision-making systems. Eligible sources were screened according to predefined inclusion and exclusion criteria and subsequently analyzed through a systematic thematic process involving initial concept extraction, coding, aggregation of similar codes, development of basic and subthemes, and organization of the resulting themes into overarching dimensions. The thematic analysis indicated that readiness for adopting AI-based decision-making systems is determined by the interaction of three major dimensions: governance, data quality and governance, and human resources. Governance comprised transparent regulatory frameworks, monitoring and accountability mechanisms, responsibility allocation, ethical policies, and compliance with national and international regulations. Data-related readiness encompassed data integrity, controlled accessibility, security and privacy, confidentiality of health data, assured standards, quality assurance, technical competencies, and digital transformation leadership. Human-resource readiness included specialized technical skills, positive knowledge and attitudes toward data sharing, investment strategies, empowerment programs, data-literate human capital, and effective technology utilization. Successful adoption of AI-based decision-making systems in public healthcare organizations requires more than technological infrastructure. It depends on the simultaneous development of governance capacity, high-quality and secure data ecosystems, and competent human resources. The proposed framework can support organizational readiness assessment, identify implementation gaps, and guide managerial and policy priorities before large-scale AI deployment in healthcare systems.

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