Assessing artificial intelligence and advanced analytics adoption: A technological, organizational, and environmental perspective

Saeed Alzahrani ()

Edelweiss Applied Science and Technology, 2025, vol. 9, issue 7, 312-325

Abstract: This study examines the organizational capabilities necessary for the effective adoption of Artificial Intelligence (AI) and advanced analytics across key industries. Employing an integrated approach, the research combines thematic analysis with an AI Maturity Model (AIMM) within the Technological-Organizational-Environmental (TOE) framework to assess AI readiness. The framework evaluates critical factors such as technology readiness, leadership support, organizational culture, and compliance. Findings reveal that successful AI adoption is strongly influenced by core organizational competencies, including data management, IT infrastructure, and cross-functional integration. Sector-specific examples from healthcare and finance demonstrate how AI enhances operational efficiency, customer experience, and decision-making processes. The study also benchmarks AI adoption trends in healthcare, finance, manufacturing, and retail, uncovering varying levels of readiness and capability. The results underscore the importance of aligning technological infrastructure with strategic leadership and a supportive organizational environment. By offering practical recommendations tailored to Saudi Arabia’s Vision 2030, the study provides actionable insights for organizations seeking to improve their digital maturity. Overall, this research delivers a comprehensive understanding of AI adoption prerequisites and offers a roadmap for leveraging analytics to gain a competitive edge in the digital economy.

Keywords: AI adoption; Predictive analytics; Technological organizational environment (TOE). (search for similar items in EconPapers)
Date: 2025
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