A Holistic Model for Integrating AI, BI, IoT, and Cloud into Enterprise Decision-Making - Yang Na; Asanova Daniya; Olga Koshkina (Theoretical Hypotheses and Empirical Results, 2026)
The convergence of artificial intelligence (AI), business intelligence (BI), the Internet of Things (IoT), and cloud computing is redefining enterprise decision-making processes by enabling real-time, data-driven, and predictive capabilities. However, organisations frequently adopt these technologies in isolation, resulting in fragmented architectures and suboptimal decision outcomes. This article proposes a holistic model for integrating AI, BI, IoT, and cloud technologies into a unified enterprise decision-making system. Grounded in the Technology Acceptance Model (TAM), resource-based view (RBV), and socio-technical systems theory, the study adopts a conceptual methodology supported by interdisciplinary literature and secondary case evidence. The proposed model consists of four interdependent layers: data generation and acquisition (IoT), data integration and storage (cloud), analytics and intelligence (AI and BI), and decision orchestration and governance. Findings indicate that integration across these layers enhances decision speed, accuracy, and adaptability, while persistent challenges—including data silos, interoperability constraints, and organisational resistance—limit effective implementation. The article further examines implications for emerging digital economies such as Kazakhstan, where national digitalisation strategies create opportunities for integrated enterprise systems. Managerial and policy recommendations are provided, along with directions for future research.