Current Volume 9
Abstract
Purpose: This study examines the role of AI-powered predictive analytics in supporting multi-sector economic growth in Saudi Arabia under the strategic direction of Vision 2030. The paper focuses on how predictive modelling, machine learning, big data integration, and AI-based decision intelligence can improve productivity, investment planning, risk management, service delivery, and non-oil sector competitiveness. Design/Methodology/Approach: The paper adopts a structured review methodology based on recent academic and institutional literature from 2020 to 2025. It synthesizes evidence from studies on artificial intelligence, digital transformation, predictive analytics, Saudi Vision 2030, and sector-specific innovation. The review covers energy, healthcare, logistics, finance, tourism, smart cities, manufacturing, and public administration. The structure follows the attached reference paper model by combining policy context, literature synthesis, sectoral analysis, conceptual framework, practical tables, and visual representation. Findings: The review finds that predictive analytics can strengthen Saudi Arabia’s economic diversification by enabling proactive planning, demand forecasting, preventive maintenance, early risk detection, smart resource allocation, and real-time decision support. Its strongest contribution appears in sectors where large data flows already exist, such as energy, finance, logistics, healthcare, and smart cities. However, the success of predictive analytics depends on data quality, interoperability, cyber security, ethical AI governance, cloud readiness, institutional coordination, and advanced human capital. Conclusion: AI-powered predictive analytics should be treated as a national economic capability rather than a narrow technical tool. When supported by strong governance and sector-specific implementation, it can help Saudi Arabia move from reactive decision-making to proactive, data-driven economic planning. Practical Implications: The paper proposes a multi-sector predictive analytics framework aligned with Vision 2030. The framework emphasizes national data infrastructure, AI governance, sector integration, talent development, and measurable economic impact. Originality/Value: This review contributes a Saudi-focused conceptual model showing how AI-powered predictive analytics can support sustainable economic diversification and knowledge-based growth across multiple sectors.
Keywords
Artificial intelligence, predictive analytics, Saudi Arabia, Vision 2030, economic diversification, machine learning, big data, smart cities, digital transformation.
Citations
IRE Journals:
Abdul Faheem "AI-Powered Predictive Analytics for Multi-Sector Economic Growth in Saudi Arabia" Iconic Research And Engineering Journals Volume 9 Issue 11 2026 Page 2021-2032 https://doi.org/10.64388/IREV9I11-1717702
IEEE:
Abdul Faheem
"AI-Powered Predictive Analytics for Multi-Sector Economic Growth in Saudi Arabia" Iconic Research And Engineering Journals, 9(11) https://doi.org/10.64388/IREV9I11-1717702
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