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From Dashboards to Decisions: Prescriptive Agentic Supply Chain Control Towers

From Dashboards to Decisions: Prescriptive Agentic Supply Chain Control Towers
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Author(s): Abdelrehim Awad (University of Bisha, Saudi Arabia)and Dhafer Alahmari (University of Bisha, Saudi Arabia)
Copyright: 2026
Pages: 28
Source title: Accelerating Logistics Through Generative AI, Digital Twins, and Autonomous Operations
Source Author(s)/Editor(s): Abdelrehim Awad (University of Bisha, Saudi Arabia)and Dhafer Al Ahmari (University of Bisha, Saudi Arabia)
DOI: 10.4018/979-8-3373-7006-4.ch009

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Abstract

Control towers have matured from descriptive dashboards into prescriptive, agentic decision systems that sense, understand, decide, act, and learn across multi-enterprise networks. By combining streaming data fabrics, digital twins, graph/causal forecasting, optimization and reinforcement learning, and multi-agent coordination, modern control towers close the loop from prediction to execution with adjustable autonomy and safety guardrails. Control towers have matured from descriptive dashboards into prescriptive, agentic decision systems that sense, understand, decide, act, and learn across multi-enterprise networks. By combining streaming data fabrics, digital twins, graph/causal forecasting, optimization and reinforcement learning, and multi-agent coordination, modern control towers close the loop from prediction to execution with adjustable autonomy and safety guardrails.

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