Revolutionizing Supply Chains: Unleashing the Power of AI-Driven Intelligent Automation and Real-Time Information Flow

Artificial intelligence (AI) and smart automation are revolutionizing the global supply chain ecosystem at an accelerated pace, providing tremendous potential for resilience, innovation, efficacy, and profitability. This paper examines how AI, machine learning (ML), and robotic process automation (R...

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Main Authors: Mohammad Shamsuddoha, Eijaz Ahmed Khan, Md Maruf Hossan Chowdhury, Tasnuba Nasir
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Information
Subjects:
Online Access:https://www.mdpi.com/2078-2489/16/1/26
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author Mohammad Shamsuddoha
Eijaz Ahmed Khan
Md Maruf Hossan Chowdhury
Tasnuba Nasir
author_facet Mohammad Shamsuddoha
Eijaz Ahmed Khan
Md Maruf Hossan Chowdhury
Tasnuba Nasir
author_sort Mohammad Shamsuddoha
collection DOAJ
description Artificial intelligence (AI) and smart automation are revolutionizing the global supply chain ecosystem at an accelerated pace, providing tremendous potential for resilience, innovation, efficacy, and profitability. This paper examines how AI, machine learning (ML), and robotic process automation (RPA) influence supply chain operations to adjust to the risks and vulnerabilities. It focuses on how AI and other relevant technologies will enhance forecasting to predict actual demand, expedite logistics, increase warehouse efficiency, and promote instantaneously making decisions. This study utilizes thematic analysis to find AI-driven supply chain applications, including logistics optimization, forecasting demand, and risk mitigation, among 383 peer-reviewed articles (2017–2024). It provides a strategic framework for dealing with vulnerabilities, operational excellence, and resilient solutions. Additionally, the research investigates how AI contributes to supply chain resilience by predicting disruptions and automating risk mitigation strategies. This paper identifies critical success factors and challenges in adopting intelligent automation by analyzing real-world industry implementations. The findings will propose a strategic framework for organizations aiming to leverage AI to achieve operational excellence, agility, and real-time information flow for effective decision-making.
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spelling doaj-art-c8ba4473c0114caeb2d4a32d160e9f8b2025-01-24T13:35:11ZengMDPI AGInformation2078-24892025-01-011612610.3390/info16010026Revolutionizing Supply Chains: Unleashing the Power of AI-Driven Intelligent Automation and Real-Time Information FlowMohammad Shamsuddoha0Eijaz Ahmed Khan1Md Maruf Hossan Chowdhury2Tasnuba Nasir3Department of Management and Marketing, College of Business and Technology, Western Illinois University, Stipes Hall 418I, 1 University Circle, Macomb, IL 61455, USACollege of Business, Law & Governance, James Cook University, Townsville, QLD 4814, AustraliaUTS Business School, University of Technology Sydney (UTS), Sydney, NSW 2007, AustraliaSchool of Business, Quincy University, Quincy, IL 62301, USAArtificial intelligence (AI) and smart automation are revolutionizing the global supply chain ecosystem at an accelerated pace, providing tremendous potential for resilience, innovation, efficacy, and profitability. This paper examines how AI, machine learning (ML), and robotic process automation (RPA) influence supply chain operations to adjust to the risks and vulnerabilities. It focuses on how AI and other relevant technologies will enhance forecasting to predict actual demand, expedite logistics, increase warehouse efficiency, and promote instantaneously making decisions. This study utilizes thematic analysis to find AI-driven supply chain applications, including logistics optimization, forecasting demand, and risk mitigation, among 383 peer-reviewed articles (2017–2024). It provides a strategic framework for dealing with vulnerabilities, operational excellence, and resilient solutions. Additionally, the research investigates how AI contributes to supply chain resilience by predicting disruptions and automating risk mitigation strategies. This paper identifies critical success factors and challenges in adopting intelligent automation by analyzing real-world industry implementations. The findings will propose a strategic framework for organizations aiming to leverage AI to achieve operational excellence, agility, and real-time information flow for effective decision-making.https://www.mdpi.com/2078-2489/16/1/26artificial intelligence (AI)intelligent automationresilient supply chainsreal-time decision-makingoperational excellence
spellingShingle Mohammad Shamsuddoha
Eijaz Ahmed Khan
Md Maruf Hossan Chowdhury
Tasnuba Nasir
Revolutionizing Supply Chains: Unleashing the Power of AI-Driven Intelligent Automation and Real-Time Information Flow
Information
artificial intelligence (AI)
intelligent automation
resilient supply chains
real-time decision-making
operational excellence
title Revolutionizing Supply Chains: Unleashing the Power of AI-Driven Intelligent Automation and Real-Time Information Flow
title_full Revolutionizing Supply Chains: Unleashing the Power of AI-Driven Intelligent Automation and Real-Time Information Flow
title_fullStr Revolutionizing Supply Chains: Unleashing the Power of AI-Driven Intelligent Automation and Real-Time Information Flow
title_full_unstemmed Revolutionizing Supply Chains: Unleashing the Power of AI-Driven Intelligent Automation and Real-Time Information Flow
title_short Revolutionizing Supply Chains: Unleashing the Power of AI-Driven Intelligent Automation and Real-Time Information Flow
title_sort revolutionizing supply chains unleashing the power of ai driven intelligent automation and real time information flow
topic artificial intelligence (AI)
intelligent automation
resilient supply chains
real-time decision-making
operational excellence
url https://www.mdpi.com/2078-2489/16/1/26
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AT mdmarufhossanchowdhury revolutionizingsupplychainsunleashingthepowerofaidrivenintelligentautomationandrealtimeinformationflow
AT tasnubanasir revolutionizingsupplychainsunleashingthepowerofaidrivenintelligentautomationandrealtimeinformationflow