Optimizing supply chains with artificial intelligence in the 4IR: A business model perspective
1 Sanctus Maris Concepts Ltd.
2 Independent Researcher, Clarksville, Tennesse, USA.
3 Independent Researcher, Abuja, Nigeria.
4 Independent Researcher, Lagos, Nigeria.
Review
Open Access Research Journal of Multidisciplinary Studies, 2023, 06(02), 086–099.
Article DOI: 10.53022/oarjms.2023.6.2.0051
Publication history:
Received on 12 October 2023; revised on 16 December 2023; accepted on 20 December 2023
Abstract:
The Fourth Industrial Revolution (4IR) heralds a transformative era characterized by the integration of advanced technologies such as Artificial Intelligence (AI) into various sectors, notably supply chain management. This paper explores how AI optimizes supply chains, enhancing efficiency, responsiveness, and resilience from a business model perspective. Traditional supply chain models often face challenges such as demand variability, inventory management, and logistical inefficiencies. By harnessing AI technologies, businesses can address these challenges through improved data analytics, predictive modeling, and automation. AI-driven supply chain optimization involves the utilization of machine learning algorithms and big data analytics to forecast demand accurately, enabling businesses to adjust their operations proactively. This shift from reactive to proactive supply chain management fosters agility, allowing firms to respond to market fluctuations swiftly. Furthermore, AI enhances visibility across the supply chain, facilitating real-time tracking of inventory levels, order status, and supplier performance. This transparency enables organizations to identify potential bottlenecks and mitigate risks effectively. The research highlights several AI applications in supply chain optimization, including automated inventory management, predictive maintenance, and intelligent logistics. Automated systems reduce human error and operational costs, while predictive maintenance minimizes downtime by anticipating equipment failures. Intelligent logistics solutions, powered by AI, optimize route planning and delivery schedules, enhancing overall operational efficiency. However, the successful implementation of AI in supply chains also poses challenges, such as the need for significant investments in technology and infrastructure, data privacy concerns, and workforce adaptation to new technologies. This paper discusses these challenges and provides recommendations for businesses to navigate them effectively. In conclusion, AI presents substantial opportunities for optimizing supply chains in the context of 4IR. By adopting AI-driven approaches, businesses can create more resilient and efficient supply chains, ultimately driving competitive advantage and sustainability in a rapidly evolving market landscape.
Keywords:
Artificial Intelligence; Supply Chain Optimization; Fourth Industrial Revolution; Business Models; Predictive Analytics; Logistics; Efficiency; Agility
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Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0