The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
AI-Powered Workforce Planning and Optimization: AI-Driven Workforce Optimization in Logistics and Supply Chain Management
Abstract
This article explores how Artificial Intelligence (AI) transforms workforce optimization in logistics and supply chain operations. By integrating technologies like machine learning, predictive analytics, robotic process automation, natural language processing, computer vision, and digital twins, organizations can shift from manual, reactive workforce planning to proactive, data-driven strategies. AI enables dynamic scheduling, real-time task reassignment, predictive labor forecasting, and continuous performance monitoring, improving efficiency and reducing costs. The article also addresses ethical concerns such as transparency, bias, and privacy, and outlines key implementation challenges including data quality, employee resistance, and digital skills gaps. Ultimately, it argues that AI is not just a tool for automation but a catalyst for strategic transformation, helping organizations create agile, resilient, and human-centered workforce ecosystems suited for today's complex supply chain landscape.
Related Content
|
Bikash Kumar, Rhythm Gaba, Rabi Shaw.
© 2026.
40 pages.
|
|
R. Velmurugan, J. Sudarvel, R. Bhuvaneswari, Ravi Thirumalaisamy.
© 2026.
28 pages.
|
|
J. Vijaya, Soumya Chandrakar, Pragya Shrivastava.
© 2026.
42 pages.
|
|
Yamini Ghanghorkar, Amruta Deshpande.
© 2026.
28 pages.
|
|
B. Bharathi, B. Kalaivani, Kasu Manaswi, Kantabathina Tejaswini.
© 2026.
28 pages.
|
|
Moumita Chowdhury, Aastha Agarwal, Alisha Parveen, Abhishek Mukhopadhyay.
© 2026.
42 pages.
|
|
Utkarsh Trivedi, Yash Vardhan, Piyush Kumar, Ansh Aryan, Parth Batra, Hitesh Mohapatra.
© 2026.
28 pages.
|
|
|