Artificial Intelligence Capabilities for Demand Planning Process

Claudia Aparecida de Mattos (), Fernanda Caveiro Correia and Kumiko Oshio Kissimoto
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Claudia Aparecida de Mattos: Industrial Engineering Department, Centro Universitário FEI, Av. Humberto de Alencar Castelo Branco, São Bernardo do Campo 09850-901, Brazil
Fernanda Caveiro Correia: Industrial Engineering Department, Centro Universitário FEI, Av. Humberto de Alencar Castelo Branco, São Bernardo do Campo 09850-901, Brazil
Kumiko Oshio Kissimoto: Department of Business Administration, Federal University of São Paulo—UNIFESP, Osasco 06120-042, Brazil

Logistics, 2024, vol. 8, issue 2, 1-16

Abstract: Background : Technological advancements, particularly in Artificial Intelligence (AI), are revolutionizing operations management, especially in the domain of supply chain management. This paper delves into the application of AI in demand planning processes within the supply chain context. Drawing upon a comprehensive review of the existing literature, the main objective of this study is to analyze how AI is being applied and adopted in the demand planning process, identifying the resources needed to build the capacity of AI in the demand process, as well as the mechanisms and practices contributing to AI capability’s advancement and formation. Methodology : The approach was qualitative, and case studies of three different companies were conducted. Results : This study identified crucial resources necessary for fostering AI capabilities in demand planning. Our study extends the literature on AI capability in several ways. First, we identify the resources that are important in the formation of the capacity to implement AI in the context of demand planning. Conclusions : This study’s practical contributions underscore the multifaceted nature of AI implementation for demand planning, emphasizing the importance of resource allocation, human capital development, collaborative relationships, organizational alignment, and relational capital and AI.

Keywords: demand planning; logistics; artificial intelligence; digital transformation; AI capability; resources (search for similar items in EconPapers)
JEL-codes: L8 L80 L81 L86 L87 L9 L90 L91 L92 L93 L98 L99 M1 M10 M11 M16 M19 R4 R40 R41 R49 (search for similar items in EconPapers)
Date: 2024
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