Table 5 Projections overview and... | Emerald Publishing

Table 5

Projections overview and descriptions

No.	Projection In 2040, AI will increase performance in the processes of the SCOR-DS model because …	SCOR-DS	Description	Sources
1	… AI is adapted and accepted by employees and management, and is fully incorporated in daily operations	Orchestrate	The workforce must accept and work with AI technologies to fully leverage their potential	Cannas et al. (2024); Durach and Gutierrez (2024); I1; I5; I6; I7; I10
2	… organizational training of employees is planned, created, and executed exclusively by AI	Orchestrate	Training the workforce is costly and time-intensive. AI applications can autonomously plan and execute organizational training activities	Richey et al. (2023); Xu et al. (2021); I2; I10
3	… only those companies using shared AI solutions for collaboration, cooperation and transparency in the supply chain network will survive	Orchestrate	AI technology and its impact on SCM processes have evolved enormously over the past Two decades. The absence of AI in SCM will therefore be a major competitive disadvantage	Durach and Gutierrez (2024); Garg et al. (2025); Hasija and Esper (2022); Xu et al. (2021); I3; I7; I8; I9; I11
4	… data protection and data security of AI applications are ensured	Orchestrate	Current data protection requirements already influence AI implementation, so viable solutions for data protection and security are required for the successful deployment of AI technologies	Durach and Gutierrez (2024); Richey et al. (2023); I7; I9; I12
5	… self-optimized planning processes and automated decision-making are done by AI	Plan	Demand planning is a Central element of SCM, covering forecasting for component procurement and finished-goods sales, and thus acts as a key driver of value creation and performance	Cannas et al. (2024); Walter et al. (2025); I1; I3; I5; I6; I8; I9; I10
6	… delivery routes are optimized (costs, time, security, safety and service levels)	Order	By examining traffic flows and weather conditions, AI can identify optimal transportation routes, reducing logistics costs and improving delivery efficiency	Garg et al. (2025); Hasija and Esper (2022); I5; I8
7	… AI is the key technology for completely unmanned factories, including automated maintenance	Order	Warehousing is a critical component of SCM, typically accounting for around 20% of a firm’s overall logistics expenditure. AI is pivotal for enhancing warehouse management practices	Perotti and Colicchia (2023); Toorajipour et al. (2021); Rad et al. (2025); I4; I6
8	… AI enables companies to automatically identify and verify suppliers that best meet their requirements for collaboration	Source	Managing supplier performance is crucial for SCM. AI allows forecasting of supplier performance trends, supporting procurement strategy refinement and mitigation of SC disruptions	Nilsson and Gammelgaard (2012); Cannas et al. (2024); Garg et al. (2025); Guida et al. (2023)
9	… AI automatically negotiates contracts with suppliers	Source	The use of AI for supplier evaluation and selection is an alternative to traditional approaches relying on manual analysis and decision-making. Using historical data and anticipated supplier behavior, AI supports the development of negotiation strategies and contractual arrangements	Richey et al. (2023)
10	… AI improves employee safety by preventively eliminating all sources of hazards	Transform	AI contributes to operator safety by enabling process optimization and real-time monitoring of machinery, thereby reducing risks and fostering safer working environments	Cannas et al. (2024)
11	… AI is enabling mass customization through autonomous production processes	Transform	AI supports planning of customization requirements by identifying patterns in customer preferences and production constraints. In manufacturing, mass customization aims to reconcile individualized product design with efficient large-scale production	Sharma and Rathore (2024); Xu et al. (2021)
12	… AI can make recommendations based on customers’ purchasing patterns, which prevents returns (almost) completely	Return	AI enhances demand forecasting by integrating real-time market trends, enabling firms to align inventory with customer needs. Reliable availability and personalized recommendations help customers make informed purchasing decisions and reduce return rates	Sharma and Rathore (2024); I8
13	… AI can assess the condition of goods/products throughout their lifecycle, contributing to a circular economy	Return	AI use in the returns process is linked to circular-economy principles, particularly reverse logistics. Recent research has focused on AI models that optimize environmental performance, positioning AI as a tool for advancing circular- economy initiatives	Cannas et al. (2024); I9

No.	Projection In 2040, AI will increase performance in the processes of the SCOR-DS model because …	SCOR-DS	Description	Sources
1	… AI is adapted and accepted by employees and management, and is fully incorporated in daily operations	Orchestrate	The workforce must accept and work with AI technologies to fully leverage their potential	Cannas et al. (2024); Durach and Gutierrez (2024); I1; I5; I6; I7; I10
2	… organizational training of employees is planned, created, and executed exclusively by AI	Orchestrate	Training the workforce is costly and time-intensive. AI applications can autonomously plan and execute organizational training activities	Richey et al. (2023); Xu et al. (2021); I2; I10
3	… only those companies using shared AI solutions for collaboration, cooperation and transparency in the supply chain network will survive	Orchestrate	AI technology and its impact on SCM processes have evolved enormously over the past Two decades. The absence of AI in SCM will therefore be a major competitive disadvantage	Durach and Gutierrez (2024); Garg et al. (2025); Hasija and Esper (2022); Xu et al. (2021); I3; I7; I8; I9; I11
4	… data protection and data security of AI applications are ensured	Orchestrate	Current data protection requirements already influence AI implementation, so viable solutions for data protection and security are required for the successful deployment of AI technologies	Durach and Gutierrez (2024); Richey et al. (2023); I7; I9; I12
5	… self-optimized planning processes and automated decision-making are done by AI	Plan	Demand planning is a Central element of SCM, covering forecasting for component procurement and finished-goods sales, and thus acts as a key driver of value creation and performance	Cannas et al. (2024); Walter et al. (2025); I1; I3; I5; I6; I8; I9; I10
6	… delivery routes are optimized (costs, time, security, safety and service levels)	Order	By examining traffic flows and weather conditions, AI can identify optimal transportation routes, reducing logistics costs and improving delivery efficiency	Garg et al. (2025); Hasija and Esper (2022); I5; I8
7	… AI is the key technology for completely unmanned factories, including automated maintenance	Order	Warehousing is a critical component of SCM, typically accounting for around 20% of a firm’s overall logistics expenditure. AI is pivotal for enhancing warehouse management practices	Perotti and Colicchia (2023); Toorajipour et al. (2021); Rad et al. (2025); I4; I6
8	… AI enables companies to automatically identify and verify suppliers that best meet their requirements for collaboration	Source	Managing supplier performance is crucial for SCM. AI allows forecasting of supplier performance trends, supporting procurement strategy refinement and mitigation of SC disruptions	Nilsson and Gammelgaard (2012); Cannas et al. (2024); Garg et al. (2025); Guida et al. (2023)
9	… AI automatically negotiates contracts with suppliers	Source	The use of AI for supplier evaluation and selection is an alternative to traditional approaches relying on manual analysis and decision-making. Using historical data and anticipated supplier behavior, AI supports the development of negotiation strategies and contractual arrangements	Richey et al. (2023)
10	… AI improves employee safety by preventively eliminating all sources of hazards	Transform	AI contributes to operator safety by enabling process optimization and real-time monitoring of machinery, thereby reducing risks and fostering safer working environments	Cannas et al. (2024)
11	… AI is enabling mass customization through autonomous production processes	Transform	AI supports planning of customization requirements by identifying patterns in customer preferences and production constraints. In manufacturing, mass customization aims to reconcile individualized product design with efficient large-scale production	Sharma and Rathore (2024); Xu et al. (2021)
12	… AI can make recommendations based on customers’ purchasing patterns, which prevents returns (almost) completely	Return	AI enhances demand forecasting by integrating real-time market trends, enabling firms to align inventory with customer needs. Reliable availability and personalized recommendations help customers make informed purchasing decisions and reduce return rates	Sharma and Rathore (2024); I8
13	… AI can assess the condition of goods/products throughout their lifecycle, contributing to a circular economy	Return	AI use in the returns process is linked to circular-economy principles, particularly reverse logistics. Recent research has focused on AI models that optimize environmental performance, positioning AI as a tool for advancing circular- economy initiatives	Cannas et al. (2024); I9

Note(s):

I: Interview partner

Source(s): Authors’ own work