What question did this study set out to answer?

The aim is to explore how AI adoption influences supply chain resilience, focusing on demand forecasting and inventory optimization.

July 26, 2026Open Access

The Impact of Artificial Intelligence on Supply Chain Resilience: A Study of AI-Based Demand Forecasting and Inventory Optimization

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DSDr. Pooja Sharma

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Implication

Literature review demonstrates AI enhances supply chain resilience via demand forecasting and inventory optimization, suggesting significant operational benefits.

Key Points

The aim is to explore how AI adoption influences supply chain resilience, focusing on demand forecasting and inventory optimization.
Conducted a structured literature review of approximately fifty peer-reviewed articles and reports from 2020 to 2026.
Emphasized AI-based applications in demand forecasting and inventory management.
Synthesized evidence on AI technologies' effectiveness in enhancing supply chain capabilities.
AI technologies improve forecast accuracy and reduce stockouts and overstocking.
Reported benefits include cost reduction, error reduction, and faster decision cycles.
Challenges such as data quality issues, implementation costs, and low explainability of AI models were highlighted.

Cite This Study

Dr. Pooja Sharma (2026) studied this question.

synapsesocial.com/papers/6a65a91fd3aea3239cd791b0 https://doi.org/10.5281/zenodo.21528260

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Implication

Literature review demonstrates AI enhances supply chain resilience via demand forecasting and inventory optimization, suggesting significant operational benefits.

The Impact of Artificial Intelligence on Supply Chain Resilience: A Study of AI-Based Demand Forecasting and Inventory Optimization

Discussion

Member takes

Implication

Key Points

Cite This Study

The Impact of Artificial Intelligence on Supply Chain Resilience: A Study of AI-Based Demand Forecasting and Inventory Optimization

Discussion

Member takes

Implication

Key Points

Cite This Study

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