AI Agents as Intelligent Planning Co-Pilots: Transforming Demand Forecasting in Large-Scale Retail Enterprises
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A. Walter, K. Ahsan, and S. Rahman, "Application of artificial intelligence in demand planning for supply chains: a systematic literature review," Int. J. Logistics Manag., vol. 36, no. 3, pp. 672-719, 2025.
Sunaina Sridhar et al., "A comprehensive framework for human-AI collaborative decision making in intelligent retail environments," Expert Syst. Appl., 2026.
Srinivas Ankam, "AI-driven demand forecasting in enterprise retail systems," Int. J. Sci. Adv. Technol., vol. 15, no. 1, 2025.
O. R. Amosu et al., "AI-driven demand forecasting: enhancing inventory management and customer satisfaction," World J. Adv. Res. Rev., vol. 23, no. 2, pp. 708-719, 2024.
Y. Yang et al., "Multi-agent deep reinforcement learning for integrated demand forecasting and inventory optimization in sensor-enabled retail supply chains," Sensors, vol. 25, no. 8, p. 2428, 2025.
Valeria Jannelli, "Agentic LLMs in the supply chain: towards autonomous multi-agent consensus-seeking," Int. J. Prod. Res., 2025.
Darian Reyes and Pierangelo Rosati, "ARIMA forecasting with LLM-powered multi-agent coordination for omnichannel retail KPIs," in Proc. IEEE Conf., 2025.
Vasanth Rajendran et al., "Automated demand forecasting in retail supply chains using deep reinforcement learning," in Proc. IEEE Conf., 2025.
M. A. Shahzad et al., "Demand forecasting for retail using three-S temporal fusion (3STF) network," 2025.
X. Liu et al., "Multi-agent deep reinforcement learning for multi-echelon inventory management," Prod. Oper. Manag., 2025.
P. Jooss et al., "Artificial intelligence and work design: implications for frontline service employees and future research," J. Service Manag., 2025.
Anmol Aggarwal, "Explainable AI for demand forecasting and price optimization: a transparent approach using tree models and SHAP," in Proc. IEEE Conf., 2025.
Min Jeong An et al., "Demand forecasting in micro-fulfillment centers using association rule-based machine learning," Int. J. Prod. Econ., 2025.
Zied Bahroun et al., "A systematic analysis of generative artificial intelligence for supply chain transformation," 2025.
NAMEER UL HAQ QURESHI et al., "Demand forecasting for Rossmann stores using weather-enhanced deep learning model," IEEE Access, vol. 12, 2024.
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