AI Future-proofing of Cloud-Based Retail Systems: Predictive Analytics & Automation
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V5I2P107Keywords:
Demand Forecasting, Inventory Management, Supply Chain Optimization, Personalized Marketing, Customer Insights, Anomaly Detection, Robotic Process Automation (RPA), AIOps (AI for IT Operations)Abstract
The integration of Artificial Intelligence (AI) into cloud-based retail systems is crucial for future-proofing the sector, ensuring long-term sustainability, and enhancing competitiveness in an increasingly dynamic market. This paper explores the roles of predictive analytics and automation in transforming cloud-based retail platforms. AI technologies such as machine learning, natural language processing, and automation tools have revolutionized retail, offering enhanced operational efficiency, personalized customer experiences, and real-time decision-making capabilities. Predictive analytics, powered by big data and AI, enables retailers to forecast consumer behaviors, optimize inventory, and refine marketing strategies. Additionally, automation within retail operations streamlines processes such as order fulfillment, customer service, and marketing, thereby reducing operational costs and improving customer satisfaction. The future-proofing of these systems is crucial, as the rapid advancement of technology demands adaptability and continuous improvement. This paper also delves into the challenges and ethical considerations related to AI deployment, including data privacy, AI bias, and system integration issues. Drawing upon case studies from leading retail companies, we highlight the practical applications and benefits of AI-driven cloud solutions in retail systems. The research also presents strategies for mitigating the risks associated with adopting cutting-edge technologies and ensuring the scalability and flexibility of AI-powered cloud systems
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