Discover how retailers are scaling AI infrastructure across stores, warehouses, and edge sites, driving real business outcomes through smarter more connected operations.
From forecasting demand to improving checkout experiences, intelligent systems are now running at the heart of daily operations.
While 91% of IT leaders planning to prioritize adoption by 2026, only one in three report tangible returns. Why? Most are still constrained by legacy systems not built for distributed compute, data orchestration, or edge performance.
Retail AI in action
Across the industry, major retailers are already experimenting with or scaling AI to improve everyday operations: from optimizing shelf availability and personalizing promotions to streamlining logistics and customer engagement.
Public examples include initiatives in predictive inventory management, AI-assisted customer service, and virtual product trials, as reported by leading brands like Walmart and Amazon. These deployments illustrate how AI is moving from pilot to production across retail environments, enabled by infrastructure built for scale, resilience, and visibility.
Is your retail infrastructure ready for AI?
AI workloads depend on distributed compute, real-time orchestration, and scalable deployment across stores, warehouses, and cloud environments. Retailers must address:
- Latency at the edge
- Fragmented IT and OT systems
- Limited visibility into energy and asset performance
- Security gaps across physical and digital infrastructure
Without an architecture designed for AI, innovation can stall just as customer expectations rise.
Key insights from the eBook
- AI delivers real-world results: Better inventory accuracy, faster fulfillment, and stronger customer engagement.
- Infrastructure powers AI: Edge compute, cooling, and orchestration are critical to support AI workloads across retail formats.
- Strategic pilots lead to scale: Start small, build the infrastructure, and scale what works.
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