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AI is reshaping how retailers operate and compete, from their deployment of AI-driven real-time inventory management to fraud detection, chatbot support agents, and hyperpersonalized shopping experiences. But for many, the IT infrastructure to support these applications either can’t support AI or can’t scale applications as use cases grow. Legacy networks were designed for predictable, centralized traffic—not the real-time, distributed, high-bandwidth demands of AI. Here's a practical list of network and IT challenges retailers need to overcome to support AI at scale and why they're vital to your success. Your bandwidth and connectivity are inadequate Aging infrastructure is struggling to keep pace with the scale and performance demands of AI across applications in stores, warehouses, and distribution centers. AI requires a steady, high-capacity data flow. When network performance lags, operations suffer immediately. Personalized offers fail to load for customers, self-checkout kiosks freeze during peak traffic, real-time inventory data disappears from management dashboards, and loyalty apps fail to sync reward points accurately. You need a network with the bandwidth, scalability, and reliability to support real-time data flows across every location and online transaction. It must be able to sustain that performance as AI adds increasing traffic to the mix. Tool sprawl and disconnected systems challenge lean IT teams Retail IT departments are overwhelmed with legacy networking architectures and fragmented point solutions. Adding new AI-ready tools without a unifying platform strategy creates a patchwork of disconnected systems. The result within many retail environments today is a widening gap between what the business wants to do with AI and what lean teams can realistically support, maintain, and secure. The antidote to such a disconnected patchwork is a unified networking and security platform that simplifies management and frees IT teams to focus on innovation instead of maintenance. Limited visibility increases your risk You can't manage what you can't see, and for many retailers, that's exactly the problem. With numerous locations that don't always have a dedicated IT presence, blind spots can multiply fast. Stores generate constant streams of data across networks, devices, and systems, but without a unified view, IT teams are often left reacting to issues after they've already impacted operations or customers, rather than catching them in real time. The fix is consolidating networking, security, and operations onto a single cloud-managed platform, so every new addition compounds value instead of adding to the burden. Fragmented and inconsistent security amplifies risk As retailers rush AI-powered apps into production, security governance often lags behind. Many organizations are adopting AI faster than they're building the policies to secure it. This governance gap leaves retail infrastructure exposed just as AI adoption accelerates. For an industry handling sensitive consumer financial data across hundreds of distributed locations, ungoverned, fragmented security isn't just a technical risk—it's a financial one. For retail executives, the message is clear: AI ambitions can't outpace network readiness. Closing the gap between bandwidth, visibility, IT capacity, and security isn't a back-office upgrade. It's a strategic imperative for competing in the AI era. Explore how to modernize your network infrastructure for the AI era. By the numbers Bandwidth and connectivity - 86% of CIOs say their networks aren't prepared for the scalability, performance, and bandwidth demands of AI¹. - Nearly 90% of retailers are piloting AI, but only 25% have operationalized it at scale². Network visibility - 37% of retailers experience high-impact infrastructure outages every single week³. - 73% of retailers use traditional monitoring tools, yet 47% still cite network visibility as their top operational improvement need³. - It takes an average of four hours to resolve outages without unified visibility³. Security and risk - 63% of organizations lack internal AI security policies⁴. - Retailers with ungoverned, fragmented AI tools pay $670,000 more per data breach on average than those with centralized controls⁵. - Time for a Change: Why Networks Aren't Equipped To Handle What's Going on in the Retail Sector, Globalgig, January 22, 2026. - 90% of retailers are using AI. Far fewer are ready to run it at scale, Retail Dive, June 15, 2026. - IT Infrastructure ROI: How Poor Network Observability Costs Retailers $9.95 Million Every Year, Highlight, 2026. - AI Cybersecurity Statistics [2026]: Facts & Trends, StationX, September 2026. - Retail Cybersecurity Statistics For 2026: Breach Costs, Ransomware, Magecart, And Bot Attacks, Swif.ai, August 4, 2026.
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