Most enterprise AI initiatives start strong and stall fast. Our new guide documents what the organizations pulling ahead are doing differently.
Most enterprise AI initiatives start strong and stall fast. We've spent the past year working with retail organizations at different stages of that journey - some stuck in pilot purgatory, others scaling AI across thousands of employees.
Our new guide identifies the three steps that separate the AI leaders pulling ahead from the laggards, drawing from our work alongside organizations seeing measurable ROI.
Retailers face a familiar squeeze: margins are thin, customer expectations keep rising, and the pressure to automate runs headlong into the need to preserve service quality. PwC reports 88% of executives plan to increase AI investment this year.
But investment alone isn't the bottleneck. Technology stacks are fragmented across e-commerce, POS, inventory, and CRM systems that weren't designed to work together. Seasonal demand cycles make ROI hard to model. And teams that understand both retail operations and AI capabilities are hard to find and harder to keep.
The organizations making progress have stopped treating these as reasons to wait.
The organizations pulling ahead each started with a specific operational problem, proved value within weeks, and expanded from there.
In the case of Shopify, they deployed Claude to power Sidekick, an AI assistant that translates complex merchant requests into actionable insights. When a merchant asks a question in natural language, Claude converts it into ShopifyQL queries that previously required technical expertise.
L'Oréal built a multi-agent system with Claude at the core, orchestrating 15+ specialized agents that work together to transform user questions into insights and visualizations for 44,000 employees across 150 countries.
Lotte Homeshopping deployed an AI assistant to provide 24/7 support for partner suppliers, handling QA inquiries, validating documentation, and guiding partners through regulatory requirements.
For organizations planning their 2026 priorities, the guide covers three essential steps: laying your foundation with stakeholder alignment and governance, launching carefully selected pilots starting with lower-risk applications, and scaling what works while building organizational capability.
Read the full Enterprise AI Transformation Guide for Retail here.
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