The AI hype cycle in retail has been intense. Every vendor claims AI. Most of it is marketing. Here's an honest assessment of what works today.

What's Real

Demand forecasting: AI/ML models genuinely outperform traditional methods for most product categories. The improvement is 15-30% in forecast accuracy for products with sufficient history.

Price optimization: Elasticity-based pricing works. Retailers who adopt it consistently see 3-8% margin improvement.

Automated reporting: LLM-powered report generation is production-ready. An agent can compile a weekly performance report that's 90% as good as a human analyst's — in 30 seconds instead of 3 hours.

Anomaly detection: Statistical methods reliably catch unusual patterns in KPIs. This is a solved problem.

What's Overpromised

Autonomous decision-making: No AI should make pricing or inventory decisions without human approval. The error rate is still too high for unsupervised action.

Perfect personalization: One-to-one product recommendations work for e-commerce at scale (Amazon). For a 20-store retailer? The data isn't there.

"AI replaces your team": It doesn't. It makes your existing team 3-5× more productive by handling the analytical grunt work. The judgment, relationships, and domain expertise remain human.

Our Bet

We believe the biggest opportunity is in the middle: AI that handles analysis and execution, with humans making the final call. Not full automation. Not just dashboards. Agent-assisted retail operations.