Essays for board members, executives and data and AI leaders. Each one takes a single question about data, AI or governance and works through what matters, why, and what it means for your decisions.
Grocery retailers have a decisive advantage in AI shopping: their data. Generic AI agents struggle with product discovery, but retailers possess years of purchase history revealing individual tastes. The race is about combining targeted AI with proprietary data.
AI shopping agents face a fundamental problem: the less you see, the less you buy. By focusing on efficiency, they eliminate the product discovery that drives grocery sales. You can't ask for what you don't know exists, and impulse purchases represent over half of grocery revenue.
When planning groceries on Monday, you don't add the cookies you'll crave Friday. AI shopping agents face this planning gap: we shop for an idealized self, not the person who wants treats after a long day. Impulse purchases represent over half of grocery revenue.
78% of employees bring their own AI tools to work. The real challenge isn't Shadow AI itself, but distinguishing harmless productivity from genuine risk. Most violations happen because employees don't recognize when they've crossed the line with sensitive data.
Retailers face opposing AI agent strategies: Walmart partners with OpenAI while Amazon blocks access. Most retailers need a third approach: invest in structured, high-quality product data that delivers value today while positioning for an AI-enabled future.
The real power of data lies in context: understanding the data itself, its origin, and its intended use. Without clear definitions and metadata, even accurate data gets misinterpreted. Treat data quality as a business decision, not a technical one.