
AI+ Retail Leaders
Scale Smarter Across Every Location
Scale smarter across every location.
Your board wants an AI strategy. Your competitors are pricing smarter, forecasting better, and personalising at a scale you can't match manually. This book gives retail leaders the STORE Protocol for governing consumer data, biometric surveillance, and algorithmic pricing; a SCALE scorecard extended for data readiness and integration complexity; 20 copy-ready prompt templates; and a 90-day plan built around commercial payback, not technology ambition. Written for people who run retail businesses, not technology teams.
- The STORE Protocol — six-check framework for Sales and customer data, Technology infrastructure, Outlet operations, Retail workforce, Ethics in surveillance and pricing, and supplier exposure
- The SCALE scorecard for retail AI investment — applied to demand forecasting, personalisation, scheduling, and operations
- A multi-location deployment discipline that handles 50, 100, or 200+ stores with consistency
- An AI strategy for the board and PE — credible, commercial, investable
- A 90-day leadership plan spanning personal mastery, commercial operations, customer experience, and workforce capability
Chief Executive Officers, Managing Directors, Chief Operating Officers, Chief Commercial Officers, Chief Merchandising Officers, and Operations Directors of multi-site retail businesses — typically 20 or more locations, up to several hundred. They own the commercial and operational strategy. They are accountable for revenue, margin, inventory performance, customer experience consistency across locations, and increasingly, digital and omnichannel integration. They manage large, geographically distributed workforces with high turnover. They make or heavily influence capital allocation decisions for technology, store estate, and supply chain. They think at the portfolio level: store performance analytics, range and ranging decisions, supplier relationships, customer loyalty economics, and workforce productivity across locations. Typically 15+ years in retail, with 5+ in senior leadership, having worked through multiple technology cycles and commercial transformations.
Also for:Regional Directors, Head of Store Operations, Head of Merchandising, Head of E-Commerce, Commercial Directors at mid-market retail groups; and board-level Non-Executive Directors of retail businesses who require strategic AI literacy. Also relevant to retail investors and private equity operating partners managing retail portfolio companies.
- Assess their retail organisation's AI readiness across commercial intelligence, customer experience, operations, workforce, and governance dimensions
- Design a retail AI strategy that addresses demand forecasting, customer personalisation, store operations, and workforce capability — with a defensible plan for the board and investors
- Apply the PRISM Prompting Framework to at least five strategic retail leadership tasks (board papers, investor communications, supplier negotiations, commercial analysis, workforce communications)
- Evaluate retail AI technology investments using the AI Investment Scorecard (SCALE) and apply the STORE Protocol to establish proportionate governance for AI deployment across consumer data, surveillance, and algorithmic pricing
- Lead retail teams through AI adoption, navigating the specific dynamics of high-turnover retail culture, multi-location execution, and the balance between algorithmic efficiency and human customer service
- Diagnostic
- How AI-Ready Is Your Retail Organisation?
- Chapter 1
- AI in Retail Leadership Right Now
- Chapter 2
- The Retail AI Landscape
- Chapter 3
- The Retail Leader's Own AI Mastery
- Chapter 4
- Commercial Intelligence with AI
- Chapter 5
- Customer Experience at Scale
- Chapter 6
- Retail Workforce in the AI Era
- Chapter 7
- Investing in Retail AI Technology
- Chapter 8
- AI Governance, Data and Ethics
- Chapter 9
- Your 90-Day Retail Leadership AI Plan
- Back matter
- Skill Summary · Recommended Next Reads · Glossary · Tool Reference
Written by engineers who build production AI systems, not consultants who present them — for retail leaders whose competitive ground is shifting under their stores.
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