Episode 188 - From Data-Rich to Insight-Driven: How AI Is Reshaping Retail in Kenya & Africa

<p>Kenyan and African retailers generate enormous volumes of information through point-of-sale systems, inventory platforms, loyalty programmes, e-commerce, mobile applications, social commerce, delivery platforms and digital payments.</p><p>However, much of that data remains fragmented, underused and disconnected from everyday business decisions.</p><p>In this special episode of the <strong>Pure Digital Passion Podcast</strong>, I moderate a discussion from the <strong>RETRAK Retail Summit 2026</strong> titled:</p><p><strong>Smarter Retail: Turning Data, AI and Insights into Competitive Advantage</strong></p><p>The session took place on Thursday, 14 May 2026, at the Sarit Expo Centre in Nairobi and brought together four experts representing retail entrepreneurship, digital payments, financial-services platforms and retail technology, as follows: </p><ul><li><strong>Judy Waruiru - </strong>Regional Managing Director, Network International</li><li><strong>Sonal Haria - </strong>Co-Founder and CEO, Canvas Cosmetics, Co-Founder, CB Consulting &amp; Media Group</li><li><strong>Eric Muriuki - </strong>Group Director, Digital Business, CEO, LOOP DFS, NCBA Group</li><li><strong>Siddesh Narkar - </strong>Head of Product, Compulynx</li></ul><p><br></p><p><strong>Topics Covered</strong></p><ul><li>Why many retailers are data-rich but insight-poor</li><li>The importance of connecting fragmented customer data</li><li>Building a unified view across stores, websites, apps and payments</li><li>Why data readiness must come before AI readiness</li><li>Using data to improve product development, pricing and assortment</li><li>How Canvas Cosmetics used customer insights to guide product development</li><li>Using payments data to understand churn, market movements and fraud</li><li>AI-supported replenishment, stock management and pricing</li><li>How AI can improve sales productivity and outreach</li><li>Balancing personalisation with customer privacy and trust</li><li>Privacy-by-design approaches to retail data</li><li>How AI agents may soon shop and pay on behalf of consumers</li><li>Practical AI actions retailers can take during the next 12 months</li></ul><p><strong>Key Message</strong></p><p><br></p><ul><li>Retailers do not need to begin with an expensive, enterprise-wide AI programme.</li><li>They should begin by digitizing operations, organising existing information, selecting one or two commercially important problems, measuring the results and building from the small w