136 VIEWPOINT Agentic AI empowers retailers with adaptive, real-time decision-making, enabling dynamic pricing, improved efficiency and proactive, data-driven operations SHIKSHYA KHATIWADA: KYNDRYL Reimagining retail with agentic AI Retailers today face unprecedented volatility: supply chain disruptions, fast changing demand signals, rising costs and relentless margin pressures. Traditional pricing engines can’t keep up with real-time market volatility. Batch processing introduces delays. Static rules fail to reflect current demand signals and disconnected systems create blind spots across the value chain. Retailers need more than incremental optimisation, they need an adaptive, data-driven architecture. This data centric operating model needs to be capable of ingesting live inputs, recalibrating models on demand and driving continuous performance improvement across all commercial functions. This is where agentic AI makes a difference. Instead of models that only generate insights for humans to interpret, agentic systems act on those insights, executing decisions in real time while keeping humans in the loop. McKinsey & Company’s article on ‘Why agents are the next frontier of generative AI’ notes that “humanin-the-loop control mechanisms are essential to ensure accuracy, compliance and fairness as AI agents interact with the real world”. In practice, this means AI agents track demand shifts, competitor pricing and inventory levels. They recommend adjustments, execute approved actions and escalate only the exceptions that require human judgement. This shifts retailers from reacting after the fact to actively steering outcomes across pricing, inventory and promotions. Kyndryl’s Agentic AI Framework emphasises that true transformation comes from humancentric AI, where intelligent agents not only automate decisions but also empower people to focus on higher-value work. Using modules such as the Ingestion engine, Agent Builder and the Core orchestrator engine, the framework transforms complex, rules-based legacy systems into modular, cloud-native services. These services are extended with new AI agents that close capability gaps and introduce new dynamic pricing agents where traditional logic falls short. The result is a unified, extensible engine that integrates with existing enterprise resource planning, customer relationship management, and e-commerce platforms while maintaining strong version control, data lineage and model governance. This architecture enables retailers to deploy domain-specific agents safely and at scale, accelerating modernisation and reducing dependence on scarce technical expertise. Build a prioritised roadmap with AI driven insights into technology health, legacy risk and cloud readiness with our Digital Transformation Accelerator using AI Agents on Microsoft Marketplace. “When agents collaborate through a common orchestration layer, retailers can adjust prices continuously across channels, protecting margins while improving customer trust”
RkJQdWJsaXNoZXIy NzQ1NTk=