Overview
This podcast episode features a conversation between Scott Wingo and Carl Howler (IBM Consulting) on the impact of AI and agentic technologies in retail, e-commerce, and CPG. The discussion covers AI’s evolution from experimentation to workflow transformation, the rise of AI native brands, agentic shopping inflection points, and the future of store and personalized retail experiences.
AI Adoption Trends in Retail and CPG
- AI discussions with clients have shifted from broad experimentation to focused workflow transformation in areas like marketing, finance, and store operations.
- Major retailers face organizational and process challenges in scaling AI, despite technological readiness.
- Many companies remain in pilot phases of AI adoption, lagging behind initial expectations.
- Data readiness remains a foundational requirement for successful AI implementation.
Agentic Commerce and the Consumer Shift
- Retail is approaching an agentic shopping inflection point reminiscent of late-1990s e-commerce disruption.
- AI-powered agents are expected to handle shopping tasks, particularly in gift-giving and routine purchases.
- Early AI adopters and fast followers will drive the next wave, with mainstream adoption expected within several years.
- The emergence of AI shopping agents raises existential questions for retailers regarding checkout processes, payments, and retail media investments.
AI Native Brands and Organizational Change
- AI native brands will use automation and agentic workflows to achieve high revenue with lean teams (20–30 people for $100M+ businesses).
- These brands will have cost advantages over legacy players by automating back-office functions such as finance, HR, and supply chain.
- Human staff will focus on orchestration, oversight, and creative functions, supported by AI agents executing operational tasks.
- Organizational charts are beginning to include digital agents as recognized contributors.
Store-Level Impacts and Personalized Experiences
- Store-level AI applications face complexity due to scaling workflows across thousands of locations.
- AI enables event-triggered workflows, inefficiency reduction, and improved customer service through automation and better labor management.
- Advancements will allow personalized in-store experiences, where associates receive real-time relevant customer information to enhance service.
- AI-driven personalization will extend beyond high-value clientele to all customers, leveraging data from digital and physical interactions.
Dynamic and Personalized Pricing
- Retailers will increasingly use AI to offer personalized loyalty pricing, varying offers by customer segment and behavior.
- Shelf and digital price tags enable frequent, targeted price updates at individual stores.
- Fully individualized pricing may remain behind-the-scenes to avoid consumer backlash; overt dynamic pricing is likely limited by regulation and operational concerns.
Recommendations / Advice
- AI strategy should be tailored to the client’s customer base and legacy technology stack.
- Brands serving early adopters or with modern stacks should lean into AI and agentic commerce early.
- Companies should prepare for AI native competitors and invest in foundational data capabilities.
Decisions
- Focus on transforming key business workflows with AI rather than broad experimentation.
- Prepare for the rise of AI native brands as a new competitive category.
Action Items
- TBD – Retail/CPG Leaders: Assess readiness of organizational data and processes for AI-driven workflow transformation.
- TBD – Strategy Teams: Monitor agentic commerce adoption and develop approaches for AI-driven customer engagement and pricing.
Questions / Follow-Ups
- How will retailers handle potential consumer resistance to individualized or dynamic pricing?
- What new policies and practices are needed for managing digital agents as part of the organization?
- How will transaction, payment, and returns processes evolve if third-party AI agents control checkouts?