Webinar

The New Era of Agentic Commerce: Building AI-Powered Shopping Experiences

Featuring

Jeff Douglas

Director Of E-commerce,
Nebraska Furniture Mart

Dimple Rao

E-Commerce Growth & Loyalty, AKIRA

The Shifting Landscape of Retail and Commerce

The retail industry is undergoing a fundamental transformation, driven by the rise of agentic AI and changing consumer expectations. This shift goes beyond adopting new tools - it demands a rethinking of how products are discovered, marketed, and delivered across an increasingly fragmented set of channels:

Evolving Discovery Behavior: Consumers are moving from keyword-based search to intent-driven, conversational queries - describing occasions, preferences, and contexts rather than product names.
Multichannel Complexity:From TikTok and Pinterest to AI-powered assistants, the number of surfaces where a brand needs to show up is multiplying - each requiring distinct content formats and strategies.
Demand Unpredictability:Viral moments, cultural trends, and shifting consumer taste can create overnight surges that traditional forecasting methods can't anticipate.
Margin Pressure and Operational Costs: Rising customer acquisition costs, high return rates, and lean budgets mean every operational efficiency directly impacts profitability.

AI is being increasingly integrated across the retail value chain, offering benefits such as:

Generative Engine Optimization (GEO) to structure product data for AI crawlers and LLM-based discovery platforms
Visual AI for product data enrichment, extracting style, occasion, and cross-sell attributes beyond basic catalog information
AI-generated content and assets - room settings, multi-angle imagery, and video from single product silhouettes
Predictive analytics for inventory allocation, demand forecasting, and customer retention modeling
Personalized marketing at scale, generating channel-specific campaigns across email, social, and emerging platforms

Leading retailers are already experimenting with these capabilities. As AI tools become more accessible, particularly within ecosystems like Shopify, the barrier to entry is lowering, making it critical for retailers of all sizes to act now.

Inside the Panel: Practitioner Perspectives on AI in Commerce

In this webinar, Jeff Douglas, Director of Ecommerce at Nebraska Furniture Mart, and Dimple Rao, eCommerce Growth & Loyalty at AKIRA, shared how their organizations are approaching AI, from discovery optimization to back-office automation.

The discussion focused on real-world deployment rather than theoretical applications, and highlighted specific use cases across both fashion and furniture retail.

AI-Optimized Product Discovery: Structuring site content and third-party feeds to rank within AI tools like ChatGPT and Gemini - moving from SEO to GEO as the new optimization frontier.
Visual AI for Asset Creation: Generating lifestyle imagery, room settings, and product videos from silhouette images with per-asset costs dropping from $0.30 to $0.03 in under a year.
Conversational Shopping Journeys: Consumers now describe intent (event type, weather, personal style) rather than search keywords requiring richer product metadata and AI-readable content structures.
Predictive Inventory Allocation: Using AI to anticipate demand by location, size, and trend addressing the critical challenge of having the right product at the right place at the right time.
These use cases reflect a pragmatic approach starting with high-impact, lower-complexity applications before moving toward fully autonomous operations.

Impact: What's Changing on the Ground

The integration of AI across retail operations is already yielding tangible shifts in how teams work and how customers engage:

Productivity Multiplier: Tasks that previously took a week - reporting, analysis, content creation are being completed in hours with AI assistance.
Faster Asset Production: AI-generated product imagery and video have reduced content creation timelines and costs by orders of magnitude.
Improved Discoverability: Retailers investing in GEO are beginning to surface in AI-powered search results, capturing demand from a new generation of shoppers.
Reduced Return Rates: Visual AI tools that let consumers preview products in their own spaces (furniture in a room, apparel on different occasions) are increasing purchase confidence and reducing costly returns.

What's Next: The Roadmap for AI in Retail

Based on insights shared by the panelists, the next phase of AI adoption in retail is focused on deeper integration, better data infrastructure, and moving from experimentation to production:

Natural language interfaces over analytics - replacing dashboards and filters with conversational queries across the entire data stack
Legacy system modernization Tasks that previously took a week - reporting, analysis, content creation are being completed in hours with AI assistance.
Autonomous order routing and supply chain optimization - AI agents that dynamically reroute orders based on real-time warehouse conditions
AI-first content operations: - generating channel-specific creative (TikTok, Pinterest, email, web) from a single product asset
Enterprise-grade AI governance - firewalled instances, data protection frameworks, and compliance-ready deployment models

This evolution marks a broader industry shift from AI as a productivity tool to AI as an operational layer. As these technologies mature, they will play an increasingly strategic role in demand forecasting, personalization, and end-to-end workflow automation across the retail ecosystem.

Conclusion

This panel demonstrated that the opportunity in agentic commerce is real, immediate, and actionable but success depends on disciplined execution, data readiness, and a clear investment framework.

AI-driven discovery is reshaping how consumers find products - retailers who optimize for GEO now will capture demand others miss.
The transaction still happens on retailer-owned channels, creating a window to build AI-powered experiences where it matters most.
Data infrastructure and enterprise security are non-negotiable prerequisites without them, even the best AI use cases stall.
The path from AI-assisted to AI-led operations is a crawl-walk-run and the smartest retailers are already walking.

At Nurix AI, we're powering the next generation of autonomous enterprise operations helping retailers move from experimentation to execution across voice, chat, and agentic AI.