On October 21 and 22 in New York City, the Reinventing Retail AI Summit brought together leaders, innovators and visionaries to explore how AI in retail is transforming the industry. The spotlight was on multi-agentic AI, a collaborative approach where intelligent agents coordinate across planning, pricing, allocation and execution. Unlike traditional, siloed systems, multi-agentic AI allows specialized agents to share information, analyze trade-offs and execute coordinated actions in real-time. Our customers showcased how they are already using this approach to optimize operations, reduce errors and deliver measurable results.

This biannual event is more than a conference, it’s a hub for sharing strategies, showcasing real-world applications and uncovering how retailers can drive retail and revenue growth through AI. As a CEO, these events are always energizing. It's inspiring to see our customers openly sharing their successes, learning from each other and discussing how AI is enabling faster decision-making across retail operations.

Driving retail growth with multi-agentic AI

Multi-agentic AI enables retailers to orchestrate multiple business functions simultaneously. Its coordinated approach helps teams act faster, respond to changing demand patterns and turn data into actionable insights, proving that AI in retail is a strategic tool for results.

At the summit, we shared examples of how multi-agentic AI is helping retailers predict demand more accurately, prevent stockouts and reduce overstocks. By automating complex processes, multi-agentic AI transforms planning cycles that previously took weeks into operations that can be completed in days, freeing employees to focus on higher-value strategic initiatives. 

AI success stories

Tailored Brands highlighted how AI in retail statistics demonstrate the results of precise inventory management on margins and customer satisfaction. After implementing AI-driven replenishment and localization, Tailored Brands achieved a 4% increase in in-stock levels, a 16% reduction in Weeks of Supply (WOS) and a drop in substitution rates from 14% to 4%.

Mavi, a global denim brand, shared how automating over 20 million inventory decisions daily led to 9.6% revenue growth and a 10.6% improvement in gross margin. Their story clearly shows how multi-agentic AI scales across complex retail networks while maintaining precision in inventory planning and allocation.

Other presenters included Alo Yoga, Mattress Firm and Tecovas, each illustrating how AI is driving operational efficiency and boosting results across diverse retail sectors. From faster inventory planning to better allocation and dynamic pricing, these case studies highlight the real-world value of multi-agentic AI for driving retail and revenue growth.

Key takeaways from the Reinventing Retail AI Summit

1. AI in retail delivers measurable results. Retailers are seeing tangible improvements in inventory, allocation and pricing.
2. Collaboration accelerates adoption. Strong retail partnerships enable faster, more scalable AI deployment.
3. Retail events foster actionable insights. Summits like ours provide a platform for sharing best practices and learning from customer successes.
4. Multi-agentic AI transforms planning. AI decisioning turns reactive, manual processes into proactive, data-driven strategies that optimize every touchpoint across the business.

The summit reminded us that AI in retail isn’t just about efficiency, it’s about transformation. With multi-agentic AI, retailers can anticipate demand, optimize inventory and make stronger decisions in real-time. As the retail landscape becomes more complex, the retailers who embrace AI today won’t just keep up, they’ll define the future of retail.

Interested in attending the next reinventing retail AI summit? Stay in touch for updates!

Prof. Gurhan Kok founded invent.ai in 2013 to develop advanced analytics solutions for the retail industry. Before invent.ai, he was a tenured faculty member at Duke University’s Fuqua School of Business. He received his Ph.D. from The Wharton School, University of Pennsylvania in 2003.