From Pilots to Profits—Agentic AI with Proven ROI, at Scale

PRASHANT AGRAWAL:
Hello, and welcome to the session. Thank you all for being here. The session is titled From Pilots to Agentic AI with Proven ROI at Scale. I’m Prashant Agrawal, CEO of Impact Analytics, and I’m honored to be joined by Valentina Labate, Chief Strategy Officer of Pittarosso and Scarpe & Scarpe—one of Italy’s largest footwear retailers.

Before we begin, I’ll take a couple of minutes to introduce Impact Analytics and who we are. We are a thousand-person organization focused on merchandising and supply chain decision intelligence. We were founded on the belief that machine learning and AI can meaningfully improve retail performance. I also teach AI in retail at Columbia Business School.

Our team is a mix of former consultants from firms like BCG and McKinsey, data scientists and engineers, and more than 50 former retailers—people who have actually sat in the merchant’s chair. We’re proud to have been ranked #72 on Fortune’s Most Innovative Companies list, alongside companies like Microsoft, Tesla, Apple, and IBM. Today, we serve more than 60 enterprise customers across fashion, apparel, specialty retail, grocery, and CPG.

Last year, our booth was covered with “Agentic AI” and “Gen AI,” and many people asked what that really meant. This year, every booth is talking about Agentic AI. Next year, the question will be: Why didn’t it work? Over the past year, we’ve shown how it can work—and Valentina is here to share that real-world journey.

With that, I’ll turn it over to Valentina.

VALENTINA LABATE:
Good evening, everyone. It’s great to be here at NRF. My name is Valentina Labate, and I’m Chief Strategy Officer at Pittarosso and Scarpe & Scarpe—two leading footwear retailers in Italy operating under the same private equity ownership.

My role isn’t just to define strategy, but to turn strategy into better decisions every single day across two brands, different teams, and different business models. Today, I want to share a concrete journey of how we introduced AI into our decision-making processes—not as a tech experiment, but as a strategic lever—using an intelligent BI platform called MondaySmart, developed with our partner Impact Analytics.

This is not a story of AI in the future. This is AI in production, inside real retail organizations.

Our starting point wasn’t a lack of data—we had plenty of data on inventory, trends, margins, and store performance. What we lacked was focus, clarity, and speed. Decision-making required extensive preparation: extracting data, aligning teams, validating numbers. People spent more time preparing data than acting on it.

For me, AI is not technology—it’s decision infrastructure. The key question was: Which strategic decisions would benefit most from AI? The answer was clear—inventory, sell-through, and performance management, and understanding not just what happened, but why it happened.

What convinced us wasn’t the dashboards—it was the logic behind them. MondaySmart doesn’t just show data; it connects, interprets, and highlights what truly matters. It removes noise, surfaces anomalies, and directs focus to where action is needed.

PRASHANT AGRAWAL:
One thing I want to emphasize is that Impact Analytics is an American company, and we’ve successfully implemented this solution in Italy. AI projects take time and effort, but MondaySmart can be implemented in as little as eight weeks.

We offer a full suite—from PlanSmart and AssortSmart to InventorySmart and PriceSmart. And today, we’re excited to announce a new evolution: MondaySmart is now called CortexEye.

CortexEye brings all enterprise data—structured and unstructured—into one place. It takes Agentic AI to the next level, allowing users to ask questions in natural language and receive guided, contextual answers tailored to their role—whether merchandising, marketing, or finance.

Reducing hallucinations and ensuring enterprise security are critical. In a business environment, everyone needs the same deterministic answer—not multiple possibilities. That’s core to our platform design.

VALENTINA LABATE:
AI adoption is still a journey, especially in a conservative market like Italy. Many people rely on decades of experience—and that experience is invaluable. Our goal was never to replace people, but to elevate them.

We didn’t create an AI lab or isolate usage to one team. From day one, this became the tool of the company. If we talk about performance, we use the same KPIs, the same language, the same platform. That consistency builds trust.

The speed and clarity changed behavior. With built-in conversational AI, teams can simply ask questions and get answers instantly—something that previously took hours of data extraction. Over time, people realized this tool empowers them rather than works against them.

PRASHANT AGRAWAL:
Let me ask one final question. What advice would you give to others starting this journey?

VALENTINA LABATE:
Don’t approach AI as a technology decision—approach it as a business decision. Start by identifying which decisions truly matter and where AI can create value.

Second, choose solutions that speak the language of the business—not just IT. Trust is everything. Without trust, adoption fails. For us, this wasn’t about hype—it was about ROI. And that’s what our private equity owners care about.

PRASHANT AGRAWAL:
That’s a great note to end on. Retail is both art and science. AI strengthens the science so leaders can focus more on the art.

Thank you, Valentina, and thank you all for joining us.