With agentic AI poised to redefine the landscape of retail, we sat down with Zainab Hussain, a leading e-commerce strategist, to discuss the groundbreaking innovations behind DaVinci Commerce. Fresh off its recognition as a Top 50 NRF Innovation for 2026, the platform is making waves by tackling some of the most persistent challenges in commerce marketing. Our conversation explores how agentic AI is collapsing campaign timelines from weeks to minutes, automating the complex web of creative compliance, and shifting the consumer journey from static landing pages to dynamic, AI-guided conversations that directly link ad exposure to verified sales.
The press release highlights that DaVinci Commerce can turn weeks of campaign development into minutes. Could you walk us through the step-by-step process of your Agentic Creative Template Generation, and share a metric that illustrates this dramatic reduction in production time for a brand?
Absolutely. The traditional process is something many in our industry feel a deep, visceral pain about. It involves endless back-and-forth between a brand’s marketing team, their creative agency, and the retailer’s media team. You’re manually checking specs, resizing assets, and praying everything is compliant. What our Agentic Creative Template Generation does is fundamentally change that workflow. A brand manager can simply upload a creative brief—the goals, the target audience, the key message—along with their core brand elements like logos and product imagery. The AI agent then autonomously pulls the specific, often complex, creative specifications directly from the retailer, whether it’s for a banner ad, a social post, or an on-site promotion. It synthesizes all of this information and generates a fully compliant, on-brand creative template in real time. We’ve seen scenarios where a multi-retailer campaign, which would typically take a team two to three weeks of design and revision cycles, is now producing its foundational creative templates in under an hour. It’s not just an incremental improvement; it’s a complete transformation of the creative production model.
Your Agentic Creative Compliance Checker is described as tackling a major industry bottleneck. Can you explain how this AI engine autonomously evaluates assets against brand, legal, and retailer rules? Please share a real-world example of a compliance issue it caught that historically would have significantly delayed a campaign.
This is where the agentic AI truly shines as a guardian of the brand. The bottleneck is real; I’ve seen campaigns delayed by a week just because a logo was two pixels off or the legal disclaimer was in the wrong font size for a specific retailer’s network. Our AI compliance engine is trained on a massive dataset of rules—brand guidelines, legal requirements for different product categories, and the unique ad specifications for every major retail media network. When a creative asset is submitted, the AI doesn’t just check for one thing; it evaluates it holistically against all these rules simultaneously. A perfect example is a campaign we saw for a health and wellness brand. The ad copy included a specific health claim that, for legal reasons, required a slightly different disclaimer in California versus New York. A human reviewer could easily miss that nuance. The AI immediately flagged the asset intended for the California market, noted the incorrect disclaimer text, and suggested the compliant version. Historically, that kind of error wouldn’t be caught until the final legal review, forcing a costly and time-consuming rework right before the launch deadline. The AI caught it in seconds.
The concept of “Agentic Shopping” is a key innovation. Instead of a landing page, you create a guided conversation. Could you describe this user experience from ad click to purchase, and explain how you technically link that conversation to verified transaction data and incremental sales?
Agentic Shopping is about meeting the consumer where they are and moving beyond the chaotic, one-size-fits-all landing page. Imagine you click an ad for a new skincare product. Instead of being dropped onto a page with fifty different serums and moisturizers, a conversational interface appears. The AI shopping agent, powered by our platform, might say, “Hi! I see you’re interested in our new serum. To help me find the perfect product for you, could you tell me a bit about your skin type?” It then guides you through a few personalized prompts, helping you make a confident choice. It feels less like being sold to and more like getting advice from a knowledgeable expert. Technically, from the moment of that ad click, we establish a unique connection that follows the user through the entire conversation. When the purchase is completed, that same connection links the transaction data back to the initial ad exposure. This allows us to provide verified, retailer-level attribution, proving not just that a sale happened, but that this specific, AI-guided interaction drove an incremental sale that wouldn’t have occurred otherwise.
Your CEO, Diaz Nesamoney, mentioned that consumers are increasingly using AI for product discovery. How does DaVinci Commerce specifically enable brands to shape that AI-driven conversation, and how does this “agentic” approach differ from the more common chatbots or AI search functions on retail sites?
That’s a crucial distinction. A traditional chatbot or an AI-powered search bar is fundamentally reactive. It waits for you to ask a question or type in a keyword. Our agentic approach is proactive and consultative. It’s not just a search tool; it’s a shopping guide. When a consumer clicks an ad, the agent already has context—it knows what product or category sparked their interest. DaVinci Commerce allows brands to essentially ‘train’ their shopping agents. They can feed the AI key product benefits, ideal conversational flows, and responses to common questions. This means the brand is actively shaping that discovery journey, ensuring their key value propositions are highlighted in a natural, helpful way. It’s the difference between a search bar giving you a list of ten blue shirts and an AI agent saying, “I see you’re looking for a blue shirt. Are you looking for something for a formal event or a more casual weekend style?” It elevates the interaction from a simple query to a genuinely useful, brand-stewarded consultation.
What is your forecast for the role of agentic AI in commerce marketing over the next five years?
Over the next five years, I believe agentic AI will become the central nervous system of commerce marketing. The focus will shift dramatically from optimizing clicks and landing pages to optimizing conversations and outcomes. Brands will no longer just be competing on price or product features on a crowded digital shelf; they’ll compete on the quality, intelligence, and helpfulness of their AI shopping agents. We will see the rise of hyper-personalization at a scale that was previously unimaginable, where a brand’s agent can have a truly one-to-one dialogue with every single consumer, tailored to their history, intent, and in-the-moment needs. Ultimately, I forecast a future where the primary way consumers interact with brands is not through websites, but through these intelligent, conversational agents, making the path from discovery to purchase more seamless, personal, and effective than ever before.
