Zohar Gilad is the CEO and co-founder of Fast Simon, a leading AI-powered optimization platform for e-commerce. With a background that bridges technology and retail, Zohar has been instrumental in driving the evolution of search, merchandising and personalization for online merchants. Under his leadership, Fast Simon has become a pioneer in applying cutting-edge AI to enhance the digital shopping journey, delivering everything from conversational commerce to real-time shopper personalization.

In this CityBiz Q&A, Zohar shares his perspective on the transformative role of artificial intelligence in e-commerce, what the next wave of innovation looks like and how Fast Simon is preparing retailers for an increasingly personalized future.

What are the next big trends in AI that online retailers should be paying attention to?

We’re entering a new phase where AI isn’t just assisting; it’s starting to act. The biggest trends I see are centered on agentic AI, which enables systems to reason, plan and take autonomous action. This means AI will not only make recommendations but also carry out complex tasks, like adjusting merchandising strategies or creating real-time bundles for shoppers based on behavior and intent.

We’re also seeing a strong push toward real-time, session-based personalization, where AI models learn and adapt to a user’s current intent and past behavior. Multimodal interaction — combining voice, image and text — is becoming more popular. Together, these advancements will make online shopping much more intuitive and responsive.

How does Fast Simon stay on top of emerging trends?

We place bets where we think the technology is headed. Some of these are multiyear plays — for example, we’re heavily invested in hybrid GenAI models that combine keyword and vector search and real-time embeddings that adapt to shopper behavior within a session. Placing these bets early allowed us to deliver better relevance, reduce the instances of “no results” and increase conversion rates by more than 30% in A/B tests.

Beyond that, we’re developing agentic capabilities that allow AI to operate within defined guardrails — making merchandising decisions, identifying underperforming products and drafting new collections based on trends. We’re already piloting these features with partners.

Agentic AI is gaining momentum — how do you think it will influence shopper behavior?

There’s a lot of interest in consumer-facing agentic AI — especially in the media — but we’re not yet seeing real-world adoption in retail. The idea of autonomous agents that shop on your behalf or design store layouts without oversight is intriguing, but it’s still more conceptual than practical today.

That said, we’re starting to see agentic AI take hold on the backend of e-commerce experiences. For example, an AI assistant that helps a merchandiser sort collections based on stock or popularity or flags underperforming campaigns is a controlled, bounded use case that provides value. It’s important to separate hype from what’s actually deployable. We’re focused on building what works for merchants now while keeping an eye on what’s next.

In what ways is AI advancing search and discovery across different sales channels and shopper touchpoints?

AI is making search much more intuitive. With multimodal support, shoppers can now use voice, images or flexible phrasing to find what they want — even if they don’t know the exact name of a product. Our hybrid search architecture allows us to understand intent better and deliver more relevant results across mobile, desktop and even chat interfaces.

This also helps merchants unify the experience across channels. A shopper might start on social, continue on mobile and convert on desktop. AI helps keep the context consistent throughout.

How is AI enabling e-commerce brands to shift from reactive to proactive strategies in customer engagement?

This is one of the most exciting shifts. With real-time shopper session embeddings, we can understand intent and behavior as they unfold. That allows brands to dynamically adjust recommendations, product positioning and messaging without waiting for post-session analytics.

Instead of reacting to past metrics, brands can now engage shoppers while they’re still in the funnel based on what they’re clicking, hovering over or searching for right now. This move from retrospective insights to in-the-moment action is where AI delivers real ROI.

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