The rapid adoption of artificial intelligence is beginning to reshape how consumers discover products, how marketers build campaigns and how brands engage with shoppers, with agentic AI emerging as a significant force in the next phase of digital commerce. At the Criteo Commerce Forum India 2026, the company’s leadership , said the industry is entering a period of technology-driven transformation where the pace of change is unprecedented and commerce AI will increasingly complement existing shopping behaviour rather than replace traditional channels.
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The event opened with welcome remarks from Szi-Wei Lo, Executive Managing Director, Criteo APAC, who spoke about India’s fast-evolving digital commerce landscape and Criteo’s long-term commitment to the market. Held at The Westin Gurgaon under the theme ‘Commerce Intelligence in Action: Making Every Commerce Moment Smarter’, the fourth annual Criteo Commerce Forum brought together more than 200 senior marketing and commerce professionals to examine the impact of AI, commerce intelligence and trusted data on India’s increasingly fragmented omnichannel ecosystem.
Diarmuid Gill, Chief Technology Officer, Criteo said Criteo’s experience with AI stretches back more than two decades, but the emergence of generative and agentic AI is taking the technology into a fundamentally different phase: “Last year was a very notable event for Criteo. We celebrated our 20th anniversary. So, from our earliest days, we’ve been using AI. So, all of this graded data, using machine learning and different advanced artificial intelligence to be able to deliver performance for us and for our clients. Now, in the last few years, there’s been this revolution of agentic AI, taking it to another level. When ChatGPT was launched, it transformed the entire ecosystem.”
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Describing the current period as the beginning of what he called the Fourth Industrial Revolution, Gill said AI would have an impact comparable to previous technological shifts, but with one major difference, the speed at which change is taking place: “We say we are at the start of the 4th Industrial Revolution. The 1st one, through steam power in the 1700s. The 2nd one, through the advent of electricity and the internal combustion engine. The 3rd, with the rise of computing, leading all the way up to the internet. And the 4th, the AI revolution. And this one, like all of the others before, are going to completely transform every single part of society. And there will be a before and an after, and nothing will ever be the same again. And the difference between this one and all of the others is the pace of change. Whereas before it happened in years and months, now it’s happening in weeks.”
India emerges as a key market for commerce AI
According to Gill, India is particularly well positioned to benefit from the AI-led transformation, with businesses and consumers rapidly experimenting with AI tools: “India is a very rapidly advancing society, and technology is one of the places where you see this most. We see that the Indian ecosystem is really embracing this new revolution. We see that more than 80% of businesses, which is huge, 4 out of 5 businesses, are looking at how they can use Agentic.”
He pointed to the rapid growth of ChatGPT adoption in India as another indication of the market’s appetite for AI-led experiences: “India now has become the second largest market. And so they assume it will probably become even the largest market for ChatGPT, which is incredible to think of the rapid adoption of this technology. And we see that Indian people, Indian consumers, are more and more using not just ChatGPT, but Cloud, Gemini, Copilot, all of these tools to help inform how they do shopping online.”
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Gill also highlighted the growing role of AI in product discovery. He said nearly half of consumers are already using AI for shopping, while shoppers using these tools are increasingly looking beyond the product they initially searched for: “And to go through some of the deeper stats, we see that almost half of people are now using AI for shopping. I know personally, I’ve used it several times this week.”
He added: “56% of shoppers who are using these also want not only the product that they ask for, but similar products. So if I buy a bike, well, what else would I buy with it? You know, the cycling equipment, the helmet, the things that go quite a long.” Rather than viewing AI-enabled shopping as a replacement for existing commerce channels, Gill sees it as an additional layer that can expand the overall opportunity for brands and retailers: “96%, and this is super interesting, so people talk about how commerce AI might take over the world. We see this as an incremental opportunity that will very much complement a lot of the way that people have been shopping already. It won’t replace, like before, when e-commerce took off, people predicted that this would be the end of bricks and mortar. This would be the end of the high street store. Instead, what we saw, it helped to grow the overall pie. We believe that commerce AI will do the same.”
From smarter advertising to intelligent decision-making Gill outlined three areas where Criteo sees commerce AI making a significant impact: improving technology, making marketing workflows more efficient and creating richer consumer experiences: “So, today, I’m going to take us to three different areas where we see commerce AI changing how it works. First, how we think it’s making tech smarter. So this new generation of agentic functionality, how it’s helping to elevate the products we build.”
The second area, he said, involves removing repetitive manual work from advertising and marketing operations: “Second, how we work on a daily basis. So, one of the things about ad technology is there’s a lot of manual work involved. Creating campaigns, setting targets, generating reports, doing all these kind of things. We believe, and in fact, we don’t just believe, we see that all of these tools are helping to really accelerate the way things are working.”
The third and potentially most significant area is the consumer experience itself: “And finally, an area which I think is one of the most exciting, is how quickly we see these impacting how people are using shopping online and how it’s elevating the consumer experiences. Criteo’s position in this emerging ecosystem is supported by its scale of commerce data and relationships, Gill said. The company has more than 17,000 direct advertiser relationships and thousands of publisher relationships, giving it visibility across different stages of the digital commerce journey.
“We have over 17,000 direct relationships with advertisers. So, they give us access to all of the commerce activity that happens across their networks. We see more transactions on an annual basis than Amazon do across their entire network. Over a trillion dollars of transactions globally,” added Gill.
He said this creates a feedback loop spanning retailer websites, browsing behaviour, advertising exposure, clicks and transactions: “We know that high quality users look at high quality content. So, giving us the full loop where we can see what happens on the retailer websites, what people do as they browse the webs, what ads they see, what ads they click on, what ads they don’t, and then what transactions they get carried out as a result of this.”
AI moves from prediction to agentic execution
Gill explained that Criteo’s AI journey has evolved from traditional machine learning and deep learning towards foundational models and agentic systems capable of supporting more complex commerce decisions: “Where this is interesting is from a shopping point of view, you can then draw lines between shoppers, products, content, and have the AI tell you what makes most sense to show to a certain person at a given place at a given time.” Gill said the technology can identify relationships between products that may not be obvious at first glance, helping marketers understand purchasing patterns and improve recommendations.
Criteo’s scale of data also enables its models to continually learn from consumer interactions: “As a user goes through their shopping experience, they land on a customer, on a retailer website. They search for a product. They look at the product detail page. Some things they add to their basket. Some things they purchase. Some things they don’t. We’re able to use this to continually train our models and be able to refine to get the most accurate predictions and recommendations.”
Gill said this intelligence can translate into measurable improvements for advertisers, including stronger prospecting, click-through rates and conversions: “Using this technology, 37% extra of new customers for prospecting audiences. Plus 20% click-through rates. And more conversions, and then most importantly, more revenue, which is, you know, kind of ultimately why our clients are doing business with us, because they get better results from us.”
MCP becomes the ‘plumbing’ for the agentic ecosystem
A key component of Criteo’s strategy is the use of Model Context Protocol (MCP) to connect AI agents with the company’s commerce intelligence capabilities. Gill described MCP as the infrastructure that allows agents to discover and interact with different functionality across systems: “This was a technology that was defined by a company called Antropic, who provide cloud, and it’s serving as the plumbing that interconnects the agentic world. All right, so layered on top of APIs, it provides a way for agents to discover what functionality is available. So as you’re able to interconnect your systems, MCP is the plumbing that would be able to connect everything together.”
Criteo has invested in making its forecasting, prediction and recommendation capabilities available through MCP endpoints, enabling customers to access them through different AI interfaces: “With Criteo, we’ve invested heavily in taking all of the rich functionality that I mentioned earlier, the forecasting, the prediction, the recommendations, and make it available to MCP endpoints, so that our clients are able to use these through these tools, so through cloud, through Gemini, through Copilot, but also within their own tools, making it incredibly rich and powerful and helping them make it easier for them to integrate into the Criteo systems.”
The implications extend beyond simply generating reports. Gill demonstrated how users can interact with Criteo’s systems using natural language to understand campaign performance, identify relevant audiences and make recommendations: “And what’s super interesting is this accelerates some of the most menial, some of the most repetitive tasks that people do on a daily basis. With the power of Agenda, you’re able to chain all of these events together, you’re able to create skills so that you’re able to then create automations that will be able to carry out all of these actions on your behalf, giving you so much efficiency and freeing you up to be able to do much more interesting work.”
Gill sees this as an opportunity to shift marketing teams towards higher-value work rather than as a threat to existing roles: “There is often people talk about the agentic world and some people see it as a threat. I see it very much as an opportunity. So to be able to give time back to our teams so that they will be able to use that time to work on higher value tasks.”
He said natural-language interfaces are also lowering the barrier to using sophisticated marketing technology: “The ability to be able to streamline that end-to-end orchestration from setup to optimization and be able to do it in a human interface. As you saw in the example, people were able to put into their human language, I want to create a campaign, I want to target this product towards whatever audience. And all of this is now feasible without a computer science degree.”
Generative AI brings new possibilities for advertising creatives
Beyond campaign management and audience selection, Criteo is also using generative AI to change how advertising creatives are developed. Gill said the company processes billions of products every day and maintains a catalogue of more than 20 billion products: “We ingest billions of products from our clients every single day. We have over 20 billion products in our product catalog, each with a different set of images, and using those images, we’re able to, using generative AI, create some really rich, engaging video experiences. We’re able to enhance images, we’re able to take a text description, be able to generate rich images from this, which makes it much, much more engaging.”
The next stage, however, is not simply about improving the advertisement itself, but making the advertisement interactive: “In fact, even in some of them, we’re able to have the ability to be able to interact so that the user can actually query and talk to the advertisement and ask questions about it.”
Towards conversational commerce experiences
Gill said AI is also creating the possibility of more conversational shopping experiences, where advertisements can become an interface through which consumers ask questions and explore products: “We have a live demo, our live example prototype running right now with a client in Europe, where we have a conversational app, an ad unit, where they can actually type into the ad, look at the product and ask for more details about the product, more information, or particularly ask for different products.”
He compared the experience to interacting with a salesperson in a physical store, where shoppers can ask questions and receive recommendations rather than simply being presented with products: “So very much driven by the context of the page that it’s on, and have the ability to be able to tailor, like you would do when you go into a store, you ask the sales person or the sales assistant about a certain product or recommend you something, you ask questions, you ask about the returns policy, you ask about all of those kind of things, which provides a very, very engaging aspect.”
For Gill, the combination of AI and Criteo’s commerce data could help bring some of that physical retail experience into digital commerce: “So one of the best experiences you have as a shopper is you walk into the store and you walk up and a sales assistant comes to you. And they’re not interested in driving a product down your neck. They just want to give you the best experience. They want to answer your questions. They want to read that advisor. That is now finally possible using these kind of systems.”
Fresh commerce data becomes critical for AI-led shopping
Gill also highlighted a key limitation of large language models in commerce: the dynamic nature of product information. Prices, inventory, promotions and product availability can change rapidly, making static information insufficient for commerce decisions: “One of the things that’s a limitation of an LLM, and we keep hearing about every time there’s a new model released, an LLM is trained by scraping all of the data that it can have access to. But the second that it’s trained, it becomes out of date. It becomes out of date because product information is very dynamic. Prices change all the time. There’s flash sales, there’s stock ruptures, there’s new models that come out, and the LLM does not know about those.”
Criteo’s proposition, Gill said, is to provide the continuously refreshed commerce intelligence that AI systems need to make relevant shopping recommendations: “Because Criteo ingests all of those over 20 billion products every single day. We always have the most up-to-date, the most rich information, so that when an LLM calls Criteo, we’re able to show exactly up-to-date information.”
Marc Fischli, Executive Managing Director, International Markets, Criteo, shared Criteo’s evolution into the commerce intelligence platform and how AI is reshaping product discovery for brands. He also highlighted that AI is growing the ecommerce pie, enabling commerce to evolve beyond retail media and targeting into truly cross-channel and full-funnel experiences: “Our new mission is to power intelligent commerce wherever it happens. Commerce remains central to what we do, but commerce intelligence that drives better and broader outcomes for our clients and the industry is becoming the heart of what we do. As AI creates new opportunities and additional channels, we believe it will grow the commerce pie rather than replace existing ones. The linear funnel no longer reflects how consumers shop today; people interact with brands across multiple touchpoints and channels in parallel. That is why we believe the future is very much full-funnel and cross-channel, with integrated campaigns that reflect the way shoppers actually discover, evaluate and purchase products.”
The forum also showcased real-world examples of how Criteo’s commerce intelligence and AI-powered decisioning are translating into measurable outcomes for brands. In an interactive session with Medhavi Singh, Country Head at Criteo India and Driv Vohra, Head of Digital Marketing, Mars Snacking, a Kellogg’s case study was demonstrated to discuss how Criteo’s cross-channel, full-funnel approach helped drive scaled reach and new-to-brand acquisition, delivering 2.1–2.3 million average weekly reach on OTT and 97% new-to-brand buyers. Vohra commented, “Commerce signals are most valuable when they help move beyond audience identification to measurable new-to-brand growth. In our campaign, Criteo used transactional signals to identify relevant breakfast-cereal audiences, build reach through OTT, and extend engagement across Meta and the open web. This cross-channel, full-funnel approach helped connect awareness and consideration with conversion and acquire new customers.”
