The agentic AI revolution: Reshaping retail and consumer interaction

Advanced AI capabilities are transforming retail as they evolve beyond simple automation and content generation to agentic AI – intelligent systems that can reason, understand context, interact, and act in increasingly human-like ways. To understand how this shift is reshaping customer experiences and business operations, we sat down with Kapil Dabi, America's market lead for retail and consumer at Google Cloud, who has been working with major retailers at the forefront of implementing these technologies.

There's a lot of buzz around "agentic AI." How would you explain it to retail executives who might be familiar with AI, but not with this more recent evolution?

Dabi: First generation AI followed a script – it was rule-based, reactive, and limited to pre-programmed pathways. Generative AI (gen AI) uses sophisticated models trained on massive datasets to produce original text, images, music, and even code. What we're seeing now is a fundamental shift to AI that can actually think, reason and act. Agentic AI doesn't just respond to questions. It processes data, evaluates information, and reaches conclusions and takes actions in the same way a thoughtful human might.

For retailers, this distinction is crucial. Earlier chatbots might help a customer find a product based on search keywords, but often couldn’t handle complex requests. Today's agentic AI can understand a customer saying, "I need a lamp that matches the décor in my living room," look at a photo they've shared, grasp the aesthetic style, and recommend products that would complement that specific environment – all while maintaining a conversation that feels natural.

What specific value does this more human-like AI bring to retail that previous technologies couldn't deliver?

Dabi: The most transformative aspect is the ability to understand both context and nuance. Let me give you an example: One of our customers, a major home improvement retailer, implemented a visual search system that doesn't just match products based on simple attributes but actually understands design concepts.

Early A/B testing showed that this system generated nearly $16 million in incremental annual revenue just for home décor items. Why? Because it better supports how humans naturally shop – visually and conceptually.

The same applies to customer service. One consumer electronics retailer transformed their support experience by implementing AI assistants that offer more personalized and efficient support for both customers and in-store employees. Their agents can reason through problems, consider specifics such as your device setup, and provide more informed and accurate responses reducing contact resolution by anywhere from 30 to 90 seconds, driving significant customer service improvements.

How is this technology changing the role of human employees in retail settings?

Dabi: We're seeing these technologies empower and augment employee capabilities and transform their roles. A great example comes from another home improvement retailer. They equipped more than 125,000 store associates with an AI assistant that gives them instant access to inventory management, personalized customer recommendations, and process information.

Now, instead of memorizing store layouts and inventory, sales associates focus on genuine human connection and problem-solving. The AI assistant retrieves all the necessary information, so the sales associate can concentrate on understanding the customer’s needs and giving them thoughtful advice.

Behind the scenes, a major food distributor is simplifying employee access to institutional knowledge across platforms like Google Workspace and ServiceNow, so they can make better decisions. It also created a centralized hub so its AI agents can collaborate with each other to solve complex business problems.

What does the customer experience look like in this new paradigm?

Dabi: It's getting more natural, personalized, frictionless, and seamless across channels.

One fast-food chain achieved a 95% success rate with their food ordering AI agent because it can engage in more natural and empathetic conversations. A popular fashion retailer we work with uses gen AI to help its contact center and concierge services quickly grasp what a customer needs and improve their response, which not only improves customer satisfaction but also drives larger purchases and reduces cost per interaction.

These new systems are also transformative because they’re multimodal. Customers can interact with retailers through voice, text, and images for a richer and more intuitive experience. A customer can take a photo of a room, ask for suggestions to "make this space feel more inviting for winter gatherings," and receive thoughtful recommendations that consider lighting, texture, and seasonal elements – all through a conversation that feels like talking to a knowledgeable friend rather than navigating a computer system.

What challenges do retailers face in adopting these more advanced systems?

Dabi: The primary challenge isn't technological but organizational. These systems require rethinking processes built around the limitations of older technologies. The retailers seeing the most success are those approaching this as a transformation initiative rather than just a technology deployment.

Talent and upskilling is another consideration. While these systems are more intuitive, they're also more powerful. Employees need guidance on how to effectively collaborate with AI that can reason and contribute ideas rather than just execute commands.

Finally, there's the data foundation. These reasoning systems can only reach their potential when they have access to comprehensive, well-structured information about products, customers, and operations.

How do you see this technology evolving over the next few years?

Dabi: We're moving toward truly collaborative multi-agent systems solving a complex business problem. Imagine a customer interaction where one AI agent understands the customer's style preferences, another specializes in supply chain visibility to confirm availability, and a third handles logistics planning – all working together seamlessly while appearing to the customer as a single coherent experience.

The ability for retailers to create custom agents tailored to specific needs will accelerate. We offer frameworks that allow retailers to build sophisticated agents with little technical expertise. This democratization means we'll see innovation coming from merchandising teams, store operations, and other business units, not just IT departments.

The most forward-thinking retailers are already winning by exploring how these systems can predict emerging customer trends, creating opportunities for service that truly anticipate customer needs.

Any final thoughts for retail executives considering these technologies?

Dabi: The Retail AI conversation is evolving beyond mere technology; it's now centered on your core business strategy and how AI serves as a powerful enabler to achieve tangible results. The focus has shifted from "what can AI do?" to "how can AI strategically drive your specific business outcomes?".

The retailers gaining competitive advantage aren't those using AI to simply automate existing processes – they're the ones reimagining what's possible when technology can think, reason, and communicate like humans. The question isn't whether to adopt these technologies, but how best to leverage them to create experiences that were unimaginable before.

The most successful implementations focus on enhancing human capabilities, for example, creating systems where AI handles routine information processing and complex reasoning tasks while humans unleash their creativity and emotional intelligence. In retail, where listening to your customers and anticipating what they need creates the trust that brings them back again and again, that's the true promise of this technology.

Learn more about how Google Cloud is helping retailers succeed with AI, here.