Retail is in its AI-powered era. From using AI to plan birthday parties to trusting AI agents for product recommendations, consumers are already rewriting the buyer journey.

Balaji Balasubramanian, President & Chief Product Officer for customer experience & consumer industries at SAP, breaks down what "agentic commerce" really means, how retailers can get ahead of the shift — and why structured product data may be your most valuable asset in 2026.

1. First things first: At NRF earlier this month, we consistently heard brands walk through how they're pivoting to "agentic commerce," or shopping journeys that begin on large language models (LLMs) or AI agents. What can retailers do to begin this journey?

Balasubramanian: NRF was another example of how brands are recognizing that consumers are increasingly using agentic AI to find and purchase products. In fact, according to recent data from SAP Emarsys, 58% of Gen Z and millennials say they would trust an AI agent to compare prices and recommend the best option.

On the show floor and during panel events, we saw retailers, grocers, wholesale distributors, fashion brands and more walk through how they're integrating agentic AI to ease customer journeys and simplify the buying process.

But to begin, brands must first ensure they have the right data foundation in place so that AI agents can surface relevant recommendations. That starts with a few core steps:

• Make product data more structured, complete and explicit, with clearly defined attributes and use cases.
• Layer in semantic summaries and context that help AI understand not just what a product is, but who it's for and why it matters.
• Tag products based on the problems they solve, since many shoppers ask AI for help with a specific need rather than searching for a product by name.

Brands that invest early in their data will be best positioned to show up in agent-driven discovery.

2. Next up: We're seeing lots of news about retailers partnering with LLM providers, beginning last year with the Walmart/OpenAI partnership and Target's ChatGPT shopping app. What does all this mean for the future of retail?

Balasubramanian: These partnerships signal a shift toward conversational commerce, where brands will meet customers on their preferred channels and turn a simple prompt into a purchase.

A message like "I'm planning a birthday party" can now spark a full customer journey, from product discovery to checkout and delivery. This shift raises the stakes for brands, who now need new engagement strategies built for these new channels.

• To capitalize on this moment, brands must think beyond front-end chat interfaces. The real value of LLMs isn't just delivering instant answers but connecting insight to action. When customer-facing intelligence is integrated with inventory, pricing, logistics, finance and customer service, retailers can sense and respond to demand signals in real time. That's only possible when interactions are powered by clean, harmonized data across the business.
• This year's holiday season showed that it's already underway, as shoppers used LLMs to generate gift ideas, compare products and find deals, bypassing traditional search, marketing and even retailers' own apps. Any retailer without a clear agentic commerce strategy or the unified data needed for AI to act with accuracy and context risks becoming invisible in the next era of shopping.

3. Okay, but: There are very few Walmarts and Targets in this world. What's actually possible for most retailers today, when it comes to AI?

Balasubramanian: Most retailers, especially small and mid-sized businesses, won't form direct partnerships with LLM providers to influence discovery. Instead, their priority should be strengthening existing product data so it's connected to backend systems and fully machine-readable. When product data is structured, accurate, and accessible, AI agents can understand offerings more clearly, anticipate demand and surface the right information faster, driving better outcomes for both retailers and customers.

Additionally, retailers can pilot AI in more targeted and practical ways, like demand forecasting, inventory optimization and basic personalization. Yet, AI only becomes a true growth driver when it's connected to accurate product and pricing data, live inventory and supply chain systems.

Leading brands know: effective AI is embedded AI, and that the technology is only as good as the data it's built on. When data flows freely across the business, AI can move from isolated pilots to enterprise-wide impact. Connected data that's harmonized across systems is the foundation of AI success.

4. The background: As AI takes a larger role in customer journeys, where should retailers intentionally insert human experience?

Balasubramanian: Shoppers are eager to support automation of processes that make their shopping smoother, like faster product discovery and streamlined checkout.

AI-powered technology allows customers to move through their journey more quickly, but human touchpoints are key to driving long-term engagement and brand loyalty. Live customer support, personalized outreach and curated experiences make the difference in building ongoing brand support and deepening customer relationships.

The best retailers use AI to handle routine tasks and free up time for humans to connect with customers in the moments that matter. For example, employees should be speaking with customers to solve complex problems and build true loyalty rather than entering a purchase order. Real, authentic human engagement balanced with thoughtful automation will drive increased customer satisfaction.

5. Here's what else: So let's talk about loyalty in the age of AI. What actually keeps customers coming back, and how can brands rebuild it?

Balasubramanian: Shoppers now expect more than points and perks in exchange for their purchase. They want brands to recognize them across channels, respect their preferences and provide experiences that feel relevant without overstepping.

It's a careful line for brands to navigate, but it's now feasible as retail leaders integrate AI in this new age of customer loyalty. AI allows brands and retailers to read signals across the journey, respond faster and build more meaningful interactions. Retailers who are implementing AI are seeing that the technology can synthesize customer data across channels in ways that help strengthen trust and loyalty.

6. Looking ahead: How do you see the next wave of AI, particularly AI agents, reshaping retail and consumer industries?

Balasubramanian: AI agents are poised to reshape retail by finally closing the personalization gap. More than half (52%) of consumers say brand experiences feel impersonal, according to the 2025 SAP Emarsys Customer Loyalty Index. As customer standards for CX rise, AI agents offer retailers a way to meet those expectations by recognizing every interaction, understanding the context and responding with relevance instantly.

They're also pushing the industry toward hyper-personalization. Today, this technology can interact with customers, interpret preferences, and surface insights that drive tailored offers, experiences, and recommendations. The next wave will advance even further by helping retailers anticipate demand shifts before they happen and reduce the risk of stockouts or oversupply. The result is a retail experience that finally matches what customers have been asking for: relevance, recognition, and seamless service.

7. The takeaway: Retail and consumer industries seem to live in permanent turbulence, from inflation to shifting trade policy to workforce disruption. How should leaders be thinking about building resilience today?

Balasubramanian: Rapidly changing trade policy, inflationary pressures and supply chain fragility are not new. Retail and consumer industries have been operating in a constant state of disruption for years. Now, these challenges have converged to squeeze revenue margins and challenge long-term strategies. Resilience is no longer about responding to the next shock but instead about building organizations that can sense change early and adapt quickly.

• The companies that can see through disruption have visibility into all data and processes from across the business. Information from areas like marketing, commerce, customer service and finance can paint a holistic picture of what customers want, where products live and what opportunities are available to optimize processes. Successful retailers know that without clean and connected data, it's impossible to respond to demand signals quickly and accurately.
• Resilient retail leaders are leveraging connected data and integrating relevant and reliable AI to address key challenges posed by disruptions. When deployed on a holistic data foundation, AI can help retailers immediately identify alternate routes, optimize inventory and predict intent. AI-driven personalization and connected operations are quickly emerging as the most dependable path to restoring customer trust and driving growth amidst industry disruption.

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