AI is Changing Shopping. Execution Will Determine Who Wins

For years, digital commerce was built around a simple assumption: people search, compare and decide. Businesses optimized every part of that journey, investing in better websites, more effective marketing, and faster checkout experiences.

That assumption is breaking down. Artificial intelligence is increasingly helping consumers research products, evaluate alternatives, and make purchasing decisions before they ever reach a brand’s website.

As a result, brands must adjust to ensure they’re visible not only to consumers, but to the AI agents increasingly helping them decide what to buy. As AI becomes a influential channel in the shopping journey, businesses will need to rethink what it means to be discovered, evaluated, and chosen.

AI is Changing the Concept of Visibility

Many organizations still view agentic commerce as something several years away. Consumers, however, are moving much faster.

SAP Engagement Cloud research shows that 29 percent of U.S. consumers already use AI agents to support purchasing decisions, rising to 43 percent among Gen Z. Meanwhile, 68 percent say AI helps them make faster, more informed choices. These numbers suggest AI is quickly becoming part of everyday shopping behavior rather than an experimental tool.

This shift matters because AI agents can evaluate products across multiple sources in seconds, potentially weighing price, availability, product attributes, reviews, customer preferences, and other signals simultaneously. That changes the role of brand visibility. Product information that was once buried on a brand’s website can increasingly influence whether a product is even considered.

It’s becoming clear that visibility in the age of agentic commerce depends less on persuasive marketing alone and more on the quality of the underlying business data. As AI plays a larger role in helping consumers evaluate products and make decisions, businesses will need to ensure those agents can assess accurate, trusted and consistent information.

The Next Storefront Isn’t a Storefront

Every major technological shift has introduced a new way for businesses to reach customers. The app economy quickly took over mobile, and social media grew into a commerce destination on a scale that few expected. Nearly every digital channel is now a marketplace in some form.

It may be tempting to think of AI as the next commerce channel. In reality, AI is becoming something much more significant: a layer that sits between customer intent and business execution.

Unlike brick-and-mortar or email marketing, AI does more than display products, prices and bundles. It evaluates them. When an AI agent recommends one product over another, it's based on pricing, availability, customer preferences, and countless other signals. Those recommendations are only as reliable as the data, systems and processes providing that information.

Agentic commerce exposes gaps for consumers to see. Disconnected platforms, out-of-date inventory, inconsistent pricing, or fragmented customer records become more than internal inefficiencies. AI recommendations are only as accurate as the data behind them, and only as valuable as the business’s ability to execute on the insights delivered.

To adapt, brands need a unified data foundation that allows AI to act with confidence rather than simply generate recommendations.

In agentic commerce, the quality of the customer experience will depend on whether AI can see the same business reality the company has to execute against: inventory, pricing, fulfillment, service capacity, and customer context.

Always-On Unified Commerce Demands Always-Ready Businesses

When AI compresses the buying journey from hours to minutes, or even minutes to seconds, businesses lose the luxury of responding after demand appears. They need to be ready the moment the signal appears.

SAP Engagement Cloud research found that 80 percent of marketers believe AI will be essential for acquiring and retaining customers in 2026 and beyond. That confidence reflects a broader shift.

Instead of periodic engagement, businesses must be prepared for continuous engagement. Achieving this requires more than deploying AI tools. It means connecting AI insights directly to operational execution so changing conditions and customer signals can inform offers, inventory decisions, and fulfillment plans in real time.

This is operational intelligence: trusted data informing better decisions, connected processes turning them into action, and the business executing with greater speed, consistency and precision. Organizations with fragmented systems will struggle to keep pace. In that environment, success becomes less about individual channels or functions and more about whether the enterprise can respond as one.

When Commerce Becomes a Stress Test

The importance of connected operations becomes especially visible during periods of peak demand.

Whether it's a global sporting event, a major product launch, or the holiday shopping season, these moments place extraordinary pressure on every part of the organization simultaneously. These moments are no longer just marketing opportunities. They're enterprise-wide stress tests that expose whether an organization can coordinate decisions and action under pressure.

Increasingly, AI agents will participate in these moments as well, helping consumers identify products, compare availability, and complete purchases within seconds.

During a surge in demand, a customer or agent interaction can affect inventory allocation, delivery promises, and service capacity. Organizations with unified customer, commerce, and operational data can stay coordinated as events unfold. Those relying on disconnected systems risk inconsistency precisely when customers and AI agents expect the opposite.

Building for Humans and Algorithms

Some organizations may assume the answer is simply deploying more AI. In reality, success depends on something more foundational than the number of AI features a business introduces.

Businesses need the foundation to make AI reliable: trusted data, strong governance, and connected systems. In other words, organizations must become operationally intelligent before they become agent-ready. AI cannot compensate for disconnected systems, fragmented data, or broken processes. It amplifies what already exists.

In the future, customers will still expect personalization, trust, and meaningful brand experiences. But increasingly, those experiences will be mediated by intelligent systems acting on their behalf. That means businesses must design experiences for two audiences simultaneously: the people making purchasing decisions and the AI agents helping them make those decisions.

Consumer behavior is changing and AI is rapidly becoming another decision-maker in the buying journey. The real question isn't whether AI will influence commerce. It already is. The question is whether businesses are prepared for a future where decisions happen faster, expectations are higher, and execution matters more than ever.

In the end, competitive advantage won't come from how much AI a company deploys. It will come from who can most reliably deliver on the outcomes AI helps create. Recommendations are becoming easier to generate. Fulfilling them consistently is becoming the real differentiator.

Balaji Balasubramanian is the president and chief product officer of SAP Customer Experience (CX). In this role, he is responsible for overall CX business including consumer industries while directly overseeing product and engineering across strategy, product management, development, user experience, security, cloud operations and product marketing.