New SAP research reveals there’s a structural shift that’s changing how businesses get chosen—and what brands can do about it.
There is a version of the customer journey most businesses have designed for. It’s the proven model and puts brands in the driver’s seat, and a version that your customers have chosen, the one that’s happening today.
The gap between them has never been wider, especially in B2B.
In the brand-designed version, discovery happens on your terms and evaluation occurs on your website, your store, or through your sales team. In the version that is actually happening, discovery and evaluation increasingly takes place inside an AI—before a customer has visited your site, entered your store, or spoken to anyone on your team. By the time they reach you, the shortlist has already been made. You were either on it, or you weren’t.
The bifurcation of the customer journey
SAP’sAI in Customer Experience Report 2027 surveyed 4,800 consumers, business buyers, CX practitioners, and decision-makers in the U.S. and Germany. The research highlights the structural shift underlying the change in buyer behaviour.
The customer journey has split. The first half—discovering options, researching alternatives, comparing, and shortlisting—is increasingly happening inside AI tools before a customer ever interacts with a brand channel. The operational half—the purchase, the fulfilment, the service, the return—all still fall to the business.
This pattern holds true in B2B. Nearly all business buyers surveyed in our research said they have used AI for purchasing or vendor selection. However, completing a transaction still requires navigating negotiated prices, contract terms, approvals, and implementation plans. The role AI plays through the journey changes. AI is taking the lead in discovery and evaluation, and acting in a support role in the later stages as business context, process, and interpersonal relationships become more important. An AI can identify the right supplier in minutes. Doing business with that supplier still takesconsiderably longer.
This is the hybrid AI buyer: not fully AI-driven, not fully human-directed—an experience that moves fluidly between both AI and brand, where the consumer expects businesses to be ready, no matter which side they’re navigating from, and most are not.
Discoverability is the new front door
For brand and marketing leaders, the implication is significant. Businesses have spent years building awareness, optimizing digital experiences, and designing paths to purchase. But if AI is now leading the initial research, the question is no longer, “Will customers find us?” It is, “Can AI find us, understand us, and confidently recommend us?”
Half of U.S. consumers now use AI in at least some of their purchase journeys.
SAP Customer Experience Chief Product Officer Balaji Balasubramanian framed it simply: if your offerings are not known to the AI engine, it won’t surface them at all. That is a discoverability problem.
And the problem runs deeper than visibility. Discoverability is no longer a periodic catalog audit or a one-time SEO exercise. It is a continuously moving target, because AI models are constantly re-evaluating what to surface, compare, and recommend.
Every attribute, every image, every specification, every availability signal, and every proof point now directly shapes whether a product gets found, shortlisted, or passed over—by both humans and machines.
Keeping a catalog “good enough” is no longer a viable standard. The new bar is a catalog that is continuously improving, using AI signals from real customer behavior. Search patterns reveal unmet demand. Taxonomy analysis reveals where products fall out of discovery. Content quality scoring reveals where descriptions, attributes, and translations are letting products down, quietly, at scale.
SAP’s Merchandising Assistant embodies this logic. Working across shop fronts, agentic search environments, and SEO at scale, it surfaces content issues, category misalignment, and assortment gaps, then drives the enrichment needed to fix them. The Catalog Optimization Agent continuously reviews product content against quality standards, identifying inconsistencies across languages and channels and delivering actionable recommendations before problems become lost revenue.
Discoverability in an AI-mediated world is earned and re-earned continuously. The businesses that understand this will be found and recommended. In other words, to meet the demands of AI as a customer, businesses must use AI to continually optimize as a supplier.
The Autonomous Enterprise behind the experience
AI exposes and accelerates the pain created by system disconnects.
There is a common thread weaving the reason that businesses struggle with both halves of the hybrid journey: the enterprise behind the customerexperience is not connected enough to support AI at any point in it, let alone all of them.
Ninety-three percent of U.S. CX decision-makers say they feel prepared for AI-enabled customers. Just six percent report that all relevant systems are actually connected end-to-end.
Real-time inventory signals informing commercial decisions. Unified customer identity across service, commerce, and fulfilment. Operational data flowing into AI at the speed of customer behavior, not the speed of a nightly batch.
Consider a retailer managing perishable goods. In the traditional model, when stock approaches expiration, the response is a markdown. It’s often unplanned, deeply discounted, and margin-destroying. The discount happens because the business is reacting to a physical reality its systems never translated into commercial foresight. Inventory data and promotion planning have been living in separate worlds, speaking different languages, and operating on different timescales.
In an autonomous, connected enterprise, those worlds merge. AI reads expiration and inventory signals from ERP in real time. It reads demand patterns, promotion history, and customer segment behavior together. It doesn’t wait for a manager to identify a problem on a shelf walk; instead it identifies the risk days in advance and configures a targeted promotion to move stock at the minimum viable discount, to the right customer, at the right moment. Promotions and inventory are managed in harmony, not in sequence.
The result is not just a smarter markdown. It is fewer unplanned markdowns altogether.
This is what the Autonomous Enterprise means in practice. It means AI sees the customer-facing layer and also reads the full operational picture beneath it: demand sensing and assortment optimization; inventory-aligned commercial decisions; continuous catalog enrichment grounded in real search signals. All of this feeds into a coherent strategy, rather than a cascade of disconnected reactions.
A competitor whose systems are connected doesn’t just execute faster. Their AI gets smarter, faster, because it’s learning from complete data, not partial signals. Their brand delivers more reliably in every customer-facing moment. The gap between connected and disconnected brands widens in the first and second half of the journey.
What the hybrid journey requires
A question for every CMO and business leader: are you designing for both halves of the journey?
As marketers, our focus will shift. Our area of influence will change. Awareness remains critical, but the focus on accurate product information, real-time pricing, and availability that can be trusted discoverable to AI increases. And it means building the operational foundation to deliver on whatever AI recommends. The moments of brand connectionlike check-out, order fulfilment, returns, or the exchange become the moments where brand can differentiate, and they’ll matter more than ever.
Brand used to be about persuasion, building awareness, creating preferences, and getting chosen.
In an AI-mediated world, it becomes about proof, reliability, service quality, and outcome certainty. Those are the signals AI uses decide whether your business deserves to be recommended, and the experience determines whether a customer comes back.
The journey has split. The responsibility for both parts of the journey has never been more unified.
Jessica Keehn is chief marketing officer for SAP Customer Experience.
