Retail loyalty has long been built around a simple assumption: customers will open your app, browse the catalog, respond to offers, and complete their purchase within your brand’s digital channels.
AI assistants are beginning to change that behavior. Customers are aggressively delegating the digital legwork of shopping—from discovering products to comparing prices—to AI. The shift is already measurable: according to Adobe, AI-driven traffic to US retail sites surged 393% year-over-year in Q1 2026, converting 42% better than traditional channels. We saw the early warning signs last summer when ChatGPT quietly absorbed 16% of Zara’s inbound web traffic and 8% of H&M’s.
What’s in this article:
- How real-time APIs that expose loyalty perks to AI may prevent algorithmic cart abandonment in today's hybrid retail era
- Why human-centric experiences remain your strongest defense against AI-driven price commoditization
- How portable loyalty credentials might eventually replace walled-garden apps to power decentralized commerce
- Ways proprietary data and machine-targeted incentives could help brands win algorithmic auctions in future AI discovery engines
This trend has fueled the specter of "invisible commerce"—the anxiety that customers will blindly click "buy" based on an AI summary, or let algorithms auto-replenish their wardrobes, severing the brand relationship entirely. But a recent DOSS survey puts this in perspective. While 77% of consumers eagerly use AI to research products, a mere 6% actually trust the machine to execute the final transaction autonomously.
The shopper is still human, but the visitor increasingly is not.
How do you build loyalty in this changed retail landscape? Navigating this transformation demands a two-phased roadmap. First, brands must master today's hybrid reality by engineering systems for both AI agents and humans. Second, they must prepare for the future, when loyalty outgrows the walled-garden app to become a portable credential.
Phase 1: The Hybrid Reality: One Program, Two Customers
To serve both human shoppers and AI agents, brands must adapt their infrastructure in three ways.
Make Loyalty Perks Algorithmically Visible
Agents optimize on quantifiable value. Brands spend millions designing gamified VIP portals and splashy banners, but if member pricing or free-shipping perks exist only in the frontend UI, an AI agent assumes the customer needs to pay full retail price (because it can only parse the data layer).
There is a valid fear among revenue leaders here: Doesn't exposing promotions via API invite bots to ruthlessly scrape our margins?
It is a fair concern, as standardizing this data will accelerate cross-brand comparability. The alternative, however, is algorithmic invisibility. In a split-second matrix evaluation, an AI will bypass your brand in favor of a competitor whose loyalty data is structured for the machine.
The plumbing required to bridge this is already standardizing rapidly. Talon.One’s Unified Incentives Protocol (UIP), released this January, laid the groundwork for exposing loyalty benefits natively to machines. More critically, Google’s Universal Commerce Protocol (UCP) allows an AI agent to authenticate a shopper’s profile and securely apply their rewards during a transaction. If your retail infrastructure isn't conversant in these protocols today, your brand simply won't appear in the AI's optimized cart.
Make Data Quality a Loyalty Feature
Even with the right APIs in place, the entire premise of agentic discovery collapses without quality, real-time data. This was evident when OpenAI pulled its Instant Checkout pilot from ChatGPT in March. The initiative, which had roughly 30 merchants live, failed because the AI relied on scraped, lagging inventory and pricing data.
Many assume that slight data latency is acceptable for top-of-funnel product discovery. But that assumes a traditional shopping journey. In an agent-assisted flow, the dynamic is different.
Consider the reality of how this works: a customer asks their AI to find a specific jacket and apply their VIP tier discount. The bot parses the retailer's available data and presents a definitive price. The customer then clicks through to execute the purchase. If they arrive at the checkout and the price has jumped (or the item is suddenly out of stock) because the retailer's data feed was lagging, the trust is instantly broken.
The customer will not blame the bot for hallucinating the price, but they will definitely blame the brand for breaking a promise. Real-time data synchronization is thus a frontline defense against algorithmic cart abandonment.
Protect the Human Relationships
As retailers rebuild systems for AI, there is also the danger of going too far. If your loyalty program is redesigned solely to satisfy a bot’s mathematical hunt for the lowest price, you risk reducing your fashion brand to a mere commodity.
The best defense against a race to the bottom is the human experience. A bot cannot feel the thrill of an early product drop, the exclusivity of a private community, or the personal touch of a styling event. But humans absolutely do. This is why programs like Levi’s Red Tab and Nike Membership continue to capture up to half of direct-to-consumer revenue and triple customer spend. They achieve this by making the shopper feel like an insider.
Retailers must continue to invest in the high-touch experiences that an LLM cannot replicate. When an AI assistant reduces the discovery phase to pure math, experiential perks are the only safeguard preventing humans from overriding their loyalty and reaching for the cheapest option.
Phase 2: The Post-Channel Era: Loyalty as a Portable Credential
Merkle forecasts that by 2030, roughly $2 trillion in digital commerce will flow entirely through autonomous AI agents. Surviving this shift means navigating four new realities:
No More Walled Gardens
Retail’s reflexive instinct is to hoard first-party data by keeping customers inside an owned ecosystem, forcing them to download an app just to access rewards. But when discovery and checkout happen inside an AI chat prompt, that walled garden could become a barrier to revenue.
The payments industry has already accepted this shift. Visa’s Intelligent Commerce and Mastercard’s Agent Pay are already issuing secure, delegable tokens bound to specific AI agents. Loyalty identities can also adopt this framework. A VIP customer need not log into your site; their AI assistant can carry a revocable "loyalty passport" containing their tier status, historical preferences, and entitlements, and present it at digital surfaces across the open web.
Algorithmic Arbitrage and the "Fit" Defense
Portability introduces a new problem: ruthless comparability. Accenture data shows that 37% of consumers will authorize their agent to break brand loyalty if it finds a mathematically superior deal.
In this algorithmic auction, legacy loyalty mechanics will fail. If your program relies on complex mental arithmetic (“Spend $150 to earn 500 points toward a future 10% discount"), an agent optimizing for immediate value will simply route the purchase to a competitor offering a flat 12% off today.
To prevent this race to the bottom, retail brands must inject non-price utility into their loyalty credentials. For apparel, that unfair advantage is fit. Online apparel returns currently hover around a margin-crushing 24.4%, with up to 53% of those attributed to fit/sizing issues. Retailers like ASOS are already clawing back margins here, cutting return rates by 160 basis points through a mix of virtual try-on technology and targeted policy changes.
Imagine a loyalty program that stores a dynamically verified body profile as part of its portable token. If a brand issues a mathematical promise—"When your agent buys our recommended size, it fits, or we absorb 100% of the return cost"—it creates a calculable value that no generic promotional code can beat. That definitive, zero-risk utility wins the AI's auction every single time.
Agent-Facing Incentives
Because AI agents will act as the gatekeepers of discovery, brands must learn to market directly to the machine. We are moving past SEO and into Agentic Engine Optimization (AEO). AI optimizes for two things: the absolute lowest price and the highest probability of task completion.
To rank on third-party discovery surfaces, your incentive design must be agent-facing. This means offering "machine-only" utility. For example, a retailer might offer an exclusive 2% discount specifically for agent-routed transactions, simply because the bot bypasses the retailer's frontend UI and lowers compute costs. Or, the brand guarantees a 99.9% inventory accuracy via API, ensuring the bot never fails its checkout task. You must mathematically incentivize the algorithm to present your cart over a competitor’s.
Security at the Speed of Autonomy
Finally, retail CxOs must address the dark side of agentic commerce. Autonomous agents are already turning loyalty point balances into soft targets for automated fraud. If a bot can browse without friction, bad actors can program an agent to easily drain unmonitored reward points across thousands of accounts in seconds.
Security must therefore scale with autonomy. Scoped permissions (allowing an agent to apply a discount but forbidding it from redeeming cash-value points), algorithmic spend limits, and per-agent token revocation will be baseline requirements for operating in the agentic era.
The Engineering Mandate
For retail CxOs, the leap from today’s walled-garden apps to the portable, tokenized loyalty of 2030 can seem daunting. The roadmap, however, is quite practical. It begins by laying the precise data foundations that AI demands, while simultaneously designing the high-touch, visceral experiences that humans crave.
Our retail and luxury retail services operate at this intersection. While the fully autonomous agentic passports of the future are still being defined, the architecture required to survive the transition must be built today. Leveraging our High AI-Q™ engineering approach, we help brands bridge the technology gap. We build the real-time data layers that satisfy the agent’s rigorous math, design the experiential loyalty programs that defend your emotional moat, and seamlessly wire the two together.
Ultimately, agentic commerce is not about bypassing the human; it is about serving a shopper who now navigates the market armed with a powerful proxy. So the question for your next executive meeting may not be how to get more people to download your app. It may be: When an AI agent searches on behalf of our best customer, what does it see?