The retail sector is going all in on AI. From chatbots and recommendation engines to demand forecasting and real-time personalization, the appetite for AI-powered tools has never been stronger. Across the board, retail leaders are eager to streamline operations, deepen customer engagement and unlock competitive advantage with data-fueled intelligence.
But amid this wave of enthusiasm, a critical oversight is holding many brands back: the underlying data infrastructure isn’t keeping up. Amperity’s 2025 State of AI in Retail report found that only 11% of brands are confident in scaling AI across enterprises. In the rush to implement new AI tools, some retailers are overlooking the essential groundwork needed to support them. Here’s the reality: even the most advanced AI can’t deliver if it’s built on fragmented, low-quality data.
Ambition Without Foundation
The latest research bears this out. Amperity found that while 97% of retailers plan to increase their investment in AI this year, only a small fraction (roughly 20%) are currently using AI to unify customer identities. AI is only as good as the data beneath it. Garbage in, garbage out—it’s that simple. And, without solid, accurate customer profiles, AI investments won’t pay off.
When customer data is siloed across ecommerce platforms, loyalty programs, mobile apps, POS systems and third-party delivery services, AI can’t deliver on its promise. Sure, it may churn out insights or send messages, but if they’re based on incomplete or mismatched profiles, the results will miss the mark. It’s the common “garbage in, garbage out” problem, applied to the most expensive technology stack many retailers have ever invested in.
The Identity Resolution Gap
At the center of this gap is the ability to reconcile all those data sources into a single, accurate, privacy-compliant view of each customer. Unfortunately, many retailers still use rules-based methods for identity resolution or avoid the problem entirely. The result can create broken or inconsistent customer experiences. For instance, a returning shopper gets welcomed like a first-time buyer, a loyalty member doesn’t see their points reflected at checkout, or a promotional email recommends products the customer already purchased in store last week.
These hiccups can have a significant impact on the business or brand. They undermine customer trust, reduce customer lifetime value and weaken AI investments made across the enterprise. The retailers pulling ahead with AI aren’t always the ones with the fanciest models—they’re the ones that fixed the foundation first. Retailers that prioritize identity resolution are able to use AI more confidently, across more functions and with far greater accuracy, resulting in the business growth that AI tools promise.
From Fragmentation to Personalization
Retailers know they need to adapt to rising consumer expectations. Shoppers expect interactions with a brand to be highly personalized and reflect their preferences in real time. To make that possible, retailers need a unified view of each customer.
With accurate, consistent profiles at the center, AI enables personalization in the moment, delivering offers based on real-time trends and behaviors that feel seamless. For example, imagine a shopper browses hiking boots on a retailer’s mobile app, but doesn’t purchase. Later that day, they walk into the retailer’s physical store. With a unified identity layer in place, an AI system can recognize this cross-channel behavior and trigger a personalized offer, such as a loyalty member discount on footwear or a recommendation for a matching hiking jacket, based on past purchases.
Beyond personalization, it also empowers smarter decision-making. Offers can be optimized based on current inventory levels, customer preferences and purchasing patterns. And because every interaction is tied back to a single customer profile, retailers can finally measure the true ROI of their marketing efforts across the full journey.
“Identity resolution may not sound glamorous, but it’s the backbone that makes AI work in the real world. It’s not just about knowing who your customers are – it’s about recognizing them in the moment and serving them with real relevance.”
Governance Matters More Than Ever
As AI becomes more embedded across the customer journey, the stakes around data governance are also rising. Amperity found that just 43% of brands use AI to directly improve customer experiences, even though most agree it has high potential to boost loyalty and lifetime value. Using advanced AI solutions and organization-wide automation raises both the opportunities and the risks for retailers.
Missteps around data privacy, consent and usage are business risks with brand, legal and financial consequences. From the EU’s Digital Markets Act to the California Consumer Privacy Act and the growing patchwork of global data privacy laws, compliance expectations are ever-evolving. That’s why identity resolution is not just a marketing priority—it’s also a compliance safeguard. When done right, it creates a governed framework for how customer data is collected, connected and activated across channels. It also ensures every AI-driven action, such as a personalized offer, an automated email or a predictive churn model, is rooted in first-party, unified data.
This kind of built-in governance is what separates responsible, future-proof AI deployments from potentially risky, short-term wins. It allows retailers to innovate with confidence, scale personalization while remaining compliant, and maintain trust at a time when customer expectations are sky-high.
Closing the Gap
For many retail leaders, the temptation in AI strategy is to focus on front-end innovation.Derek Slager There is a wide range of shiny objects that make big promises around productivity, efficiency, growth and transformation. But real transformation starts with the unglamorous work of fixing customer data. Every other AI investment depends on it. Retailers looking to close the gap between AI ambition and AI performance need to start with identity. It won’t grab headlines, but it will determine who wins.
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Derek Slager, Co-Founder & CTO of Amperity
Derek co-founded Amperity to create a tool that would give marketers and analysts access to accurate, consistent and comprehensive customer data. As CTO, he leads the company’s product, engineering, operations and information security teams to deliver on Amperity’s mission of helping people use data to serve customers. Prior to Amperity, Derek was on the founding team at Appature and held engineering leadership positions at various business and consumer-facing startups, focusing on large-scale distributed systems and security.
