The AI Fluency Gap: Why Retail’s Next Competitive Advantage Lies Beyond Generative AI

The retail industry has never been more fluent in artificial intelligence, and yet, never more limited by it. Most retail leaders can articulate the power of generative AI. They’ve seen chatbots draft marketing copy, image tools design product listings, and data models predict seasonal demand. But ask those same teams how AI could bridge online and offline engagement or automate loyalty through first-party data, and the conversation often trails off.

This “AI fluency gap” isn’t about intelligence; it’s about connection. It reflects the distance between knowing what AI can generate and understanding how it can orchestrate experiences that unify every physical and digital signal to deliver real, measurable impact.

The Cost of Fragmented Fluency

Retailers that stop short at surface-level AI adoption are leaving significant revenue on the table. Consider the average brand that spends millions on digital ads yet fails to capture who actually engages in-store or through packaging. Data from McKinsey shows that firms leveraging a single customer view — one unified, cross-channel customer profile — see a 15 percent increase in revenue and 20 percent higher customer retention.

The economic loss of failing to activate offline signals is harder to measure but easier to feel. When physical interactions go unrecorded, brands miss crucial opportunities for retention, replenishment, and advocacy. It’s not that they lack data; it’s that the data lives in silos, which is separated by channels, departments and outdated systems.

A Maturity Curve for AI in Retail

Most retailers today fall somewhere along a three-phase maturity curve:

1. Experimentation: Testing generative AI tools in isolated departments (e.g., marketing or creative).
2. Fragmented Adoption: Deploying multiple models across different systems without integration or oversight.
3. Connected Fluency: Building an AI-powered customer journey that bridges digital engagement, in-store experience, and product-level insights.

Reaching the third phase doesn’t require a massive overhaul. It starts with connecting what already exists, including linking point-of-sale data with loyalty platforms, embedding unique digital identifiers on packaging, and ensuring every product interaction feeds back into the customer record.

What 'Connected Fluency' Looks Like

True AI fluency isn’t about using the most advanced model. It’s about enabling intelligence to flow freely between customer touchpoints. Imagine a world where a consumer scans a product, receives a personalized tutorial, joins a rewards program, and triggers predictive replenishment, all without switching devices or channels. That’s connected fluency in action: frictionless, data-informed, and mutually rewarding.

It also redefines loyalty. When customers feel recognized and supported at every step, whether they’re shopping in-store, online, or through social, the result isn’t just retention, but advocacy.

Bridging the Gap

Retail leaders can start closing the AI fluency gap today by focusing on three immediate priorities:

• Integrate first-party data early. Treat every consumer interaction as a potential data touchpoint.
• Automate loyalty activation. Use AI to recognize and reward behavior across all channels.
• Educate across teams. Build a shared understanding of how AI connects marketing, operations, and customer experience.

AI will continue to redefine what’s possible in retail. However, the winners won’t be those that use AI to create more content; they’ll be the ones that use it to create more connection.

Kait Stephens is the CEO and co-founder of Brij, an AI-powered software platform that bridges the gap between offline and online channels for omnichannel brands.