The uncomfortable truth about physical retail in 2026

For decades, physical retail relied on a simple advantage: proximity.

If you were nearby, you were visible.If you were visible, you had a chance at footfall.

That logic is now broken.

Today, shoppers don’t start with streets, maps, or directories.They start with questions.

“Where can I buy running shoes right now?”“Is there a gift shop open near me?”“Which mall has sustainable fashion brands?”

And increasingly, those questions are answered by AI, not by search engines, maps, or signage.

Being nearby no longer guarantees being chosen.

Proximity has been replaced by answerability

AI assistants don’t “see” geography the way humans do.

They don’t walk past your storefront.They don’t notice your façade.They don’t explore.

They retrieve answers.

If a shopping centre or retailer can’t be clearly understood by AI systems — what stores exist, what they sell, what’s open, what’s relevant — they simply don’t appear in the answer.

From the shopper’s perspective, that location effectively doesn’t exist.

The new discovery funnel looks very different

Traditional funnel:

• Awareness → browsing → comparison → visit

AI-driven funnel:

• Intent → answer → action

This shift matters because:

• The shopper is already high-intent

• The list of options is short

• Visibility is binary: you’re in the answer, or you’re not

There is no “page two”.

Why shopping centres are especially vulnerable

Shopping centres face a structural disadvantage in the AI era:

• Tenant data is fragmented

• Product-level visibility is inconsistent

• Promotions change constantly

• Opening hours, services, and amenities are often outdated online

To AI systems, many centres are still black boxes — large physical destinations with no clear, structured understanding of what’s inside.

That’s where proximity fails.

Discovery is now a data problem, not a location problem

The centres and retailers that are winning footfall today share one thing:

They are machine-readable.

Their stores, products, services, and offers are structured in a way that AI systems can:

• Read

• Understand

• Reference

• Recommend

Platforms like Gonow Luma exist specifically to solve this gap — turning fragmented retail data into AI-ready discovery infrastructure so physical locations can appear naturally inside AI-generated answers, not just on maps. Gonow Luma — Product & Services…

But the broader insight matters even more than the tool.

What “being discoverable” really means now

For retailers and shopping centre owners, the new questions are:

• Can AI clearly understand what I sell, not just where I am?

• Can it match my offering to real shopper intent?

• Can it confidently recommend my location instead of another?

Footfall is no longer won at the entrance. It’s won before the shopper leaves home.

The strategic shift leaders are already making

Forward-looking centres are moving from:

• Marketing → infrastructure

• Visibility → answerability

• Maps → meaning

They’re treating AI discovery as a core retail channel, not a future experiment.

Because in an AI-first world, the front door to retail isn’t glass.

It’s a question.