This revised feature reorganises the main retail details in JLL and “Algorithmic Foot Traffic”: How AI Agents Could Reshape Shopping Centres for clearer reading while preserving the original information.

Updated and fact-checked: JLL’s 2026 analysis is better described as “agentic commerce” than a literal claim that algorithms will control every mall visit. The idea is that AI shopping agents may increasingly research, compare and purchase for consumers, changing which stores and centres receive demand.

What agentic commerce changes

Traditional e-commerce still requires a person to search, compare and click. Agentic commerce moves more of that process to software: a user can state a goal, budget and constraints, then allow an AI assistant to identify options or potentially complete the transaction. If that behaviour becomes common, retailers will have to serve two audiences at once — the human shopper and the software agent acting on the shopper’s behalf.

That affects product data, stock accuracy, delivery information and reputation signals. A retailer with incomplete or inconsistent data may be invisible to an AI assistant even if its physical store is attractive.

Why physical shopping centres can still benefit

JLL’s argument is not that AI eliminates stores. Transactional purchases may become more automated, which could make social, entertainment, food and service-based reasons for visiting a centre more important. Centres that function as destinations — with restaurants, events, leisure and brand experiences — offer something an autonomous purchasing agent cannot replicate.

This is similar to earlier retail shifts. E-commerce reduced the need to visit a shop for every purchase, but strong centres adapted by changing tenant mixes and investing in experience. Agentic commerce could accelerate that division between places that are merely collections of shops and places people choose to spend time.

What “algorithmic foot traffic” really means

The phrase is useful as a metaphor: software recommendations may increasingly influence where people go, which brands they discover and whether a trip is worthwhile. A shopping assistant could recommend a centre because several requested products are in stock there, because a service appointment is available, or because the trip can combine shopping with food or entertainment.

For centre owners, that increases the value of real-time data and digital visibility. For shoppers, it could make trips more efficient. The risk is that the biggest platforms become powerful gatekeepers, which makes transparency, competition and privacy important policy questions.

Sources checked

The global retail landscape is undergoing a profound transformation. From the rise of e-commerce to the emergence of AI-driven shopping assistants, consumer behavior has continuously evolved. Now, according to new insights from JLL, shopping centres are entering a new era—one defined by algorithmic foot traffic.

This shift represents more than just technological advancement. It signals a structural change in how consumers discover, choose, and physically visit retail destinations. In this in-depth article, we explore what algorithmic foot traffic means, how it will reshape shopping centres, and why it could redefine the future of retail globally.

What Is Algorithmic Foot Traffic?

Algorithmic foot traffic refers to a future where artificial intelligence systems influence or directly determine where consumers shop physically. Instead of humans browsing stores or even websites, AI-powered agents—often called shopping assistants—will make purchasing decisions and recommendations.

According to JLL analysis, AI-driven recommendations will increasingly dictate where consumers go, effectively shifting the source of foot traffic from human impulse to machine logic.

This concept builds on the broader trend of agentic commerce (A-commerce)—where AI systems handle product discovery, comparison, and purchasing on behalf of users.

The Evolution of Retail: From Footfall to Data Flow

️ Traditional Foot Traffic

Historically, shopping centres relied on:

  • Location (high streets, malls)
  • Anchor tenants (department stores)
  • Promotions and events
  • Seasonal demand

Foot traffic was largely organic and human-driven.

The E-commerce Shift

The rise of online shopping changed everything:

  • Consumers began browsing digitally
  • Price comparison became easier
  • Convenience overtook location

Yet, physical retail survived by adapting—focusing on experience and convenience.

Enter Algorithmic Retail

Now, AI is set to redefine the journey again:

  • AI assistants search, compare, and purchase
  • Recommendations are personalised and automated
  • Physical store visits may be influenced by algorithms

This is where algorithmic foot traffic comes in.

How AI Will Drive Physical Store Visits

1. AI as the New Gatekeeper

In the near future, consumers may say:

“Buy me the best running shoes under £100.”

Instead of browsing stores, an AI agent will:

  • Compare products across retailers
  • Select the best option
  • Decide whether to buy online or direct the user to a store

This means AI becomes the gatekeeper of retail demand.

2. Discovery Shifts from SEO to AEO

Retailers have long optimised for search engines (SEO).
Now, they must optimise for AI recommendation systems, known as:

Agentic Engine Optimisation (AEO)

This includes:

  • Structured product data
  • Real-time pricing
  • Availability signals
  • Trust and reputation metrics

Shopping centres will need to integrate these signals into their ecosystems.

3. Algorithmic Routing of Consumers

AI systems could:

  • Recommend specific malls or retail districts
  • Suggest stores based on preferences and proximity
  • Optimise shopping routes for efficiency

In this model, foot traffic is no longer random—it is engineered.

Why Shopping Centres Will Still Thrive

Despite fears that AI could reduce physical retail, JLL argues the opposite:
shopping centres will remain highly relevant—but only if they evolve.

The Rise of Experiential Retail

AI can handle transactional shopping, but it cannot replicate:

  • Social experiences
  • Entertainment
  • Dining
  • Community interaction

JLL notes that modern retail centres are becoming:

“Community Engagement and Entertainment Centres.”

Experience vs. Efficiency

Aspect AI Commerce Physical Retail
Speed High Moderate
Convenience High Moderate
Experience Low High
Social Interaction None Strong

The future lies in blending both worlds.

The “Destination” Model

Shopping centres are evolving into destinations offering:

  • Cinemas and events
  • Food courts and fine dining
  • Fitness and wellness spaces
  • Interactive brand experiences

These elements are immune to algorithmic automation.

Investment Trends: Confidence in Retail Property

Despite technological disruption, investment in retail centres is strong.

  • Australia saw $14 billion in retail property transactions recently
  • Europe is experiencing increased leasing activity and store openings
  • The UK market is projected to hit a 10-year investment high in 2026

This indicates that:
Investors believe physical retail will adapt, not disappear

Challenges of Algorithmic Foot Traffic

While promising, this shift comes with challenges.

️ 1. Loss of Customer Data

If AI agents handle transactions:

  • Retailers may lose direct customer relationships
  • Email and loyalty data could disappear

This weakens traditional CRM strategies.

2. Privacy and Trust Issues

Consumers may hesitate to:

  • Share financial data with AI
  • Allow algorithms to make purchasing decisions

Trust will be a key adoption factor.

3. Impact on Secondary Retail Centres

Not all shopping centres will benefit equally.

  • Prime, experience-driven centres will thrive
  • Secondary centres may struggle if:
    • AI prioritises convenience
    • Foot traffic becomes concentrated

4. Reduced Impulse Buying

AI removes friction—but also spontaneity.

Traditional retail thrives on:

  • Window shopping
  • Impulse purchases

Algorithmic shopping may reduce these behaviors.

Opportunities for Retailers and Developers

1. Smart Retail Infrastructure

Shopping centres can integrate:

  • AI-driven analytics
  • Real-time foot traffic data
  • Predictive demand modelling

This creates smarter retail environments.

2. Omnichannel Integration

Retailers must unify:

  • Online platforms
  • AI assistants
  • Physical stores

This ensures seamless customer journeys.

3. Personalised Experiences

Using data, centres can offer:

  • Tailored promotions
  • Custom in-store experiences
  • Dynamic layouts

4. Partnerships with Tech Platforms

Collaboration with:

  • Fintech companies
  • AI platforms
  • Logistics providers

will be essential to remain competitive.

The Future of Shopping Centres in an AI World

Scenario 1: AI-Driven Mall Visits

AI assistants could:

  • Plan entire shopping trips
  • Recommend stores within a mall
  • Schedule visits during low-traffic times

Scenario 2: Hybrid Shopping Journeys

A typical journey might look like:

  1. AI recommends a product
  2. User visits a store to تجربة (experience)
  3. Purchase happens via app or AI

Scenario 3: Global Retail Ecosystems

Retail becomes:

  • Data-driven
  • Globally connected
  • Hyper-personalised

Shopping centres become nodes in this ecosystem.

Final Thoughts

The concept of algorithmic foot traffic marks a turning point in retail history. As AI begins to influence not just what we buy—but where we go to buy it—shopping centres must adapt or risk irrelevance.

Yet, the outlook is far from bleak.

Physical retail is not dying—it is evolving into something more human, more experiential, and more integrated with technology than ever before.

The winners in this new era will be those who:

  • Embrace AI rather than resist it
  • Invest in experiences rather than transactions
  • Understand that the future of retail is both digital and physical

Conclusion

Shopping centres are entering a new age—one where algorithms guide footsteps, data shapes decisions, and experiences define success.

As highlighted in the JLL report published on 7 April 2026, the retail sector is not being replaced by AI—it is being reimagined.

What this means for shoppers

Retail stories are most useful when they distinguish between a temporary trend and a structural change. Viral videos can create sudden queues, while insolvency news can affect refunds and warranties, and AI-driven discovery can change how shoppers find stores. None of those developments automatically tells a consumer whether a purchase is good value.

Shoppers should still compare prices, read return terms, check the identity of the seller and keep proof of purchase. When a story is driven by social-media popularity, it is sensible to treat virality as a discovery signal rather than evidence of product quality. When a company is in administration, official administrator notices are more reliable than promotional posts.