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How AI Personalisation Is Quietly Running Black Friday — And Reshaping Retail’s Biggest Shopping Event

25 November 2025

Black Friday is no longer just a massive sales day. It has become the ultimate real-time test environment for AI personalisation, recommendation engines, and predictive retail systems. As global retailers compete for customer attention, the winners increasingly rely on AI-driven shopping experiences to convert, retain, and satisfy millions of shoppers under extreme pressure.

In 2024, Black Friday quietly evolved into retail’s largest AI experiment — a moment when generative AI, dynamic pricing algorithms, and real-time personalisation models perform at unprecedented scale.

Below, we break down how major retailers like Walmart and Marks & Spencer are using AI during peak shopping season, and why Black Friday has become a turning point for the future of e-commerce.

Why AI Personalisation Is Redefining Black Friday

Black Friday used to be about deep discounts. Today, it’s about AI-driven customer experience.

Three forces are shaping the shift:

  • Massive traffic spikes accelerate machine-learning model training

  • Shoppers behave differently than during the rest of the year

  • Retailers rely on predictive and generative AI to compete on speed, relevance, and convenience

Black Friday now serves as a live stress test for the AI infrastructure powering modern retail: recommendation engines, search personalisation, dynamic pricing, and real-time optimisation.

Walmart’s AI Assistant “Sparky” Shows Where Retail Is Headed

In 2024, Walmart showcased one of the most advanced examples of AI personalisation in retail with Sparky, its generative-AI shopping assistant. Sparky uses Walmart’s massive first-party dataset to:

  • Help customers discover products

  • Generate personalised shopping ideas

  • Compare options

  • Guide decision-making

During Black Friday, these capabilities become critical. Millions of shoppers search across broad categories simultaneously. Sparky reduces friction by delivering hyper-targeted product suggestions and contextual guidance in real time.

Walmart’s approach highlights a shift across retail:
AI personalisation is becoming conversational, predictive, and deeply integrated into peak shopping experiences.

M&S Uses AI to Power Hyper-Personalised Clothing Recommendations

Marks & Spencer offers another real-world example of AI’s role in modern retail. Earlier this year, M&S deployed an AI style advisor that:

  • Analyses body shape

  • Matches lifestyle preferences

  • Recommends outfits from millions of combinations

During Black Friday — when choice overload is most acute — this system helps customers navigate rapidly changing product availability and promotions.

This is the new face of AI-driven fashion personalisation:
subtle, useful, and tailored precisely to the customer’s purchase intent, even under heavy holiday traffic.

Black Friday Has Become Retail’s High-Velocity AI Training Ground

There is no other moment in the retail calendar when AI systems learn as fast.

1. Traffic volumes accelerate model improvement

Black Friday compresses weeks of behavioural data into hours:

  • Click streams surge

  • Search queries spike

  • A/B tests reach significance rapidly

  • Browsing patterns evolve minute-by-minute

For retail data scientists, this is machine-learning harvest season — the period when models recalibrate with unprecedented accuracy.

2. Recommendation engines undergo peak stress

Product discovery is where personalisation makes or breaks the customer experience during Black Friday. AI systems must:

  • Predict intent instantly

  • Reorder product grids dynamically

  • Serve relevant results for vague or high-volume search terms

  • Avoid latency or poor suggestions

If recommendations slow down by even milliseconds, conversion drops and basket sizes collapse.

3. Black Friday behaviour is unique — and AI must adapt

Shoppers behave differently than during the rest of the year:

  • More price-sensitive

  • Faster to compare retailers

  • More curious about new brands

  • More likely to buy for others

  • More responsive to urgency and scarcity

AI models trained on “normal” shopping patterns must adjust in real time. Only the most robust systems succeed.

Dynamic Pricing and Reinforcement Learning Take Over Black Friday

AI-powered pricing engines now influence a growing share of discounts during Black Friday.

Retailers deploy reinforcement learning models to:

  • Determine optimal discount depth

  • Personalise incentives by segment

  • Create dynamic bundles

  • Protect margins hour-by-hour

Peak shopping season is uniquely suited for RL models because:

  • Consumer reactions are instant

  • Competitor prices move constantly

  • Profitability changes with every surge

In effect, Black Friday has become the Super Bowl of dynamic pricing AI.

AI Helps Predict — and Reduce — Black Friday Returns

Returns are one of the biggest profit killers in retail, especially after Black Friday.

AI models are increasingly used to:

  • Flag high-return-risk items

  • Improve size recommendations

  • Identify patterns behind bad product-fit experiences

  • Detect potential quality issues

  • Reduce fraudulent returns

Peak season gives these models the volume they need to improve dramatically.
A single weekend provides more real-world product feedback than an entire quarter.

AI Personalisation You Don’t See: Hidden Algorithms Running the Shopping Journey

During Black Friday, many of the most effective AI systems are invisible. They quietly optimise:

  • Homepage layouts

  • Category navigation

  • Search accuracy

  • Product descriptions

  • Delivery promise windows

  • Checkout flows

  • Payment options

Two shoppers visiting the same retailer’s website may experience entirely different journeys — from product sorting to fulfilment options — all powered by real-time AI personalisation.

This is the new normal for AI-driven e-commerce.

Industry Data Confirms the Shift: AI Is Now Central to Black Friday Strategy

E-commerce and retail platforms including Bloomreach, Shopify, Salesforce Commerce Cloud and others reported that heading into Black Friday 2024:

  • Retailers were significantly increasing their investment in AI for search, recommendations, and personalisation

  • More than half of customers expected AI assistance for holiday shopping

  • “Gift finder” AI tools rose in popularity

  • Personalised discovery improved conversion rates

  • Inventory prediction models improved fulfilment accuracy

The message is clear:
AI personalisation has become the competitive edge in peak shopping season.

Inside the AI War Room: How Retailers Manage Black Friday in Real Time

During Black Friday, many major brands effectively run “AI war rooms” where engineers and data scientists monitor:

  • Model latency

  • Personalisation errors

  • Search performance

  • Inventory prediction accuracy

  • Pricing engine behaviour

  • Real-time traffic surges

  • A/B test outcomes

If a recommender model collapses or a pricing engine miscalculates, millions of dollars can be lost in minutes.

This is why Black Friday is a defining moment for retail AI resilience.

The Future of AI Personalisation Beyond Black Friday

Based on the pace of innovation across retail, the next stages of AI personalisation will include:

  • Conversational shopping experiences (Walmart is already leading)

  • Generative AI-driven product discovery

  • Unified customer profiles across stores and apps

  • Predictive delivery and fulfilment

  • Regulation-driven transparency in personalisation

  • Autonomous retail systems that optimise themselves

And Black Friday will continue to be the largest annual testing ground for these innovations.

It’s All About Intelligent Retail

Behind every sale, countdown timer, and product recommendation is a complex mesh of AI systems.

For consumers, Black Friday seems chaotic.
For retailers, it has become a precise and orchestrated AI-driven operation.

The retailers that perform best aren’t the ones with the deepest discounts —
but the ones with the most effective AI personalisation engines.

And the insights gained during those 48 hours will shape the next year of e-commerce.