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Home/Use Cases/Retail

AI for Retail & E-commerce

Connect in-store and digital data into one intelligent experience — forecasting, personalisation, pricing, and service that lift conversion, margin, and loyalty.

The Landscape

The retailer that understands the customer — and the shelf — in real time.

Retail and e-commerce sit on an unusually rich and fragmented data estate: POS, e-commerce, CRM, inventory, supply chain, and a flood of customer signals across channels. The winners aren't the ones with the most data — they're the ones who turn it into the right product, at the right price, in stock, in front of the right customer.

That's a stack of decisions AI makes well: what demand will be by SKU and store, what to recommend to a given shopper, how to price and promote in response to demand and competitors, and how to keep inventory honest across store, warehouse, and online so you stop over- and under-selling. On the service side, conversational and agentic AI handle the high-volume questions, returns, and order changes that otherwise swamp support.

We build to connect those decisions rather than scatter point solutions — and with the guardrails personalisation and pricing require, so the experience feels helpful, not creepy, and stays within the rules.

High-Value Use Cases

Where AI pays off across retail.

Six high-value use cases, each mapped to the AdeptivIQ capability that powers it.

Predictive AI

Demand Forecasting & Replenishment

Predict demand by SKU, store, and channel and trigger replenishment before stockouts — balancing service levels against the cost of carrying inventory you don’t need.

  • Outcome — fewer stockouts and lost sales, with leaner working capital tied up in stock.
Predictive AI

Personalised Recommendations

Surface the right products from browsing, purchase, and intent signals — across the site, app, email, and support channels — so discovery feels tailored rather than generic.

  • Outcome — higher conversion, larger baskets, and stronger customer lifetime value.
Predictive + Agentic AI

Dynamic Pricing & Promotions

Evaluate demand, competitor prices, and margin targets to recommend or push price and promotion changes across channels — without waiting on a manual pricing cycle.

  • Outcome — protected margin and more responsive, competitive pricing.
Agentic AI

Omnichannel Inventory Visibility

Synchronise stock across store, warehouse, and online, and let an allocation agent decide how inventory is positioned and replenished across locations and demand.

  • Outcome — no more over- or under-selling, and smarter inventory placement.
Conversational AI

Conversational Shopping & Support

Guide shoppers through discovery and checkout, answer order and delivery questions, and handle standard returns and refunds end to end — around the clock.

  • Outcome — 24/7 self-service, higher conversion, and a lower cost to serve.
Computer Vision AI

Loss Prevention & Fraud

Monitor store and transaction behaviour for shrinkage and fraud signals — from checkout anomalies to geofencing patterns — and alert staff before losses mount.

  • Outcome — reduced shrinkage and fraud loss across stores and channels.
Featured Use Case

Personalisation, in depth.

A shopper with a full cart — AI personalising one customer across every channel
one customer,
every channel PREDICTIVE AI
ONE CUSTOMER, EVERY CHANNEL

One customer, understood across every channel

Most retailers personalise in fragments: the website has one recommendation engine, email has another, the store knows nothing about either, and pricing runs on its own cycle. The customer feels the seams — a discount on something they just bought, a recommendation that ignores their last visit.

We unify the signals into a single view of intent and act on it consistently: recommendations, offers, and pricing that draw on the same understanding of who the customer is and where they are in their journey, online and in store. Where a decision can be made in the moment — the next best offer, the right product to surface, a re-engagement campaign — an agent carries it out across channels.

The payoff is the experience customers actually reward: relevant, coherent, and timely — which shows up as conversion, basket size, and the kind of loyalty that survives the next competitor's promotion.

Recommendation enginesCustomer LTVDynamic pricingJourney orchestrationRe-engagement
Capabilities That Apply

The building blocks behind retail AI.

Each use case above is powered by one or more of our core capabilities.

Predictive AI

Forecasting, scoring, and pattern detection at scale.

Agentic AI

Agents that plan and act across your systems, with oversight.

Conversational AI

Chat and voice that resolve real customer needs.

Computer Vision AI

Inspection, detection, and visual decisions at scale.

Ready to put AI to work in retail?

Tell us where the opportunity is — forecasting, personalisation, pricing, service — and we'll map the fastest path to measurable impact. No jargon, no overselling.

Talk to us about retail AI →