What challenges did Coles face before AI implementation?

Manual produce selection and checkout processes resulted in long wait times and inconvenience for shoppers. Customers commonly abandoned purchases at deli counters if not served promptly (within 20–40 seconds). Existing solutions for managing store AI workloads were isolated and site-specific, lacking a unified approach. The highly dispersed nature of Coles’ operations across 1,800 sites challenged centralized data and AI management.

What was the impact of the AI solution?

Significantly reduced checkout wait times via automated produce recognition. Decreased incidence of abandoned deli counter purchases through timely staff alerts. Elevated overall customer satisfaction and operational efficiency. Enabled unified, scalable edge AI management across over 1,800 store sites.

Source

MicrosoftExpandedProductionEvidence: Medium55/100

Coles transforms in-store experience and efficiency through AI-powered edge platform

Use case typeLivestock monitoringUpdated Jun 13, 2026

Coles, a leading Australian supermarket chain, implemented an innovative digital platform to unify AI workload management and enhance the retail customer experience. Using Microsoft Azure Stack HCI and Azure AI with NVIDIA GPUs, Coles introduced Computer Vision for high-accuracy produce recognition at checkout and queue monitoring at deli counters. The company developed the Intelligent Edge Backbone (IEB) platform to centralize data, orchestrate AI workloads, and deliver real-time event notifications to staff across its extensive network of over 1,800 stores. This system streamlines checkout, reduces customer wait times, and improves operational efficiency in a way that is privacy-conscious—ensuring the technology does not identify individuals or collect personal data. The initiative is described as a global-first for retail, enabling immediate actions like staff alerts or system notifications to improve service readiness and customer satisfaction.

Organization: Coles
Industry: Retail
Location: Australia
Published: March 2024

Reported outcomes

Strategic outcomes

New product / capabilityAutomated produce recognition at checkoutCustomer experience & trustReduced checkout wait timesCustomer experience & trustReduced abandoned deli purchasesScale & capacityUnified edge AI across stores

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: Coles
Provider: Microsoft
Maturity: Production
Linked source: news.microsoft.com

This system streamlines checkout, reduces customer wait times, and improves operational efficiency in a way that is privacy-conscious—ensuring the technology does not identify individuals or collect personal data

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 3 of 3

1Automated Produce Recognition at Checkout
2Real-Time Queue Monitoring for Deli Counters
3Centralized Edge AI Workload Management

Manual produce selection and checkout processes resulted in long wait times and inconvenience for shoppers.
Customers commonly abandoned purchases at deli counters if not served promptly (within 20–40 seconds).
Existing solutions for managing store AI workloads were isolated and site-specific, lacking a unified approach.
The highly dispersed nature of Coles’ operations across 1,800 sites challenged centralized data and AI management.

Developed and deployed the Intelligent Edge Backbone (IEB) utilizing Microsoft Azure Stack HCI, Azure AI, and ML.
Used NVIDIA A16 GPUs for high-efficiency AI workload execution across many retail locations.
Implemented Computer Vision at checkout for automated produce recognition and at deli counters for real-time queue monitoring.
Delivered real-time event notifications to staff via connected systems and devices, orchestrated centrally.

Technologies

Azure AI Azure Stack HCI Azure ML Computer Vision NVIDIA GPUs

Significantly reduced checkout wait times via automated produce recognition.
Decreased incidence of abandoned deli counter purchases through timely staff alerts.
Elevated overall customer satisfaction and operational efficiency.
Enabled unified, scalable edge AI management across over 1,800 store sites.

Architecture

Coles’ Intelligent Edge Backbone (IEB) uses Microsoft Azure Stack HCI and Azure AI to centralize management of AI workloads across 1,800+ retail sites. Computer Vision models operate locally for checkout and queue monitoring. Event data is sent through the backbone to notify staff or systems in real time, creating a unified and responsive operations environment.

Sources & evidence1

Evidence: Medium55/100Evidence strength