McFadyen Digital · Case Studies
Real-world AI in Commerce
205 documented AI implementations across commerce — filterable by industry, value chain, technology, and outcome. Every entry is sourced and quantified where the data exists.
- 205
- Implementations
- 12
- Industries
- 16
- AI technologies
A global lifestyle player deploys a generative AI shopping assistant and lifts conversion rates by up to 20%
A global lifestyle and beauty brand deployed a gen-AI-powered LLM shopping assistant trained on product data and consumer preferences — achieving up to a 20% lift in conversion rates, reported in a McKinsey analysis of gen AI in the beauty sector.
AWS-powered Virtual Engineering Workbench cuts automotive test-case creation time by up to 80% using Amazon Bedrock
An AWS Professional Services team integrated Amazon Bedrock into the Virtual Engineering Workbench (VEW) for automotive software testing, reducing test-case creation time by up to 80% while maintaining accuracy through a human-in-the-loop approach. The solution was implemented in production in four weeks.
Microsoft automates end-to-end bug triage with two AI agents in Azure DevOps, reducing time from identification to resolution
Microsoft built and published an Auto Triage AI solution using Copilot Studio and Azure DevOps, using two autonomous agents to extract bug details from customer emails, generate reproduction steps, create bug records, and post follow-up updates automatically.
ASDA scales mobile test coverage by 50% and cuts manual testing effort by 70% with Perfecto AI
UK supermarket giant ASDA adopted Perfecto AI's cloud-based testing platform to automate mobile and web testing across its ecommerce site, mobile app, Scan & Go, and Rewards apps — achieving a 50% increase in test coverage, 70% reduction in manual testing effort, and a 4x expansion in device and OS coverage.
Bestseller builds 110 automated test cases in 3 months with Leapwork, democratizing QA across fashion brands
Denmark-based fashion group Bestseller implemented Leapwork's low-code test automation platform, enabling functional business users to create and maintain test flows across Dynamics 365, POS, and e-commerce systems — without relying exclusively on technical staff.
Deutsche Bank cuts test data provisioning time 80% with synthetic data for ESG onboarding
Deutsche Bank's Credit Risk Technology team adopted the Synthesized platform to generate high-fidelity, privacy-safe test data for ESG onboarding workflows, cutting data access delays dramatically and embedding synthetic data into CI/CD pipelines.
NVIDIA's Hephaestus framework saves pilot teams up to 10 weeks of development time with AI-generated tests
NVIDIA's DriveOS team built Hephaestus (HEPH), an internal generative AI framework that automates test-case creation from software architecture and interface control documents, saving pilot teams up to 10 weeks of development time per engagement.
Auchan unifies web and mobile testing with Katalon to accelerate e-commerce DevOps delivery
French multinational retailer Auchan adopted the Katalon platform including Runtime Engine, TestCloud, and TestOps to automate web and mobile testing across browsers and devices, reducing manual regression work and improving release reliability for its e-commerce and order management systems.
Walmart deploys AI/ML forecasting across 4,700 stores to prevent holiday stockouts and supply chain disruptions
Walmart's centralized AI/ML inventory platform analyzes demand at the individual item-store-day level, enabling proactive replenishment, geographic redistribution of inventory, and anomaly 'forgetting' to avoid over-correcting on one-time events.
eBay scales 8 petabytes of production data into 1 GB de-identified test subsets with Tonic.ai, unblocking automated testing
eBay's 8-PB distributed data ecosystem made staging unreliable and automated testing expensive. Using Tonic.ai's subsetting and de-identification platform, eBay provisioned privacy-safe 1 GB subsets across ten critical domains — shortening development cycles and increasing automation pass rates.
Microsoft's flaky test management system spans 100 product teams, flags 49,000 flaky tests, and prevents 160,000 unnecessary session failures
Microsoft built a company-wide flaky test management service — embedded in CloudBuild and CloudTest — that supports over 100 product teams, has identified approximately 49,000 flaky tests, and has prevented more than 160,000 test sessions from failing unnecessarily, dramatically improving developer productivity across its global engineering organization.
Netflix's Pensive system auto-diagnoses and remediates failed big-data jobs across hundreds of thousands of daily workflows
Netflix's AI-driven Pensive platform uses a rules engine augmented by ML clustering to classify and automatically fix failed batch and streaming data jobs — reducing manual operational burden across the world's largest cloud-based streaming data platform.
Slack's Project Cornflake cuts flaky test job failures from 56.8% to 3.9% and saves 553 hours of triage time
Slack's Mobile Developer Experience team built an automated flaky test detection and suppression system — Project Cornflake — that reduced test job failure rates from 56.76% to 3.85% in under a year, saving 553 hours of manual triage time across Android and iOS mobile codebases with 27,000+ automated tests.
eBay scales 8 PB data ecosystem to 1 GB test subsets with Tonic.ai, accelerating release velocity
eBay used Tonic.ai's synthetic data and subsetting platform to give developers on-demand access to production-like test data, eliminating staging unreliability and fueling faster automated testing cycles.
GitHub reduces flaky builds by 18x — from 9% of commits to less than 0.5% — with automated detection and quarantine
GitHub built an internal flaky test management system for its Ruby on Rails monolith that reduced the percentage of commits with at least one flaky build from approximately 9% (1 in 11 commits) to less than 0.5% (1 in 200), an 18x improvement, by automatically detecting, containing, and delegating flaky failures to the engineers who introduced them.
Meta's predictive test selection captures 99.9% of regressions while running only one-third of tests, doubling infrastructure efficiency
Meta (formerly Facebook) deployed a machine-learning predictive test selection system that catches more than 99.9% of regressions before they reach the trunk, while running just a third of all dependent tests — halving testing infrastructure costs.
Gymshark's 8-hour Black Friday crash cost £100,000 and forced a full ecommerce replatform to Shopify Plus
After its Adobe Commerce site collapsed under Black Friday traffic in 2015, fitness apparel brand Gymshark migrated to Shopify Plus — reaching £41 million in annual sales by 2017 and processing thousands of orders per minute without an outage.