What challenges did Legal & General face before AI implementation?

Automate document classification and data extraction at scale. Improve customer experiences with generative AI. Reduce the carbon footprint of application workloads while improving operational efficiency.

What was the impact of the AI solution?

The company can process thousands of documents concurrently in 30 minutes. The automation freed up five employees for higher-value work. The company is learning how to manage, train, and maintain ML models for future generative AI use cases.

Source

Scaled productionEvidence: Medium65/100

Legal & General Sustainably Transforms Operational Efficiency with Generative AI on AWS

Use case typeIntelligent document processingUpdated Jun 13, 2026

Legal & General Retail (L&G Retail), part of the UK financial services group Legal & General, uses generative AI on AWS to improve customer experiences and automate document processing. The company also applies the AWS Well-Architected Framework Sustainability Pillar to reduce the carbon footprint of its applications.

Organization: Legal & General
Industry: Insurance
Location: United Kingdom
Published: May 2026

Reported outcomes

Time: 30 minutes

Time & speed

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Time: 30 minutes

AWSMay 13, 2026Case studyInferred claimMedium evidence strength

The company can process thousands of documents concurrently in 30 minutes.

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

Customer: Legal & General, L&G Retail
Provider: AWS
Maturity: Scaled Production
Linked source: AWS

Automate document classification and data extraction at scale

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 3 of 3

1Document Processing Automation
2Customer Service Enhancement
3Sustainability Optimization

L&G Retail built on AWS to automate document processing, including classification and data extraction.
The company used machine learning capabilities for document management and expanded into generative AI on AWS for new customer-focused use cases.
It applied the AWS Well-Architected Framework Sustainability Pillar to assess and improve the sustainability posture of its applications.

Technologies

AWS Generative AI Machine Learning AWS Well-Architected Framework AWS Well-Architected Framework Sustainability Pillar

The company can process thousands of documents concurrently in 30 minutes.
The automation freed up five employees for higher-value work.
The company is learning how to manage, train, and maintain ML models for future generative AI use cases.

Sources & evidence1

Evidence: Medium65/100Evidence strength