What challenges did Avery Dennison face before AI implementation?

Avery Dennison needed to reduce the cost of scaling translation across the enterprise. The company wanted to expand self-service document translation while preserving layouts and formatting for common enterprise document types. It also needed a workflow that allowed human review and post-edit feedback for improving translation quality.

What was the impact of the AI solution?

In three months, Avery Dennison increased translated page count by 700%. Translation cost was reduced by 90%. Employees gained on-demand access to general-purpose and company-specific translations, improving inclusion and enabling native-language expression.

Source

GCP

Avery Dennison: AI translation self-service using Translation Hub, AutoML, and human-in-the-loop feedback

Use case typeWorkflow automationUpdated Jun 13, 2026

Avery Dennison, a materials science company, used Google Cloud Translation Hub to provide employees with self-service document translation across many languages. The implementation was designed to reduce translation costs, preserve document formatting, and support human-in-the-loop post-editing feedback for company and general-purpose translations.

Organization: Avery Dennison
Industry: Consumer & Food
Location: United States
Published: October 2022

Reported outcomes

+700%

quantified impactOther quantified impact

−90%cost

Strategic outcomes

Scale & capacityScaled enterprise translation self-serviceNew product / capabilityPreserved document layout and formattingEmployee experienceEnabled on-demand native-language expressionCost efficiencyReduced translation scaling costs

Primary read

Use case focus

Showing 3 of 3

1Document Translation
2Employee Experience
3Workflow Automation

Avery Dennison needed to reduce the cost of scaling translation across the enterprise.
The company wanted to expand self-service document translation while preserving layouts and formatting for common enterprise document types.
It also needed a workflow that allowed human review and post-edit feedback for improving translation quality.

Avery Dennison implemented Google Cloud Translation Hub as an enterprise-scale translation AI agent.
The solution used Google Cloud AI technology including Neural Machine Translation and AutoML translation models.
It supported self-service translation of Google Docs, Slides, PDFs, and Microsoft Word files while preserving layout and formatting.
The workflow included granular management controls for post-editing human-in-the-loop feedback and document review.

Technologies

Google Cloud Translation Hub AutoML Neural Machine Translation Document AI

In three months, Avery Dennison increased translated page count by 700%.
Translation cost was reduced by 90%.
Employees gained on-demand access to general-purpose and company-specific translations, improving inclusion and enabling native-language expression.

Sources & evidence1

Groundedness: 5/5

Primary source

AI-generated summary. Verify important details with the linked sources before relying on this case.

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Customer evidence