Case Study #2: Christie’s

Engagement Snapshot

Engagement Role: Principal Digital Consultant / Product Lead

Sector: Luxury / Digital Commerce

Period: 2023–2026

Scope: AI-enabled content operations within the global digital ecosystem

Capabilities: AI Product, Workflow Automation, Responsible AI, Product Discovery, Governance, Adoption

Technology: Azure AI, Sitecore, human-in-the-loop workflow

Methodology

• Ran a structured Discovery: stakeholder interviews, workflow mapping, and data audit.

• Identified SEO metadata automation as a high-impact pilot for GenAI.

• Designed an Azure-based AI agent integrated with CMS workflow, trained to generate meta tags, meta descriptions and alt text from article or image input.

• Implemented human-in-the-loop editing for quality control.

Context

Global editorial and content teams were managing metadata-intensive workflows manually. The opportunity was not simply to add generative AI, but to identify where automation could remove repetitive effort without reducing editorial control, quality or accountability.

Challenge

AI-generated metadata had to work inside an established enterprise content workflow. The solution needed to produce useful outputs while supporting human review, GDPR, auditability, quality controls and operational adoption.

Engagement Mandate

EPOCS Global was engaged to shape and deliver the AI-enabled workflow, connecting editorial needs, CMS operations, governance requirements and measurable business value.

Approach & Delivery

Problem framing and discovery

• Mapped existing content and metadata workflows.

• Identified metadata automation as a high-value AI use case.

• Defined the operational outcome rather than treating AI adoption as an objective in itself.

Product and workflow design

• Designed an Azure AI metadata assistant integrated into editorial workflows.

• Embedded human-in-the-loop review so editors retained control over generated outputs.

• Defined acceptance, quality and operational controls around the workflow.

Responsible AI and governance

• Embedded GDPR, data governance, auditability and quality controls.

• Considered workflow and business-impact risk alongside model/output quality.

• Designed adoption around human oversight rather than full automation.

Broader AI roadmap

• Defined a GenAI roadmap for editorial tooling and workflow automation.

• Delivered AI-driven translation across 50+ languages for localisation and personalisation use cases.

Outcomes

• Metadata coverage increased from 65% to 98%

• Manual effort reduced by 70%

• Approximately 40 staff hours per week saved

• Established a governed pattern for human-supervised AI inside enterprise content operations

Why It Mattered

The value came from embedding AI into a real operating process with measurable time savings and clear human accountability. It demonstrated how AI could improve content operations without treating governance or editorial judgement as afterthoughts.

Capabilities

AI Product · GenAI · Human-in-the-Loop · Responsible AI · Workflow Automation · Product Discovery · Governance