Scaling Accessibility Compliance with AI-Augmented Content Workflows
A Renegade Proof-of-Value sprint testing how AI can safely augment content operations.
Impact from the Proof-of-Value Sprint
Faster workflows
Accessibility issues identified earlier in the authoring process.
Greater coverage
Editorial teams able to review more content within the same time.
Improved consistency
Accessibility standards applied more consistently across pages.
AI did not replace editorial judgement
Gave the teams the ability to maintain compliance and quality at scale.
Context
A large European government organisation supporting €36bn of international exports annually.
Its website ecosystem plays a critical role in delivering trusted information about programmes, funding and services to businesses around the world.
This work explores how AI can support digital teams while maintaining the governance and quality required of an international organisation.
A Proof-of-Value (PoV) sprint is a structured six-week method for testing how AI can augment real workflows in a controlled enterprise environment.
Rather than attempting large-scale transformation immediately, the PoV approach focuses on one workflow, one team and one site, generating practical learning that can later scale across the organisation.
The first use case focuses on accessibility compliance on one core website.
DISCOVER
Understand the workflow and define the use case.
DESIGN
Create AI playbooks, prompts and governance
checkpoints.
TEST
Run the workflow with real editorial teams and real content.
REFINE
Measure results, capture learning and build a knowledge bank.
SCALE
Replicate the model for additional workflows and sites.
The Challenge
Accessibility compliance is a legal requirement for public sector organisations.
It’s also a complex operational task. Editorial teams must be sure that every page meets accessibility standards while maintaining speed and consistency across a large web estate.
Accessibility also plays an increasingly important role in AI visibility and trust.
AI systems interpret and summarise web content on behalf of users. Content that is clearly structured and accessible is easier for machines to understand, interpret and cite.
This means accessibility is no longer only a compliance requirement.It’s also a signal of trust and clarity in AI-mediated discovery environments.
Two core objectives:
Maintain legal accessibility compliance
Improve consistency and scalability of accessibility checks across editorial workflows
The Renegade Approach
Our Proof-of-Value sprint method is used to explore how AI could support accessibility compliance in practice.
Rather than deploying technology first, the initial focus is on redesigning the workflow itself.
Working alongside client editorial teams, we:
Analyse how accessibility compliance currently happens in practice
Identify friction points and manual effort in the workflow
Redesign the workflow to combine AI assistance with human governance
Configuring AI for the Workflow
Using the KIO AI assistant inside the CoreMedia Content Management Platform, the first step is to train and configure the tools for the specific web environment, before moving on to use case specific playbooks.
Configuration and system training:
Training the assistant on the organisation’s CMS implementation
Creating prompts tailored to Enterprise Ireland content structures
Designing AI playbooks for accessibility review
Testing and refining outputs with real editors and real content
Editors worked with the system inside their normal CMS environment, allowing the workflow to be tested under real operational conditions.
Learning by Doing
A key goal of PoV sprints is hands-on learning. Editors were trained while working with the new workflow, building practical understanding of how AI can assist their work.
The project generated a growing knowledge bank including:
Prompt libraries
Workflow playbooks
Governance patterns
Lessons learned from the sprint
This knowledge remains within the organisation and forms the foundation for future AI workflow use cases.
Outcome
The work demonstrated how AI can augment accessibility workflows safely and effectively.
The project delivered:
Faster workflows
Accessibility issues identified earlier in the authoring process
Greater coverage
Editorial teams able to review more content within the same time
Improved consistency
Accessibility standards applied more consistently across pages
AI did not replace editorial judgement.
It strengthened the ability of teams to maintain compliance and quality at scale
From Pilot to Capability
The initial focus is intentionally on one workflow and one website.This allowed the client to explore AI augmentation safely while building internal knowledge and confidence.Once validated, the workflow model is replicated across additional sites and future AI use cases using the same Proof-of-Value sprint method.Over time, these individual use cases build towards a broader capability:AI-augmented content operations that remain governed, trusted and scalable
Andy Wood
Strategy Lead
Three decades of experience helping organisations navigate major technology shifts.
I can help you:
• Deliver next-generation digital experiences for customers
• Understand AI across business operations & customer experience
• Align enterprise technologies with operational & strategic goals
