Digital inclusion: raising the bar with AI and automation

With accessibility more important than ever, inclusive AI can help enterprises become proactive and scale solutions.

In an increasingly digital world, accessibility is more than a check-box compliance—it is a fundamental measure of user experience. It determines whether people of all abilities can navigate, interact with and benefit from your digital products and services. It reflects how deeply we design for inclusion and empathy. At its core, it is about ensuring that no user is left behind and that every experience is welcoming. As more of our learning, work and daily life shifts online, building accessible experiences isn’t just the right thing to do. It is a competitive edge and a shared responsibility.

Why digital accessibility matters more than ever

The world is increasingly digital, but not yet universally accessible. And that gap comes at a cost: to users, to businesses and to society at large.

• Over 1.3 billion people globally live with some form of disability, according to the World Health Organization.
  
  
• Research from Web Accessibility in Mind, or WebAIM, finds that 71% of users with disabilities abandon websites that are hard to use.
  
  
• Businesses are estimated to lose over $6.9 billion annually due to inaccessible websites, as customers with disabilities turn to more accessible competitors.
  
  
• Global regulations, from the European Accessibility Act to Section 508 of the Rehabilitation Act of 1973 in the U.S., are making inclusive design a legal and reputational imperative.

From acknowledgement to action

While the need for digital inclusion has long been widely acknowledged, the real challenge lies in scaling solutions effectively. Traditional methods were often slow, reactive and inconsistent and could not keep up with today’s pace of digital delivery. We needed a smarter way forward—one that could embed accessibility into the development process, ensuring faster detection, consistent validation and actionable insights at scale.

At Cognizant Moment, we responded to this challenge with a multi-stage strategy rooted in technology, empathy and innovation.

Wave 1: Laying the foundation with automation-first accessibility

The first step in our transformation journey was to build a strong, scalable foundation powered by intelligent automation. Our accessibility accelerator provided a platform to automate audits, validation and reporting by enabling:

• Automated full-page and component-level scans for early detection of accessibility issues
  
  
• Simulated keyboard navigation, mimicking human behavior to validate keyboard accessibility
  
  
• Accessibility violations categorized by severity and user impact, ensuring proper prioritization
  
  
• Integrated manual and automated reporting with real-time dashboards, reducing overhead and improving visibility

This foundational wave redefined accessibility assurance by transforming it from a reactive checkpoint to a proactive, programmatic capability.

Wave 2: Generative AI for smarter, contextual recommendations

While automation accelerated detection of issues, it lacked the contextual intelligence needed to guide meaningful action. Accessibility issues often lacked business context, and remediation guidance was either too technical or too generic. This is where gen AI redefined the game by evaluating experiences and generating tailored, actionable fixes. It enabled us to:

• Evaluate images for accessibility barriers and generate appropriate descriptions, alternative text or visual alternatives
  
  
• Generate transcripts and captions for audio and video content, supporting deaf and hard-of-hearing users
  
  
• Assess content hierarchies and layouts to identify areas that may overwhelm or confuse users with cognitive disabilities

This wave brought intelligent remediation into the workflow by shifting the focus from “what’s wrong” to “how to fix it meaningfully.”

Wave 3: Agentic AI for human-centric experience simulation

Automation and generative AI brought scalability and contextual intelligence to accessibility. While they addressed the “what” and “how” of accessibility issues, the “why it matters” was still missing. Today, we are taking a bold step forward by using AI agents to understand how users actually experience digital interactions, beyond what code alone can reveal.

We are actively piloting agentic AI solutions that simulate diverse user journeys and identify the gap between compliance and actual, lived experience. These intelligent agents are designed to replicate how users with different disabilities engage with digital content. Here are some examples:

• A low-vision persona navigating with screen magnifiers and contrast settings
  
  
• A user with limited dexterity relying entirely on keyboard navigation
  
  
• A neurodivergent user dealing with cognitive load or dense instructional content
  
  
• A color-blind persona interacting with charts and alerts on dashboards

Each simulation assesses digital journeys from an end-user perspective, providing insights on friction, confusion and failure points that traditional audits simply cannot detect. While this is an emerging capability, it marks our shift from merely measuring accessibility to actively experiencing it.

The Accessibility Innovation Lab: where ideas become impact

All these waves of innovation, automation, generative AI, and agentic AI, are fueled and validated by our Accessibility Innovation Lab. This is a space where:

• Teams experiment with assistive tech integrations to solve real-world problems
  
  
• Prototypes are tested with simulated and real users to ensure experiential alignment
  
  
• AI models are trained to evolve with user behavior and design trends

In short, by combining deep accessibility expertise with AI-driven intelligence and a human-first mindset, Cognizant Moment is systematically reshaping how accessibility is approached and delivered. This shift moves us from reactive audits to proactive, inclusive design. It replaces static fixes for compliance with intelligent, empathetic experiences. Most importantly, it redefines accessibility not as rules-driven testing, but as a form of human-centered design.

Ultimately, this transformation is not just about making digital experiences accessible. It’s about making them inclusive and intelligent.