Closing the Gaps: Harnessing AI Accessibility Agents in Your Workflows

In our recent blog post, Find Earlier, Fix Faster, and Prove Progress with AI Accessibility Agents, we introduced a new generation of AI-powered capabilities designed to help organizations close three critical gaps holding accessibility programs back:

• The risk gap: Difficulty understanding and prioritizing risks
• The resolution gap: Difficulty remediating issues efficiently
• The evidence gap: Difficulty demonstrating ROI

We discussed how our AI agents and capabilities empower teams to navigate these challenges by finding issues earlier, fixing them faster, and proving progress. But what does that mean in practice?

In this blog, we’ll explain how your team can harness our new AI tools to tackle real-world accessibility challenges. Specifically, we’ll explore how each of the eight announced AI capabilities help you plug the risk, resolution, and evidence gaps in your day-to-day workflows.

Closing the risk gap

We introduced three features—Common Findings, AI Filtering, and Monitoring Summaries—that close the risk gap by giving you clarity on your portfolio-wide risk status.

Let’s dive into how each of these tools helps you focus on the actions that drive meaningful progress.

Common Findings

Many accessibility teams struggle to balance large, continually changing lists of findings from across their organization. Prioritizing issues across assets, pages, and components, while reconciling duplicate findings, can demand hours of manual work. That’s why we created Common Findings.

Common Findings aggregates and organizes automated testing data from all your web assets in a single place within the Level Access Platform. It then reviews this data for duplicate or near-duplicate issues and intelligently condenses those similar findings into one.

The result is a single table that you can use to streamline prioritization. For example, you can filter the table to quickly identify:

• The most frequently recurring issue across all your websites (e.g., a critical issue affecting 175 pages across multiple sites).
• The issue affecting the greatest number of pages or assets (e.g., a high-severity issue affecting 17 of your 20 assets).

However you choose to prioritize, Common Findings lets you skip the manual list-making so you can stay focused while managing accessibility at scale.

AI Filtering

Teams don’t just encounter challenges managing findings across their organization—many accessibility leaders also struggle with issue prioritization at the asset level.

To address this problem, we developed Digital Asset Findings. Digital Asset Findings allows you to filter and sort all findings within a single digital asset, in a centralized location.

Now, we’re introducing AI Filtering to make prioritizing issues in Digital Asset Findings even easier. With AI Filtering, you can sort findings using natural language—no manual filtering required. Just ask for what you need—for instance, “new critical findings” or “findings without a task”—to receive a filtered list.

Monitoring Summaries

With the ability to scan up to 10,000 pages, monitoring is a powerful tool for tracking the accessibility status of your site over time.

But this data is only as valuable as the story you can tell with it. The more easily you understand what happened in your latest monitoring results, the more quickly you can surface risk, identify areas for improvement, and formulate next steps. That’s where AI Monitoring Summaries come in.

Our Monitoring Summaries feature takes the results of your last two monitors, compares them, and intelligently generates a concise summary of changes between these two scans, along with recommendations for how to move forward. In just moments, you can determine whether your accessibility status is moving in the right direction and what to do next—so you can focus on taking action, not sifting through data.

Closing the resolution gap

We also introduced three features that help close the resolution gap—Level CI Code Suggestions, Audit Summaries, and Ask LevelAI—by bringing guided remediation directly into the tools your teams already use.

So, how can you use these features to fix issues faster?

Level CI code suggestions

Thanks to advancements in testing tools, developers can now find issues more proactively than ever. But actually fixing these issues is often still a time-consuming process. That’s because many development teams lack tools for addressing accessibility barriers when it’s easiest—that is, when code is still in development.

We built Level CI specifically to meet this need. This developer-first tool integrates directly into your CI pipeline to monitor and manage accessibility quality in code branches and pull requests (PRs). And with AI code suggestions, Level CI now brings automatically generated accessible code snippets directly into your development workflow.

This means developers can now access the accessibility status of their change, info about the relevant issue, and an AI-generated code suggestion for how to fix that issue all from within their GitHub PR. As a developer, you can review the code suggestion and choose to ignore it or commit the change right away.

The result? Instant accessibility insights and improvements embedded in your development process, without any additional lines of code.

Audit Summaries

Manual audits are incredibly rich sources of information about accessibility issues on your site, and how to address them. But navigating through an audit report to understand what issues to prioritize can be a difficult, time-consuming task. Audit Summaries changes that.

Audit Summaries live inside of each of your manual audit reports, and provide four unique ways to automatically organize and prioritize your audit results:

• Optimizing for a Voluntary Product Accessibility Template (VPAT®)
• Optimizing for risk reduction
• Disability affected
• Most affected page

After you select one of these options, the Audit Summaries tool will intelligently surface the most important issues from your audit, group them in alignment with your goals, and suggest a prioritized order for them. If you chose to optimize for a VPAT, for example, Audit Summaries will group issues by Web Content Accessibility Guidelines (WCAG) success criteria and suggest an order to help you support as many categories as possible with the fewest number of fixes. It’ll even create links to pre-filtered lists of issues that it intelligently grouped for you.

No matter your objective, the Audit Summaries tool helps your team move from audit to action in minutes.

Ask Level AI

Sometimes the seemingly smallest questions (How do I access a specific feature? What does this acronym mean? Which Level Access Academy course should I take next?) can cause the biggest delays for teams trying to make progress.

We know that timely, contextual answers and advice are critical to helping teams maintain velocity. That’s why we created Ask LevelAI, an always-on chatbot designed to provide instant, context-aware answers to your questions.

What makes Ask LevelAI unique is that it’s specifically trained on all our proprietary information—from how-to guides and thought leadership articles to Level Access Academy courses and product-specific resources—in addition to information about WCAG and international accessibility standards.

Drawing on this expansive knowledge base, Ask LevelAI can provide expert-quality answers to questions on topics ranging from general accessibility best practices to specific pieces of legislation and how parts of the Level Access Platform work. It can even offer guidance for approaching a particular problem your team is facing.

Ask LevelAI is available from nearly every page in the platform, meaning it’s always on standby to answer your questions. What you ask is totally up to you, but some prompts our customers have liked using so far include:

• What is a [Level Access product or service; e.g., DAMM Assessment]?
• What risks do I face for accessibility if I am operating a [product or industry category; e.g., software product] in [region; e.g., France, Europe, New York State]?
• I just took the [course name; e.g., Buttons and Links for User Interface Designers] course in Academy, can you create three multiple choice questions to quiz me on the material?
• Can you give me some recommendations on how I might fix a [rule title / issue name; e.g., button element missing accessible name] issue?

Whatever roadblocks you may run into, Ask LevelAI is ready to help.

Closing the evidence gap

Finally, we introduced the Reporting Agent to help close the evidence gap by turning raw data into a single source of truth that links effort to risk reduction and ROI.

The Reporting Agent

At many organizations, reporting on accessibility is anything but a streamlined process.

Too often, teams are left chasing data across tools and teams, only to have to manually stich together spreadsheets. Enter the Reporting Agent.

With the Reporting Agent, generating a custom, leadership-ready report is easy. Since the Reporting Agent can tap into all testing data you have stored in the Level Access Platform, all you need to do is configure your report, and hit generate. The result tells the story of your performance using a combination of text, tables, and graphs to convey each milestone with clarity.

Of course, every team’s reporting needs are unique. The Reporting Agent lets you tailor your report’s output based on your goals or target audience. By customizing parameters like data frequency, timeframe, and focus (resolved or unresolved findings), you can ensure every stakeholder gets the information they care about.

For example, an engineering manager might want a weekly breakdown of unresolved findings from the last quarter to refine process, while an accessibility champion might need a monthly breakdown of resolved findings over the last year to demonstrate their program’s impact to executives.

Coming soon: Our MCP-server

The seven capabilities we discussed bring intelligence into your existing accessibility processes, closing the three critical gaps programs face today. But how can you prepare your program for the AI-driven future of work?

Our Model Context Protocol server (MCP-server) embeds accessibility knowledge in AI-powered workflows by allowing other AI assistants to communicate with Level Access.

As an example, developers are increasingly using AI assistants built right into their integrated development environments (IDEs) to accelerate everyday development work. With our MCP-server, these developers will be able to ask those same assistants for information like the latest accessibility test results of a page, more insight on a particular issue, or recommendations for how to approach a fix.

This deep integration between embedded AI tools and accessibility intelligence will help teams stay focused, maintaining velocity while delivering experiences that work for everyone.

From capabilities to competitive advantage

Our AI capabilities are more than features. They’re part of a broader shift toward hybrid intelligence, where AI accelerates accessibility work and human expertise ensures it’s done right. By combining the power of AI with human judgment, teams can go beyond closing gaps and build accessibility into their operating model.

Want to experience these capabilities in action? Request a demo and learn how to move from promise to practice—without adding headcount or slowing down your team.