Find Earlier, Fix Faster, and Prove Progress with AI Accessibility Agents

Digital accessibility is more critical—and more complex—than ever. Legal and regulatory pressure is rising. Digital portfolios have expanded beyond web, now spanning mobile apps and documents. And AI is accelerating how experiences are designed and shipped.

As organizations’ needs have changed, the digital accessibility solutions market has evolved, moving through three waves:

• Wave 1: Services and manual audits
• Wave 2: Platforms and basic automation
• Wave 3 (today): AI accessibility tools embedded in everyday workflows

Most organizations are stuck in Wave 1 or Wave 2, creating three gaps that stall progress: risk, resolution, and evidence. This piece explores why these gaps are limiting programs’ impact—and how Level Access’s AI accessibility agents and capabilities can empower your organization to close them by finding issues earlier, fixing them faster, and continuously proving progress.

What’s holding accessibility programs back?

Digital and product teams are striving to meet rising demand for accessible experiences with tools that simply can’t keep up. So, it’s not surprising that many teams struggle with the same three challenges:

1. The risk gap: Teams can’t understand their real risk status. Findings pour in from audits and scans, across digital assets. Duplicates and noise bury the information that matters. Without combing through spreadsheets, it’s impossible to assess accessibility across your digital assets.
2. The resolution gap: Teams can’t fix issues quickly enough. Audits don’t provide actionable insight for developers. The guidance that’s available sits outside teams’ everyday tools, forcing constant context-switching that slows releases.
3. The evidence gap: Teams can’t prove they’re making progress. Accessibility champions struggle to connect accessibility data to business outcomes, making it difficult to provide leaders with a compelling story about their programs’ impact. Without a way to easily surface the most relevant data, champions can’t make a strong business case, funding dries up, and momentum stalls.

Find. fix. prove. How AI accessibility tools close the gaps

Closing these gaps takes more than another dashboard. It takes intelligence built into where work actually happens, so accessibility stops being a side project and becomes part of an organization’s operating system.

Level Access’s AI accessibility agents are embedded across our platform and existing workflows to help you find risk earlier, fix issues faster, and prove progress continuously.

Here are three ways that our AI for accessibility can help your team rewire how work gets done:

1. Find earlier: Close the risk gap.

For most teams, the bottleneck isn’t detection—it’s triage and knowing where to start. Audits stack up, spreadsheets multiply, and it’s difficult to know which issues will really move the needle.

Our AI technology powers three key capabilities that work in tandem to surface real risk and guide strategic prioritization:

• Common Findings shrinks triage time from days to minutes by grouping identical issues across sites and templates. You can use it to assign and validate issues in bulk, and dismiss false positives at scale.
• AI Filtering lets you filter issues by asking questions in natural language. This makes it easy to isolate exactly what matters and create a targeted backlog.
• Monitoring Summaries turn every scan into a story. You gain visibility over what changed since the last run—and why—with recommended next steps, so you can steer action instead of chasing data.

Together, these AI accessibility tools help you cut through the noise to gain clarity on your portfolio-wide risk status, and focus on the actions that drive meaningful progress.

2. Fix faster: Close the resolution gap.

Knowing what to fix is only half the battle. Landing fixes quickly—without derailing releases—is where most teams struggle.

Our AI agents and capabilities close the resolution gap by bringing guided remediation directly into the tools your teams already use.

• LevelCI Code Suggestions provide standards-aligned remediation guidance, complete with explanations and references, directly in your pull requests.
• Audit Summaries translate findings from lengthy audit reports into prioritized takeaways aligned with your organization’s goals, so your team can move from audit to action in minutes.
• Ask LevelAI keeps work moving with on-demand accessibility expertise. Our chatbot provides instant, context-aware answers to questions on topics ranging from standards to implementation—right inside the Level Access Platform. That means non-experts don’t have to wait for time with a specialist to get the information they need to make progress.

The outcome? Less context-switching, fewer roadblocks, and faster release cycles.

3. Prove progress: Close the evidence gap.

Too often, reporting on accessibility progress means chasing metrics across tools and stitching together spreadsheets—only to find yourself wrangling multiple sources of truth and struggling to map data back to business outcomes.

The Reporting Agent changes that. In moments, accessibility teams can generate leadership-ready summaries—tied to resolved and unresolved findings—so executives, compliance teams, and program owners share one defensible view of progress.

Paired with Monitoring and Audit Summaries, the Reporting Agent turns raw data into a single source of truth that links effort to risk reduction and ROI, helping shape a standardized narrative about accessibility across your organization.

“This launch marks the next era of AI accessibility tools, one built on trust and designed to scale. By focusing on embedded accessibility intelligence, we give organizations the confidence to measure progress, prove impact and grow their accessibility programs—sustainably.” — Mark Zablan, CEO, Level Access

Stay in-flow as work evolves: Introducing our MCP-server

By closing the risk, resolution, and evidence gaps, you can address the barriers limiting your accessibility progress today. But how can you prepare your program for the future of work? As AI assistants become standard in development and design workflows, our Model Context Protocol server (MCP-server), coming soon, ensures accessibility intelligence flows seamlessly into these environments, keeping teams focused and productive.

Hybrid Intelligence: platform + AI + experts

AI alone isn’t enough. The future of accessibility is hybrid intelligence, where AI accelerates action and human expertise ensures trust.

“As we built this next generation of AI, we anchored it in a single conviction: AI must amplify human expertise, not eclipse it. The result is an AI tool built for outcomes, not just outputs.” — Andrew Chung, Chief Product Officer, Level Access

Because here’s the truth: while AI for accessibility delivers power, it’s the fusion with human expertise that brings trust, accountability, and strategic value. That partnership is what turns technology into a true competitive advantage. McKinsey & Company puts it well: “Agents are not simply magical plug-n-play pieces. They must work across systems, reason through ambiguity, and interact with people—not just as tools, but as collaborators.”

Build an intelligent accessibility program

With AI innovation from Level Access, programs shift from checks to outcomes. Issues surface sooner, fixes land faster, and progress is clear, defensible, and continuous. Learn more about our agents and capabilities on our AI hub page.

Ready to experience our AI accessibility tools in action? Request a demo and learn how to close your risk, resolution, and evidence gaps—without adding resources.

Frequently asked questions

How does AI assist in accessibility remediation?

AI accessibility tools accelerate remediation by bringing guidance directly into the tools where teams work. Instead of long, static audit reports and constant context-switching, AI-powered capabilities like LevelCI Code Suggestions and Audit Summaries provide prioritized, standards-aligned fixes inside development workflows. This eliminates guesswork, reduces delays, and helps teams go from issue detection to resolution in minutes—not weeks.

How does AI improve web accessibility?

AI improves web accessibility by finding barriers earlier, fixing them faster, and proving progress continuously. Capabilities like Common Findings and AI Filtering cut through duplicate results and noise, surfacing the issues that matter most. Monitoring Summaries then track changes over time, so teams can focus on high-impact improvements across websites, apps, and digital assets—creating a more inclusive experience for every user.

How is AI used for accessibility?

AI accessibility tools are embedded directly into everyday workflows, turning accessibility from a side project into part of an organization’s operating system. They help teams triage issues, guide remediation, and generate executive-ready reports—all in real time.