216digital.
Web Accessibility

ADA Risk Mitigation
Prevent and Respond to ADA Lawsuits


WCAG & Section 508
Conform with Local and International Requirements


a11y.Radar
Ongoing Monitoring and Maintenance


Consultation & Training

Is Your Website Vulnerable to Frivolous Lawsuits?
Get a Free Web Accessibility Audit to Learn Where You Stand
Find Out Today!

Web Design & Development

Marketing

PPC Management
Google & Social Media Ads


Professional SEO
Increase Organic Search Strength

Interested in Marketing?
Speak to an Expert about marketing opportunities for your brand to cultivate support and growth online.
Contact Us

About

Blog

Contact Us
  • How Digital Accessibility Is Changing in 2026

    Running a website today means juggling a long list of responsibilities. Performance, security, content updates, design refreshes, AI experimentation, compliance questions. Accessibility often sits somewhere in the middle of that list. Important, but easy to push aside when other deadlines feel more urgent.

    As 2026 gets closer, keeping up is becoming more difficult. Expectations are higher, changes are happening faster, and many website owners are wondering: What does this mean for my site? How much do I need to do? How can I keep up without always scrambling to fix accessibility?

    If you’re trying to plan ahead, digital accessibility can feel like one more moving target. This article walks through three shifts shaping 2026 and offers a practical way to prepare without adding extra stress.


    Shift 1: Why Digital Accessibility Is Becoming Core Website Infrastructure

    One of the biggest changes in 2026 is how teams position the work. Instead of treating accessibility as a project with an end date, more organizations are treating it like website infrastructure. Similar to security or performance, it has to hold up through releases, new content, vendor updates, and design changes.

    Why One-Time Accessibility Fixes No Longer Work for Modern Websites

    For years, teams often handled accessibility as a one-time fix. They would address the issues, publish a report, and then move on. Most did the best they could with the time and resources available.

    Now, teams notice how quickly earlier accessibility work can lose its value if it is not part of the site’s ongoing process. Work gets passed between teams, new content is added months later, and templates are reused in unexpected ways. Accessibility gaps come back, not because people ignore them, but because there are no consistent habits to support them.

    This trend also appears in enforcement. In 2024, 41% of web accessibility lawsuits were copycat cases, according to UseableNet. Many of these organizations had already tried to improve accessibility, but as their sites changed, old issues resurfaced, or new ones emerged. Without ongoing attention, earlier efforts lose their impact.

    This is where accessibility debt builds up. Small problems add up over redesigns, framework changes, staff changes, and tight deadlines. Each issue may seem small, but together they create a growing backlog that becomes harder and more expensive to fix.

    How Standards Are Becoming the Baseline, Not the Bonus

    Another change is that expectations are becoming more consistent in contracts and partner requirements. Many organizations that used to follow WCAG 2.1 are now treating WCAG 2.2 as the new standard. This matters because it changes what vendors must support, how teams are measured, and what counts as “done.”

    For website owners, this means accessibility is less likely to be treated as a special request and more likely to be considered a standard requirement for modern websites, especially when contracts, platforms, or enterprise stakeholders are involved.

    What Accessibility as Infrastructure Looks Like in Practice

    When accessibility is treated as infrastructure, it shows up upstream. It’s embedded in the acceptance criteria, not something discovered in an audit. And it’s supported by QA so issues are found in testing, not raised by users later.

    Many teams are also seeing the benefits of using native HTML. Native elements have built-in features that assistive technologies handle well. By using standard controls, teams spend less time fixing bugs, patching ARIA, or maintaining custom widgets that can become difficult to manage.


    Shift 2: How AI Is Changing Digital Accessibility Workflows

    AI isn’t just helping teams work faster. It’s changing how websites come together in the first place. Pages are generated, components are assembled, content is drafted, and updates go live quickly, often faster than traditional review cycles can realistically support.

    For most teams, the risk isn’t one bad decision. It’s how quickly small issues can spread. When accessibility problems enter the system early, they don’t stay isolated. They show up again and again across templates, campaigns, and key user paths before anyone has a chance to step in.

    That’s why accessibility now feels less like a checklist and more like ongoing quality control. The work is about keeping experiences steady while everything around them keeps changing.

    AI Will Build More, Developers Will Still Steer

    By 2026, AI will handle much of the day-to-day building work. It will generate pages, assemble components, and draft content as part of normal production.

    But in complex environments, developers aren’t going away.

    Large organizations still need people who understand how systems fit together, how integrations behave, and where things tend to break. The role shifts away from writing every line by hand and toward guiding AI output, validating results, and fixing what doesn’t hold up in real use.

    From a digital accessibility standpoint, this changes where risk lives. Issues are less likely to come from a single coding mistake and more likely to come from how AI systems are configured, connected, and allowed to operate at scale.

    Where AI Helps and Where It Falls Short

    AI is genuinely useful for work that’s difficult to manage by hand. It can surface patterns across large sites, group related issues, and turn long reports into better priorities. It can also help draft content or suggest alt text, as long as a human reviews the final result.

    Where it falls short is in judging the actual experience of using a site.

    Modern websites are assembled from layers. Design systems, CMS platforms, personalization tools, third-party scripts, and AI-generated elements all influence what ends up in the browser, sometimes after the underlying code has already been reviewed.

    Assistive technologies interact only with what is rendered on the screen. They don’t account for intent or what the code was supposed to produce. Automated tools can catch many technical issues, but they often miss broader usability problems when the final experience becomes inconsistent or difficult to navigate with a keyboard or screen reader.

    What Teams Need Before Scaling AI

    Teams tend to get the most value from AI when the basics are already solid. That usually means consistent components, documented behavior, and shared expectations for what “done” really means.

    It also means being prepared for last-mile issues. Some accessibility problems don’t show up until everything is live and interacting. Fixing them requires ownership of the user experience, even when the root cause sits inside a vendor tool or generated workflow.

    Over time, accessibility becomes a useful signal. When AI-driven experiences fail accessibility checks, they often reveal broader quality problems, including structure, clarity, and stability, not just compliance gaps.

    By 2026, digital accessibility work will sit closer to the center of how teams manage AI quality. Not as a separate initiative, but as part of how they keep digital experiences usable, reliable, and resilient.


    Shift 3: Why Leadership and Culture Decide Whether Accessibility Actually Sticks

    Even with strong tools and standards, progress can still stall. It often comes down to how decisions are made when priorities compete.

    Where Accessibility Breaks Down Without Leadership Alignment

    Most accessibility challenges do not come from a lack of awareness. They come from unresolved tradeoffs. Teams know what needs to be done, but they are unsure who has the authority to slow things down, ask for changes, or say no when something introduces risk.

    If accessibility relies on individual advocates instead of shared expectations, it becomes fragile. Leadership alignment changes this. When accessibility is seen as part of quality, teams stop debating its importance and start planning how to deliver it within real constraints.

    What Effective Accessibility Leadership Looks Like Day to Day

    Leadership is shown more by actions than by statements. Accessibility becomes part of planning, not just a follow-up task. Teams set aside time to fix issues before release, not after problems arise. Tradeoffs are discussed openly, with accessibility considered along with performance, security, and usability.

    Clear governance supports this work. Teams know who owns decisions, how issues are prioritized, and when a release needs to pause. These signals remove uncertainty and help teams move with confidence.

    Why Skills and Shared Ownership Matter More Than Champions

    Training matters, but not as a one-time event. Skills need reinforcement as tools and workflows change.

    Designers need patterns they can reuse. Developers need reliable interaction models and accessibility testing habits. Content teams need guidance that fits fast publishing cycles. Product and project leaders need support prioritizing accessibility work early, not after problems surface.

    As these skills become more common, digital accessibility is no longer just for specialists. It becomes part of how everyone on the team works together.

    How Culture Shapes Accessibility Outcomes Over Time

    Culture is what remains when tools change, and people move on. It shows up in whether accessibility issues are treated like real bugs, whether reviews include keyboard and focus checks, and whether success is measured by task completion instead of surface-level scores.

    This shift toward focusing on real outcomes is becoming more common. Teams are now looking at whether users can complete important actions easily, not just if a scan passes.

    In 2026, organizations that keep making progress are those where leadership supports accessibility, teams share the right skills, and everyday decisions reflect these values.


    Turning These Shifts Into a Strategy That Holds Up

    These changes build on each other. Treating digital accessibility as infrastructure makes it more stable. Using AI helps teams move faster without losing control. When leadership and culture support the effort, progress continues even as priorities change.

    A practical approach for 2026 does not mean fixing everything at once. It means being consistent. Start by making sure ownership and standards are in place. Then add accessibility to the workflows teams already use, like design systems, development reviews, content publishing, and QA. Once these habits are set, scaling is about preventing backsliding, not starting over each time.


    Looking Ahead to Accessibility in 2026

    Accessibility has always been about people. It is about whether someone can complete a task, understand information, or participate fully in a digital experience without unnecessary barriers. As digital environments continue to evolve through 2026, with faster release cycles and broader use of AI, having a steady strategy becomes less about reacting and more about staying aligned.

    The teams that move forward with confidence are the ones that treat digital accessibility as part of how their digital work functions every day.

    At 216digital, we can help develop a strategy to integrate WCAG 2.1 compliance into your development roadmap on your terms. To learn more about how our experts can help you confidently create and maintain an accessible website that meets both your business goals and the needs of your users, schedule a complimentary ADA Strategy Briefing today.

    Greg McNeil

    January 7, 2026
    Web Accessibility Remediation
    2026, AI-driven accessibility, Small Business, Web Accessibility, web development, Website Accessibility
  • How Accessibility Helps Your Site Thrive in AI Search

    Not surprisingly, organic traffic is becoming harder to predict, even when rankings remain steady. Search results are answering more questions directly, especially through AI Overviews, which means fewer users need to click through to individual pages. Gartner has suggested that traditional search volume could decline by around 25% by 2026, a pattern many teams already see reflected in their analytics.

    These shifts in AI search are happening fast, and staying visible now means doing more than waiting for users to show up. A big part of this shift is how clearly your site presents information as a reliable source. For organizations that rely on search visibility, this is a major change and puts new focus on something many teams have overlooked: web accessibility.

    From Blue Links to Answer Engines

    Search behavior is changing in ways that affect your visibility. Google’s AI Overviews now show up in over 60% of searches, according to Xponent 21, so many users get their answers at the top of the page before looking at links. People are also starting their research in new places. Adobe Analytics found a 4,700% year-over-year jump in traffic to U.S. retail sites from AI tools like ChatGPT and Perplexity by mid-2025. This shift helps explain why your analytics might feel unpredictable, even if your keyword rankings stay the same.

    Ranking still matters, but it no longer guarantees attention like it used to. Now, the key question is whether your page is clear and well-structured enough to be included in the answers users see first—often before they even think about visiting your site.

    AEO and GEO in the Age of AI Search

    Answer Engine Optimization centers on preparing content so that answer engines recognize it as a reliable source. It focuses on clarity, structure, and directness because these are the signals systems rely on when assembling summaries.

    Generative Engine Optimization is similar, but it focuses on large language models. When someone asks an AI assistant a question related to your work, GEO checks if the assistant can understand your content well enough to use it. Often, pages that are good for AEO are also good for GEO, since both rely on clear organization and predictable markup.

    Both frameworks share a practical requirement: information needs to be arranged in a way systems can understand without guesswork. Headings that follow a sensible hierarchy, concise explanations near the top of a section, and consistent semantic HTML help models determine how topics relate and which sections belong in the answer they produce.

    Why Accessibility Improves AI Search Discoverability

    This is also where accessibility carries more influence than many teams expect. WCAG-conformant sites already use patterns that support machine understanding: clear hierarchy, descriptive labels, consistent navigation, and stable markup. These fundamentals help people move through a site, and they help automated systems interpret its structure with greater confidence.

    The connection shows up in the data. A Semrush analysis of 10,000 websites found that WCAG-compliant sites gained 23% more organic traffic and ranked for 2 more keywords than non-compliant sites. Many teams see similar improvements when they strengthen accessibility. The site becomes easier to navigate, the content becomes easier to interpret, and systems can use that information with more accuracy.

    As AI Overviews, chat tools, and assistants become more important for finding information, accessible sites offer the clarity and consistency these systems need. The more predictable your site’s structure is, the more likely your content will be understood, trusted, and reused in modern search experiences.

    How AI Tools “Read” Your Pages More Like Assistive Tech

    AI systems do not see websites the way people do. They read the code. In many ways, they act like non-visual users, depending on HTML structure, headings, landmarks, labels, and text alternatives to understand meaning and relationships. Because of this, accessibility can influence AI search results more than many teams expect.

    Clear structural cues reduce uncertainty for machines:

    • Headings define topic boundaries and hierarchy.
    • Landmark regions separate main content from navigation and repeated interface elements.
    • Meaningful link text provides context when read out of sequence.
    • Alt text turns images into usable information.

    Accessibility research reinforces the value of this clarity. Sites without strong accessibility foundations can see an estimated 20 to 30% loss of traffic to AI-driven discovery tools.

    JavaScript-heavy builds introduce additional risk. Many AI crawlers rely on the initial HTML and may not execute client-side scripts consistently. When essential content only appears after rendering, it can be missed. Server-side rendering, static generation, and pre-rendering help ensure that core content is visible to both assistive technologies and AI systems.

    Accessibility Foundations That Improve AI Search Understanding

    Accessibility lays the groundwork for how both people and automated systems understand a page. These practices give AI tools a cleaner map of the page, so it is easier to tell what each section is about and how they connect. When these elements are in place, a site becomes easier to navigate and easier for models to interpret with confidence.

    Semantic Structure and Headings

    A single descriptive H1 supported by a clear H2 and H3 sequence helps define the outline of the page. This hierarchy shows how ideas fit together, where one topic ends, and another begins. For pages that answer common questions, using a question-style heading with a direct answer near the top can serve users well and support models that look for natural question-and-answer pairs.

    Alt Text for Multimodal AI

    Images and diagrams that carry meaning need short, accurate alt text so their purpose is clear. These descriptions help visitors who cannot see the image and help AI systems understand what each visual represents. As multimodal models continue to expand, consistent text alternatives remain an important signal.

    Clear Language and Section Hierarchy

    Straightforward phrasing and well-organized sections reduce effort for readers. They also reduce uncertainty for AI systems that rely on clean, focused paragraphs to interpret and summarize content. When each block stays centered on one idea and headings reflect the structure beneath them, both audiences can locate the information that matters most.

    Logical DOM Order and Keyboard Flow

    Logical source order supports keyboard navigation and creates a clear reading path for tools that may not execute every script. Grouping related elements together and keeping navigation patterns consistent helps preserve that clarity across pages. These patterns improve usability and reduce the risk of misclassification by crawlers.

    Stability and Performance for Crawlers

    Stable pages that load quickly benefit everyone. They reduce the likelihood of timeouts or partial content that can limit what models see. Many performance improvements that support accessibility—such as limiting layout shifts or relying on lighter scripts—also make the page easier for AI systems to access and analyze.

    Together, these foundations make the site more inclusive and easier for models to segment, interpret, and reuse content accurately across AI-driven experiences and AI Search results.

    Content Patterns That Help Your Site Earn AI Citations

    Once the structure is sound, content design determines whether a page becomes a cited source in AI Search and other modern discovery layers.

    Shape Sections Around Clear Questions and Direct Answers

    Pages that reflect natural-language questions paired with direct answers match with conversational prompts used in AI Search tools. Purposeful FAQ sections often perform well when they address specific user needs rather than serving as content dumping grounds.

    Use Lists When They Strengthen Understanding

    Lists and step-by-step formats break information into clean units that AI systems can reuse. They work especially well for processes, comparisons, and summaries.

    Write With Precision So Content Is Easy to Interpret

    AI systems favor content that is specific and free of vague claims. A warm, natural voice combined with concrete language improves comprehension for both people and machines.

    Expand Sections With Helpful Detail Instead of Extra Filler

    Pages that include definitions, context, and edge cases provide richer material for AI systems to evaluate and reference.

    Schema Markup Signals That Strengthen AI Search Interpretation

    Schema adds an extra layer of meaning that supports the work already done through accessible structure. It helps automated systems understand what type of content a page contains, how sections relate to each other, and when a page offers information that can answer specific questions. When used alongside well-defined headings and well-organized content, schema gives AI-driven tools a more complete picture of the page.

    Focus on the formats that add the most value.

    • Article schema works well for long-form guides that explain a topic in depth.
    • FAQ Page schema is helpful when a page includes genuine question-and-answer pairs that reflect actual user intent.
    • HowTo schema supports instructional content where each step has a purpose and appears in a consistent order.

    What matters most is alignment between the schema and the visible content. The structure described in the markup should match what someone sees on the screen. When the content within the schema reflects the real wording and the real sequence on the page, it becomes a strong confirmation signal for systems that depend on accuracy to generate reliable responses.

    Research from OpenAI, Google, and Bing shows that large language models benefit from pages that combine semantic HTML with structured data. Schema does not replace accessible code or strong writing, but it can reinforce the clarity already present. When the foundation is solid and the markup supports it, pages are easier for both people and automated systems to interpret and reuse.

    Practical Steps to Improve Accessibility and AI Search Performance

    You do not need a brand new site or a big replatform to prepare for what is coming. Teams that adapt well usually start small, with a few important templates, a focused audit, and clear patterns they can use again.

    Start With an Accessibility and Discovery Audit

    Begin with a short list of pages that already matter to your business. Core service pages, high-performing blog articles, and pages that answer common customer questions are the best place to start.

    Review these pages through two lenses. First, run automated accessibility checks to surface issues with headings, alt text, landmarks, and link clarity. Then, test how those same pages appear in AI-driven environments by searching real user questions in Google AI Overviews, ChatGPT, Perplexity, and Bing Copilot.

    This establishes a practical baseline for both accessibility and AI Search visibility.

    Repair Structure Before Adding Content

    Fix your heading order, make sure the DOM is logical, and clearly define navigation and main content areas. These steps reduce confusion for assistive technologies and help AI systems read your content more reliably.

    Shape Content Around Real Questions

    Add focused FAQs where they make sense. Use question-style subheads followed by clear answers early in each section. Break dense explanations into smaller units that are easier to extract and reuse.

    Use Schema to Reinforce Clarity

    Apply Article, FAQPage, or HowTo schema only when it accurately reflects the visible content. Schema works best as confirmation, not decoration.

    Monitor and Maintain

    Accessibility and AI readiness are not one-time efforts. Regular checks, shared patterns across teams, and ongoing monitoring help prevent regressions as content evolves.

    Accessibility as a Long-Term Strategy

    Search is changing, and teams everywhere are still learning how to work in an environment shaped by AI summaries, conversational queries, and systems that select only a handful of sources. There is no perfect playbook yet. Teams are still learning what long-term visibility will require as AI Search matures.

    What we do know is that accessibility helps. Clear structure, predictable markup, meaningful alternatives, and human-centered content give people a better experience, and they give machines the signals they need to interpret information with confidence. These fundamentals place your site on steady ground as AI Search continues to expand.At 216digital, we help teams build this foundation. We can work with you to create a strategy that brings WCAG 2.1 compliance into your development plans in a way that fits your goals and workflow. If you want to see how our experts can help you create and maintain an accessible website that meets your business goals and your users’ needs, schedule a free ADA Strategy Briefing today.

    Greg McNeil

    December 11, 2025
    Web Accessibility Remediation
    Accessibility, AI search, AI-driven accessibility, SEO, Web Accessibility, Website Accessibility
  • Is ChatGPT a Substitute for Web Accessibility Remediation?

    Is ChatGPT a Substitute for Web Accessibility Remediation?

    If you’ve worked in digital long enough, you’ve probably heard it: “Couldn’t we just use ChatGPT to fix the accessibility stuff?”

    It’s an honest question. The tools are impressive. AI can summarize dense docs, spit out code snippets, even draft copy that sounds decent. When you’re staring at a backlog with limited budget, “free and fast” feels like a gift.

    Here’s the truth: speed without understanding rarely saves time. ChatGPT is great at producing. What it isn’t great at is deciding. And web accessibility—the real kind, not just error cleanup—is full of decisions.

    So, while it can support web accessibility remediation, it can’t replace it. Because remediation isn’t just about fixing what’s broken; it’s about understanding why it broke and what the right fix means in the context of your design, your users, and your codebase.

    What Remediation Really Looks Like

    Real remediation is closer to detective work than to one-off development. You trace how a problem shows up in the interface, how it travels through templates, and why it keeps coming back.

    It starts with discovery—learning how the site is put together and where risky flows live, like checkout or account pages. Then comes testing, both automated and human, to catch what scanners miss: poor focus order, ambiguous instructions, unlabeled controls, shaky widget behavior.

    From there, you triage and translate findings into work your team can actually ship. You plan fixes, weigh impact and effort, and roll changes through your stack. Finally, you validate with real assistive tech—keyboard, screen readers, voice control—to confirm the fix is a fix for real people.

    AI can sit beside you for parts of that journey. It can help reason through code or rephrase unclear labels. But it can’t feel when something “technically passes” yet still fails a user. That kind of judgment is learned, not generated—and it’s why web accessibility remediation stays a human-led process.

    Where ChatGPT Earns Its Keep

    Used by someone who understands accessibility, ChatGPT is genuinely helpful. It’s fast at rewriting small markup patterns. It can unpack a WCAG success criterion in plain language. It can draft alt text you’ll refine, or outline starter docs a team will own.

    It’s also great for teaching moments: when a new dev asks, “Why ARIA here?” AI can frame the idea before a specialist steps in with specifics.

    Think of it as an eager junior colleague—useful, quick, and worth having in the room. Just don’t hand it the keys.

    The Problem of “No Opinion”

    Here’s where AI hits the wall: it has no sense of context and no opinion of its own.

    Accessibility isn’t a math problem. Two developers can solve the same issue differently—both valid on paper, one far more usable in practice. That judgment call is the job.

    Because ChatGPT predicts what looks right, it can sound confident and still be wrong: adding a <label> but leaving a placeholder that confuses screen readers; copying a title into alt and causing duplicate announcements; “fixing” contrast by nudging color values without checking the full component state.

    Some barriers simply require a human to decide. Take alt text, for example: ChatGPT can’t actually see what an image is, how it’s being used, or what role it plays in the design. It doesn’t understand whether that image conveys meaning or is purely decorative—and that context determines whether alt text is needed at all. Without that judgment, even the best AI guess risks being wrong for the user.

    When you’re fixing accessibility, “almost right” is often still wrong. And when someone asks you to show due diligence, “we asked a chatbot” isn’t a defensible audit trail for web accessibility remediation.

    The Hidden Cost of “Free”

    Teams that lean too hard on AI learn fast that “free” isn’t free.

    You spend hours double-checking output, rewriting prompts, and chasing new issues that didn’t exist before. Sometimes you even end up debugging phantom problems the model invented.

    Meanwhile, the real barriers remain. Automated tools and AI together tend to catch only a slice of what actually affects users; the messy, contextual stuff slips through.

    So the report looks cleaner, the error count drops, and real people still struggle. That’s not progress. That’s paperwork dressed up as progress—and it leaves risk on the table, which is the opposite of web accessibility remediation.

    Even if AI manages to correct every automated scan error, it won’t protect you from real exposure. We’re now seeing a clear shift in ADA litigation: most new lawsuits aren’t built on automated findings anymore. They’re targeting manual issues—things uncovered by human testing and user experience barriers—because that’s where easy wins live for plaintiff firms. So even if AI covers one base, it leaves another wide open—and that’s the one most likely to cost you.

    Why Human-Led Web Accessibility Remediation Still Matters

    When you bring in a team that lives this work, you’re getting far more than bug fixes—you’re gaining traction. Instead of chasing one-off errors, you start to see the larger patterns behind what keeps breaking and why.

    A strong remediation partner brings clarity to your roadmap by tying priorities to real user impact and legal risk. Their fixes hold up through redesigns because they focus on underlying causes rather than surface-level symptoms.

    There’s also the advantage of human validation—review that’s defensible, thoughtful, and grounded in actual user experience. With the right process, accessibility becomes part of everyday development instead of something bolted on at the end.

    That’s the real promise of web accessibility remediation: not perfection, but predictability you can trust as your site evolves.

    How to Use AI the Right Way (With Guardrails)

    AI belongs in the workflow. It just doesn’t belong in charge.

    Use ChatGPT to speed up work you already understand, not to make calls you can’t verify. Let it draft checklists, summarize long audit exports, or propose markup for a pattern you’ve already chosen.

    Then layer on what AI can’t do: manual testing, AT validation, and the human decision-making that turns “technically correct” into “genuinely usable.”

    With that guardrail, AI becomes an accelerator for web accessibility remediation, not a shortcut that creates rework.

    What You Actually Get from Professional Remediation

    When you bring in a team that lives this work, you’re getting far more than bug fixes—you’re gaining traction. Instead of chasing one-off errors, you start to see the larger patterns behind what keeps breaking and why.

    A good remediation partner helps you understand where to focus first by tying priorities to real user impact and legal risk. They deliver fixes that continue to hold up through redesigns because the underlying causes—not just the surface-level symptoms—are addressed.

    You also gain something automated tools can’t offer: human validation that stands up to scrutiny. And with the right team, accessibility becomes part of how your site operates going forward, rather than something added after the fact.

    That’s the real value of web accessibility remediation. It’s not about perfection—it’s about creating a level of predictability you can trust as your site evolves.

    AI Doesn’t Make Judgment Calls—People Do

    ChatGPT is a powerful tool. It can teach, inspire, and save time—but it can’t care. Accessibility is about care: for users, for quality, for inclusion.

    AI can suggest the “how.” People understand the “why.” And perhaps most importantly, AI can’t shield you from the kinds of lawsuits that automation no longer catches.

    If your team is experimenting with AI and you want to make sure it helps instead of hurts, start with a conversation. Schedule an ADA briefing with 216digital. We’ll show where AI fits safely, where human oversight is non-negotiable, and how to build a plan that keeps your site open to everyone.

    That’s web accessibility remediation done right—fast where it can be, thoughtful where it must be.

    Greg McNeil

    November 10, 2025
    Testing & Remediation
    Accessibility Remediation, Accessibility testing, AI-driven accessibility, automated testing, Web Accessibility Remediation
  • AI-powered Checks for Accessible PDF: Are They Enough?

    AI-powered Checks for Accessible PDF: Are They Enough?

    Your team ships PDFs every week—policies, forms, reports. They look polished. But if a screen reader hits the footer before the body, the file isn’t usable. That’s the gap an accessible PDF is meant to close. Laws like Section 508 and WCAG don’t treat PDFs as special exceptions; if a document lives on your site, people should be able to move through it as easily as a web page. AI helps with the basics and saves time. The real question: how far can you trust it on its own?

    Before we dig into tools, here’s how the standards actually fit together.

    What An Accessible PDF is—And Why the Law Cares

    Two complementary standards govern PDF accessibility. PDF/UA (ISO 14289) defines how a PDF’s internals must be constructed so assistive technologies can reliably parse and convey the content. The Web Content Accessibility Guidelines (WCAG) governs outcomes when that PDF is published on the web—what users must be able to perceive, operate, understand, and rely on.

    PDF/UA (ISO 14289): Technical Conformance

    PDF/UA requires a correct structure tree with semantically appropriate tags (headings, lists, tables, figures), accurate role mapping, and a logical reading order. It expects:

    • Properly associated table headers and scopes.
    • Descriptions for non-text content; decorative material marked as artifacts.
    • Form fields (AcroForms) with programmatically associated labels, names, and instructions.
    • Declared document language and consistent language shifts where needed.
    • Links, bookmarks, and metadata that reflect actual structure.
    • The goal is consistent exposure of semantics to accessibility APIs so screen readers announce content as intended.

    WCAG for PDFs: Publication Context and User Outcomes

    When a PDF is part of web content, WCAG success criteria apply (e.g., 1.3.1 Info and Relationships, 1.3.2 Meaningful Sequence, 2.4.6 Headings and Labels, 3.1.1 Language of Page). WCAG focuses on the experience: users must navigate by headings, traverse content in a meaningful sequence, operate everything via keyboard, and understand relationships in tables, lists, forms, and links.

    How They Fit Together

    Think of PDF/UA as the engineering spec (how the file is built) and WCAG as the published experience (what users can actually do). Meeting one without the other leaves gaps—either structurally sound but unusable in context, or polished in presentation but unreliable under the hood.

    Operational Definition of “Compliant”

    In practice, compliance means a screen-reader user can:

    • Move by headings in a sensible hierarchy;
    • Traverse content in sequence;
    • Complete forms with announced labels and instructions;
    • Understand tables with correctly exposed headers;
    • Access links and landmarks without detours.

    With the standards context set, let’s look at why many PDFs still miss—and where automation helps versus where expert review remains essential.

    Why PDFs Are So Often Non-compliant

    Most teams don’t author in PDF first; they export—and that’s where trouble starts. Typical failures include missing or incorrect tags, reading orders that jump around, scanned pages without OCR, and forms or tables whose structure isn’t exposed to assistive tech. A quick snapshot:

    • No tags or the wrong tags → a screen reader announces “graphic, graphic, graphic” through a one-page flyer.
    • Reading order off → Footnotes should be read before the body copy.
    • Scanned pages with no OCR → 12 images, zero searchable text.
    • Mis-structured forms/tables → required fields can’t be reached; headers don’t announce.

    At scale—monthly statements, board packets, downloadable reports—small mistakes multiply. The volume is exactly why many teams turn to automation to keep pace and to move each file closer to an accessible PDF without starting from scratch.

    What AI-powered Accessibility Tools Do Well (Today)

    Give an AI checker a clean annual report and it can often spot headings, set a reasonable reading order, and propose alt text you can refine. That alone can cut remediation time significantly. Modern tools handle a few tasks particularly well:

    • Recognizing layout blocks (headings, paragraphs, lists)
    • Running OCR on scanned content to restore real text
    • Drafting tags for simpler figures (e.g., charts vs. logos)
    • Flagging obvious misses (untagged images, empty titles, missing language metadata)

    They’re fast, consistent, and tireless. Most importantly, they reduce the grunt work so specialists can spend time where judgment matters. What they can’t do is confirm that structure equals meaning—or guarantee that the end result behaves like an accessible PDF for every user scenario.

    Where AI Still Falls Short—and Why People Still Matter

    Some documents ask more than a model can answer. Two common gotchas:

    • Nested tables and forms. A claims form with merged cells can look “tagged” but read like alphabet soup.
    • Meaning vs. style. A bold sentence in a paragraph isn’t a heading; many models tag it that way.

    Tools also struggle with language switches mid-document, disclaimers that must tie to the right section, and reading orders that look logical to software but feel disorienting in a screen reader. A file may “pass” an automated check yet remain frustrating to use. That gap is not just usability—it’s risk. A defensible review still needs a human to ask: Does this read like an accessible PDF for someone relying on assistive tech?

    The Hybrid model for Accessible PDF Compliance

    Start with the tool, finish with a person.

    • AI first pass: establish the skeleton, set reading order, surface missing text alternatives, and catch obvious metadata gaps.
    • Human pass: repair tables, confirm form flow, check headings/links, and test a few pages with NVDA or VoiceOver.
    • Evidence trail: keep a short log of what changed and who checked it; if questions come later, you have the paper trail.

    This model balances speed with judgment. It scales because automation removes repetition while reviewers focus on the parts that shape the experience and, ultimately, compliance for an accessible PDF in the real world.

    AI is Powerful, But Not a Solo Act

    AI can accelerate the work, but it can’t replace judgment. If you’re balancing risk with reality, a two-pass workflow (tool, then human) is the path that holds up. The payoff is practical: fewer errors, faster cycles, clearer records, and a more reliable accessible PDF experience for your audience.

    If you want a second set of eyes—or a process your team can pick up and run—216digital can help. Schedule an ADA briefing with 216digital, and we’ll map a workflow that fits your documents, your deadlines, and your compliance goals.

    Greg McNeil

    August 26, 2025
    Legal Compliance
    Accessibility, accessible PDF, Ai and Overlay Widgets, AI-driven accessibility, PDF, PDF/UA (ISO 14289), WCAG, Web Accessibility, Website Accessibility
  • How WCAG Applies to AI-Generated Content

    How WCAG Applies to AI-Generated Content

    AI is changing the way we create. From blog posts and product descriptions to social media graphics, work that once took hours can now be done in seconds. This speed is powerful—but it also carries risk. In the rush to publish, it’s easy to miss a crucial question: Is this content accessible?

    The Web Content Accessibility Guidelines (WCAG) apply to everything online—whether written by a person, coded by a developer, or created by an AI tool. That means AI-generated content is not exempt. If you’re using AI to scale your digital strategy, accessibility must remain part of the foundation.

    This guide explains how WCAG applies to AI-driven workflows and offers a simple checklist to help you review AI-written text, visuals, and layouts. The goal: to help you publish faster without leaving inclusion behind.

    Why AI-Generated Content Creates Accessibility Risks

    AI tools can be incredible productivity boosters. But they are not accessibility tools. A common mistake is assuming that if something looks polished, it must be usable for everyone. In reality, accessibility requires more.

    AI-generated content often misses the real-world needs of diverse users. For example, it might:

    • Write vague alt text like “image of a person” instead of describing the purpose.
    • Suggest design elements with poor color contrast.
    • Use bold text instead of proper heading tags like <h2> or <h3>.

    If left unchecked, these issues can shut people out, frustrate customers, and even create legal risk. The takeaway is simple: AI-generated content is not automatically compliant with WCAG. It needs human oversight.

    WCAG Still Applies—No Matter Who (or What) Creates the Content

    WCAG, developed by the W3C, is the global standard for digital accessibility. It’s built around four principles:

    • Perceivable: Users must be able to perceive the information (like adding alt text for images).
    • Operable: Content should be easy to navigate and interact with (keyboard accessibility matters).
    • Understandable: Information should be clear and predictable.
    • Robust: Content must work with assistive technologies now and in the future.

    These rules apply equally to all content, whether it’s human-created or AI-generated content. In the United States, the Americans with Disabilities Act (ADA) has fueled thousands of lawsuits over inaccessible websites and apps. Courts often turn to WCAG as the standard for compliance—and they aren’t alone. Many countries, including those in the European Union and Canada, also rely on WCAG as the foundation of their digital accessibility laws.

    That means WCAG isn’t just a best practice—it’s often the measuring stick for legal compliance. Regardless of whether content was written by a human or generated by AI, if it excludes people with disabilities, it can be litigated upon. The risk is real: inaccessible content can damage your brand, frustrate customers, and create costly legal battles.

    The AI Accessibility Checklist

    This checklist will help you review AI-generated content before publishing. Each step ties directly to WCAG principles, making accessibility practical and manageable.

    For AI-Written Text

    • Use clear language: Choose plain, everyday words instead of jargon or long, complex phrasing.
    • Ensure proper headings: Use semantic HTML like <h2> and <h3> so screen readers and assistive tech can navigate. Avoid using bold text as a replacement.
    • Write descriptive links: Swap vague text like “click here” for something meaningful, such as “Download our accessibility guide.”
    • Keep a consistent flow: Break up large blocks of text into shorter paragraphs, bullets, or numbered lists so readers can follow easily.
    • Format for scanning: People often skim. Use headings, bullets, and white space to make sure they can still understand the main points at a glance.

    For AI-Generated Images and Visuals

    • Provide meaningful alt text: Describe the purpose of the image, not just what it looks like. For example, instead of “photo of a person,” write “Customer smiling while using our product.”
    • Avoid text inside images: Important words should always appear as live text so they can be read by screen readers and resized.
    • Check contrast: Make sure text and background colors meet at least a 4.5:1 ratio so words are readable by people with low vision.
    • Don’t rely on color alone: Use shapes, labels, or patterns in addition to color to communicate meaning. This helps users who are colorblind.

    For AI-Generated Multimedia

    • Add synchronized captions for videos: Captions must match the audio in both timing and content.
    • Provide transcripts for audio files: A text version allows people who can’t hear—or who prefer to read—to still access the information.
    • Include audio descriptions: When visuals add meaning that isn’t spoken, narrate those details so blind users don’t miss them.

    For AI-Generated Layouts, Code, or Documents

    • Ensure keyboard accessibility: Test navigation using only Tab, Shift+Tab, and Enter keys. All interactive elements should be reachable.
    • Create accessible PDFs: Include proper headings, a logical reading order, alt text for images, and searchable text.
    • Support text resizing: Content should still work when zoomed to 200% without breaking the layout.
    • Apply ARIA correctly: ARIA landmarks and roles can help when HTML alone isn’t enough, but they should never replace semantic tags.

    Testing Your Output

    • Manual review: Always look at the content yourself. Automated tools can’t replace human judgment.
    • Assistive tech testing: Try screen readers, keyboard-only navigation, or voice input tools to see how real users will experience it.
    • Automated scans: Use tools like WAVE, or Lighthouse to quickly flag common issues, then verify the results manually.

    Running through this checklist regularly will catch most accessibility gaps before content reaches your audience.

    Building Accessibility Into Your AI Workflow

    The best way to make accessibility stick is to build it into the workflow, not tack it on at the end. Here are some ways to do that:

    • Use accessible prompts: When you ask AI to create content, guide it with instructions like “Write at an 8th-grade level with clear headings and descriptive link text.” This increases the chance that the draft will already meet accessibility standards.
    • Start with strong templates: Use page layouts, design systems, or document templates that are already set up with accessibility in mind. This reduces the risk of introducing barriers later.
    • Assign responsibility: Make accessibility review part of someone’s role in the publishing process so it doesn’t get skipped.
    • Iterate with feedback: If you notice that AI keeps generating inaccessible elements—like vague alt text or poor contrast—update your prompts or workflow so those issues don’t repeat.
    • Set clear standards: Document rules for headings, alt text, link labels, color use, and formatting. Apply these rules consistently so everyone on your team is aligned.

    By treating accessibility as a normal part of the process, AI-generated content becomes an asset to inclusion instead of a risk factor.

    Accessibility Isn’t Optional—Even with AI

    AI may be changing how quickly we create, but accessibility is what ensures that work actually connects with people. WCAG provides the framework, but it’s people—teams like yours—who make sure the digital world is usable for everyone.

    The risks of overlooking accessibility are real, from frustrated customers to lawsuits. But the rewards are greater: trust, inclusivity, and a digital presence that welcomes all. The good news is you don’t need to slow down to get it right. With the right checklist and habits built into your workflow, accessibility becomes part of how you publish—not an afterthought.

    At 216digital, we help businesses bring accessibility into every stage of content creation—including AI-generated content. If you’re unsure where you stand, consider scheduling a personalized ADA briefing with our team.

    It’s a practical next step toward a digital experience that truly works for everyone.

    Greg McNeil

    August 11, 2025
    Legal Compliance
    Accessibility, AI-driven accessibility, AI-generated content, WCAG Compliance, Web Accessibility, Website Accessibility
  • Don’t Wait for AI Accessibility Tools to Catch Up

    Don’t Wait for AI Accessibility Tools to Catch Up

    AI is everywhere right now. It’s drafting blog posts, churning out social captions, even scanning websites for compliance issues. And if you’ve been keeping up with the hype, you’ve probably noticed one claim in particular: that AI can solve accessibility.

    For a business moving at full speed, that promise sounds almost too good to pass up. Install a plugin, run a scan, check a box—done. But accessibility doesn’t work like that. These tools can point out some issues, sure, but they rarely fix the barriers that actually keep people with disabilities from using your site, your app, or your documents. The cracks stay hidden under a shiny patch.

    And those cracks matter. Real people get shut out of digital spaces. Companies expose themselves to lawsuits and financial hits. And maybe most importantly, the bigger goal—building technology that works for everyone—keeps getting delayed.

    This article takes a closer look at what AI tools really can (and can’t) do, and why waiting for automation to “catch up” is a risky bet. More than that, it gives you practical steps to start building accessibility into your digital strategy today—steps that create lasting, meaningful change.

    AI Is Exciting—but Not a Magic Bullet

    AI tools like AudioEye can scan sites, flag issues, and apply quick fixes in real time—like adding alt text, adjusting color contrast, or correcting heading levels. For busy teams, it feels like a shortcut to digital inclusion.

    But here’s the reality check: research shows AI accessibility tools typically catch only 20–30% of issues. That leaves a massive gap—and it’s a gap with real consequences for users who can’t access your content, and for your legal risk.

    What AI Accessibility Tools Miss

    Most AI accessibility tools and overlays don’t actually fix your code. They act like a layer on top of your site, attempting to correct problems as the page loads. The underlying barriers remain in your codebase, breaking accessibility where it matters most.

    Here are some of the common issues AI often misses or misinterprets:

    • Missing headings that prevent screen reader users from navigating efficiently.
    • Images with no alt text—or worse, incorrect auto-generated descriptions that mislead rather than help.
    • Links with vague text like “click here” that don’t explain their purpose.
    • Form fields with no labels, making it impossible for assistive tech users to complete them.
    • Required fields that aren’t marked as required.
    • Submit buttons with no clear labels, leaving users stuck at the finish line.

    These aren’t minor hiccups—they’re major roadblocks. And they can’t be “patched over” by automation.

    Even more importantly: AI doesn’t know how real people use your site. It doesn’t test whether your video player works with voice commands, whether your interactive map is navigable by keyboard, or whether your carousel is usable for someone with limited dexterity. Human judgment and lived experience are irreplaceable.

    AI Might Improve—Eventually

    Will AI accessibility tools improve? Absolutely. At some point, automation may be able to deliver more accurate fixes, faster and at scale. But that capability is years away—not weeks. Your users and your legal obligations can’t wait for that future to arrive.

    Legal Risk: You’re Responsible Today

    Accessibility laws don’t include a “wait until AI gets better” clause. The Americans with Disabilities Act (ADA), the European Accessibility Act (EAA), and Canada’s AODA all require accessible digital content right now.

    And the lawsuits are growing: in 2024, more than 4,000 ADA Title III lawsuits were filed in the U.S. alone. By the end of 2025, experts expect nearly 5,000. In the first quarter of 2025, nearly 200 suits specifically targeted companies that relied on overlays or AI accessibility tools to claim compliance—claims that didn’t hold up in practice.

    High-profile cases underscore the risk. In January 2025, the U.S. Federal Trade Commission fined accessiBe $1 million for deceptive claims that its AI product guaranteed WCAG compliance. The reality: it didn’t. And regulators, courts, and customers are paying attention.

    Accessibility Pays: Beyond Risk Avoidance

    Avoiding lawsuits matters, but accessibility is also an opportunity. About 20% of the global population lives with a disability. That’s one in five potential customers who may face barriers if your site isn’t accessible.

    Accessibility also improves usability for everyone:

    • Captions help not only people with hearing loss but also those in noisy environments.
    • High contrast improves readability in bright light or for anyone with color sensitivity.
    • Clear link text and consistent layouts make navigation easier and faster for all users.

    These changes lead to stronger customer loyalty, better SEO, and a brand reputation for being inclusive and trustworthy. Accessibility isn’t just compliance—it’s good business.

    How to Act Today—Practical Steps

    If automation isn’t enough, what’s the path forward? The good news: it’s clear and manageable.

    1. Test manually: Explore your site with assistive technologies like screen readers or voice navigation. Even better, involve people with disabilities in your testing process. Their feedback reveals barriers no scan will catch.
    2. Use automation wisely: Scanners and overlays can still help identify issues like missing alt text or low contrast. Just remember: they’re helpers, not full solutions.
    3. Adopt a hybrid model: Combine automation with human-led testing and remediation. Let AI handle repetitive checks, and let experts ensure usability and compliance.
    4. Integrate accessibility into your process: Make it part of everyday workflows—design, development, content creation, and media production. Fixing accessibility at the source saves time, money, and stress.

    Accessibility becomes much easier when it’s built into how your team works every day.

    Looking Ahead

    The future of AI accessibility tools is promising, but they’re not a replacement for human insight. Even as AI advances, accessibility will still require oversight, inclusive design, and empathy for how people actually use technology.

    For now, the choice is clear: don’t wait. The risks are here today, but so are the opportunities to create better digital experiences. Even small improvements—like labeling form fields or ensuring captions—make a real difference.

    By acting now, you reduce legal risk, improve usability, and position yourself to take advantage of AI when it’s truly ready.

    Ready to get started? Schedule an ADA briefing with 216digital to see where your digital content may fall short. Learn which tools can help, what requires expert attention, and how to build accessibility into your roadmap. Clear guidance, no hype—just a realistic plan for moving forward with confidence.

    Greg McNeil

    August 6, 2025
    Legal Compliance
    Accessibility, Accessibility Remediation, Ai and Overlay Widgets, AI-driven accessibility, Website Accessibility
  • AI Accessibility Platform or Just an Overlay?

    The digital accessibility space is flooded with promises. Some companies advertise sleek, one-click solutions to fix web accessibility issues overnight. They now call themselves an “AI accessibility platform” rather than what they truly are: overlays.

    It sounds good. Who wouldn’t want artificial intelligence to solve complex compliance problems automatically? But here’s the catch: most of these so-called AI accessibility platforms are just rebranded overlays—front-end widgets that apply a visual layer over a website to appear accessible. They rarely address the root issues. Even worse, they can give businesses a false sense of compliance and leave disabled users frustrated.

    What Is an Overlay, Really?

    A web accessibility overlay is a third-party tool that’s added to a site through a snippet of JavaScript. It tries to modify the user experience dynamically. Common features include contrast toggles, font size adjustments, keyboard navigation enhancements, and screen reader fixes.

    These overlays are easy to install and often marketed as a quick path to ADA or WCAG compliance. Some now claim to use AI to identify and fix accessibility issues in real-time. But while the buzzword changed, the fundamental technology hasn’t.

    The AI Smokescreen

    Labeling a product as an “AI accessibility platform” gives it an air of sophistication. But in many cases, artificial intelligence plays a minimal role—or none at all. Even when developers use AI to detect accessibility issues, it still can’t replace expert human review or hands-on code-level remediation.

    Here’s why that matters:

    • AI can miss context. It may detect that an image lacks alt text but can’t determine if the description is meaningful.
    • AI can’t restructure content. Accessibility isn’t just about fixing what’s visible—it’s also about semantic structure, logical flow, and proper HTML.
    • AI can’t interpret intent. True accessibility requires understanding the purpose of design and interaction elements. That takes human judgment.

    In short, AI might help flag issues, but it can’t fix them at scale with the nuance needed for real-world usability.

    The Real Risks of Relying on Overlays

    Many businesses adopt AI accessibility platform, believing they’re safe from lawsuits. They’re not. In fact, overlays are now being cited in accessibility lawsuits. Plaintiffs and advocacy groups argue that these tools are ineffective and even obstructive.

    The risks include:

    • Legal exposure. Courts have increasingly ruled that overlays do not ensure ADA compliance. Plaintiffs with disabilities have successfully sued companies using these tools.
    • Bad UX for disabled users. Overlays can conflict with screen readers, override user settings, or interfere with native assistive tech.
    • False security. Businesses relying on accessibility widgets might mistakenly believe they’re protected, overlooking critical accessibility issues that thorough audits and remediation would easily identify. In fact, in 2024 alone, 1,023 companies using accessibility widgets on their websites faced lawsuits.

    What Real Accessibility Looks Like

    True digital accessibility is not a checkbox or a plugin. It’s a commitment to inclusivity that starts in your codebase. That means:

    • Semantic HTML structure
    • Meaningful alt text
    • Keyboard navigability
    • Proper ARIA roles
    • Logical content order
    • Form labels and error identification

    These elements can’t be patched with JavaScript after the fact. They have to be built into the foundation of your site.

    Expert-Led Accessibility Works

    This is where companies like 216digital come in. Unlike overlay vendors, 216digital doesn’t promise overnight compliance. Instead, they deliver code-based accessibility services rooted in real expertise.

    Their process includes:

    • Manual audits by accessibility professionals
    • Comprehensive WCAG testing across devices and assistive technologies
    • Remediation services that fix issues in your site’s actual code
    • Ongoing support to maintain compliance over time

    This approach not only improves accessibility for users with disabilities but also strengthens your brand, SEO, and legal compliance.

    Don’t Fall for AI Accessibility Platform

    Rebranding overlays as “AI accessibility platforms” is a clever marketing move. But it doesn’t make them more effective. Businesses need to look past the buzzwords and focus on what truly matters: building accessible websites that work for real people.

    Overlays offer a temporary illusion of compliance. But for lasting accessibility, legal protection, and a genuinely inclusive user experience, expert-led, code-based solutions are the only path forward.


    If you’re serious about accessibility, skip the overlay. Choose real remediation. Choose a partner like 216digital who understands that accessibility isn’t just a feature—it’s a foundation.

    Start by filling out the contact form below to schedule your complimentary ADA briefing with 216digital today.

    Greg McNeil

    April 2, 2025
    Legal Compliance
    Accessibility, Ai and Overlay Widgets, AI-driven accessibility, Overlay, WCAG, Web Accessibility, Widgets
  • AI-Driven Accessibility: Hype vs. Reality

    AI is everywhere—powering self-driving cars, filtering spam emails, and even generating images out of thin air. Naturally, it has found its way into web accessibility, promising to make websites easier to navigate for people with disabilities.

    At first glance, AI-driven accessibility seems like a game-changer. A tool that scans a website, detects issues, and applies fixes in real-time—no costly audits, no manual updates. The promise is enticing: instant compliance, a better user experience, and minimal effort. For businesses seeking a quick fix, it sounds like the perfect solution.

    But is it really that simple, or is it just hype?

    The Hype of AI-Driven Accessibility

    AI accessibility solutions are marketed as a fast and effortless way to make websites compliant with accessibility laws and more user-friendly for people with disabilities. These tools use machine learning and automation to scan websites for accessibility issues, detect missing alt text, adjust contrast, and improve keyboard navigation. The idea is that AI can take the burden off businesses, making accessibility seamless and automatic.

    Companies selling AI accessibility promise a range of benefits:

    • Instant fixes for common accessibility issues like alt text, contrast adjustments, and heading structure corrections.
    • Enhanced user experience, with real-time captions, AI-generated image descriptions, and improved navigation.
    • Time and cost savings, reducing the need for expensive audits and manual accessibility updates.

    Some AI tools even claim to predict user needs and adjust websites dynamically, removing barriers before they become a problem. The pitch is simple: AI makes accessibility compliance quick, cost-effective, and easy.

    But can it actually deliver?

    The Reality: Limitations and Challenges

    AI-driven accessibility tools aren’t the magic solution they claim to be. In many cases, they fail to address deeper accessibility issues and even create new barriers. Here’s why:

    1. AI-driven Accessibility is Superficial

    While AI can generate alt text, it often provides vague or inaccurate descriptions. A picture of a service dog might be labeled as “dog” with no context, leaving a blind user without crucial details. Infographics and charts? AI struggles with those too, often giving meaningless labels instead of useful explanations.

    Automated contrast adjustments and heading restructuring may technically meet compliance guidelines, but that doesn’t mean they work in real-world use. These fixes can break website layouts, confuse users, and sometimes even make navigation worse rather than better.

    2. AI Can Introduce New Barriers

    AI tools often interfere with how people with disabilities already navigate the web. Screen reader users, for example, may encounter misplaced labels, incorrect headings, or navigation menus that suddenly stop working. Some AI tools even override user settings, blocking assistive technology that people rely on.

    Overlays—those AI-powered add-ons that promise “instant accessibility”—are particularly notorious for making things worse. Instead of removing barriers, they often add unnecessary complexity, frustrating users rather than helping them.

    3. AI-driven Accessibility Misses Barriers

    Studies show that AI can only detect 20-30% of accessibility barriers, meaning that websites relying solely on AI remain 70-80% inaccessible. Many critical accessibility issues require human judgment and testing—something AI simply cannot replicate.

    At 216digital, we have seen a sharp rise in lawsuits targeting screen reader-related issues that AI fails to detect. These include missing ARIA labels, poor keyboard navigation, and dynamic elements that don’t update correctly for assistive technology users. Businesses that trust AI for compliance often realize too late that their sites remain inaccessible and legally vulnerable.

    4. False Sense of Compliance

    Many businesses assume that adding an AI overlay or accessibility widget makes their website compliant with the Americans with Disabilities Act (ADA). But compliance is about actual usability—not just ticking a box.

    In 2024 alone, 1,023 companies using AI overlays were sued for accessibility violations according to Useablnet’s 2024 End of the Year Report. The reality is that these tools do not make a site fully accessible; they often only mask deeper issues. Lawsuits and regulatory actions continue to prove that true accessibility requires meaningful fixes, not just automated patches.

    Case Studies and Real-World Examples

    Many companies have learned the hard way that AI-driven accessibility doesn’t work.

    1. The Failure of AI-driven Accessibility

    One of the biggest offenders? accessiBe—an AI overlay that promises instant accessibility. Thousands of users with disabilities have reported that it makes websites harder to use, not easier. These overlays don’t fix the real problems; they just add a layer of automated code that interferes with assistive technology.

    2. Frustrated Users Speak Out

    A New York Times article, For Blind Internet Users, the Fix Can Be Worse Than the Flaws, highlighted how AI-driven overlays create more frustration than solutions. Blind advocate Mr. Perdue put it plainly: “I’ve not yet found a single one that makes my life better. I spend more time working around these overlays than I actually do navigating the website.”

    This isn’t just one person’s experience—over 862 accessibility advocates and developers have signed an open letter urging businesses to stop using these flawed AI solutions. Even the National Federation of the Blind has condemned AI-driven accessibility tools, calling them inadequate and ineffective.

    3. The Legal Consequences

    If the ethical concerns don’t scare businesses away, the lawsuits should. In 2024 alone, 1,023 companies were sued for relying on AI-driven overlays instead of making genuine accessibility improvements.

    Recently, major compliance agreements have begun explicitly stating that AI-driven overlays do not meet accessibility standards. Companies using tools like AudioEye, accessiBe, and Accessibility Spark are at higher risk of lawsuits than those making real accessibility changes.

    The Necessity of Human Oversight

    If AI isn’t the solution, what is? People.

    1. Accessibility Experts Know What AI Doesn’t

    Human experts understand accessibility in a way AI never will. They know how people actually use websites, what works, and what doesn’t. They can ensure websites are genuinely accessible—not just compliant on paper.

    2. AI and Humans Can Work Together

    AI isn’t completely useless, but it needs to be used as a tool, not a crutch. Real people need to review, test, and implement fixes.

    3. Accessibility is an Ongoing Process

    Web accessibility isn’t something you fix once and forget. It requires regular monitoring and updates. That’s where a11y.Radar from 216digital comes in—it provides continuous accessibility monitoring to keep websites truly usable for everyone.

    The Future of AI-driven Accessibility

    AI is improving, but it’s nowhere near ready to handle accessibility on its own. Moving forward, we need:

    • Better AI training that includes input from people with disabilities.
    • Stronger regulations to ensure AI tools don’t create new barriers.
    • More user involvement so that AI tools are built with real-world accessibility needs in mind.

    Conclusion

    AI-driven accessibility tools might sound appealing, but they’re not the answer. Automated solutions—especially overlays—often create more problems than they solve. If businesses truly care about accessibility, they need to invest in real solutions that actually work.

    The bottom line? AI can assist, but human expertise is irreplaceable.

    Want accessibility done right? Schedule an ADA briefing with 216digital today and get a roadmap to real, lasting accessibility.

    Greg McNeil

    February 19, 2025
    WCAG Compliance
    Accessibility, Ai and Overlay Widgets, AI-driven accessibility, Overlay, Website Accessibility

Find Out if Your Website is WCAG & ADA Compliant







    216digital Logo

    Our team is full of expert professionals in Web Accessibility Remediation, eCommerce Design & Development, and Marketing – ready to help you reach your goals and thrive in a competitive marketplace. 

    216 Digital, Inc. BBB Business Review

    Get in Touch

    2208 E Enterprise Pkwy
    Twinsburg, OH 44087
    216.505.4400
    info@216digital.com

    Support

    Support Desk
    Acceptable Use Policy
    Accessibility Policy
    Privacy Policy

    Web Accessibility

    Settlement & Risk Mitigation
    WCAG 2.1/2.2 AA Compliance
    Monitoring Service by a11y.Radar

    Development & Marketing

    eCommerce Development
    PPC Marketing
    Professional SEO

    About

    About Us
    Contact

    Copyright 2024 216digital. All Rights Reserved.