Accessibility as an SEO Strategy: How Inclusive Design Helps AI Crawl and Understand Your Site

Quick Summary

The Semantic HTML: The Foundation for AI-Friendly Accessibility section provides further insight into how structured markup enhances both accessibility and SEO. For instance, the table highlights semantic HTML's role in improving crawlability, as discussed in that section.

When addressing alt text implementation, Image Alt Text and AI-Generated Summaries explains how descriptive image labels benefit both users and AI systems. This aligns with the "Quick Summary" table’s emphasis on alt text as a low-effort, high-impact fix.

For actionable steps on conducting audits and prioritizing accessibility improvements, Implementing Accessibility as an SEO Strategy outlines a structured approach, including tools like Lumar mentioned in the "Practical Next Steps" section.

Why Accessibility Matters for SEO

Accessibility and SEO are deeply intertwined, with inclusive design directly influencing how search engines and AI systems interpret and rank websites. Over 94.8% of the top 1 million websites globally fail to meet basic Web Content Accessibility Guidelines (WCAG) standards, highlighting a widespread gap in digital inclusivity. This failure isn’t just a compliance issue-it’s a missed opportunity for SEO. Search engines like Google prioritize content that is easy to crawl and understand, and accessibility features such as semantic HTML, alt text for images, and structured headers create clear pathways for crawlers. When these elements are absent, search engines struggle to parse content accurately, leading to lower visibility in results.

Accessibility Improves Crawlability and AI Understanding

Search engines and AI tools rely on structured, predictable code to extract meaning from web pages. Semantic HTML-using tags like <header>, <nav>, and <article> instead of generic <div> elements-gives both users and machines context about a page’s layout. For example, a screen reader uses header tags to navigate sections, while an AI might use the same structure to generate summaries for features like Google’s AI Overviews. Without these cues, AI systems can misinterpret content, leading to incomplete or irrelevant results.

Real-world SEO improvements from accessibility fixes are well-documented. One study found that optimizing alt text alone can increase image search visibility by 30% or more. Similarly, adding descriptive link text (e.g., “Read our accessibility guide” instead of “Click here”) helps crawlers understand the purpose of linked pages. These changes don’t just benefit users with disabilities-they also align with search engine priorities, creating a feedback loop where accessibility enhances rankings, which in turn drives more traffic. See the Image Alt Text and AI-Generated Summaries section for more details on how alt text impacts both users and AI systems.

Who Benefits and Why It Matters Now

The primary beneficiaries of accessibility-driven SEO strategies include businesses, marketers, and users with disabilities. For businesses, the financial incentive is clear: the global disability market represents $13 trillion in spending power. By making websites accessible, companies tap into this audience while reducing legal risks from accessibility lawsuits. Marketers see direct gains through improved search visibility and user engagement metrics like lower bounce rates. Users with disabilities, meanwhile, gain equal access to information, which is both ethical and legally mandated in many regions.

AI tools are amplifying the importance of accessibility in SEO. Large language models (LLMs) like those powering Google’s AI Overviews or Perplexity rely on high-quality, accessible text to generate accurate responses. If a webpage lacks proper formatting or uses inaccessible multimedia, AI systems may exclude it from summaries or recommendations. This creates a new layer of competition: websites that ignore accessibility risk being overlooked not just by human users, but by the algorithms shaping modern search experiences. Building on concepts from the Semantic HTML: The Foundation for AI-Friendly Accessibility section, structured code ensures AI systems can effectively process and prioritize content.

Practical Steps to Align Accessibility with SEO

Implementing accessibility as an SEO strategy requires a focus on foundational elements:

• Semantic HTML: Replace generic tags with descriptive ones to clarify content roles.
• Alt Text: Describe images concisely, balancing detail with brevity. A 2025 study found pages with optimized alt text saw a 15–20% increase in organic traffic.
• Keyboard Navigation: Ensure all interactive elements work without a mouse, improving both usability and crawlability.
• ARIA Landmarks: Use these to define regions like menus or footers, guiding screen readers and search engines.

By addressing these areas, websites not only meet accessibility standards but also align with evolving SEO best practices. The result is a site that performs better in search results, delivers a superior user experience, and remains competitive in an AI-driven digital landscape.

Semantic HTML: The Foundation for AI-Friendly Accessibility

Semantic HTML provides the structural foundation that both users and machines rely on to interpret web content. Unlike generic tags like <div> or <span>, semantic elements such as <header>, <nav>, and <article> explicitly define the purpose of each section. This clarity ensures screen readers can navigate content logically for users with disabilities while enabling search engines and AI systems to extract meaning accurately. For example, a

The Importance of Semantic HTML for Accessibility and AI

Search engines and AI models process websites similarly to how humans do: by identifying patterns and context. When developers use heading tags (<h1> to <h6>), they create a hierarchy that mirrors the structure of printed documents. A <h1> tag should define the page’s primary topic, followed by <h2> for major sections and

Semantic HTML also reduces the need for screen readers to infer layout from HTML. A <nav> element paired with aria-label attributes ensures keyboard users and voice-assisted tools can access menus without confusion. By prioritizing semantic structure, developers create a single source of truth for all users, whether they’re interacting with a site through a browser, a screen reader, or an AI-powered search bot.

Structuring Content with Proper Heading Hierarchy

A well-organized heading structure is critical for both usability and search engine indexing. Start with one <h1> per page to signal the main topic, then use <h2> for primary sections. Subheadings should follow a logical sequence, avoiding skipped levels like jumping from <h2> to <h4>. This hierarchy not only guides human readers but also helps crawlers determine content relevance. See the Implementing Accessibility as an SEO Strategy section for strategies on maintaining consistent heading structures to optimize for both accessibility and search visibility.

Consider a recipe website:

This example uses semantic tags to define navigation (<nav>), lists (<ul>, <ol>), and headings, ensuring clarity for users and machines. Skipping <h1> tags or overusing <div> elements would obscure these relationships, making it harder for screen readers and crawlers to function effectively.

Best Practices for Semantic HTML Implementation

To maximize accessibility and SEO, combine semantic tags with additional metadata. ARIA (Accessible Rich Internet Applications) attributes like aria-label or aria-describedby add context where HTML alone is insufficient. For example, a button with aria-label="Search" clarifies its purpose for screen readers. However, overusing ARIA can introduce errors-rely on native HTML elements whenever possible.

Microdata or JSON-LD can further enhance machine readability by defining entities like recipes, articles, or events. A recipe page might include:

<div itemscope itemtype="https://schema.org/Recipe">
 <h1 itemprop="name">Spaghetti Carbonara</h1>
 <div itemprop="ingredients">Spaghetti, Eggs, Pancetta</div>
</div>

This metadata helps search engines display rich results, like recipe snippets in Google. Tools like AnyPost.ai’s AI Content Generator can automate semantic structure generation, but manual review is essential to ensure accuracy. As discussed in the Measuring Accessibility and AI Crawl Success section, verifying the effectiveness of these implementations is critical for long-term performance.

Image Alt Text and AI-Generated Summaries

Image alt text serves as a bridge between visual content and both users with disabilities and AI systems. For screen readers, it translates images into spoken or braille descriptions, ensuring equal access to information. For AI-generated summaries, it provides the textual context needed to interpret visual elements accurately. Without descriptive alt text, AI models may mislabel images or overlook their relevance entirely. This is especially critical for complex visuals like infographics, charts, or abstract art, where automated tools struggle to infer meaning without human input. Building on concepts from the Semantic HTML section, alt text complements structured markup by adding descriptive context that AI systems rely on to understand page content.

Effective alt text balances brevity with clarity. Consider an image of a product: "Waterproof hiking boots in black with red laces, designed for rugged outdoor terrain." This example describes the item’s key features while avoiding unnecessary details like brand names unless relevant. For abstract or symbolic images, focus on the emotional or conceptual message. An abstract painting might use alt text like "Modern abstract artwork featuring contrasting shades of blue and gold, evoking a sense of calm and energy." These descriptions help AI systems categorize images correctly and improve their ability to generate context-aware summaries.

Best practices for writing alt text include prioritizing user intent and search relevance. Start by asking: What is the image’s purpose on this page? If it’s a data visualization, summarize the main takeaway rather than listing all data points. For product images, highlight attributes like color, size, or usage. Avoid generic phrases like "image of" or "picture of"-instead, focus on actionable details. Keywords should be included naturally, aligning with the page’s content strategy. For example, a recipe site might use "Golden-brown chocolate chip cookies on a white plate, freshly baked" to reinforce search terms like "homemade cookies" or "baking recipes."

The impact of alt text extends beyond accessibility. Search engines use it to index images in visual search results, directly affecting traffic from platforms like Google Images. A well-crafted alt text increases the likelihood of an image appearing in searches related to its content. AI-generated summaries, such as those in Google’s AI Overviews, also rely on this text to construct concise page summaries. As mentioned in the Why Accessibility Matters for SEO section, accessibility improvements like alt text enhance how search engines interpret and rank content. If an AI encounters an image of a "solar-powered home with a rooftop panel array and a charging electric vehicle," it can infer the page’s focus on renewable energy solutions. Poorly written or missing alt text forces AI systems to guess, often leading to irrelevant or incomplete summaries.

Tools like AnyPost.ai’s Smart Linking feature automate alt text generation by analyzing image content and suggesting descriptive text. While automation saves time, manual review is essential to ensure accuracy and alignment with brand voice. See the Implementing Accessibility as an SEO Strategy section for more details on balancing technical execution with user-centric design. Start by using AI-generated suggestions as a baseline, then refine them to reflect nuance or specificity. For example, an automated tool might describe a photo as "A group of people walking," but a revised version could clarify, "A diverse group of hikers trekking up a mountain trail at sunrise." This level of detail enhances both accessibility and search performance, making it a cornerstone of inclusive SEO strategy.

Internal Linking and Site Architecture for AI

Internal linking serves as the backbone of a site’s architecture, guiding both users and AI crawlers through interconnected content. For AI systems, these links act as signals that establish relationships between pages, clarify content hierarchy, and distribute authority across the site. When implemented effectively, internal links help search engines prioritize important pages while reducing the risk of orphaned content. The foundation of this strategy lies in clear, descriptive anchor text-the clickable text in a link-that provides context for both users and AI about the linked page’s purpose. As mentioned in the Semantic HTML: The Foundation for AI-Friendly Accessibility section, semantic structure supports this clarity by organizing content logically, which complements the role of anchor text. For instance, using “explore our web accessibility guidelines” instead of “click here” gives crawlers explicit clues about the destination content.

The Role of Internal Linking in Site Architecture and AI Crawling

A well-structured site architecture ensures AI can efficiently crawl and index pages without getting lost in disjointed or redundant content. Internal links create a logical flow that mirrors how users navigate, which search engines replicate to understand your site’s thematic focus. For example, a blog about digital marketing might use category pages as central hubs, linking to individual posts on SEO, content strategy, and analytics. This hub-and-spoke model not only organizes content but also reinforces topical relevance for AI by clustering related pages under broader themes.

Search engines rely on these link structures to determine which pages deserve higher priority. If an AI crawler encounters a page with multiple high-quality internal links, it may interpret that page as more authoritative or central to the site’s purpose. Conversely, pages with few or no internal links risk being overlooked entirely. To maximize this effect, ensure every new piece of content connects naturally to existing hubs and related posts. For instance, a new article on “inclusive design principles” could link back to a central accessibility guide while also cross-referencing older posts on color contrast and font readability.

Effective Internal Linking Strategies for AI Understanding

The hub-and-spoke model is one of the most effective strategies for organizing content in a way that aligns with AI’s expectations. Hubs act as comprehensive resource pages that link to more specific subtopics, forming a network that simplifies navigation. For example, an educational website might create a hub titled “Web Accessibility 101,” which links to pages on screen reader compatibility, keyboard navigation, and semantic HTML. Each subtopic then links back to the hub and connects to related content, creating a cohesive structure that AI can easily map.

Contextual linking within content is equally critical. Place links where they add value, such as defining terms or expanding on concepts. For example, when discussing “ARIA attributes” in a technical article, link directly to a dedicated explanation of their role in accessibility. See the Semantic HTML: The Foundation for AI-Friendly Accessibility section for more details on how ARIA attributes integrate with semantic structure. Avoid overloading pages with excessive links, which can confuse crawlers and dilute authority. Instead, focus on linking to the most relevant and high-quality pages. Tools like AnyPost.ai’s Smart Linking feature automate this process by analyzing content and suggesting contextually appropriate links, ensuring consistency without manual effort.

Best Practices for Implementing Internal Links and Accessibility Standards

To strengthen internal linking for AI, combine technical SEO practices with accessibility principles. ARIA (Accessible Rich Internet Applications) attributes improve screen reader compatibility for users while providing additional context for crawlers. For instance, using aria-label on navigation menus clarifies their purpose, helping AI interpret their function. Similarly, microdata and schema markup can enhance how search engines categorize content, making it easier for AI to associate pages with specific topics. Building on concepts from the Why Accessibility Matters for SEO section, structured data like microdata reinforces the relationship between accessibility and SEO by providing explicit signals to crawlers.

When implementing these practices, prioritize consistency. Use ARIA attributes sparingly and only where necessary to avoid cluttering code. For microdata, apply standardized schema types that align with your site’s content goals. By integrating these practices with a robust internal linking strategy, you create a site architecture that is both user-friendly and optimized for AI understanding.

Measuring Accessibility and AI Crawl Success

Measuring accessibility and AI crawl success requires a structured approach that combines technical tools, data analysis, and strategic adjustments. Start by identifying key metrics that reflect both user experience and search engine performance. Crawl rate-how quickly search engines discover and process your pages-and indexing status-whether pages are included in search results-are foundational indicators. Lower crawl rates often signal technical barriers, such as poor site architecture or missing metadata, while incomplete indexing may suggest accessibility issues that hinder AI understanding. Building on concepts from the Internal Linking and Site Architecture for AI section, poor site architecture can significantly impede crawlers.

Key Metrics and Tools for Evaluation

To track these metrics, integrate tools like Google Search Console and Ahrefs. Google Search Console provides real-time data on crawl errors, indexing coverage, and mobile usability, which directly correlate with accessibility. For example, if the console flags "missing alt text" errors, it highlights accessibility gaps that also confuse AI crawlers. See the Image Alt Text and AI-Generated Summaries section for more details on the role of alt text in accessibility and search performance. Ahrefs complements this by analyzing backlinks and content performance, revealing how accessibility improvements impact SEO visibility.

For deeper accessibility audits, automated tools like Lumar evaluate semantic HTML, contrast ratios, and keyboard navigation compliance. These tools generate scores that align with the Web Content Accessibility Guidelines (WCAG), ensuring your site meets global standards. As mentioned in the Semantic HTML: The Foundation for AI-Friendly Accessibility section, semantic HTML is critical for both users and machines. Pair these with manual testing-using screen readers or browser extensions-to catch nuanced issues like mislabeled buttons or unclear navigation.

Best Practices for Tracking and Analysis

Regularly exporting data from these platforms into visual dashboards helps identify trends. For instance, a declining crawl rate after a site update might indicate newly introduced barriers, such as excessive JavaScript that delays AI parsing. Use line graphs to compare accessibility scores before and after design changes, making it easier to attribute performance shifts to specific actions.

Set up automated alerts for critical metrics. If indexing drops below a threshold, or if new accessibility violations emerge, these alerts prompt immediate troubleshooting. For teams managing large sites, scheduling weekly reports from tools like Lumar ensures consistent monitoring without manual overhead.

The Role of AI in Measuring Success

Machine learning algorithms now play a significant role in analyzing crawl and accessibility data. AI can predict which pages are most likely to cause crawl errors based on historical patterns, such as repetitive content or broken links. It also identifies correlations between accessibility fixes and improved search rankings. For example, adding structured data (like schema markup) not only aids screen readers but also helps AI crawlers extract context more efficiently, boosting visibility in features like Google’s AI Overviews.

Platforms like Lumar leverage AI to automate audits, flagging issues like low-contrast text or missing form labels while suggesting fixes. These tools reduce the manual effort of evaluating thousands of pages, enabling teams to prioritize high-impact changes. Over time, machine learning models refine their accuracy by learning from user interactions-such as which fixes lead to the greatest SEO gains-creating a feedback loop that improves both accessibility and search performance.

By combining these metrics, tools, and AI-driven insights, you create a feedback system that turns accessibility into a proactive SEO strategy. Regular audits, data visualization, and automated monitoring ensure your site remains inclusive and optimized for both users and crawlers.

Implementing Accessibility as an SEO Strategy

Implementing accessibility as an SEO strategy requires a structured approach that balances technical execution with user-centric design. Start by auditing your site’s current accessibility using tools like Lumar’s optimization platform, which identifies gaps in semantic HTML, image alt text, and navigation structure. Semantic HTML forms the foundation of accessible content-use h1 to h6 tags to create a logical heading hierarchy, ensuring screen readers and search engines can parse your content effectively. As mentioned in the Semantic HTML: The Foundation for AI-Friendly Accessibility section, using elements like <nav>, <main>, and <footer> improves both accessibility and AI crawlability. For example, avoid skipping heading levels (e.g., jumping from h2 to h4

Product Features

Step 1: Optimize Content with Alt Text and Descriptive Links

Image alt text is critical for both accessibility and SEO. Write concise, descriptive alt attributes that explain an image’s purpose, such as “A woman using a smartphone to browse an e-commerce site” instead of generic labels like “image123.jpg.” See the Image Alt Text and AI-Generated Summaries section for more details on crafting effective alt text. Similarly, anchor text should clarify the destination of links. Replace phrases like “click here” with descriptive text like “Download our accessibility guide.” This practice helps screen readers navigate your site and gives search engines context to index your pages accurately.

Step 2: Build an Accessible Site Architecture

A well-structured site improves user experience and AI crawlability. Organize content using landmark elements like <nav>, <main>, and <footer> to define regions clearly. For instance, wrap your primary navigation in <nav aria-label="Main Menu"> to signal its purpose to assistive technologies. Building on concepts from the Internal Linking and Site Architecture for AI section, ensure your site’s information architecture follows a logical flow-group related pages under relevant categories and use breadcrumb trails to reduce navigation complexity.

Step 3: Leverage Tools for Automation and Audits

Tools like AnyPost.ai streamline accessibility improvements by automating repetitive tasks. Its AI Content Generator suggests alt text for images and optimizes headings for readability, while Smart Linking identifies opportunities to add contextual internal links. Pair these tools with manual audits using Siteimprove’s accessibility crawler, which highlights issues like low color contrast or missing form labels. As discussed in the Measuring Accessibility and AI Crawl Success section, regular audits (quarterly is ideal) ensure compliance with evolving standards and maintain AI-friendly SEO.

Maintaining Accessibility and Addressing Challenges

Accessibility requires ongoing effort. Budget constraints often limit resources, but prioritizing high-impact changes-like adding alt text or fixing broken links-delivers measurable SEO benefits quickly. For teams with limited expertise, platforms like Lumar offer automated fixes for common accessibility issues, reducing manual labor. However, avoid relying solely on automation; human testing with screen readers or keyboard navigation uncovers nuanced problems that tools might miss.

Overcoming Common Obstacles

A frequent challenge is balancing design aesthetics with accessibility. For example, decorative images may lack alt text, but adding alt="" (an empty attribute) signals they’re non-essential. Similarly, complex data visualizations require text-based summaries to remain accessible. When time or budget limits accessibility work, start with high-traffic pages and expand incrementally. The business case for accessibility-highlighted in Lumar’s research-shows that inclusive design reduces legal risks and expands audience reach, making it a strategic priority for long-term SEO success.

By integrating accessibility into your SEO workflow, you create a user-first web environment that aligns with AI’s evolving ability to interpret and rank content. Tools like AnyPost.ai and Lumar provide actionable insights, but sustained success depends on a culture of continuous improvement-auditing, testing, and refining your approach to meet the needs of all users.

Conclusion and Next Steps

Accessibility strengthens SEO by making websites more navigable for both users and AI systems. When you prioritize inclusive design, you improve AI crawling, enhance content clarity, and expand your audience reach. Search engines like Google increasingly rely on AI to interpret content, and accessible practices-such as structured headings, alt text for images, and semantic HTML-directly support this process. Building on concepts from the Semantic HTML: The Foundation for AI-Friendly Accessibility section, semantic elements like <header> or <nav> provide clear signals for crawlers and users alike.

Take Immediate Action to Improve Accessibility

Start with an audit using tools designed for scalability and precision. Platforms like Lumar’s optimization suite analyze accessibility alongside SEO metrics, identifying gaps in code structure, contrast ratios, or navigation flow. For example, its automated crawls highlight missing alt attributes or improper heading hierarchies-common barriers for screen readers and search bots alike. See the Image Alt Text and AI-Generated Summaries section for more details on how alt text bridges visual content for both users and AI systems. Once you identify issues, prioritize fixes that have dual benefits: adding descriptive alt text improves image SEO and aids visually impaired users, while semantic HTML enhances both crawler efficiency and keyboard navigation.

For smaller teams, manual checks remain essential. Use browser extensions to test contrast compliance or validate form labels. The Content Accessibility Guide outlines practical steps, such as avoiding CAPTCHAs that block screen readers or ensuring video transcripts are searchable. Every adjustment reduces friction for users and search engines, gradually boosting your site’s visibility in AI-driven results.

Measure Progress and Adapt Strategies

Accessibility isn’t a one-time fix-it requires continuous monitoring. Integrate tools like Google Search Console to track crawl errors that might stem from inaccessible content. As mentioned in the Measuring Accessibility and AI Crawl Success section, pairing technical audits with AI-specific metrics ensures alignment with evolving algorithms. For instance, if a page’s structured data is mislabeled, both rich snippets and screen readers fail to interpret it correctly. Pair this with AI-specific metrics: Google’s AI Overviews favor content that’s clearly organized and contextually labeled, so track how accessibility updates correlate with increased snippet visibility.

Training is equally vital. Encourage your team to adopt inclusive habits, such as writing concise headings or avoiding color-only cues for information. The Microsoft Inclusive Design Toolkit offers workshops to build this mindset. Over time, these practices become second nature, ensuring new content remains accessible without retrofitting.

After implementing Lumar’s recommendations, our bounce rate dropped by 18% while organic traffic grew 25% in six months.

By treating accessibility as an ongoing strategy, you align with both user needs and algorithmic priorities. Start small, measure outcomes, and scale improvements iteratively. The result is a site that ranks higher, serves more users, and adapts to the AI-powered future of search.

Frequently Asked Questions

1. Why is accessibility important for SEO?

Accessibility is vital for SEO because it enhances how search engines and AI systems crawl and interpret websites. Features like semantic HTML, alt text, and structured headers create clear pathways for crawlers, making it easier for AI to understand content contextually. This alignment with search engine algorithms improves visibility in results. For example, the article notes that 94.8% of top websites fail WCAG standards, highlighting that accessibility isn’t just ethical but a strategic SEO advantage.

2. How does semantic HTML improve SEO?

Semantic HTML uses specific tags like <header>, <nav>, and <article> instead of generic <div> elements to define a page’s structure. This provides context for both users (e.g., screen readers) and AI systems, enabling crawlers to parse content more effectively. The article emphasizes that semantic markup directly supports AI-driven features like Google’s AI Overviews by making content more structured and predictable, which search engines prioritize for ranking.

3. What role does alt text play in SEO and accessibility?

Alt text describes images using descriptive labels, benefiting both users with visual impairments and search engines. For SEO, it helps crawlers understand image content, improving visibility in image search results. The article cites a study showing alt text optimization can boost image search visibility by 30% or more. Additionally, AI systems rely on alt text to generate accurate summaries, ensuring content is interpreted correctly across platforms.

4. What tools can help with accessibility audits?

Tools like Lumar, mentioned in the article, streamline accessibility audits by identifying issues such as missing alt text or improper header structures. These tools automate the process of checking WCAG compliance, allowing businesses to prioritize fixes efficiently. The article recommends using such tools as part of a structured approach to implement accessibility improvements, ensuring both user inclusivity and SEO gains.

5. How do structured headers impact SEO?

Structured headers (<h1>, <h2>, etc.) organize content hierarchically, making it easier for crawlers and users to navigate. The article explains that descriptive header text (e.g., “Accessibility Improves Crawlability”) helps AI systems and search engines grasp a page’s topic flow, improving relevance scores. Screen readers also use headers to guide users, reinforcing that accessibility and SEO goals align through clear content organization.

6. Can improving accessibility increase website traffic?

Yes, enhancing accessibility often boosts traffic by making content more discoverable and usable. The article highlights that fixing accessibility issues like alt text or semantic HTML can lead to higher search rankings, as crawlers prioritize well-structured, accessible sites. For example, optimizing alt text alone has been shown to increase image search visibility significantly, driving more organic traffic to the site.

7. What are the first steps to implement an accessibility SEO strategy?

Begin by conducting an accessibility audit using tools like Lumar to identify gaps (e.g., missing alt text or non-semantic HTML). Prioritize fixes such as adding descriptive alt text, using semantic HTML, and structuring headers logically. The article recommends following a step-by-step approach, starting with low-effort, high-impact changes, to gradually align with WCAG standards while improving SEO performance.