The Latest Must-Dos for AI Search Visibility

In this piece, you’ll learn:

• Why crawlability and indexability come before any on-page optimization matters for AI visibility
• What meta descriptions can and can’t do for AI citations versus traditional snippets
• How alt text serves accessibility first, AI comprehension second — not the other way around
• Where image metadata and provenance (EXIF, IPTC, C2PA) fit into AI trust signals
• Why schema markup clarifies meaning without guaranteeing AI visibility
• How to measure AI visibility now that Search Console reports generative AI impressions

In our corner of the Universe, there is always a change in AI visibility with one or another of the search algorithms.  Personally, I monitor my clients’ AI visibility across all the different verticals we serve daily. One thing is clear: the pace of change in search has only been accelerating in the past few years. AI Overviews now make up nearly 65% of all search results on Google, and AI summaries have become the main gist of every result before people click a link. Tools like ChatGPT, Perplexity, and Claude answer questions directly instead of showing a regular search results page. Still, many SEO tips follow the same checklist. It’s still the fundamentals, but how you do it is different. Now it’s not just about ranking, but about understanding, pulling from, and referencing your content.

 

It is a good idea to refresh one’s memory of some of the basics of on-page optimization. Meta descriptions, alt text, image metadata, and schema markup are four important ones. The above are just some of the factors involved in making AI search visible. The basics such as fresh content, crawlability, indexability, originality, structure, links, and authority remain most important. These four practices enhance clarity, accessibility, search appearance, and machine readability. This guide describes each and how they work together.

Before you work on any of the 4 elements, check whether your page is accessible. To be included in Google’s AI Overviews and AI Mode, your page should be indexed and appear in Google Search with a snippet. No additional technical preparations are needed for these AI features. If you want your content to be found, summarized, cited, and linked to, OpenAI recommends granting OAI-SearchBot access to your site for ChatGPT Search. Meta description or schema changes aren’t necessarily as impactful as things like robots.txt, noindex tags, authentication, bot protection, CDN or WAF settings, and JavaScript code.

Meta descriptions help control how a page appears on search engine results pages. Here is a blog post of ours from a couple of months ago: “SEO Can’t Fix a Broken Brand Reputation!”

Optimization can help make your website visible, but it cannot fix whatever issue you are having with your website’s operations or reputation. So, the meta-description for that article could be “SEO can help make your brand easier to find, but it can’t fix your brand’s reputation. Here are some operational fixes, and what to do to help build brand trust.”

That lets the searcher know what the article is about and how the page is presented. However, there’s no proof that an AI platform reviews that meta description and, based on this, decides to quote the article.

Alternative text (alt text) is a text alternative to non-text content, including images, and is required for accessibility reasons, above all. Image metadata can convey rights, creator, licensing, and provenance information.

Schema markup communicates the meaning of entities and the relationships between them in a machine-readable way, which can help the page qualify for rich results supported by the schema. Article schema can explicitly indicate to an algorithm that this is an article, it’s written by Nami Ataee, published by Dream Warrior Group, published on May 7, 2026, and it’s about SEO, reputation, marketing, and such.

Google’s current documentation does not regard the meta description as a required ranking element for AI search, but only as a source for the snippet that appears in search. Google can create snippets from page content if it is a more appropriate response to the query, so hours spent creating snippets may not be as useful as they were several years ago. That changes the rationale behind the old game of counting characters and makes a concise, accurate description of the pages that count most useful.

Meta descriptions are still relevant. While they might not directly influence AI ranking, they do play a role in page visibility in search engines and provide greater control over your message. A meta description is useful for your most important pages, where it defines what the page is about and helps Google provide a strong snippet on the search results page. If Google does rewrite your description, they take bits that are relevant to the search query and assembles them into your description. This can be effective sometimes, but other times it can be confusing and difficult to read. If your brand value is important, don’t forget to control the message on your most vital web pages. It is easy to write a descriptive, on-brand meta description for your homepage, main landing pages, and top content, and it can make your site look great in search results.

 

In traditional search, brand control is most important because it helps you match the query with your meta description. In AI-powered search, there is little robust evidence that meta descriptions affect citations or rankings. Nevertheless, writing strong descriptions for your key pages clarifies the page’s topic and can influence your snippet in search results.

Another reason meta descriptions matter is that Google doesn’t always display them. If you can’t summarize any page in one or two sentences, it’s probably not a good page. If you can’t, the page may be too much or too little. This habit not only benefits the snippet but the entire page as well.

This is where meta descriptions tie in with the rest of the practices in this guidebook. Not focusing a page makes it harder to create clear alt text, complete schema, or consistent image metadata. If you state your focus in your meta description, it will help with your on-page optimization efforts.

If you have lots of pages, it’s logical to prioritize. Start with home, main service or category pages, top landing pages, and key content. Not having a meta description isn’t a setback for AI visibility; it’s a huge help to Google when your key pages do have a strong meta description, and it helps maintain your message.

Alt Text was previously limited to an image-SEO tactic, such as using keywords to help images appear in Google Image Search. However, there’s more to it. Alt Text is primarily for accessibility. Describes an image to people with screen readers or when an image is not visible. Search systems also use alt text to understand images, along with the rest of the page and computer vision.

Alt text can also improve an image’s clarity by providing a concise, precise description. According to Google, it uses page context, computer vision, and alt text to understand images. While good alt text is accessible and can be search-engine friendly, it is not a single indicator of credibility or AI citation. Other factors such as page copy, image context, captions, filenames, and the image itself also play a role.

Good alt text throughout a page improves accessibility, provides image context, and conveys meaning. The modern search and AI systems take into account visual as well as text signals. While some evidence suggests AI rankings and citations can improve with more descriptive ALT text, there isn’t enough evidence that this is always true. Utilize alternative text for improved accessibility and provide search engines with meaningful context, but not as an AI ranking mechanism.

Accessibility and SEO may go hand in hand by requiring clarity, descriptions, and a clear purpose. They aren’t the same, and accessibility shouldn’t be done solely for SEO. The key overlap is that clear, well-structured pages help assistive technology and search systems.

Alt text and image metadata are related, but they are not the same. Alt text is in the page’s HTML and describes the image in context. EXIF, IPTC, and C2PA data are carried with the image file and can reveal technical details, the creator, rights, and the image’s sources. While there’s no definitive evidence that photo metadata boosts rankings, it’s great for attribution, licensing, proving ownership, and certain image searches.

The indirect value of image metadata and its relationship to structured data is more beneficial. Structured data/ITPC metadata may be used to display rights, licensing, and credits for who created an image from Google Images. Additionally, Google’s metadata can feature C2PA metadata in its “About this image” and has adopted IPTC Digital Source Type for AI-generated images. While these features can facilitate attribution and licensing, they are not definitive ranking or AI attribution signals.

The importance of image provenance is increasingly rising as individuals seek to understand the origin of images and their authenticity, whether they are original or manipulated, or AI-generated. There are standard ways of sharing this information, such as via IPTC and C2PA. This can be useful for publishers, eCommerce stores, photographers, museums, and brands that are interested in ownership, licensing, attribution, and authenticity. The primary advantage is that it brings transparency around provenance and rights, rather than a ranking or trust mark for search engines.

The first step in selecting which images to optimize is to determine page speed and image file size.  They are crucial, as slow images can negatively affect your Core Web Vitals and the overall page. Then add good alt text for accessibility and AI understanding. Use descriptive file names so search engines can learn more about your pictures. Structured data and IPTC metadata can also play a role, particularly in licensing and for AI-generated images, to ensure sources and origins.

For example, when our client Pacific Symphony is performing Beethoven’s 4th Symphony. When we added the image caption to the alt text, we would write something like, “photo cover for Beethoven’s 4th Symphony, Conductor Alexander Shelley with his arms crossed”. The conductor’s name, orchestra, performance date, and copyright would be found in the image information. If these details align on both layers, users and search engines can easily tell who created the work, who performed it, and what rights are attached, though that doesn’t necessarily ensure AI citation.

While schema is a significant technical SEO tactic, it’s not the primary shift with AI search. For years, schema has focused mostly on rich results, such as improved product, event, organization, and article listings. It still does that and provides unambiguous machine-readable data on entities and relationships.

Also known as structured data, schema markup is code you place on your pages, often using tools like Schema.org, to clearly and precisely define the meaning of your content and its connections. Some believed schema wasn’t as crucial as it was before Google’s changes to FAQ/HowTo rich results; however, it’s still valuable for supported search features and for clearly displaying entities. Google has claimed structured data is not needed for AI Overviews or AI Mode, and there is no special schema for their generative AI search. However, we have found that AI Overviews can include false information without guidance from Schema, classes, performances, and products. While schema may not ensure your content is visible to AI, it helps ensure your information is presented accurately. AI can derive meaning from regular text, but it can sometimes misinterpret entities and relationships. Structured data can make some of that meaning explicit. For example, markup can specify what kind of entity something is (such as Organization) and link it to an official URL, location, event, course, product, or other entity, minimizing confusion between entities with the same name. Context is helpful machine-readable information, but AI systems don’t have to use it; they can use many other retrieval and ranking signals.

A complete, consistent schema setup can help machines understand your page. It defines the important entities and their relationships, rather than letting the AI figure it out. This will help eliminate confusion but will not let you control how an AI system understands, ranks, or quotes your page.

All four practices of this guide are now combined, but must not be considered technical. While these four practices work best together, they are not necessarily interdependent. Meta descriptions summarize a page’s focus for search. Alt text provides an accessible text alternative to images. Provenance, creator, and rights are elements that can be displayed in IPTC and C2PA metadata. Schema is a structured representation of the visible entities and their relationships. Do not change any facts if they are repeated more than once. The idea is not to send mixed messages, but not to send an artificial ‘AI sentence ‘.The idea is not to give mixed messages, but not to give an artificial ‘AI sentence ‘. Consistency is important: any name, description, information about the image, its date, geography, or any such fact expressed in structured data should match what is written on the page. The combination may help to improve clarity, but the mix does not ensure that any particular combination will be included in or cited in an AI-generated answer.

This depends on your page content and which schema is most appropriate. Common types include Organization, LocalBusiness, Article, Product, Event and subtypes, Course or CourseInstance, and ImageObject. Event-based markup works well for performing arts and is typically better than a generic label. If your content and Google’s rules permit it, then use review and rating markup. Check if Google supports markup using Google’s Rich Results Test, and validate other types of markup using Schema.org validation. While good markup makes your page easier for the machines to read, it doesn’t mean that AI systems will trust, rank, and cite your page.

At sites where images have commercial, documentary, or cultural significance, such as publishers, photographers, museums, and ecommerce sites, these three types of metadata complement each other, offering a good example of using several layers to coordinate. Every layer has its own purpose and should be used for it and not as an AI ranking signal.

Measuring AI visibility has progressed further than it did a year ago. In June 2026, Google launched dedicated Generative AI performance reports in Search Console for visibility. Measuring AI visibility is now easier than it was a year ago. Google recently released its own AI performance report in Search Console, showing visibility in AI Overviews and AI Mode as of June. You can view impressions, pages, countries, devices, and dates for sites that you can access. In addition, ChatGPT analytics allow you to see referrals when users click through from links. These reports don’t include all prompts or ranking factors. However, they are still useful for testing prompts and screening referrals, which is a broader SEO discipline rather than supplanting ranking and retrieval systems. AI search fetches from indexes and other sources and determines what to synthesize and which resources to cite. Crawlability, Indexability, Relevance, Originality, Authority, Page Experience, and usefulness of content remain important. The content decisions that make content more machine-readable often also make it easier for people to read.

To make the most of these four practices, try to use them together rather than one at a time. Meta descriptions are a brief description of the page for search. Alt text provides alternative text for images. Origin, creator, rights, and provenance may be visible in the image metadata. Schema conveys the same information and relationships in a structured fashion. It’s best to do all 4 well to stay consistent and make it easier for machines to read, but for the best results, your content must be crawlable, indexable, relevant, useful, and worth citing.

These practices still constitute good web basics for AI search. Schema markup, accessibility-focused alt tags, image provenance and rights metadata (where applicable), and good meta descriptions can be the building blocks of your visibility. This is not intended to beat the algorithm. The best long-term approach is to integrate these with a crawlable website, truthful and original content, robust topic coverage, valuable first-party content, and monitoring where AI systems cite and send traffic. An organization whose information is easy to find, verify, understand, and reuse will be better positioned as AI gets better at searching.

None of these four practices — meta descriptions, alt text, image metadata, schema — will get you cited by AI search on their own. What they do is remove ambiguity: about what a page is, what an image shows, who made it, and how entities relate to each other. That clarity doesn’t guarantee inclusion in an AI-generated answer, but it puts the odds in your favor and keeps your site legible to both people and machines. The sites that win here aren’t chasing an algorithm hack — they’re the ones that stay crawlable, keep their facts consistent across every layer, and treat these basics as infrastructure rather than a checklist to clear once and forget.