Guide

How to optimize images for AI search, LLMs and shopping agents

AI answers, visual search and shopping agents choose the product photos they show from what they can read: your pages, your files and your product data. This guide explains how each of them finds and reads images, then gives a twelve-step method, built on what Google, Microsoft, OpenAI and the standards bodies publish.

  • Updated
  • 15-minute read
  • 37 primary sources

Key takeaways

  • There is no special “AI markup” for images. Google says its AI features run on the same index and ranking systems as Search, and that optimizing for them is still SEO: an indexable page, a real image and words that describe it.
  • AI systems read images mostly through text: alt text, the file name, captions, the page around the image and structured data. Write them for people; machines read the same words.
  • Shopping answers and agents also read product feeds. Keep your Merchant Center feed complete, with the same images as your pages.
  • Visual search compares pixels: sharp photos of the real product, well framed, from several angles, without promotional overlays. From 31 January 2027, Merchant Center wants at least 500 × 500 pixels.
  • Credits and AI labels in the file build trust. Keep your IPTC credits, and keep the AI label on AI-generated product images: Merchant Center requires it.
  • Nobody can promise a place in AI answers. What you can do is make sure nothing stops your images from being found, understood and trusted.

How AI systems find and read your images

“AI search” isn't one system. Four kinds of readers meet your product photos, and each reads something different. Optimizing for all four is mostly the same work, done once.

  • AI answers in search

    Google's AI Overviews and AI Mode, Copilot and Bing, ChatGPT search, Perplexity. They find pages in a search index, write an answer, and show images from the pages they rely on.

    Reads: the page, its images, alt text, file names and structured data.

  • Language models that see

    Multimodal models can describe the pixels of an image they're given: a blue bag with a gold buckle. The pixels can't tell them the brand, the model, the size or the price.

    Reads: the pixels, plus the text around them.

  • Visual search

    Google Lens, Circle to Search, Google Images, or a photo asked about in AI Mode. Google now splits a photo into the objects it contains and searches for each one.

    Reads: the pixels, then product data to link a match to an offer.

  • Agents

    Browser agents that click through a store for someone, and shopping agents that compare and buy. Browser agents read screenshots, the page's code and its accessibility tree; shopping agents read product feeds.

    Reads: alt text, labels, product feeds.

The common thread: text and data travel further than pixels. A model may see a blue handbag; only your page can tell it that it's the Mila bag by Maison Lune, in calf leather, €240, in stock. The method below makes sure each reader gets that, in four layers.

Layer 1 · Steps 1 and 2

Be found

An AI answer can only show an image its systems could fetch and index. Many images are lost here, to a robots.txt rule or to a gallery that only appears once scripts run.

Let search and AI crawlers fetch your pages and images

To be shown as a link in AI Overviews or AI Mode, Google says a page needs to be indexed and eligible to appear in Search with a snippet, with no other technical requirement. Both features use Googlebot: there is no separate AI crawler to allow. Other assistants search the web with crawlers of their own, and each needs to be let in.

Crawlers for search and for model training are separate, and so are the robots.txt names that control them. Blocking GPTBot or the Google-Extended token keeps your content out of model training; it doesn't take you out of ChatGPT search or Google Search. Blocking OAI-SearchBot or Googlebot does.

Robots.txt nameWhat it's for
GooglebotGoogle Search, AI Overviews and AI Mode
Googlebot-ImageGoogle Images, Discover and Search's image features
BingbotBing and Copilot answers
OAI-SearchBotChatGPT search
PerplexityBotPerplexity's search results
Claude-SearchBotClaude's search results
ChatGPT-User Perplexity-User Claude-UserPages opened because someone asked the assistant to (OpenAI and Perplexity say robots.txt may not apply to theirs)
GPTBot ClaudeBot Google-ExtendedModel training only (Google-Extended is a token, not a crawler)
# Search and AI search: let them fetch pages and images
User-agent: Googlebot
User-agent: Googlebot-Image
User-agent: Bingbot
User-agent: OAI-SearchBot
User-agent: PerplexityBot
User-agent: Claude-SearchBot
Allow: /

# Model training: a separate choice, with no effect on search
User-agent: GPTBot
User-agent: ClaudeBot
User-agent: Google-Extended
Allow: /

Sitemap: https://www.example.com/sitemap.xml

Do this

  • Check that robots.txt doesn't block your image folders or your CDN's paths: Anthropic, for one, says its search partners only index images their crawlers are allowed to fetch.
  • In Search Console, check the generative AI setting. “Include” is the default; “Exclude” takes a site out of AI Overviews, AI Mode and Discover's AI features.
  • Let Google show large image previews, in Search, Discover and AI Overviews, with <meta name="robots" content="max-image-preview:large">.
  • Don't put noindex on product pages, and don't serve images only to signed-in visitors.
  • Keep one stable address per image, as Google asks. A new URL is a new image for every index that knew the old one.

Put real, fast images in the HTML

Google finds images in <img> elements, through their src and srcset attributes; inside a <picture>, keep an <img> with a src as the fallback. Google doesn't index images set as CSS backgrounds. Agents that read the page's structure see the same thing: an <img> with alt text is an image, a background is decoration.

Lazy-loading is fine with the browser's own loading="lazy", which keeps the address in the HTML, but never on the main product image: it's usually the largest element on the page, and how fast it appears is one of Google's Core Web Vitals (Largest Contentful Paint). Give it fetchpriority="high" instead, and set its width and height so nothing moves when it loads.

<img src="/images/blue-leather-handbag-front-1500.jpg"
     srcset="/images/blue-leather-handbag-front-750.jpg 750w,
             /images/blue-leather-handbag-front-1500.jpg 1500w"
     sizes="(min-width: 64em) 50vw, 100vw"
     width="1500" height="1500"
     alt="Blue leather handbag with gold buckle, front view"
     fetchpriority="high">

Google Search supports BMP, GIF, JPEG, PNG, WebP, SVG and AVIF, but Merchant Center doesn't take AVIF: keep JPEG, PNG or WebP files for your product feed. Compress every image, so pages load fast for shoppers and crawlers alike.

Do this

  • Tell Google which image represents the page: it reads og:image and schema.org's primaryImageOfPage to choose thumbnails in Search and Discover. Avoid logos, text-heavy images and extreme proportions.
  • For Discover, use images at least 1200 pixels wide.
  • If a gallery is built by scripts, or images live on a CDN's domain, list them in an image sitemap.

Image compressor
Compress JPEG, PNG and WebP product photos in your browser, with descriptive file names and alt text.

Layer 2 · Steps 3 to 6

Be understood

Google combines computer vision with the words around an image to understand it, and AI answers quote words. Steps 3 to 6 give every image the right ones, in the places each reader looks.

Give every file a descriptive name

Google's image guidelines say a file name can give it clues about what an image shows: blue-leather-handbag.jpg says far more than IMG_4032.jpg. Keep names short and descriptive, separate words with hyphens, as Google recommends for addresses, and translate them on a localized site.

Name a product's photos as a set, so each one says what it adds: blue-leather-handbag-front.jpg, blue-leather-handbag-side.jpg, blue-leather-handbag-buckle-detail.jpg, blue-leather-handbag-worn.jpg. Most stores keep the uploaded name in the image's address, so rename before you upload.

Image compressor
Type the product name once: every photo is renamed in lowercase with hyphens, ready to upload.

Write alt text for people, screen readers and agents

Alt text is an image's description in the page's code. Google calls it the most important attribute for giving it information about an image, and uses it with computer vision and the page's text. Screen readers read it aloud. In the accessibility tree that browser agents read, an image is its alt text: when an agent doesn't study a screenshot, that's all it knows about the photo.

Describe what the image shows, as you would to someone on the phone. A simple formula: the product, its key detail, then the view or context.

GoodBlue leather handbag with gold buckle, front view
Too vagueBag
Keyword stuffingbag handbag leather bag blue bag cheap bag buy bag

Do this

  • Keep it to about 125 characters, and don't start with “image of”: screen readers already announce an image.
  • Give each photo of a gallery its own alt text: what this view adds (side view, buckle detail, worn on the shoulder).
  • Use the words shoppers would use, once and naturally: color, material, product type, and the brand when it shows.
  • If AI writes your alt text, check every one: Google's guidance on AI-generated content asks for exactly that.
  • Leave alt text empty (alt="") on purely decorative images, so nobody has to hear them.

Where it goes depends on your platform. Image SEO for AI writes alt text into each file, in the IPTC field made for it, “Alt Text (Accessibility)”. Since version 7.0, WordPress reads that field when you upload an image and fills in its alt text: on WooCommerce, your alt texts arrive with your images. Shopify doesn't read alt text from the file: each image has its own alt text field, which you can fill from the alt-text.csv list in your ZIP, or in bulk through Shopify's product CSV.

Platform export
Turn your alt texts into import files for Shopify, WooCommerce, Magento and BigCommerce.

Surround each image with the words it can't say

Google uses the page around an image to understand it: the title, the headings, the caption, the text nearby. Put each product photo on the page about that product, close to its name and description, and caption lifestyle and editorial photos (<figcaption>).

AI answers quote text, not pixels. Write as text what a photo can't state: brand, model, material, dimensions, color names, price, availability. And don't put essential information only inside an image: a size chart, a list of ingredients or care instructions saved as a picture is hard for every reader, people included.

Microsoft's advice for appearing in AI search answers says it plainly: “Always provide alt text or present critical details in HTML.” Bing also asks sites to keep text, images and video consistent about the same products. Use the same product name and color in the title, the alt text, the file name, the structured data and the feed.

Describe products and images in structured data

Structured data (JSON-LD) states facts in a form machines can't misread. For a product, use Product markup with its offer, brand, GTIN and images: the image is required for Google's merchant listings, and Google recommends several high-resolution images, in 16×9, 4×3 and 1×1 formats, of at least 50,000 pixels (width × height).

{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Mila handbag, blue calf leather",
  "brand": { "@type": "Brand", "name": "Maison Lune" },
  "gtin13": "3760000000017",
  "image": [
    "https://www.example.com/images/blue-leather-handbag-front-1x1.jpg",
    "https://www.example.com/images/blue-leather-handbag-front-4x3.jpg",
    "https://www.example.com/images/blue-leather-handbag-front-16x9.jpg"
  ],
  "offers": {
    "@type": "Offer",
    "price": "240.00",
    "priceCurrency": "EUR",
    "availability": "https://schema.org/InStock"
  }
}

For images you want credited, Google's image license metadata adds an ImageObject with the image's address and at least one of creator, credit text, copyright notice or license. With a license link, Google Images can show a “Licensable” badge.

Two rules matter more than any property. The markup has to match what the page shows: same price, same images, same availability. And there is no AI-specific schema: Google says its AI features don't need special structured data. Mark up what's true and visible, nothing else.

Image schema generator
ImageObject and Product JSON-LD for your photos, with Google's credit fields, checked as you type.

Layer 3 · Steps 7 to 9

Be trusted

Images get copied, resized and reposted. What's written inside the file says who made it, whether AI made it and what it shows, wherever it ends up.

Sign your images: credits and license in the file

IPTC metadata is the standard photographers, news agencies and image libraries use to store credits inside image files. Google Images reads its Creator, Credit Line and Copyright Notice fields, and suggests filling in at least those three. Add a Web Statement of Rights, a link to your license terms, and Google can show the “Licensable” badge without any markup on the page.

Credits travel with the file to marketplaces, resellers and anyone who downloads it, where page markup can't follow. They're how a copy of your photo points back to you.

Image compressor
Set your brand, copyright and website once: they're written into every photo of the batch.

Label AI-generated images honestly

Google Merchant Center requires every product image made with generative AI to say so in its metadata, such as the IPTC digital source type TrainedAlgorithmicMedia, and asks you not to remove it, in main, additional and lifestyle images alike. Google Search's “About this image” shows the AI information in C2PA Content Credentials, which ChatGPT and other AI tools write into their images, in Google Images, Lens and Circle to Search.

In the European Union, the AI Act's transparency rules (Article 50) apply since 2 August 2026. AI tools must mark what they generate in a machine-readable way (those already on the market have until 2 December 2026), and realistic AI images of real people, objects or places that could pass for genuine have to be disclosed. When an AI image shows your real product, disclosing it protects your listings.

Labels and watermarks are different things. A label is metadata, and removing metadata removes it. An invisible watermark such as Google's SynthID is part of the pixels: no optimizer removes it. Google's Gemini app can check an image for it, and Google is bringing those checks to Search and Chrome. A missing label never proves that an image wasn't made with AI.

Image compressor
The optimizer removes hidden data by default; switch on “Keep Google's AI tag” to write the label back into AI-made product photos.

Shopify product page image audit
See which images of a Shopify product page carry an AI label, and which carry credits.

Clean the files, keep what helps

Photos straight from a phone or camera carry more than pixels: GPS coordinates, the camera's serial number, dates, the editing software and its history, sometimes a thumbnail of the original crop. None of it helps search, all of it adds weight, and some of it, like where a photo was taken, is nobody's business.

Remove it, then write back only what helps: your credits (step 7), the alt text and description, and the AI label when step 8 applies. Check what your platform keeps: CDNs often strip metadata from the resized copies they serve (Cloudflare has a setting to keep Content Credentials), while the original upload usually keeps it.

Remove EXIF data
Remove GPS location, camera details and AI tags from your photos, pixels untouched.

Layer 4 · Steps 10 to 12

Be chosen

Found, understood and trusted, an image still has to be the one a system picks: for a visual match, in a shopping answer, or by an agent comparing products.

Visual search starts from pixels. Google doesn't publish separate advice for it, beyond its image guidelines, nor how Lens recognizes products. It does publish what it expects from product photos in Merchant Center, and those rules make photos easy to match.

Merchant Center ruleValue
Minimum size500 × 500 pixels for every product from 31 January 2027
RecommendedAbout 1500 × 1500 pixels
Maximum16 MB and 64 megapixels
FormatsJPEG, WebP, PNG, non-animated GIF, BMP, TIFF (no AVIF)
FramingThe product fills 75 to 90% of the image
Not allowedPrices, calls to action, promotional text, watermarks, added logos, borders, placeholder images

Google's visual search now breaks a photo into the objects it contains and runs a search for each: in a lifestyle photo, every product you sell is something a shopper can be matched to.

Do this

  • Make the main image the real product, sharp, evenly lit, on a plain background, with accurate colors.
  • Add more angles and details, and photos of the product in use: each is another chance to be matched.
  • Selling clothes or shoes? Google's virtual try-on builds on your images: one garment, on a front-facing model or laid flat, at least 512 × 512 pixels (1024 or more is better).
  • Keep the same photos on your site and in your feed, so a match leads to your offer.

Visual search checker
Check product photos against Google's published image requirements: size, framing, sharpness, background.

Feed the shopping graphs

Shopping answers draw on product data as much as on pages. Google's AI Mode shopping is built on its Shopping Graph, more than 50 billion product listings, and Merchant Center free listings can appear in Google Images and Lens. Since January 2026, the Universal Commerce Protocol (UCP) lets shoppers check out from AI Mode and Gemini, with the retailer still the seller.

In a Merchant Center feed, image_link is the main image, additional_image_link adds up to ten more, and lifestyle_image_link up to five photos of the product in use (at least 600 × 600 pixels, without text). Microsoft Merchant Center feeds help products appear in Copilot. ChatGPT accepts merchant product feeds that ask for a direct JPEG or PNG image of the exact variant, plus optional additional images, and already includes Shopify and Etsy stores. Shopify's Agentic Storefronts share each product's title, description, options, images, price and availability with AI assistants.

Do this

  • Fill in every image field you have photos for, with GTINs, brand, color and material: the more complete the data, the more questions a product can answer.
  • Give each variant its own image, so a shopper asking for “navy” sees navy.
  • Fix Merchant Center's image issues (too small, promotional overlay, generic image) first: they can keep products out.
  • Update the feed when photos change, and keep its image addresses identical to your pages'.

Make product pages readable by agents

Google's guide to AI features notes that browser agents may read a page's screenshots, its code and its accessibility tree, the structure assistive technologies use. Chrome's documentation for developers puts it simply: agents review the accessibility tree to find what they can act on. What helps a screen reader user helps an agent.

Do this

  • Give every product image alt text, and every gallery control a name: “Show image 2 of 6: side view”, not an unlabeled arrow.
  • Name color swatches in text (“Navy”, “Cognac”), and update the main image and its alt text when a variant is chosen.
  • Use real buttons and links, keep the layout stable, and don't lay transparent overlays, such as zoom layers, over images.
  • Put the main image and its alt text in the HTML the server sends, and keep prices, sizes and availability as text next to the images.

Shopify product page image audit
Audit every image of a Shopify product page: alt text, file names, hidden data, AI labels, compression.

Measure what AI sees

You can't see every answer an assistant gives, but you can see more than a year ago.

  • Search Console counts AI Overviews and AI Mode in its Performance report, with the rest of web search. Its Generative AI report shows their impressions, and the “Web: multimodal” search type covers Lens, Circle to Search and image uploads: that's where visual search shows up.
  • Merchant Center lists image issues for each product, and its AI performance insights report on AI Mode and AI Overviews in some countries. Bing Webmaster Tools counts citations in Copilot and Bing's AI summaries.
  • Count AI crawlers in your server logs: OAI-SearchBot PerplexityBot Claude-SearchBot Googlebot-Image. If they never fetch your images, start again at step 1.
  • Watch visits from chatgpt.com, perplexity.ai, copilot.microsoft.com and gemini.google.com in your analytics.
  • Ask the assistants about your products, with your customers' words, and look at the images and pages they show. Try Google Lens on your own photos.
  • Run Lighthouse in Chrome: it now checks how usable a page is for agents. Audit your product pages after every change to your theme or your photo workflow.

What doesn't help

  • Special files and markup for AI. Google says Search ignores llms.txt files, which neither harm nor help, and that its AI features need no special schema. We found no major AI platform that documents reading them either.
  • Rewriting or “chunking” pages for AI. Google lists it among the things you don't need to do. Clear pages written for people are what its AI features use.
  • Keywords stuffed into alt text and file names. Google's image guidelines warn against it, and it makes alt text useless for the people who hear it.
  • Removing metadata to rank. It lightens files and protects privacy; it isn't a ranking factor. Removing the AI label from AI-generated product images breaks Merchant Center's rules.
  • Blocking AI search crawlers and hoping to be cited. An assistant can't show what its crawler wasn't allowed to fetch. Decide on training separately (step 1).

The checklist

Twelve steps on one screen. Each one links back to its explanation.

Sources

This guide is built on the documentation each company and standards body publishes about its own products and rules, read in October 2026, and on our own tests of how stores serve images. Rules change: when one matters to you, check it at its source.

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The short version: it's free, your photos stay on your device, and a JPEG stays a JPEG.

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Is there a special way to optimize images for AI search?

There's no special markup or file. Google says its AI Overviews and AI Mode run on the same index and ranking systems as Search, and that optimizing for them is still SEO. What matters is that crawlers can fetch your images, that words describe them (alt text, file name, the page around them) and that your product data is complete.

Do ChatGPT, Gemini and Perplexity look at the images themselves?

Their models can describe an image they're given. To choose which images to show and to know what they are, AI search relies mostly on the page around them, their alt text, file name and structured data, and for products on shopping data. Pixels can show a blue bag; only text can say which bag.

Does alt text still matter now that AI can see images?

Yes. Google still calls it the most important attribute for understanding an image, screen readers depend on it, and browser agents read it in the page's accessibility tree. It's also the one description of an image you fully control.

Should I block AI crawlers?

Decide on search and training separately. Search crawlers such as OAI-SearchBot, PerplexityBot or Claude-SearchBot fetch the pages assistants show: block them and your images can't appear there. Training crawlers and tokens, such as GPTBot or Google-Extended, only concern model training. Google-Extended doesn't keep you out of AI Overviews: Search Console's generative AI setting does.

Will removing EXIF data help my images rank?

No: metadata isn't a ranking factor. Removing it protects your privacy (GPS location, camera serial numbers) and lightens files. Keep or write back what helps: your credits, your alt text and, on AI-generated product photos, the AI label Merchant Center requires.

Do I need an llms.txt file?

No. Google says Search ignores llms.txt files and that they neither harm nor help, and we found no major AI platform that documents reading them. For images, alt text, structured data and product feeds are what these systems use.

How do I know if my images appear in AI answers?

Search Console counts AI Overviews and AI Mode in its Performance report, shows their impressions in its Generative AI report, and reports visual searches (Lens, Circle to Search) under “Web: multimodal”. Bing Webmaster Tools counts citations in Copilot. Look for AI crawlers in your server logs and for visits from chatgpt.com or perplexity.ai, and ask the assistants about your products.

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