How to optimise images for AI search

AI searching for images online

How to optimise images for AI search

It seems that AI is now everything and everywhere. And whether we like it, hate it or fear it – we have to adapt and evolve with it if we want our business to thrive. So, in this article, we will focus on AI search optimisation of your website's images

Traditional SEO strategies for optimising images are still relevant for AI searches. However, AI-driven search engines and technologies (like Google Lens, Bing Visual Search, and other visual AI tools) have unique considerations.

Here are some tips for optimising images specifically for AI-based search:

 

  1. Optimise for Image Recognition (Visual AI)

AI-driven search engines rely on machine learning models to interpret the actual content of an image, not just metadata. AI-powered tools scan the image's actual pixels, detecting objects, colours, and even text within the image itself.

So, use clear, high-quality images with a well-defined subject. Avoid clutter or overly complex visuals, as AI might misinterpret them.

Example: An image of "a desk with plants, a cup of coffee, and a laptop" should have the main subject clearly framed (e.g., the laptop) to match user intent.

  1. Leverage EXIF Data (Metadata Specific to AI Tools)

Ensure EXIF metadata is accurate and aligned with your content goals.

While traditional SEO focuses on file names and alt text, AI tools can go deeper, using EXIF data to add context. AI search tools can sometimes extract information directly from the EXIF metadata embedded in image files (e.g., geolocation, time, and camera settings).

Example, if your image promotes a local service, include geotags for the relevant location.

 

  1. Use AI-Generated Image Tags and Categories

Proactively optimise your images for the same algorithms search engines use, to ensure accuracy in results. AI algorithms categorise and tag images based on their contents. Help guide this process by using tags that align with your intent.

Use AI tools like Google Vision AI or Microsoft Azure Computer Vision to reveal how an AI ‘sees’ your images and the keywords it associates with it. If they’re not matching your aims, consider revising the image.

 

  1. Incorporate Text Within Images for AI OCR (Optical Character Recognition)

OCR allows AI tools to surface your image for text-related queries, even if the content isn’t mentioned in your alt text or metadata. AI search tools like Google Lens can detect and read text embedded in images. Add readable, high-contrast text to key visuals where appropriate. For instance, a product image could include the product name or a QR code for added context.

 

  1. Optimise for AI-Powered Voice and Visual Search

AI search is often paired with voice and visual assistants, which prioritise query context over static keywords. Voice and visual search often rely on AI to connect users to relevant images, so support your images with conversational keywords or natural language queries people use for voice search.

Example: Use alt text like: "What does a modern ergonomic chair look like?" instead of just "modern chair."

 

  1. Enhance Images for Schema Markup in AI Context

AI often pulls from structured data for featured snippets, rich results, and detailed image results. Schema markup helps AI tools retrieve richer results.

Use ImageObject schema with additional AI-relevant properties, like:

      • description: A summary of the image content.
      • license: Licensing information.
      • representativeOfPage: Mark if the image represents the page's main topic.

 

  1. Use AI-Generated Content with AI Search in Mind

AI algorithms reward originality, and generating visuals ensures your content is unique to your site. AI-based tools prioritise unique content to avoid redundancy.

Generate custom visuals using tools like DALL·E or MidJourney and pair them with original metadata to stand out in AI-curated search results.

  1. AI-Driven Image Sitemaps

While basic sitemaps help with indexing, AI prioritises context-rich image data for better matching. Traditional image sitemaps tell search engines about your images, but AI search relies on deeper integration.

Use tools like Screaming Frog or SEMRush to audit your image sitemap for missing properties that AI uses (e.g., captions, contextual links).

 

  1. Contextual Awareness in AI Search

AI interprets images based on their surrounding context (text, headings, and links).  It AI relies on the relationship between the image and the text to surface accurate results. So, align your content clusters.

For example, if your image shows "how to prune a bonsai tree," make sure the surrounding content mentions "bonsai tools," "types of pruning," etc.

 

These tips are not silver bullets for success, but applying them will ensure your competitors do not leave you behind.

 

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Author

Hope Varnes is a Chartere Marketer with over 15 years experience in digital marketing. She is specialises in Google Ads, PPC, content marketing, and marketing strategy. She has a Master’s in Digital Marketing and eCommerce and is Google Certified. She is an expert in leveraging digital platforms to drive brand awareness, lead generation, and revenue growth.