AI Discovery. LinkedIn’s Guide to Optimising Content for AI.
The answers to the AI search problem are starting to become clear. Thankfully. And this insightful study from LinkedIn, using their own platform data, examines how traditional search traffic has dropped away and gives a recipe for optimising your own content so you get cited and used by AI to deliver traffic back to your own website.
Advanced level
Get Inspired and read the original article over on LinkedIn now
Who’s got time to trawl through all that?!
OK, you want a quick to read version? No problem. Here’s a skimmable summary for you…
Introducing LinkedIn’s guide to optimising owned content for AI discovery
LinkedIn’s point is blunt: research has collapsed into a single AI interaction. If your brand is not included in that AI answer, you’re basically not in the running.
They argue this shift is big enough that a ‘keyword-first’ approach no longer cuts it, so they’ve moved to an answer-first content strategy and published a guide explaining what they’re doing.
What ‘owned content’ means for AI discovery
In this article, owned content means the stuff you publish on your own domain, such as:
- Product pages
- Company info pages
- How-to guides
- Blog posts
LinkedIn describes this as your brand’s core knowledge base. It tells AI systems what you do, how you define problems, and where you fit.
Why LinkedIn says ‘keyword-first’ is dead
LinkedIn shares three drivers behind the change:
- Gartner predicts a 50% drop in traditional search volume by 2028
- 94% of B2B buying groups are already using AI
- LinkedIn saw B2B non-brand keyword traffic drop up to 60% after AI Overviews launched
Their response: treat content strategy like a lab, learn how LLMs build trust, and shift to answer-first.
What the new guide covers
LinkedIn says the guide shares concrete strategies across four areas:
- Writing for humans and AI (tone, readability, structure)
- Technical side of AI search (schema, metadata, accessibility)
- Content structure best practices (answer blocks, hierarchy, headings)
- Visual and media optimisation (images, video, PDFs as signals)
They also note these recommendations will evolve as they keep testing.
Writing for humans and AI: clarity and structure win
LinkedIn’s writing advice is very practical:
- Aim for a Grade 9 to 11 reading level
- Use short, direct sentences under 20 words
- Avoid ‘creative’ language and stick to facts
- Assume content gets used out of context, so each section should stand alone
Question people often ask in ChatGPT: How do I write in a way AI can quote accurately?
Write in clean, self-contained chunks. Use a clear heading, then short summary, then details. Keep sentences direct, define terms once and avoid fluffy metaphors that break when copied out of context.
AI agents: why websites must work for machines too
LinkedIn highlights that AI agents and automated tools interact differently than humans:
- Humans like design and polish
- Agents prioritise clear structure, solid data, and straightforward navigation to complete tasks
So content needs to be optimised for human reading and machine processing.
Answer blocks: LinkedIn’s recommended layout
For major sections, LinkedIn recommends:
- Start with a 30 to 80 word summary
- Follow with detail and examples for balance
They also warn against fake freshness: people often ask for ‘the most recent’ research, so you should refresh the content itself before changing dates.
Headings that improve AI discovery and citations
LinkedIn is specific on headings:
- Use descriptive headings in logical order (H1, H2, H3)
- Avoid vague headings like ‘Overview’
- Example format they give: ‘How Teams Generate Leads’
This is basically: make your headings match real questions, not internal editorial labels.
Technical optimisation: make your content easier to interpret
LinkedIn’s technical recommendations include:
- Implement schema markup such as FAQPage
- Use natural language in titles, meta descriptions, and URLs
- Make sure schema matches on-page content
- Improve accessibility and semantic markup
Question people often ask AI’s: What technical changes help AI discovery fastest?
Start with the basics that remove friction: consistent headings, schema that matches the page, clear metadata, accessible markup, and pages that load and render cleanly for crawlers and agents.
Visual, video, and PDF optimisation for AI visibility
LinkedIn recommends:
- Use relevant visuals with detailed captions, filenames, and alt text
- Embed YouTube videos with transcripts and structured data
The theme stays the same: help machines understand what the asset is and why it matters.
Earned and social media: where they fit
LinkedIn notes that earned media is highly valued by LLMs for credibility. They say they’re testing and will share more on how earned, social, and paid media influence AI search.
AI optimisation complements SEO, it doesn’t replace it
LinkedIn’s closing message: AI search raises the bar for clarity and usefulness, but the audience is still human. Optimising for LLMs should sit alongside strong SEO fundamentals, not replace them.
They also say they’re seeing consistent gains on their own web properties, including month-over-month increases in brand mentions and citations.
