The Three-Stage Process
Both search engines and AI systems follow similar workflows, which can be simplified into three core stages:
Discovering &
Consuming
Organizing &
Understanding
Using &
Serving
Discovering & Consuming
Search Engines
Need to find and collect your content before they can show it to users. Googlebot and Bingbot:
- ● Crawl websites systematically
- ● Follow links and discover new pages
- ● Read HTML and process content
- ● Store information for indexing
AI Models
Like ChatGPT and Gemini also need content for their training phase. They obtain data from multiple sources:
- ● Website crawling (using bots like GPTBot, ClaudeBot, and Google-Extended)
- ● Publicly available datasets (Wikipedia, CommonCrawl, BookCorpus)
- ● Third-party partner data
- ● User feedback and testing data
Organizing & Understanding
Search Engines
"Index" content by analyzing and cataloging what they find. This involves:
- ● Processing text content and structure
- ● Analyzing images, videos, and other media
- ● Understanding relationships between pages through links
- ● Capturing language and geographic signals
- ● Evaluating quality signals
AI Models
"Train" on their collected data, analyzing patterns and relationships to build understanding. During training, models:
- ● Parse content and context
- ● Learn linguistic patterns and relationships
- ● Set "weights" (parameters) that help predict likely next words
- ● Build "understanding" of topics, concepts, and connections
Using & Serving
Search Engines
Retrieve relevant pages from their index when users query them, then rank results based on:
- ● Relevance to the search query
- ● Content quality signals
- ● User experience factors
- ● Authority and trustworthiness
- ● Freshness and accuracy
AI Models
Generate responses by using their training to predict and create new content that addresses user prompts. They leverage:
- ● Patterns learned during training
- ● Contextual understanding
- ● Probabilistic predictions
- ● Real-time retrieval augmentation (accessing current web data)
Applying This Knowledge
Search engines and AI models share remarkably similar discovery and processing workflows. This means you don't need separate strategies for "SEO" and "AI optimization." Strong web fundamentals and quality content create a foundation that works across all discovery channels. Here's how to maximize your visibility:
- Audit your technical foundation. If crawlers can't access your content efficiently, you're losing visibility across all discovery channels. Ensure clean architecture, proper semantic HTML, and fast load times.
- Invest in content quality over volume. One comprehensive, authoritative piece outperforms ten shallow ones in both search and AI contexts. Demonstrate expertise through original research and practical insights.
- Structure matters. Use proper headings, semantic HTML, and clear organization to help both systems understand your content hierarchy and relationships.
- Think in frameworks, not platforms. Rather than chasing every new AI feature or search update, build on solid principles that transcend individual platforms.
- Monitor both channels. Track traditional search traffic and emerging AI referrals (ChatGPT, Perplexity, Gemini) to understand your full discovery footprint.
Ready to Improve Your AI Visibility?
Now that you understand the parallels between search and AI discovery, take action to assess and optimize your digital presence across both channels.
Sources & Further Reading
For additional information and technical details about search engines and AI models see these resources: