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ResearchFebruary 5, 2026

Introduction to Decision Boundaries in AI Search

When you ask ChatGPT "What's the best project management tool?", it doesn't search the web in real-time. Instead, it synthesizes an answer from its training data and any grounding sources, making probabilistic decisions about which tools to mention.

This is the Decision Boundary—the threshold at which an AI model switches from ignoring your brand to citing it.

Understanding the Threshold

Traditional SEO metrics like Domain Authority or backlink counts don't directly influence LLM recommendations. Instead, AI models evaluate:

  • **Semantic Authority**: How strongly your brand is associated with specific concepts
  • **Contextual Relevance**: Whether your offering matches the user's implied needs
  • **Frequency and Recency**: How often and recently your brand appears in relevant contexts

The Monte Carlo Approach

At Sill, we use Monte Carlo simulations to map these boundaries. By running thousands of prompt variations and adjusting one variable at a time, we can identify the exact threshold where citation probability changes.

For example, we might find that a SaaS tool is cited 80% of the time when described as "enterprise-grade" but only 20% when positioned for "small teams."

Why This Matters

Understanding your Decision Boundary allows you to:

  1. Optimize positioning: Adjust messaging to cross citation thresholds
  2. Identify gaps: Discover where competitors have stronger semantic authority
  3. Measure progress: Track visibility changes over time with precision

The future of brand visibility is probabilistic. The brands that understand this will win.