How to Optimize for AI Visibility and Prepare for Agentic Search - Moz

How to Optimize for AI Visibility and Prepare for Agentic Search

June 4, 2026 10 min read

Written by: Aleyda Solis Edited By: Chima Mmeje

How To Optimize Your Site for AI Visibility and Agentic Features

When I speak with SEOs about AI search, I usually see three types of reactions:

The reality is more nuanced. AI search doesn’t replace SEO — instead, it expands what SEO needs to influence.

The fundamentals still matter, but the way we prioritize them needs to evolve.

In this article, I will share a cost-effective strategy to boost AI search visibility and prepare for agentic commerce.

P.S. This is part two of an article repurposed from my Moz webinar. I recommend reading part one if you want the full context.

Three principles to prioritize AI search optimization

The ten characteristics I covered in part one help you diagnose what may be limiting your AI visibility, but diagnosis is only useful if it leads to prioritization.

The challenge now is knowing where to focus first, how to avoid wasting resources chasing isolated prompts, and reporting progress in a way that connects visibility to business impact.

That’s where these three principles come in.

Principle 1: Stop using traffic as the main KPI for AI search impact

While traffic remains relevant, it is not a sufficient indicator of visibility, influence, or commercial success in AI search.

Users can now discover, compare, and validate your brand within AI platforms before visiting your site.

While some journeys still result in clicks, AI influence often occurs earlier and is more difficult to attribute. Consequently, measured AI referral traffic should be viewed as a minimum baseline of impact, not the maximum.

Instead of evaluating AI search success mainly through sessions, separate your reporting into two groups:

Tier 1: Core business KPIs (the real north stars)

Tier 2: AI visibility and referral metrics (directionally helpful)

From there, measure your AI presence using these KPIs:

Next, build prompt groups by product line, audience, journey stage, market, and commercial priority. Then, monitor your brand presence across those groups.

You can do this with the Moz AI Research toolkit. Click Prompt Suggestions under AI Research and enter a topic.

AI search starts with a prompt

Identify prompts that matter to your brand with Prompt Suggestions in Moz Pro.

Use these metrics to assess AI business impact

Measuring AI business impact requires separating signals by confidence level. This is important because not all AI visibility can be directly attributed as a referral in analytics.

Metrics include:

Observed (highest confidence, lowest coverage):

How many users clicked and converted from an AI answer?

Start by tracking these to measure and assess your AI impact:

Proxy (medium confidence, broader coverage)

Proxy signals complement observed data by correlating with AI influence. These directional metrics from internal analytics or external modeling tools help track AI traffic and visibility without direct proof.

They help answer questions like:

Start with what you own:

Modeled (lowest confidence, planning only)

These estimates apply assumptions to observed and proxy data, covering influenced pipeline, revenue, and incrementality. Use them to build an investment case, but never as definitive proof of performance.

They help to answer questions like: If we assume X% of branded search lift is AI attributable, what’s the implied pipeline?

Do not blend these three layers into one single “AI impact” number. Report what’s observed, inferred, and modeled separately, with clear confidence levels and assumptions.

Tying your AI search presence and readiness status with these business KPIs turns optimization into accountable, ROI-positive work.

Principle 2: Build topical authority with content that AI systems can easily retrieve, understand, and cite

The era of mapping a group of queries to a single page is gone. Because of query fan-out and how content gets synthesized, AI can extract from any page across your site taxonomy.

Your optimization work needs to go beyond ranking a landing page for a target query. The goal is to build topical and decision-stage coverage that makes your brand easy to understand, compare, cite, and recommend.

Cover the full customer journey

Every stage needs content that answers the questions users and AI systems need to resolve:

Start by prioritizing topics already driving AI visibility or organic demand. Then, expand into related questions and user constraints to capture adjacent opportunities.

Expand keyword maps with decision-constraint matrices

Keyword maps are still useful, but for AI search, they need to include decision constraints.

Users are moving beyond generic terms and instead using specific constraints such as foot type, budget, location, terrain, and durability.

To earn visibility in these journeys, your site needs to make those attributes explicit, consistent, and easy to extract.

Invest in informational content

Informational content remains important, especially when it helps users evaluate options, understand trade-offs, and make better decisions.

Even in commercial journeys, AI systems often rely on informational, comparative, and third-party sources to support recommendations.

Structure content for retrieval

Moz has a guide on adjusting your content strategy for AI Mode that covers this in depth, and the advice applies across AI platforms generally.

The core principles:

E-E-A-T principles apply here because well-structured, expert-led content is also highly citable content.

For AI visibility, expert-led content needs to be extractable, up to date, and corroborated by reliable external sources.

Avoid client-side rendered JavaScript for key content sections and links

Don’t assume AI crawlers will render JavaScript in the same way Googlebot can. Make critical content and key entity signals available in the initial HTML or through reliable server-side rendering.

Images and videos also need to be crawlable and indexable. Use descriptive alt text, accessible media files, relevant surrounding copy, and clear page context so visual assets can support, rather than block, understanding.

Check and monitor crawlability toward AI bots

Use technical SEO validation tools, log file analysis, and crawler testing to monitor whether AI bots can access your important pages. This should become part of your recurring technical SEO checks, especially for high-impact pages.

Principle 3: Strengthen Brand Authority through third-party corroboration

Third-party sources play a major role in how AI systems understand and describe brands. For example, AirOps research found that 85% of brand mentions in AI search came from third-party sources rather than brand-owned content.

The exact percentage will vary, but the implication is that your site is not the only source shaping your AI visibility.

Growing Brand Authority for AI visibility requires coordinated work across:

Positive sentiment and positioning matter more than ever. It’s no longer enough to earn mentions, links, or citations. The context of those mentions matters.

Expand your optimization efforts based on where the gaps are

The core SEO pillars still matter, but the questions we ask under each one need to expand:

Concluding thoughts: Experiment, be flexible, and keep learning

We’re still early in AI search. The data available today is incomplete compared with what SEOs have built up over decades in traditional search.

That means AI search optimization needs to be practical, flexible, and evidence-led.

Use the readiness framework from part one to diagnose where your site and brand are currently weak. Then prioritize optimization that improves AI search visibility.