Build an SEO content roadmap for AI search by starting with business goals, finding relevant topic opportunities, checking the live search results, grouping queries into pages, prioritizing by value and intent, and briefing content for both readers and search features. This six-step workflow is Corey Morris’s approach at Voltage, described in an October 2, 2026, Search Engine Journal article; it is a practical method, not a guarantee of rankings or traffic.
1. Set the business outcome before researching keywords
Decide what the roadmap is supposed to produce: qualified leads, ecommerce revenue, or another measurable business result. That decision gives each topic a reason to exist and helps distinguish a useful opportunity from a large search-volume number that does not serve the organization.
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Write down the intended outcome and the audience or decision it relates to before opening a keyword tool. A topic should have a plausible route from the searcher’s need to the outcome; if it does not, it may not belong on this roadmap.
2. Find topic opportunities, then screen the gap
Build a keyword universe by comparing your site with the sites that compete for search visibility. Those may differ from the companies your sales or product teams consider direct competitors. In Morris’s example, Ahrefs Content Gap accepts a site and two to four competitors for a focused comparison, with an interface limit of up to ten. The workflow can be adapted to another SEO platform.
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- Choose search competitors. Include sites that rank for topics your audience searches, not only familiar commercial rivals.
- Find missing terms. Identify relevant queries for which competing sites rank and your site does not.
- Review the ranking pages. Check what those pages cover and whether their search intent fits your audience and offer.
- Filter and export useful candidates. Use difficulty, volume, and ranking ranges as screening signals, then export relevant terms for later grouping.
- Remove false opportunities. Exclude branded, off-intent, and otherwise irrelevant terms before turning the gap into a work list.
A content-gap export is input for editorial judgment, not a publishing queue. The example in Morris’s October 2026 article compares “3pl” (KD 47 and 29,000 monthly searches), “3pl fulfillment” (KD 11 and 2,600), and “3pl companies” (KD 18 and 5,000). These are illustrative figures reported in that article, not current keyword metrics; check a live data source before using them for a decision.
3. Inspect the search results, including AI Overviews
For each shortlisted topic, inspect the actual results page rather than inferring the opportunity from a keyword metric. Record whether Google shows an AI Overview, which other features appear—such as ads, People Also Ask, or a local pack—and which pages the Overview cites.
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Morris describes using Ahrefs Keywords Explorer to find terms that trigger AI Overviews and Site Explorer’s Organic Keywords report to check whether the site’s pages appear in them. Equivalent data from another platform can support the same investigation. The central question is strategic: is the opportunity to earn a click, to be cited in an AI Overview, or to pursue both?
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An AI Overview is not an automatic reason to abandon a topic. It can change the likely value of a click and the outcome worth pursuing, so set expectations from the observed SERP rather than assuming a conventional ranking will bring the same traffic as before.
What the click-through evidence says—and does not say
In a February 4, 2026, Ahrefs study update, Ryan Law reported that AI Overview presence correlated with a 58% lower average click-through rate for the top-ranking page. The analysis compared 150,000 keywords with an AI Overview against 150,000 informational keywords without one, using aggregated Google Search Console average desktop CTR data. It compared December 2023 with December 2025; for the AI Overview group, position-one CTR was 0.073 in December 2023 and 0.016 in December 2025. The reported 58% estimate is observational, based on an aggregated sample, and is not a forecast or guaranteed loss for an individual site or query.
4. Turn keywords into page-sized clusters
A keyword list is not a page plan. Decide which queries can be answered well by one destination and which represent distinct needs that deserve separate pages. Morris’s example uses shared ranking pages, including Parent Topic clustering, or shared terms to identify related queries.
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Organize the working sheet as Cluster > Group > Keyword. For each keyword, record difficulty, volume, intent, and SERP features. Then map each cluster to a destination such as a hub page, service page, or article. The result should be a set of pages with a clear purpose, not multiple pages competing to answer the same question.
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Compare each cluster against the business objective and the conditions on its SERP. Use the following factors together; no single metric captures the full opportunity.
- Ranking difficulty: Is the site realistically positioned to compete for the topic?
- Business potential: Could a useful page contribute to the chosen business outcome?
- Intent and conversion proximity: Is the searcher learning, comparing options, or close to a lead or purchase?
- SERP and AI Overview conditions: Is the likely value a click, an AI citation, or both?
- Search volume: Use volume to distinguish otherwise comparable opportunities, not as the first test of value.
In Morris’s 3PL example, “3pl fulfillment” and “3pl companies” rank ahead of the broader “3pl” opportunity because their intent is more commercially specific. An Amazon FBA prep cluster also advances despite lower search volume because its intent is closer to buying. These are examples of how to apply the framework, not universal rankings for those topics.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.6. Brief each page for its audience and its SERP
Turn every prioritized cluster into a brief that connects the planned page to both the searcher’s need and the observed results. Include:
- the primary keyword and supporting terms;
- the searcher’s intent stage and the business outcome the page can support;
- relevant SERP features, including any AI Overview and its cited pages;
- the destination page type and its role in the site’s content structure; and
- the angle, evidence, and expertise that make the page useful beyond a generic answer.
For the finished content, Morris recommends putting direct answers near the top of relevant sections, using headings that reflect how people search, supporting claims concisely, adding concrete expertise and named detail, using structured data, and linking supporting pages to the hub. Treat those as editorial and site-structure choices, not a promise of inclusion in an AI Overview. Use AI to accelerate drafting or analysis while keeping human expertise, evidence, and editorial judgment responsible for the final work.
Test the roadmap on one cluster
Before changing the whole content operation, establish a baseline and try the workflow on one cluster. Compare its results with content produced using the previous approach. That gives the team a contained way to assess whether the new prioritization and briefing process is helping before scaling it across the roadmap.
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