Google AI Overviews: how MSPs can win the cited-source spot

Google AI Overviews has become a meaningful traffic surface for MSPs through 2025 and into 2026. Buyer queries that used to return ten blue links and a maps pack now return a generated answer with two to four cited sources sitting above everything else. Whether your MSP is one of those cited sources matters more than whether you rank fourth or seventh below it.

We’ve helped MSPs work towards the cited spot for clients including Aspire Technology Solutions and Acronyms IT Support. The pattern is consistent across the engagements. There’s no silver bullet, but there is a small set of moves that compound, and most MSPs are leaving them on the table.

How Google AI Overviews picks its sources

AI Overviews draws from Google’s classic web index, with a layer of generative reasoning on top. The candidate sources for a given query come from a relatively small set, typically the top ten to twenty organic results, with weighting for authority, freshness, structured data and how directly the page answers the question.

For MSP-shaped queries, three things tend to drive selection:

• Topical alignment to the specific question. A page about “managed IT support for accountancy firms in Manchester” beats a generic “managed IT services” page for that query, even if the second page outranks it for broader terms.
• Local relevance and entity clarity. AI Overviews leans on local signals more than ChatGPT or Perplexity do. MSPs with strong local SEO foundations get cited more often.
• Page structure that maps to the question shape. Definitions, lists and direct answers near the top of the page outperform meandering service descriptions.

We’ve covered the underlying retrieval logic in more detail in how LLMs cite sources.

What MSP buyer queries actually look like

Before optimising for AI Overviews, it helps to be specific about which queries matter. Across our MSP client base, the queries that surface AI Overviews most often fall into three groups:

• Definitional. “What is co-managed IT?” “What does an MSP do?” “How is MDR different from EDR?”
• Comparison and selection. “Best MSP for law firms in Birmingham.” “How to choose an IT support provider.” “MSP vs in-house IT pros and cons.”
• Pricing and scoping. “How much does outsourced IT support cost?” “Average MSP pricing per user UK.” “What’s included in 24/7 IT support?”

The third group is the one most MSPs avoid because they prefer to keep pricing off the public site. We understand the commercial reasoning, and we’ve seen it cost real visibility in AI Overviews. A page that gives buyers a credible range, with caveats, will outperform a page that says “contact us for pricing” every time.

Page structures that get cited

The pages that earn citations from AI Overviews share a fairly tight structure. We’ve found this works as a template:

1. Direct answer in the first paragraph. Two or three sentences that answer the page’s core question without the buyer having to scroll.
2. Quick context. Who the answer applies to. Mid-market businesses, professional services firms, organisations with X to Y users.
3. A definitional or comparative section with clear subheads. Often best as a short table or list.
4. Specific pricing or scoping detail. Even a range with caveats. “Most UK MSPs charge £50 to £150 per user per month for fully managed IT, depending on after-hours coverage and security tooling included.”
5. A clear local or sectoral hook. Where applicable, name the towns, sectors or sizes you actually serve. Generic pages do not get cited for specific queries.
6. Author byline and recent date. With Article and Person schema. This pairs with what we covered in structured data for AI search.

We’ve also covered the writing-craft side of this in writing content that AI search engines actually cite. For local-search foundations, the same principles in local SEO for IT support companies still apply.

The local SEO dimension

Google AI Overviews is the AI search surface where local SEO matters most. Other engines treat geography lightly. Google does not. For MSPs whose buyers are typically within sixty miles, the local foundation has to be in good shape before AI Overviews will reach for your pages.

The basics still apply. A complete and accurate Google Business Profile, consistent NAP details across directories, locally relevant landing pages and citations from local press or trade bodies. We’ve found MSPs with strong Business Profile reviews, particularly recent ones with substantive text, get cited disproportionately.

Local schema also helps. LocalBusiness (or the more specific ProfessionalService) schema with accurate address, hours, areaServed, sameAs and aggregateRating where you have it. Done honestly, this is one of the cheaper wins.

Building topical authority around an MSP’s actual offer

MSPs tend to spread thin across the things they sell. A site might cover Microsoft 365, Azure, Google Workspace, cybersecurity, helpdesk, networking, telephony and procurement, all on shallow service pages. AI Overviews rewards depth, not breadth.

We typically work with MSP clients to pick three to five topical areas where they have genuine depth and build out content clusters around them. Topic clusters with a strong pillar page, supporting articles and clear internal linking pull more weight in AI search than a sprawling, undifferentiated site does. We’ve covered the cluster model in topic clusters for tech companies.

For an MSP that serves law firms heavily, that might mean a pillar on “IT support for law firms” with cluster pieces on legal-specific compliance, document management, secure remote work, practice management software integrations and so on. A site that does this gets cited for legal-IT queries far above its weight class. We’ve drilled into the wider opportunity in AI search for IT services.

Practical sequence we’d recommend

If you’re an MSP starting from scratch, the rough sequence we’d run:

1. Audit current AI Overviews appearance. Pick fifteen buyer-intent queries. Run each in a logged-out, location-set browser. Note who’s cited and where you appear.
2. Tighten Google Business Profile and local foundations. This is table stakes.
3. Pick two or three topical pillars where you have real depth. Resist the urge to do all of them at once.
4. Rewrite or commission cornerstone content with the page structure described above. Direct answers, specifics, pricing where you can.
5. Add Article, Person, Organization and LocalBusiness schema as covered in structured data for AI search.
6. Re-run the audit at six and twelve weeks. Track citation movement, not just rankings.

This is meaningful work. It’s also the work that pays back, because AI Overviews citation tends to be sticky once established.

A note on what does not work

We’ve watched several MSPs invest in tactics that did not move AI Overviews citation. Bulk programmatic location pages with thin content, AI-generated articles with no original viewpoint, schema spam on pages where the markup did not match the content and reciprocal-link schemes hoping to lift authority. None of these worked. Most of them slightly hurt.

The honest path is fewer, deeper pages, written by or with people who know the topic, with clean foundations and patient measurement.

If you’d like a second opinion on your AI search strategy, drop us a line. MSP work is one of the bigger parts of our AI SEO practice, and we’re usually happy to compare notes on what’s been working and what hasn’t.