Local SEO in 2026: When AI Overviews Go “Global”

Most SMBs don’t lose local customers because they rank poorly. They lose them because Google’s AI Overviews can answer the question using someone else’s market—sometimes a different country, currency, or set of rules.

That’s the shift many U.S. small businesses are feeling in early 2026: search is getting less like a “list of nearby options” and more like a synthesized explanation. Helpful for research. Risky for anyone who depends on local intent turning into calls, bookings, and checkouts.

This post is part of our “How AI Is Powering Technology and Digital Services in the United States” series, where we track how AI changes the way customers discover, evaluate, and buy. Here, the practical problem is global search misalignment: AI Overviews pulling in out-of-market sources for queries that should be local.

What’s actually happening with Google AI Overviews

AI Overviews prioritize “most defensible explanation” over “most usable local result.” That single design choice explains why a Boston homeowner searching “best heat pump rebate” might see a Canadian program cited, or a U.S. buyer searching “price of [product]” gets a UK page shown in dollars only after they click.

Traditional SEO was built around ranking and serving: Google finds relevant pages, then serves the best regional version using signals like location, language, and hreflang.

AI Overviews are built around retrieval and grounding: the system tries to reduce wrong answers by collecting high-confidence “fact chunks” from many sources. If an out-of-market page has the cleanest explanation of one sub-point, it can win the citation—even if it sends a customer to a dead end.

The “fact chunk” is the new unit of competition

In classic search, pages compete. In generative search, snippets of meaning compete.

AI Overviews often break one query into multiple parallel sub-queries (sometimes called query fan-out): definitions, eligibility, steps, constraints, comparisons, etc. Your page may be great overall, but if a competitor’s (or your own other-country page) has a clearer paragraph about one sub-facet, that paragraph may become the cited anchor.

One-liner worth remembering: In AI Overviews, you don’t just need the best page—you need the best extractable block.

Why “geographic leakage” is a feature for Google—and a bug for SMBs

From an engineering perspective, global leakage can be a success. From a business perspective, it’s lost revenue.

Google’s generative systems are trying to be:

• Comprehensive (cover all plausible interpretations)
• Grounded (cite sources to reduce hallucinations)
• Diverse (avoid citing the same handful of sites)

None of those goals include “make sure the user can buy/book locally.” That’s the commercial blind spot.

Ambiguous queries trigger expansion, not localization

Ambiguity is the accelerant.

In traditional local search, ambiguity was often resolved late using context (location, past behavior, device). AI Overviews respond differently: ambiguity triggers semantic expansion. The system explores many meanings at once so it can produce a defensible answer.

For SMBs, that means queries like these are more at risk:

• “best payroll software” (country-specific compliance)
• “how to register a business name” (state vs federal vs other countries)
• “VAT vs sales tax” (U.S. user, global explanation)
• “delivery times for [product]” (varies by region)

If the Overview is trying to cover all interpretations, it may cite sources that are accurate but not actionable in your customer’s location.

Why perfect hreflang can still lose

hreflang was designed for serving the right regional URL once a page is selected.

AI Overviews often decide citations upstream, during retrieval. If the system pulls a specific out-of-market URL as the highest-confidence source for a sub-answer, downstream geo logic has limited ability to swap it.

Put bluntly: hreflang can help Google serve the right page. It doesn’t guarantee Google will retrieve the right page for grounding.

The SMB impact: fewer clicks, lower conversion, messier attribution

When AI Overviews cite the wrong market, SMBs get hit three ways: visibility, conversion, and measurement.

1) Local visibility gets “crowded out” at the top

AI Overviews sit above (or interwoven with) classic results. Even when your site ranks well, the Overview can siphon attention toward a source card that’s not you—or not your U.S. page.

2) Conversion collapses when intent meets the wrong market

Out-of-market citations cause predictable outcomes:

• pricing in the wrong currency
• shipping not available
• phone numbers that can’t be called locally
• forms that reject U.S. ZIP codes
• compliance guidance that’s legally irrelevant

The user doesn’t blame the AI system. They blame the experience. Then they bounce.

3) Your analytics won’t clearly show the damage

A hard part for SMBs: commercial harm isn’t always visible.

If users get what feels like an “answer” in the Overview, they may not click at all (zero-click). If they do click an out-of-market URL and bounce, you won’t see that as lost conversion in your own analytics.

The result is a quiet problem: pipeline softens, and you can’t point to one obvious ranking drop.

How to protect local visibility: a practical GEO checklist for SMBs

The goal is simple: make the “most complete version of the truth” also the most locally usable version. In practice, that means building content for generative retrieval, not just blue-link ranking.

Below is a defensive playbook you can implement without an enterprise SEO team.

1) Create “semantic parity” across your key location pages

If you operate in multiple regions (or you have country subfolders), tiny differences can make one page more “citable.” AI systems may normalize similar pages as the same meaning and then choose the one that looks fresher or clearer.

What to do:

• Keep core product/service explanations consistent across locations
• Don’t let one market page become the “most updated” while others lag
• Standardize key sections: pricing logic, availability, warranties, returns, service area

Tip: If you updated your /ca/ page last month but not your /us/ page, don’t be surprised when the Canadian page gets cited for a U.S. query.

2) Write in extractable blocks that match fan-out questions

AI Overviews love content that’s easy to lift cleanly.

On your highest-intent pages, add short sections that answer common sub-questions directly:

• eligibility
• steps
• timelines
• constraints
• common mistakes
• who this is for

A good pattern is:

• a 1–2 sentence direct answer
• a short bulleted list of conditions
• a quick “If you’re in the U.S., here’s what applies” line

This doesn’t make your content “dumbed down.” It makes it retrievable.

3) Add explicit market validity signals (don’t rely on inference)

AI systems don’t reliably infer commercial usability from prose alone. You need clear, machine-readable cues and unmistakable text cues.

Practical steps SMBs can take:

• Put service area and availability in plain language near the top (not buried in the footer)
• Use consistent NAP details (name, address, phone) across the site
• Add strong on-page cues like:
  • “Available in the United States”
  • “Serving customers in Texas and Oklahoma”
  • “Pricing shown in USD”
• Use structured data where relevant (LocalBusiness, Product, Offer, Service)

One-liner: If a customer can’t buy it in your market, say so clearly—because the model won’t protect you from that mismatch.

4) Reduce ambiguity with “location-anchored” phrasing

If ambiguity triggers global expansion, you want to remove ambiguity.

You can do that by anchoring your content to U.S. realities:

• reference U.S. agencies, standards, or compliance where appropriate
• include state-level examples if you serve specific states
• use U.S. units, terms, and expectations consistently (USD, ZIP codes, business entity types)

This isn’t about stuffing “United States” everywhere. It’s about making the page’s meaning unmistakably tied to the market.

5) Audit where AI Overviews are stealing (or misrouting) demand

You don’t need fancy tooling to start. Do a monthly check for your top 20 queries:

• branded + “pricing”
• “near me” variants (even if AI Overviews are less common)
• “how much does [service] cost”
• “best [service] in [city]”
• “requirements for [service]”

Track:

• whether an AI Overview appears
• which sources are cited
• whether citations point to your correct U.S. URLs
• whether your competitors’ out-of-market pages appear

If you see leakage, treat it like a conversion issue, not a “rankings” issue.

A quick example: a multi-location service business

Say you run a U.S.-based accounting firm with pages for different states, plus a Canada-targeted content hub because you acquired a small Canadian practice.

Your U.S. page says:

• “We help small businesses file quarterly taxes.”

Your Canadian page says:

• “We help small businesses file quarterly taxes. Here’s a step-by-step checklist and common mistakes.”

Those are semantically close, but the Canadian page has clearer, more structured “fact chunks.” When a user searches “quarterly tax filing checklist,” AI Overviews may cite the Canadian page—even if the user is in Ohio and needs U.S. guidance.

The fix isn’t mystical. You’d:

• add the same checklist structure to the U.S. page
• include U.S.-specific steps and references
• explicitly label jurisdiction (“U.S. quarterly estimated taxes”)
• ensure freshness and internal linking support the U.S. version

What to do next if local leads matter to you

If you’re an SMB, the actionable stance is this: stop treating AI Overviews as “just another SERP feature.” They change what it means to be visible.

Start with the pages that drive revenue (services, pricing, location pages). Make them easy for AI systems to cite correctly by tightening market cues and structuring content into retrievable blocks.

Generative search will keep expanding across platforms—Google, chat tools, AI assistants inside SaaS products, even support agents that quote the web. The businesses that win won’t be the ones that chase every algorithm rumor. They’ll be the ones that make their answers both accurate and actionable for the right market.

What’s one high-intent query you rely on for local leads—and have you checked what AI Overviews are citing for it this month?