The AI search benchmark report: how small businesses get found in the age of AI

About this report

If you run a small business, the way customers find you is changing at the layer between the question and the click. AI-driven search is no longer a side experiment for early adopters. It now shapes answers inside Google, ChatGPT, Perplexity, Bing, Amazon, Apple, and other discovery surfaces that customers already use.

This report exists because small business owners deserve clear, evidence-based answers about what’s actually happening – not hype, not panic, and not a technical whitepaper written only for search specialists.

We built this as a reference you can come back to. Whether you’re a local service provider in Calgary, a DTC brand shipping across North America, or a B2B firm selling software to mid-market companies, you’ll find something here that applies directly to your business.

This is the inaugural edition of what will become an annual series. Future editions will include proprietary benchmark data from controlled testing across major AI search platforms. This edition draws on academic research, industry studies, and official platform documentation to give you the clearest practical picture of where things stand right now.

How to use this report:

If you’re short on time, start with the Executive Summary and Chapter 5 (your action plan). If you want the full picture, read straight through. If you’re data-minded, Chapter 3 has the numbers. If you want to understand how your specific business type is affected, jump to Chapter 4.

Scope note:

This report uses “AI search” to describe user-facing systems that retrieve, synthesize, summarize, recommend, or cite information in response to a search-like query. That includes Google AI Overviews and AI Mode, ChatGPT Search, Perplexity, Bing/Copilot search experiences, marketplace shopping assistants, and local discovery surfaces where AI changes how businesses are selected or described.

It does not treat every chatbot interaction as search. A private AI assistant drafting an email is outside this report. A customer asking an AI tool which accountant, software product, restaurant, agency, or supplier to choose is inside it.

Evidence note:

AI search data changes quickly, and different studies use different query sets, markets, devices, and collection windows. When numbers conflict, this report favors transparent methodology over the biggest headline. The point is not to pretend the field has already settled. The point is to give operators a reliable decision framework while the field is still moving.

Chapter 1: the search revolution that’s already here

Your customers haven’t stopped searching. They’ve stopped scrolling. AI now answers their questions before they ever see your website – and increasingly, before they even see a list of links.

What AI search actually is

Simple definition: AI search is when a system searches the web on your behalf, reads the results, and writes you a synthesized answer with links to its sources. Instead of giving you ten blue links and asking you to figure it out, it gives you an answer and tells you where it got the information.

That’s a fundamental shift. For decades, search engines were librarians – they pointed you to the shelf. Now they’re more like research assistants – they read the books and give you a summary. In practice, AI search shows up in four overlapping ways.

The first is standalone AI search tools – platforms like ChatGPT Search and Perplexity that search the web in real time, synthesize an answer, and show you exactly which sources they pulled from.

The second is AI answers embedded inside traditional search. Google’s AI Overviews and AI Mode are the biggest examples. You search on Google the way you always have, but now an AI-generated answer may appear before the traditional results. Broad query-coverage estimates vary sharply by study: Pew found AI summaries on 18% of tracked Google searches in March 2025, Semrush found AI Overviews on 15.69% of monitored queries in November 2025, and a 2026 academic study found 13.7% activation across trending queries, rising to 64.7% for question-form searches. The exact percentage matters less than the pattern: AI answers concentrate on the kinds of questions small businesses often answer with educational content.

The third is blended search, where AI-generated answers coexist with ads, maps, shopping modules, reviews, and business listings on the same page. This is where things get complicated for businesses, because your visibility now depends on multiple elements working together – not just your organic ranking.

The fourth is multimodal search – searching with images, voice, your camera, or a mix of inputs. Google’s Lens lets you search by pointing your phone at something. Apple’s visual intelligence can summarize what you’re looking at and search across your apps. This type of search is still emerging, but it’s growing quickly and it changes what “being findable” means.

How fast this moved

The speed of adoption is hard to overstate.

In 2023, Google previewed its generative search experiment in Search Labs, and Microsoft normalized AI-generated answers inside Bing. It felt experimental. Most businesses could safely ignore it.

By 2024, the experimentation phase was over. Google launched AI Overviews broadly across the United States. Amazon launched Rufus, its AI shopping assistant. Apple announced Apple Intelligence. OpenAI launched ChatGPT Search.

In 2025, things accelerated. Google introduced AI Mode – a deeper, more conversational search experience that lives alongside traditional search. ChatGPT Search became available to everyone in supported regions, with no account required. Anthropic added web search to Claude. Microsoft retired its legacy Bing Search APIs and pushed developers toward AI-grounded alternatives.

And in 2026, the scale became undeniable. Google’s I/O 2026 opening keynote put AI Overviews above 2.5 billion monthly active users and AI Mode above one billion monthly active users. Amazon renamed Rufus to Alexa for Shopping. Research published this year shows that AI search exposure expanded from 7 countries in 2024 to 229 countries in 2025. DuckDuckGo also reported renewed demand for AI-optional search experiences after Google’s AI-heavy Search announcements, a reminder that not every customer wants the same level of AI mediation.

This timeline points to one practical reality: most businesses are no longer early to this shift. If you have not thought about how AI search affects your business, you are already catching up.

Business impact

The core shift is simple. For twenty years, the game was about ranking. Get your website to the top of Google, and customers would find you. That model still matters, but it is no longer the whole story.

Now, the game is increasingly about being cited. When a customer asks ChatGPT “What’s the best accounting software for a small Canadian business?” or asks Google “Who does managed IT in Vancouver?”, the AI doesn’t just show a list of links. It writes an answer. It names specific companies. It cites specific sources.

If your business isn’t in that answer, it effectively doesn’t exist for that customer in that moment.

The rest of this report will show you exactly what the data says about this shift, how it affects different types of businesses, and what you can do about it.

Chapter 2: the platforms reshaping how customers find you

You keep hearing about AI search, but nobody tells you which platforms actually matter for your business. The answer depends on what you sell, who you sell it to, and how your customers search. Some platforms affect nearly everyone. Others are critical for certain business types and irrelevant for others.

Here is the platform map as of 2026.

Google Search: AI Overviews and AI Mode

Google is still the center of gravity for online discovery, and it now has two major AI search surfaces.

AI Overviews are the AI-generated summaries that appear at the top of regular Google search results. They’ve been broadly available since 2024, Google expanded them to more than 200 countries and territories in 2025, and Google’s I/O 2026 opening keynote put usage above 2.5 billion monthly active users. When an AI Overview appears, it typically pushes traditional results further down the page – and as we’ll see in Chapter 3, that changes click behavior.

AI Mode is a separate, more conversational search experience that Google introduced in 2025. Think of it as Google’s answer to ChatGPT: you can ask complex, multi-part questions and get detailed, synthesized responses with links. Google says it has already crossed one billion monthly users. One notable design choice: when Google’s confidence in an AI response is not high enough, AI Mode may return traditional web links instead, which is a useful trust signal.

Google also continues to invest in multimodal search through Lens, where users can search using images, their camera, and combinations of text and visual input.

For virtually every small business, Google is the highest-priority platform to understand and optimize for.

ChatGPT Search

OpenAI’s ChatGPT Search gives users timely, web-grounded answers with inline citations and a sources panel. Since February 2025, it’s been available to anyone without requiring an account, which means its reach has expanded well beyond the early-adopter crowd.

Two things matter for businesses. First, ChatGPT Search can show inline citations that link directly to your pages – making the quality and crawlability of your content directly relevant. Second, ChatGPT’s Memory feature can influence how it rewrites and personalizes searches, which means the same question asked by two different users may surface different results.

ChatGPT Search is especially important for B2B discovery and research-heavy purchase decisions. When executives, analysts, and consultants are evaluating vendors or researching solutions, ChatGPT is increasingly part of that workflow.

Microsoft Bing and Copilot

Microsoft has been aggressive about integrating AI into its search ecosystem. Bing grounding provides real-time web data with citations, freshness filters, and specific market and language parameters. Microsoft’s Copilot products – used across the enterprise suite – lean on Bing for web-grounded answers.

A telling signal: in 2025, Microsoft retired its legacy Bing Search APIs and pushed developers toward AI-based alternatives. That’s a clear institutional bet that AI-grounded search is the future, not a feature bolted onto the old model.

For businesses with enterprise customers or significant Microsoft ecosystem exposure, Bing/Copilot visibility matters more than the general market share numbers might suggest.

Perplexity

Perplexity has positioned itself as a search-native AI answer engine, meaning it was designed from the ground up to search the web in real time and return cited answers rather than retrofitting AI onto an existing search product.

Its key differentiator is citation transparency. Perplexity emphasizes real-time ranked web results, and its interface makes sources visually prominent. Its API also exposes structured controls such as domain filtering, search filters, and user-location context, which gives agencies and power users more precision than most competitors.

Perplexity runs separate crawlers for indexing and user-initiated requests – a distinction that matters for businesses managing their crawl permissions and content access policies.

While Perplexity’s overall user base is smaller than Google’s or ChatGPT’s, it has strong mindshare among AI-forward professionals and tech-savvy decision-makers. If your customers are in that category, Perplexity deserves attention.

Apple: the local discovery powerhouse

Apple’s AI search play is less about competing with Google on general web search and more about owning the local discovery and device-integrated experience.

Apple Intelligence – launched in 2024 – combines on-device AI with visual intelligence features that can summarize what you’re looking at and search across apps. Apple Business lets companies claim their locations on Apple Maps, control hours, images, key details, and gain insights about customer discovery.

For local businesses, this is one of the highest-risk AI-search shifts. Apple Maps is the default mapping and navigation experience for many iPhone users. If your business listing on Apple Maps is inaccurate – wrong hours, wrong address, or worse – the consequences can be immediate. In 2024, a restaurant owner publicly reported a significant sales hit after Apple Maps incorrectly marked the business as permanently closed. That is a warning about what happens when entity data breaks down on a platform your customers rely on.

Apple has also brought Maps advertising to the United States and Canada, adding a paid discovery layer for local businesses.

Amazon: the shopping search revolution

If you sell products on Amazon, the AI search shift is happening inside your marketplace too. Amazon launched its Rufus AI shopping assistant in 2024 and renamed it Alexa for Shopping in May 2026, moving the assistant more directly into Amazon.com and the Amazon app.

This isn’t general web search – it’s conversational shopping. Customers can now ask natural-language questions about products, compare options, and take purchase actions through an AI interface. For sellers and brands on Amazon, this represents a new discovery layer that operates differently from traditional keyword-based Amazon search.

This is a high-priority surface for ecommerce businesses selling on Amazon, but it’s not a substitute for general web search benchmarking.

DuckDuckGo: the privacy alternative

DuckDuckGo offers Duck.ai as an optional AI search interface, but its most interesting role in 2026 is as a counterpoint. After Google’s AI-heavy announcements at I/O 2026, DuckDuckGo saw renewed interest from users actively seeking search experiences without AI summaries.

This signals something businesses should pay attention to: not every customer wants an AI-mediated experience. There’s a growing segment that prefers traditional search, and DuckDuckGo is capturing some of that demand. For benchmarking purposes, it’s a useful comparison surface – not a primary optimization target.

Open-source search stacks

For businesses that want to build their own AI-driven search – on their website, in their help center, across internal documents, or inside a product catalog – open-source tools like Elastic, OpenSearch, Vespa, and Haystack provide the building blocks.

These aren’t platforms your customers search on directly. They’re tools for building search experiences you control. Elastic and OpenSearch support semantic and hybrid search workflows. Vespa handles vector search and retrieval-augmented generation. Haystack provides modular retrieval pipelines across multiple backends.

This matters most for agencies building client solutions, mid-market businesses with complex product catalogs, or any company that wants to run AI search on its own terms rather than depending entirely on public platforms.

Quick reference: which platforms matter most for your business

Swipe sideways to see the full table on smaller screens.

Chapter 4 breaks down how each business type is specifically affected, with the risks and opportunities unique to your model.

Chapter 4: how your business type shapes your risk

A plumber in Toronto, a DTC skincare brand, and a B2B cybersecurity firm all face AI search disruption – but the risks hit differently depending on how your customers find you and what they’re looking for when they do.

Local service businesses

If you run a local business – a dental practice, a plumbing company, a restaurant, a law firm, an accounting office – your exposure to AI search is primarily through maps, local business listings, review ecosystems, and answer-style queries like “best dentist near me” or “emergency plumber in Ottawa.”

AI is changing this in two ways. First, comparison and recommendation queries that used to generate a list of ten links now often get a direct AI-generated answer. The AI names specific businesses, describes what they offer, and sometimes makes explicit recommendations. If you’re not in that answer, a potential customer may never see you.

Second, the accuracy of your business data across platforms has become operationally critical. It’s no longer just about Google Business Profile. Apple Maps, Bing Places, and other platforms all feed into AI answers. When that data is wrong – incorrect hours, a missing phone number, an outdated address – the consequences can be immediate. The Apple Maps restaurant incident we covered in Chapter 2 is an extreme example, but the underlying risk applies to any local business that depends on accurate discovery across multiple surfaces.

Your priority platforms are Google (AI Overviews and AI Mode), Apple (Maps and Business), and Bing/Copilot.

Ecommerce and retail

If you sell products online, AI search disruption looks different. Your exposure comes through AI shopping assistants, product comparison answers, and marketplace-native AI search.

Amazon’s shift from Rufus to an integrated Alexa for Shopping experience means that product discovery on the world’s largest marketplace is becoming conversational. Customers can ask natural-language questions about products, compare options, and take purchase actions through an AI interface – which changes what it takes to be surfaced. Product detail quality, review depth, and competitive positioning all feed into AI-generated shopping recommendations.

Outside Amazon, AI search engines like Google and ChatGPT increasingly answer product comparison queries directly. “Best wireless earbuds under $100” or “most reliable dishwasher brands in Canada” are the kinds of queries where AI answers are replacing the click-through-and-browse behavior that used to drive organic traffic.

Your priority platforms are Google (AI Overviews and AI Mode), Amazon (Alexa for Shopping), ChatGPT Search, and Bing.

B2B companies

If you sell services or software to other businesses, your AI search exposure comes primarily through educational queries, vendor comparison prompts, and synthesis-style answers.

When a CFO asks ChatGPT “What’s the best cloud accounting software for a 50-person Canadian company?” or a CTO asks Perplexity “How do I evaluate managed IT providers in Ontario?”, the AI reads guides, reviews, documentation, pricing pages, and case studies – then writes a recommendation. If your content isn’t part of what it reads, you won’t be part of what it recommends.

This makes thought leadership and educational content a direct discovery asset, not just a brand-building exercise. The depth, clarity, and freshness of your published content directly influence whether AI systems include you in the answers that matter.

Your priority platforms are Google (AI Overviews and AI Mode), ChatGPT Search, Perplexity, and Bing/Copilot.

The common thread

The details differ by business model, but the direction is the same: every type of business now needs to be visible across multiple AI surfaces, not just one. Chapter 5 lays out the specific moves you can make – regardless of your size or budget.

Chapter 6: measuring what actually matters

Most small businesses have no idea whether they’re showing up in AI search answers – or what’s being said about them when they do. Fixing that doesn’t require expensive tools. It requires knowing where to look.

The metrics that matter

The biggest mistake you can make is looking for one overall “AI search score.” Different platforms perform differently across different dimensions, and what matters most depends on your business type. A balanced scorecard approach is far more useful.

Focus on four metric families.

Trust and grounding: Are your pages being cited by AI search platforms? When they are, do the AI-generated statements accurately represent what your pages say? As Chapter 3 showed, a significant share of AI citations don’t fully support the claims they’re attached to. You want to be cited, but you also want to be cited accurately.

Visibility and reach: When someone asks an AI platform a question relevant to your business, do you show up? How often is your brand mentioned in the answer? How often are you in the recommended shortlist? Tracking branded queries across platforms monthly will give you a baseline.

Search quality: Are the AI-generated answers about your industry – and about your business specifically – stable and accurate? If the same question generates different answers every time, or if AI answers about your category contain errors, that’s something you need to know.

Business impact: Ultimately, you care about whether AI search drives traffic, leads, calls, and purchases. Track this through your existing analytics (Search Console, GA4, Apple Business insights, seller reporting) and specifically look for changes in the referral sources and landing pages that are growing or shrinking.

A practical framework

Start with what you already have. Google Search Console includes sites appearing in Google’s AI features inside overall Search traffic, but it does not give small businesses a dedicated, universal AI Overview or AI Mode filter. GA4 tracks referral traffic by source. Apple Business provides discovery insights for local businesses. Amazon seller reports show how your products perform in marketplace search.

Then add AI-specific monitoring. At minimum, run your most important branded and category queries across Google, ChatGPT, and Perplexity once a month and record whether you appear, what’s said about you, and which sources are cited. This doesn’t need to be automated to be useful – a monthly manual check gives you a practical baseline.

The most important thing is to look at both sides of the ledger. Track losses in classic organic traffic and gains in AI referrals or branded mentions. Focusing on only one side gives you an incomplete picture.

A simple AI visibility log

Use one row per prompt per platform.

Over time, this log becomes more useful than a one-time audit. You will see which platforms change, which competitors keep appearing, which sources influence answers, and where your business is being misrepresented.

Match metrics to your business type

If you’re a local business, focus on map and listing visibility, local action rates (calls, directions, website visits from listings), and entity accuracy across platforms.

If you’re in ecommerce, focus on product citation rates, inclusion in comparison answers, and presence in AI shopping assistant results.

If you’re B2B, focus on brand mention rates in research queries, citation quality for your content, and whether your thought leadership is being surfaced in the platforms your buyers use.

Chapter 7: where AI search is headed

Everything covered here describes a market that’s still shifting. The platforms, the data, and the rules of visibility are changing faster than most businesses can track. Here is where things are headed and what that means for decisions you make today.

Trends to watch

AI answers are becoming more common, but coverage varies by query type. Broad public studies do not agree on a single AI Overview coverage number. Pew found AI summaries on 18% of tracked Google searches in March 2025, Semrush found 15.69% coverage in November 2025, and a 2026 academic study found 13.7% activation across trending queries. The important pattern is concentration: question-form, long-tail, educational, and comparison-style searches are much more exposed than simple navigational queries.

Traditional search volume is under pressure. Industry analysts are projecting meaningful declines in traditional search volume as more users get answers directly from AI. The specific numbers vary by source and methodology, but the directional trend is consistent: AI search is absorbing demand that used to flow through traditional results.

Multimodal search is expanding. Visual search through tools like Google Lens, voice search through AI assistants, and camera-based search through Apple’s visual intelligence are growing. “Being findable” increasingly means your content and business information need to work across text, images, and voice – not just typed keywords.

Platform divergence is increasing. What works on Google may not work on ChatGPT, Perplexity, or Amazon’s shopping assistant. Each platform has its own crawlers, its own indexing decisions, its own retrieval logic, and its own presentation format. Optimizing for one platform at the expense of others is increasingly risky.

Regional behavior differences matter. Canadian searches and American searches don’t always produce the same AI answers, even for similar queries. Google personalizes based on location and language. ChatGPT uses location-derived context. Claude infers location from IP. If you serve Canadian customers, you need to understand how these platforms behave in the Canadian market specifically – not just assume U.S. results apply to you.

How this report will evolve

This is Edition 1. Future editions will add proprietary benchmark data from a controlled, 180-prompt cross-platform test covering Google (AI Overviews and AI Mode), ChatGPT Search, Bing/Copilot, Perplexity, and a classic Google search control – run from Canadian IPs with U.S. comparison subsets.

The methodology framework for that benchmark is outlined in Appendix A. Our goal is to make this the reference that Canadian businesses trust when they need to understand how AI search is evolving and what it means for their visibility, their traffic, and their revenue.

The bottom line

Classic SEO still matters. It remains relevant, and anyone telling you to abandon it is wrong. But it is no longer enough on its own.

The winning strategy for the AI search era is not complicated, but it does require intentional effort: make your content easy for AI to find and trust, keep your business information consistent everywhere it appears, and build the kind of web presence that earns citations – not just rankings. Treat AI search as infrastructure, not an experiment.

The businesses that get this right in 2026 will have a meaningful head start. The ones that wait will be playing catch-up in a game where the rules are still being written.