The new discovery layer

How people find businesses is changing again

For the last 20 years, finding a local business meant a Google search. You optimized for Google: keywords, backlinks, page speed, local listings. If your SEO was good, you appeared in the top results. If someone was looking for what you offered in Edmonton or Red Deer or Grande Prairie, they found you.

That model has not gone away. But a parallel discovery channel has emerged, and for some high-intent queries it is becoming the first stop. Someone looking for a supplier, a contractor, a professional service, a product recommendation, or a local business may start not with Google but with a question to ChatGPT, Perplexity, or Gemini. They ask in plain English. They get a synthesized answer that names specific businesses, explains why, and sometimes links directly.

Perplexity's last official volume figure was 780 million queries in May 2025. ChatGPT search draws on search partners, and a site needs to allow OpenAI's OAI-SearchBot crawler to appear in its results. The businesses named in those responses are not randomly selected.

The question for any Alberta small business is not whether this channel matters. It is whether your business appears in it, and if not, why not and what to do.

The mechanics

What drives AI recommendations

AI platforms synthesize recommendations from several overlapping sources. Understanding them is the first step to influencing them.

High Impact
Online review volume and recency
Google, Yelp, and industry-specific reviews carry significant weight in our audits. AI models can learn which businesses are trusted from the density and sentiment of public reviews. A business with 12 reviews from 2021 is likely to be treated differently from one with 80 reviews in the past 12 months.
High Impact
Structured data and Schema.org markup
Schema.org markup tells search engines explicitly what your business is, what it does, where it is, and who it serves. Google says structured data isn't required to appear in its AI search features, but it helps search engines understand a page. Without it, systems must infer your business details from unstructured web content, and inferences are less reliable than explicit signals.
Medium Impact
Business profile completeness
Google Business Profile, Bing Places, Apple Maps, and industry directories. An incomplete or inconsistent profile (wrong hours, a missing phone number, outdated service descriptions) can signal unreliability to AI systems pulling structured business data.
Medium Impact
Content depth and expertise signals
AI platforms favour businesses with substantive web content that demonstrates genuine expertise in their category. A page that explains what you do, who you serve, what outcomes you produce, and why you are credible gives AI systems confidence to cite you by name.
Emerging
Machine readability
Model Context Protocol (MCP) is an open protocol Anthropic released in November 2024 for connecting AI assistants to tools and data. WebMCP is a separate browser proposal, edited by engineers from Microsoft and Google, that lets a web page offer actions to AI agents; Chrome opened an early preview in February 2026. No AI search provider has documented using either to decide recommendations, but readiness may make it easier for AI agents to act on your site once support is in place.
Emerging
llms.txt and AI guidance files
llms.txt (similar in spirit to robots.txt) is a proposed file, described at llmstxt.org, that gives AI tools a plain, machine-readable summary of your site. It is a proposal rather than an adopted standard, and Google Search does not use it, so treat it as an optional extra rather than an advantage.

The opportunity

Why Alberta small businesses have an opening right now

AI platform optimization (AEO, GEO, machine readability) is, in our view, roughly where SEO was in the early 2000s. Businesses that understood early that Google rewarded structured, crawlable, authoritative content often built advantages that lasted. Businesses that waited often found themselves playing catch-up against entrenched competition.

The AI-recommendation layer is earlier in that cycle. In our experience, most Alberta small businesses have not audited their AI visibility. Many have not implemented structured data beyond the basics. Few have considered how their Google Business Profile, their review velocity, or their content depth is interpreted by AI systems synthesizing recommendations.

Businesses that move now give themselves a better chance of being cited consistently. Businesses that wait may find that competitors have already built the signals AI platforms rely on.

  • Illustrative example: An Edmonton contractor has 60 Google reviews averaging 4.8 stars, a complete GBP with photos and updated service descriptions, and a website with structured data. When someone asks Perplexity for a reliable contractor in Edmonton, that contractor is likely to be named.
  • Illustrative example: A Red Deer professional service firm has a website last updated in 2022, 11 reviews, and no Schema.org markup. When the same kind of query is run, the firm may not appear, despite having more experience and better client outcomes than the firm that does.
  • Illustrative example: A Grande Prairie retail business has added llms.txt and structured product data, and maintains a live Google Business Profile. As AI agents begin to look up local product availability, that structured information may make its inventory easier for them to find and cite.

Start here

The Discoverability Check: understanding where you stand

Before investing in AI-platform optimization, you need to know where you actually stand. That is the purpose of the Discoverability Check, Spencer Morley Consulting's free entry point for Canadian small businesses.

Send your business name and city. Jordan runs the queries by hand across ChatGPT, Perplexity, and Google's AI for your category and market (no automated grader) and captures what those engines currently say about your business and about your competitors.

Entry-Point Service
Discoverability Check
Free
No cost and no obligation to work together after

You get the results by email within one business day: whether AI names your business in your category, who it is recommending instead, and the single clearest gap. The free Check does not carry a score or a competitor leaderboard; those come with the paid Discoverability Report. It is the recommended starting point for every small business client, because the optimization decisions that follow are only valuable if they address the right gaps.

Common questions

Frequently asked questions

If we already rank well on Google, are we fine?

Not necessarily. Google ranking and AI platform discoverability share some signals (reviews, business profile completeness, content quality) but diverge on others. AI answers can also depend on content explicitness and entity consistency in ways that traditional SEO work may not address. Structured data helps search engines understand your pages, though Google says it isn't required for its AI search features. Ranking well on Google is a good foundation but is not a substitute for AI-specific discoverability work.

How long does it take to see results?

AI platform visibility can change faster than traditional SEO; some signals (Google Business Profile updates, structured data additions) can affect AI recommendations within weeks. Review velocity is a longer play: the difference between 20 and 80 reviews takes time to build, but the compounding effect is significant. We ran this process on our own business and saw measurable improvement in AI visibility within 60–90 days.

What is WebMCP and why does it matter for my business?

WebMCP is a proposed browser standard, drafted in a W3C community group with editors from Microsoft and Google, that lets a website offer actions to AI agents. It is separate from the Model Context Protocol (MCP), the open protocol Anthropic released in November 2024 for connecting AI assistants to tools and data. Chrome opened an early preview of WebMCP in February 2026. For businesses, preparing for WebMCP may make it easier for AI agents to act on your site accurately once support is in place. No AI search provider has documented using it to decide recommendations, so treat it as preparation rather than a ranking advantage.

Is this just for businesses in Edmonton?

No. Spencer Morley Consulting's small business AI track serves businesses across Alberta. The Staff AI Risk Review, Discoverability Report, and Managed Discoverability services are all delivered remotely and are as relevant for a business in Lethbridge, Grande Prairie, or Red Deer as for one in Edmonton.