Generative engine optimization in Toronto: how B2B companies win AI answers in crowded, regulated markets

Toronto is a dense B2B market. Toronto Global describes the city as the second-largest financial centre in North America after New York, with all five of Canada's largest banks headquartered in the region and about 10,000 financial service businesses employing more than 270,000 people. The same agency reports a tech workforce of more than 285,000, citing CBRE, and lists artificial intelligence as a key subsector.

For a marketing leader, that density has a direct consequence. Your buyers sit in the same towers as your competitors' buyers, and a typical category, whether it is regulatory reporting, customer onboarding, claims software or data platforms, has a long list of credible vendors. When a buyer asks an assistant for options, the answer names a handful of them. Being in that answer is the new shortlist, and in a crowded category the assistant needs a clear reason to pick you.

Buyers are already working this way. Forrester reports that 94% of business buyers use AI during their buying process. The same research found that buyers check AI output against trusted sources such as peers, product experts and analysts, and that they are far less forgiving of claims without proof. Toronto GEO is therefore less about clever page tricks and more about proof that holds up when a buyer checks it.

We group buyer prompts into five types, because each type draws on different sources and needs a different asset. The examples below are the kind of prompts we test for Toronto clients; yours should come from sales calls and lost deal notes.

Google's AI Mode raises the bar on the longer prompts. Google rolled AI Mode out in Canada in English in August 2025 and explained that it breaks a question into subtopics and runs many searches at once, a technique it calls query fan-out. It also reported that early users asked questions two to three times longer than traditional searches. A Toronto prompt such as "claims platform for an OSFI-regulated insurer with Canadian data residency and Guidewire integration" fans out into several sub-questions, and each one needs a page that answers it plainly.

Google also states that there are no extra technical requirements for AI Overviews or AI Mode beyond being indexed and eligible to show a snippet. For ChatGPT, check that OAI-SearchBot, the crawler OpenAI uses to surface sites in ChatGPT search, is not blocked by a rule meant for GPTBot, its training crawler.

Two groups of Toronto companies face a regulatory layer in GEO. The first is vendors selling into federally regulated financial institutions. OSFI's Guideline B-10 on third-party risk management took effect on May 1, 2024. It covers third-party arrangements broadly, not only material outsourcing, and expects banks and insurers to scale due diligence to the risk and criticality of each arrangement. In practice, risk, security and procurement people join the buying group, and they ask assistants the same due diligence questions they will later put in a questionnaire. If your security, resilience and subcontractor facts are not public in some form, the assistant answers from whatever it can find, which may be a competitor's page or an old forum thread.

The second group is the regulated firms themselves: banks, insurers, wealth managers and fintechs marketing their own services. Assistants repeat what they find, including retired products, old rates and wording that never went through approval. The Competition Bureau's general impression test is a useful reminder: a representation can mislead even when each statement is literally true, because the overall impression counts. We are not legal advisors, and your compliance team sets the rules. Our point is practical: GEO content should go through the same review path as your ads.

• Build an approved claims library: product facts, certifications, client counts and outcomes legal has signed off, with an owner and a review date.
• Date every factual page, and update the date only when the facts change.
• Retire outdated pages with redirects rather than leaving them live for assistants to quote.
• Ask partners, directories and associations to correct descriptions that no longer match your approved wording.

When five vendors make similar claims on their own sites, assistants look outside them to choose. That is consistent with what Forrester found about buyers seeking validation from peers, experts and analysts. In Toronto that outside layer usually includes industry associations, analyst and research coverage, review platforms, partner marketplaces for the core systems you integrate with, conference speaker and sponsor pages, business media and podcasts, and comparison articles written by others.

Our recommendation is to work from evidence rather than volume. Run your buyer questions first, record which domains the assistants actually cite, and pick the 10 to 15 sources that show up most for the questions tied to pipeline. Then earn a correct presence on those: an accurate listing, a contributed expert piece, a case study a partner will publish, a speaking slot. A Toronto fintech that appears accurately on the five sources assistants cite for its category is in a stronger position than one with fifty thin mentions nobody cites.

Comparison content deserves its own line in the plan. Buyers in crowded categories ask assistants to compare named vendors, and if you do not publish a fair comparison, someone else's version becomes the source. Keep it honest: state where a competitor is the better fit. Assistants and buyers both discount pages that claim to win on every row.

1. Weeks 1 to 2: collect 40 to 60 buyer questions with sales and customer success, split by shortlist, comparison, risk and compliance, cost and local presence, and mark the ones closest to pipeline.
2. Weeks 2 to 3: run every question in ChatGPT, Gemini, Perplexity, Claude and Google AI Overviews or AI Mode, and record who is named, how you are described, and which sources are cited.
3. Weeks 3 to 4: build or refresh the approved claims library with legal and compliance, so every page and listing that follows uses signed-off wording.
4. Weeks 4 to 7: rewrite category, comparison, security and pricing pages so each answers one question in its first lines, and fix crawler access, indexing and facts locked in PDFs.
5. Weeks 6 to 10: work through the 10 to 15 third-party sources from the baseline, correcting listings and earning placements where you are missing.
6. Weeks 10 to 12: rerun the full question set, compare with the baseline, and report changes next to AI referral visits, self-reported source and opportunities in the CRM.
7. Week 12: agree the next quarter’s priorities with sales, based on the questions where you are still absent or misdescribed.

Assistants have no rank to report, so measurement rests on a repeatable question set. Each month, score every question for three things: whether you are named, whether the description is accurate and approved, and which competitors appear next to you. Across the set, that gives you a share of answer by category and by prompt type. Our article on measuring share of answer explains the scoring in detail.

Then connect it to revenue. Add a GA4 segment for visits referred by AI assistants, knowing that some apps pass no referrer, and add a "how did you hear about us" field to demo and contact forms. Report both next to meetings and opportunities from the CRM, so the program is judged on pipeline rather than on mentions. Google reports AI feature traffic inside the normal Search Console performance data, so treat Search Console as a health check rather than a GEO dashboard.

Before the first baseline, run through our AI search visibility checklist. It covers crawler access, indexing, structured data that matches visible text, and the page patterns assistants quote most reliably.

We are a Montreal-based revenue generation agency that works with Toronto and GTA companies on Eastern Time. Our generative engine optimization service runs alongside our paid media, ABM and RevOps work, so AI visibility is reported in the same CRM view as the rest of your pipeline. Our Toronto GEO page lists what the engagement includes, and our Toronto page covers the wider program for GTA teams.

If you are still comparing providers, our guide to choosing a GEO agency in Canada lists the questions to ask, including how French-language and US markets are handled.

If you want to know how assistants describe your company today, talk to our team. We will run a short set of your buyer questions before the call and show you where you stand.