Generative engine optimization in Montreal: winning AI answers in English and French

Montreal B2B companies sell into some of the most technical buying committees in North America, and many of them sell globally from day one. Montréal International lists more than 1,400 researchers and experts at Mila, the deep learning research institute in the Mile-Ex neighbourhood, and 60,000 workers with AI-related skills in the region. It describes Greater Montréal as Canada's leading aerospace hub, with more than 43,000 jobs, more than 230 businesses and six prime contractors including Airbus, Bombardier, Bell, CAE, MDA and Pratt & Whitney. In life sciences and health technologies, it reports more than 55,000 private-sector jobs in Québec, with 85% of the ecosystem based in Greater Montréal.

Those numbers matter for GEO because they shape who asks the questions. An engineer at an aerospace supplier, a data science lead at a software firm and a clinical operations director at a contract research organization all use assistants differently. They ask long, specific questions, they expect technical precision, and they notice quickly when an answer gets a capability or a certification wrong. A generic "we are a leading provider" page gives an assistant nothing to repeat.

The second difference is language. Many Montreal teams sell in English to the US and Europe while their Québec customers, partners and employees read in French. GEO here has to work in both languages at once, and it has to stay consistent across them.

Google started rolling out AI Mode in Canada in English on August 21, 2025. On October 14, 2025, its French-Canadian blog announced that AI Mode was available in French. Google describes AI Mode as built for long, multi-part questions, and says it splits a question into subtopics and runs many searches at once before writing an answer. In practice, a buyer who asks in French often triggers searches against French-language pages, French media and French directories.

That is where many Montreal companies lose ground. The English site is detailed, current and full of proof. The French site is a shorter translation from two years ago, missing the newest products, the certifications and the case material. When a buyer asks "quels fournisseurs de logiciels de maintenance aéronautique au Québec" the assistant can only work with what exists in French, so it may name a competitor whose French pages are simply more complete.

Our recommendation is to treat English and French as two markets that share one fact base. Keep a single approved claims library, publish it in both languages, and use Québec French terminology that buyers actually type rather than a literal translation. Link each English page to its French equivalent with hreflang so search systems understand they describe the same thing. Our article on SEO and GEO for Montreal companies covers the bilingual page basics; this guide focuses on the GEO program on top of them.

The Government of Québec lists the obligations of businesses under the Charter of the French language, and one of them is to make catalogues, advertising and websites accessible in French. New obligations under the reformed Charter took effect on June 1, 2025, including rules on French in trademarks on products and on the prominence of French in signage visible from outside a premises. For GEO, the practical point is simple: a complete French site is expected, and the work you do to meet that expectation is also the work that gets you into French AI answers.

Privacy rules shape measurement. Québec's Law 25 brought in provisions in stages from 2022 to 2024. The government notice for September 22, 2023 lists new rules on consent to collect and use personal information, new information and transparency duties, and a requirement that technology products offered to the public use the highest privacy settings by default. Any tracking you add to measure AI-referred visits should go through the same consent and disclosure review as the rest of your analytics.

This is general information, not legal advice. Confirm your own obligations with qualified counsel. Our overview of Bill 96 and B2B websites lists the marketing assets we review first.

Each sector draws on different sources when an assistant builds a shortlist. The table below is the starting point we use; the actual prompts should come from your sales calls, lost deal notes and support tickets, in both languages.

Two patterns hold across all five. Assistants reward specific nouns: the process, the standard, the therapeutic area, the integration. And they lean on third parties to confirm what you say about yourself, so a listing that contradicts your website hurts you in both languages.

This is the plan we run with Montreal clients. It assumes a marketing lead, a subject matter expert from product or engineering, and someone who can approve claims.

1. Weeks 1 and 2: build a question set of 40 to 60 buyer questions, split evenly between English and French, and grouped by sector, use case and comparison.
2. Weeks 2 and 3: run the set in ChatGPT, Gemini, Perplexity, Google AI Overviews and AI Mode, and record who is named, how you are described and which sources are cited, in each language.
3. Weeks 3 and 4: write an approved claims library with product facts, certifications, sectors served and proof you can name, then have it reviewed in English and Québec French.
4. Weeks 4 to 7: rewrite the 10 to 15 pages that matter most so each opens with a direct answer, and bring the French versions to full parity with the English ones.
5. Weeks 6 to 10: correct and complete the third-party sources found in the baseline, starting with directories, associations and partner listings where you are missing or misdescribed.
6. Weeks 10 to 12: rerun the full question set, compare it with the baseline by language, and report the change next to AI-referred visits and opportunities in the CRM.
7. Week 12: agree the next quarter’s focus with sales, based on the questions where you are still absent in either language.

There is no rank to report in an AI answer, so measurement rests on the fixed question set. Each month, score every question on three points: are you named, is the description accurate and approved, and which competitors appear beside you. Report share of answer separately for English and French, because a strong English result can hide a weak French one. Our guide to measuring share of answer explains the scoring.

Then tie it to revenue. Create an analytics segment for visits referred by AI assistants, knowing some apps pass no referrer, and add a "how did you hear about us" field in both languages to demo and contact forms. Report both next to meetings and opportunities in the CRM. Make sure the consent banner and privacy notice cover this tracking before you rely on it.

One mistake to avoid: judging the program from screenshots of a single answer. Answers vary by session, phrasing and language. A monthly rerun of the same set is the only view leadership should act on.

PlanConversion is a revenue generation agency based in Montreal. Our team works in English and French, and our generative engine optimization service runs alongside our paid media, ABM and RevOps work, so AI visibility sits in the same pipeline reporting as every other channel. Our Montreal GEO page lists what the engagement includes, and our Montreal page covers the wider program for local B2B 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 answers are tested and reported.

If you want to see how assistants describe your company today in English and in French, talk to our team. We will run a short set of your buyer questions in both languages before the call.