How Founders Can Help Bring AI Innovation Back to Canada

AI leadership was born in Canada, but it’s being commercialized elsewhere.

Canada has been at the forefront of artificial intelligence (AI) research — think Geoffrey Hinton, Yoshua Bengio, and Richard Sutton. But when it comes to commercialization, we’re watching OpenAI, DeepMind, and Anthropic take the lead. Why?

Because Canada isn’t leveraging its own AI breakthroughs fast enough in real-world businesses. Meanwhile, legacy industries still run on pen, paper, and Excel, leading to major productivity loss. That’s an opportunity for entrepreneurs. How?

https://www.linkedin.com/pulse/canada-us-productivity-gap-returns-trend-michael-willox

Step 1: Finding the Right Problems to Solve

The biggest AI opportunities aren’t in building another chatbot. They’re in automating repetitive, manual, high-stakes work where human error costs time and money.

Here are three high-potential areas for AI-driven automation.

1. Automating Data-Heavy, Error-Prone Workflows

Target: Industries that still rely on PDFs, emails, and spreadsheets to process complex documents — think insurance underwriting, legal contracts, equipment leasing, and procurement.

How to do it:

Build an AI-powered data extraction tool that ingests contracts, invoices, and policies.
Pair it with anomaly detection to flag missing or incorrect data.
Automate email responses and approval to cut down manual back-and-forth.

Example: An AI underwriting assistant that scans insurance applications, cross-references risk factors, and flags inconsistencies before submission.

2. Replacing Middle Managers in Excel Hell

Target: Any business where employees spend 80% of their time copy-pasting from one document to another.

How to do it:

Identify high-volume, high-error workflows in industries like real estate, property management, and government procurement.
Deploy AI assistants to automate these tasks, ensuring speed and accuracy.
Build an integration layer so AI plugs into legacy software (SAP, QuickBooks, etc.).

Example: A construction project AI that scans invoices, matches them to contracts, and auto-approves payments.

→ Axeo has good ties with the construction industry, if you want to conduct market research.

3. Ensuring Compliance and Risk Management

Target: Compliance-heavy industries like healthcare, financial services, and government that struggle with regulatory paperwork, audits, and documentation.

How to do it:

Build an AI compliance tool that auto-generates reports and audits for regulatory bodies.
Use natural language processing AI to identify key risks from documents.
Automate record-keeping to maintain compliance with government standards.

Example: An AI-powered financial compliance tool that scans transactions for red flags, generates reports for regulators, and assists auditors.

The Big Challenge: Confidentiality

Notice one thing about all those ideas?

Contracts, invoices, insurance, government procurement — they all deal with sensitive information. Privacy is one of the major setbacks to implementing any AI automation.

Your solution needs to be secure, or your potential clients won’t use it. Compliance standards exist in all industries, and you have to make sure your solution follows them, for example by using encryption.

As challenging as it sounds, think of it this way: specializing in a narrow field and nailing its compliance requirements will make you a key resource for those companies. Automation done well will be a blessing to them if it can help avoid human error and protect their data better.

Step 2: Building an Acquisition Flywheel

Even the best AI product won’t sell itself. Now that you have your idea, it’s time to turn it into a business making $10M in annual recurring revenue (ARR):

Flood LinkedIn, X (Twitter) and YouTube with 60-second videos solving real industry problems.
End every video with a free lead magnet (AI demo, template, or industry report).
If a video hits 2%+ click-through rate, boost it with ad spend.
Target $3 per lead, aim for 100 leads per day.
Launch one new lead magnet per month to keep engagement fresh.

Example: A free AI lease auditor that scans and analyzes rental agreements, to capture the attention of the real estate market then upsell to a full automation suite.

Canada’s AI Leadership Can Be More Than Just Research

We have the talent. We need to commercialize it.

If Canadian founders focus on AI for old-school industries, they won’t just build great businesses — they’ll reclaim Canada’s place as a leader in AI innovation.

Let’s not just publish AI papers — let’s turn them into $10M+ ARR startups that help modernize the country.

Got an idea? Apply at Axeo to get access to funding, mentorship, and industry connections.