In a profession where legal accountability is measured in millimeters, the rise of AI introduces both immense promise and regulatory uncertainty. For civil engineering firms in Canada, adopting AI is as much a matter of innovation as it is compliance.

This week, we’re stepping into the shoes of a compliance officer… walking you through the legal and regulatory frameworks that govern AI use in engineering — what they mean, how they impact your firm, and what you must do to avoid exposure.

1. Artificial Intelligence and Data Act (AIDA)

In June 2022, the Government of Canada tabled the Artificial Intelligence and Data Act (AIDA) as part of Bill C-27, the Digital Charter Implementation Act, 2022. As stated in the bill, it was expected to come into effect no earlier than 2025, so it is coming. The Artificial Intelligence and Data Act, or AIDA, is Canada’s proposed legal framework for high-impact AI systems. Though not yet passed into law, it introduces obligations for firms deploying AI in engineering, construction, and infrastructure. As per the government of Canada’s website, “[It] would set the foundation for the responsible design, development and deployment of AI systems that impact the lives of Canadians.”

Under AIDA, “high-impact systems” may include tools that affect public health, safety, or the environment — all core concerns in civil engineering. This means that if you use an AI tool to optimize structural loading, generate design scenarios, or make recommendations on safety-critical infrastructure, your software may be regulated.

6 Key Requirements for Firms:

• Human Oversight and Monitoring
• Transparency
• Fairness and Equity
• Safety
• Accountability
• Validity and Robustness

Practical Takeaway:
If you’re integrating AI into your workflows — whether it’s for bidding, design, or asset management — you must be able to explain and document how that AI behaves. No more “black box” shortcuts.

2. PIPEDA / CPPA – Privacy Law for Personal Data

The Personal Information Protection and Electronic Documents Act (PIPEDA) — soon to be replaced by the Consumer Privacy Protection Act (CPPA) — governs how firms collect, use, and disclose personal information.

In engineering, you may think this doesn’t apply — but think again. RFPs, submittals, and internal records may contain names, signatures, financial records, or employment data. If you run an AI tool across old project files or emails that contain this kind of data — even for internal knowledge management — you may be subject to disclosure and consent rules.

3. Algorithmic Impact Assessments (AIAs)

While AIAs are currently required for federal departments, they set a precedent that private firms working with government agencies may soon be expected to follow.

If your firm bids on public infrastructure — roads, transit, wastewater — and you use AI to assist in any workflow that touches deliverables, you may be expected to submit a formal algorithmic impact assessment. According to the Government of Canada’s website, “The tool is a questionnaire that determines the impact level of an automated decision system. It is composed of 65 risk questions and 41 mitigation questions. Assessment scores are based on many factors, including the system’s design, algorithm, decision type, impact and data.”

4. Cybersecurity Compliance (NIST, CCCS)

Whether it’s through CCCS (Canadian Centre for Cyber Security) or NIST (U.S. Standard adopted in Canada), engineering firms are increasingly being evaluated on their cyber hygiene.

For AI tools, that means:

• Securing API keys
• Encrypting prompts and responses
• Preventing unauthorized access to training data or internal models

5. Digital Charter (ISED Canada)

The Digital Charter, developed by Innovation, Science and Economic Development Canada, outlines key principles guiding Canada’s approach to AI: trust, fairness, transparency, and control.

While not legally binding, it heavily influences how courts and public institutions evaluate tech products — especially when disputes arise.

6. AI Tax Credits & Budget 2024 Incentives

One piece of good news: Canada is putting money behind this transformation.

The 2024 Budget introduced:

• A 20% tax credit on qualified AI investments
• A $2.5 billion national investment in AI-related infrastructure and adoption, focused on SMEs

This is a direct path for smaller and mid-sized engineering firms to adopt AI tools responsibly without eating the full cost.

Firms working with vendors like Sidian can frame their investments not just as innovation, but as recoverable expenses.

Final Thoughts

This list is not all inclusive but gives a glimpse into some of the regulations that will be controlling AI use and implementation. It is important to be aware of the regulations of AI like you are the codes that govern engineering.

It is vital that tools are designed:

• Securely
• Legally
• And transparently

It’s not just about building better. It’s about building responsibly.