The CAICB Responsible AI Pathway

Run leaner with AI. Stay inside the lines.

Responsible AI training, built for high-stakes work

Most AI training teaches people which buttons to press. Responsible AI training teaches them where the lines are.

AI can make an organization faster, leaner and more efficient. It can also leak data, make unfair decisions and erode trust when no one sets the rules. The Responsible AI Pathway gives your people both: practical ways to save time and a clear sense of what AI should never be trusted to do alone.

We built it the way high-stakes professions such as aviation and medicine train their people: learn it, practise it, then prove it. As a result, every module ends with a checklist your team can put to work the next day.

  • Learn: short plain-language lessons. No hype, no jargon.
  • Practise: real workplace scenarios. You decide what the AI may do, what a person must check, and what is off-limits.
  • Prove: a knowledge check and a practical checklist. Pass both to earn the module certificate.

Every module is mapped to a recognized framework, so what your team learns lines up with what regulators and auditors look for.

Courses coming soon. Join the membership list to be first in.

Module 1: AI Foundations (for everyone) – Coming Soon

What AI is, what it is not, and how to use it safely at work and at home.

  • What AI tools actually do, and why they sometimes make things up
  • Bias: how it gets in, and how to spot it in an answer
  • Your privacy rights in Canada, including the right to know when a decision about you was automated
  • Safe everyday use: what never goes into an AI tool

Practical checklist: Before I use AI for this task, have I removed personal and confidential information, and will I check the answer before I rely on it?

Aligned with: PIPEDA, Quebec Law 25, OECD AI Principles.

Module 2: Working Within the Parameters – Coming Soon

This is where efficiency and integrity meet. Your team learns to set the boundaries before the AI starts work, not after something goes wrong.

  • Green tasks: AI may do them with a quick check (drafts, summaries, scheduling, first-pass research)
  • Yellow tasks: AI may assist, a named person signs off (customer replies, reports, code, pricing)
  • Red tasks: a person decides, AI does not (hiring, firing, credit, discipline, medical or legal calls)
  • Data rules: what may and may not be shared with an AI tool
  • How to check AI output before it leaves the building
  • When and how to tell customers and staff that AI was used

Practical checklist: Is this task green, yellow or red? Who signs off? What data is going in?

Aligned with: Government of Canada Guide on the use of generative AI, Canada's Voluntary Code of Conduct on generative AI.

Module 3: Governance in Practice – Coming Soon

For owners, managers and compliance leads who need AI rules that hold up.

  • Writing a one-page AI use policy your staff will actually follow
  • An AI inventory: what tools you use, who owns them, what data they touch
  • A simple risk register for AI
  • The four functions of the NIST AI Risk Management Framework: Govern, Map, Measure, Manage
  • What an ISO/IEC 42001 AI management system asks of you
  • Canada's Algorithmic Impact Assessment as a model for scoring risk
  • What to do when AI gets it wrong: an incident plan

Practical checklist: Do we have a policy, an inventory, a risk owner and an incident plan?

Aligned with: NIST AI RMF 1.0, ISO/IEC 42001, Treasury Board Directive on Automated Decision-Making.

Module 4: Ethics and Moral Judgment – Coming Soon

The law sets the floor. This module is about doing right by people when no rule covers the situation.

  • The question that comes before "can we?": should we?
  • Four tests for any AI decision: Is it fair? Did people consent? Who is accountable? Could we explain it to the person affected?
  • Efficiency without harm: cutting cost and time without cutting corners on people
  • Case drills drawn from hiring, customer service, pricing and workplace monitoring

Practical checklist: Would we be comfortable explaining this use of AI to the person it affects, face to face?

Aligned with: OECD AI Principles, Canada's Voluntary Code of Conduct on generative AI.

Module 5: Regulatory Watch

Canada has no AI-specific law in force today. The former Bill C-27, which held the Artificial Intelligence and Data Act (AIDA), died in January 2025. The rules that apply now come from privacy law, provincial law and, for anyone selling into Europe, the EU AI Act. Status checked September 30, 2026.

  • Bill C-36, Protecting Privacy and Consumer Data Act (Canada): introduced June 15, 2026 and at second reading. Proposed, not yet law. Adds transparency rules for automated decision systems.
  • PIPEDA (Canada): in force. Governs how private-sector organizations handle personal information.
  • AI for All national strategy (Canada): launched June 4, 2026. A plan, not a law. Includes a National AI Literacy Initiative and a planned Canada Trusted AI Certification program.
  • Directive on Automated Decision-Making (federal government): in force for federal institutions, and a useful model for any organization.
  • Quebec Law 25: in force. People must be told when a decision about them is made solely by automated processing.
  • Ontario Bill 194 (public sector): Royal Assent November 28, 2024. Public bodies using AI must be open about it and keep an accountability framework.
  • EU AI Act: in force, as amended July 27, 2026. Transparency rules apply from August 2, 2026; high-risk rules from December 2, 2027; AI in regulated products from August 2, 2028.

Practical checklist: Which of these laws touch our customers, our staff or our markets?

See where Canadian AI rules stand

Role Tracks – Coming Soon

Each track starts with Modules 1 to 4, then adds what that role needs.

  • Business Leaders and Executives: where AI saves real cost and time, the risks you own, and setting the AI policy
  • HR and Workforce: AI in hiring and reviews, limits on monitoring, and preparing staff for change
  • Operations and Digital Transformation: automating processes inside the green, yellow and red lines, and checking AI vendors
  • Public Sector and Nonprofits: Ontario Bill 194, the federal Directive, and public transparency
  • Careers and Job Seekers: working alongside AI, skills that stay human, and using AI honestly in a job search

Community Programs – Coming Soon

Programs for people who are too often left out of technology.

  • Newcomers to Canada: practical AI tools for housing searches, language support and settling in
  • Indigenous Knowledge and Cultural Innovation: AI content that respects Indigenous knowledge, and spotting cultural bias in AI tools
  • Women in Tech and Business: building AI skills from beginner to confident leader
  • Accessibility: using AI with assistive devices for daily independence
  • Tech and IT Professionals: machine learning basics, data science and prompt writing, no coding required

Be first in.

The Pathway opens in stages. Join the CAICB Membership Program and we will tell you when each module goes live.

Join the Membership Program

About this training

CAICB is an independent Canadian not-for-profit. It is not a government agency. This training is educational and is not legal advice. Last reviewed: September 30, 2026.

en_USEnglish
en_USEnglish