Ontario Published Its AI Evaluation Framework. Most Organizations Haven't Read It.
Ontario's Privacy Commissioner and Human Rights Commission released six AI principles. They're not law yet, but they are the evaluation standard. Here's what they mean.
On January 21, 2026, Ontario's Information and Privacy Commissioner (IPC) and Ontario Human Rights Commission (OHRC) jointly released six principles for the responsible use of artificial intelligence. IPC__
The document is 12 pages. It covers how organizations should design, deploy, govern, and retire AI systems. And it applies to both public and private sector organizations operating in Ontario.
Most legal commentary has focused on the fact that these principles are not legally binding. That framing misses the point.
Lerners LLP__ notes that the IPC and OHRC have stated these principles will "ground our assessment of organizations' adoption of AI systems." Translation: when an organization's AI use comes under regulatory scrutiny for privacy violations or human rights complaints, the IPC-OHRC Principles are the yardstick. Not legislation, but the published evaluation criteria the regulators will apply.
That distinction matters less than most organizations think.
The Six Principles
The IPC and OHRC state that all six principles carry equal weight and should apply throughout an AI system's lifecycle, from design to decommissioning. OHRC__
- Valid and Reliable. AI systems must produce accurate outputs. Organizations need processes to test, monitor, and validate AI performance over time, not just at deployment.
- Safe. AI must be developed and governed in ways that protect human rights, including privacy and non-discrimination. Safety applies to the technology itself, the data feeding it, and the decisions it influences.
- Privacy-Protective. AI systems should follow a privacy-by-design approach, anticipating and mitigating risks from the earliest design stages. The IPC's existing Privacy Impact Assessment Guide applies directly here.
- Human Rights-Affirming. AI must not create or reinforce discrimination. Organizations are expected to identify bias in training data, test for discriminatory outcomes, and adjust systems proactively. This aligns with the OHRC's mandate and extends existing human rights obligations into automated decision-making.
- Transparent. Organizations must notify individuals when they interact with AI systems or receive AI-generated information. This goes beyond disclosure at the point of interaction. It includes making information available about how AI systems work and what data they use.
- Accountable. Someone specific must be responsible for each AI system, with the authority to pause or shut it down. Governance structures need clear roles, documented decision-making processes, and human-in-the-loop oversight.
Why "Not Legally Binding" Is Misleading
Torys LLP__ notes that inadequate governance, oversight, or control of AI systems may give rise to legal, regulatory, and reputational consequences, regardless of whether these specific principles carry the force of law.
Ontario's privacy laws already require organizations to protect personal information. Human rights legislation already prohibits discrimination. The IPC-OHRC Principles do not create new legal obligations. They clarify how existing obligations apply to AI.
When the IPC investigates a privacy complaint involving an AI system, it will assess whether the organization followed these principles. When the OHRC evaluates a human rights complaint about automated decision-making, these principles frame the analysis. That is how soft law becomes hard consequences.
Torkin Manes__ reinforces this point: the principles serve as a framework for organizations to operationalize their existing obligations under Ontario's privacy and human rights legislation.
The Inventory Problem
The first practical challenge most organizations face is not compliance. It is awareness.
MLT Aikins__ recommends that organizations start by identifying what AI they are already using, including tools they may not have considered "AI." Spam filters, customer chatbots, resume screening software, scheduling optimization tools, and predictive analytics dashboards all potentially qualify as AI systems under the IPC-OHRC framework.
Most mid-size organizations have an estimated 5 to 15 tools with AI components embedded in their operations. Few have inventoried them. Fewer have assessed them against privacy or human rights obligations.
This is not a theoretical problem. Ontario's Bill 149__, which took effect January 1, 2026, already requires employers with 25 or more employees to disclose AI use in hiring. HRPA__ reports an influx of questions from employers uncertain about which of their existing tools trigger the disclosure requirement. Together with the OPS AI Directive, IPC-OHRC Principles, and Bill 149__, these three frameworks form Ontario's unified AI governance system.
Three Overlapping Frameworks
Ontario organizations now face three overlapping AI governance frameworks. Start with our full overview of Ontario AI governance frameworks__.
Bill 149__ (Workers for Workers Four Act): Requires AI disclosure in job postings. In effect since January 1, 2026. Applies to employers with 25+ employees.
IPC-OHRC Principles: Six principles for responsible AI use across all organizational functions. Released January 21, 2026. Applies to public and private sector.
OPS AI Directive: Requirements for the transparent and accountable use of AI by provincial institutions. Released January 7, 2026. The IPC and OHRC have publicly urged provincial institutions to align the OPS Directive with their principles. IPC__
Each framework has different scope and requirements. Together, they signal a clear regulatory direction: Ontario expects organizations to know what AI they use, govern it responsibly, and demonstrate accountability when asked.
What Operational Compliance Looks Like
Legal analysis tells you what the principles say. Operational compliance requires you to build the systems that implement them. That gap is where most organizations stall.
Five steps that move an organization from awareness to operational readiness:
Conduct an AI inventory__. Catalogue every tool, platform, and system with AI capabilities. Include third-party vendor tools. Classify each by risk level based on the data it processes and the decisions it influences.
Run impact assessments. The IPC's Privacy Impact Assessment Guide and the OHRC's Human Rights AI Impact Assessment provide structured frameworks. Apply them to every tool in the inventory, starting with the highest-risk systems.
Assign accountability. Designate a specific individual responsible for AI governance, with documented authority to pause, modify, or retire systems. This is not a committee role. It requires a named person with real authority.
Build transparency mechanisms. Document how each AI system works, what data it uses, and how individuals can inquire about AI-driven decisions that affect them. Create notification protocols for AI interactions.
Establish monitoring and review cycles. AI governance is not a one-time project. Systems change, data evolves, and regulatory expectations shift. Quarterly reviews against the IPC-OHRC framework prevent governance drift.
The Window
Organizations that build governance now do it on their own timeline. Organizations that wait build it under regulatory pressure, with investigators already asking questions.
Ontario's regulatory framework is still forming. Federal AI legislation (AIDA) stalled when Parliament prorogued, but its risk-based classification concepts continue to shape regulatory thinking. Torys LLP__ The window between published principles and enforced requirements is when the cost of compliance is lowest and the competitive advantage of early adoption is highest.
The practical starting point is an inventory of every AI system touching personal data, matched against the IPC and OHRC principles outlined above. DeployLabs' AI Governance Readiness Assessment__ produces that inventory, identifies gaps in documentation and oversight, and delivers a prioritized remediation roadmap — typically completed within two weeks.
If your organization operates AI systems in Ontario and has not yet mapped them against these three regulatory layers, a structured governance assessment identifies the gaps before enforcement does. DeployLabs' AI Governance Readiness Assessment__ walks through your current AI inventory, data handling practices, and policy documentation against the IPC, OHRC, and Bill 149 frameworks covered in this article.
DeployLabs builds AI governance frameworks for mid-size organizations. If your organization uses AI and has not conducted an inventory or impact assessment, book a discovery call__.