Artificial intelligence and competition
This white paper from the Competition Bureau of Canada explores how artificial intelligence intersects with Canadian competition law and market dynamics. It examines the structure of AI markets—including infrastructure, development, and deployment—and analyzes potential competition issues such as market concentration, barriers to entry, cartels, and deceptive marketing practices. Finally, the paper outlines a competition policy assessment toolkit to help policymakers design pro-competitive regulations for the AI sector.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
This paper is for policymakers, regulators, market participants, and researchers seeking to understand the intersection of artificial intelligence and competition law in Canada.
What the document contains
The document covers proposed definitions for artificial intelligence, the components of AI markets (infrastructure, development, and deployment), vertical relationships, and specific competition concerns including mergers, monopolistic practices, cartels, and deceptive marketing practices. It also presents a competition policy assessment toolkit for evaluating AI regulations.
The document does not provide binding legal rules, specific enforcement outcomes, final determinations, or formal regulatory recommendations, noting instead that it is meant to foster dialogue and gather stakeholder feedback.
- The paper provides an overview of AI technologies, market structures, and potential competition impacts in the context of Canadian law.
- AI markets rely heavily on access to crucial inputs such as compute, data, and specialized talent, which can create high barriers to entry.
- Vertical integration and high market concentration among large technology firms raise potential concerns regarding exclusionary conduct and market power.
- AI could potentially facilitate anti-competitive outcomes such as algorithmic coordination, tacit collusion, and predatory pricing.
- Policymakers are encouraged to apply pro-competitive principles—such as technology neutrality, interoperability, and low regulatory burdens—when designing AI policies.
· Purpose and overview · Section 1: Introduction to artificial intelligence · Section 2: Markets for artificial intelligence · Section 3: AI and competition · Conclusion · Glossary
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
0/5Clear responsibility for AI outcomes
screening score · 2026-10-23
Fairness
1/5Non-discrimination and equitable treatment
Use of synthetic data incurs risks in terms of data contamination and bias propagation
Section 3.1.1
screening score · 2026-10-23
Human Dignity
0/5Respect for the inherent worth of persons
screening score · 2026-10-23
Human Oversight
4/5Humans remain in control of consequential decisions
Firms which use AI for decision-making purposes, may need to ensure proper human oversight to identify and correct any potential anti-competitive decision making of AI.
Section 3.1.5
screening score · 2026-10-23
Privacy
1/5Protection of personal data and private life
The Bureau engages in cross-governmental collaboration on this front, engaging with the Office of the Privacy Commissioner (OPC)
Purpose and overview
screening score · 2026-10-23
Transparency
2/5Openness about how AI systems work and are used
AI may also lead to increased frequency of interaction between competitors, due to greater ease in detecting competitor price changes and quicker responsive price adjustments.
Section 3.2.1
screening score · 2026-10-23
Enforcement
4/5Consequences and compliance mechanisms with real force
The Competition Bureau investigates and acts when it discovers abuses of market power or mergers that are likely to substantially lessen or prevent competition.
Section 3.1
screening score · 2026-10-23
Impact Assessment
2/5Required assessment of an AI system's risks/impacts before or during use
falsely promising that an AI product performs a task better than a non-AI product, not performing risk analysis, and fabricating that a product uses AI
Section 3.3
screening score · 2026-10-23