Most published AI governance frameworks were designed with large, well-resourced organizations in mind. The NIST AI RMF Playbook, ISO/IEC 42001, and the EU AI Act conformity assessment process all assume access to dedicated legal, compliance, data science, and ethics functions – resources that most small and mid-sized enterprises (SMEs) simply do not have. An organization with 50 employees and a single IT generalist faces a different governance challenge than a bank with a model risk management team.
This chapter addresses how smaller organizations can build governance that is real and defensible – not theatrical – without the infrastructure of a large enterprise.
What Cannot Be Skipped
Certain governance activities are non-negotiable regardless of organizational size, because they address the root causes of the harms that governance exists to prevent:
AI inventory. You cannot govern systems you have not catalogued. Every organization using AI – regardless of size – must maintain a current list of AI systems in use, including AI embedded in third-party software (HR platforms, CRMs, accounting tools, customer service chatbots). This is the minimum viable starting point. The NIST AI RMF’s Map function provides structured prompts for this exercise.
Named accountability. Governance without a named owner defaults to no governance. Even a small organization needs one person designated as responsible for AI governance decisions and escalation – this does not require a Chief AI Officer, but it does require a name.
Basic risk triage. Not all AI tools carry the same risk. A grammar-checking tool is not equivalent to an AI system that screens job applications or generates credit recommendations. A simple risk triage – does this system make or substantially influence decisions that affect people? does it process sensitive personal data? – allows an SME to concentrate governance effort where harm is most plausible.
Vendor due diligence. Most SMEs consume AI through vendor platforms rather than building it themselves. A short vendor questionnaire – covering what the system does, what data it uses, how it was validated, and what the vendor’s own AI governance practices are – provides a defensible record that the organization exercised appropriate diligence.
What Can Be Deferred
Smaller organizations can reasonably defer: formal AI management system certification (ISO/IEC 42001 certification is appropriate once governance is operationally mature); advanced fairness testing and algorithmic audits (appropriate for high-risk systems, not for low-risk AI use); and full-scale model validation processes (appropriate for internally developed models, less critical for off-the-shelf tools with documented vendor validation).
Available Resources for Canadian SMEs
Canada has meaningful government-backed resources for SMEs building AI governance capacity:
The Business Development Bank of Canada’s LIFT initiative – launched in April 2026 and backed by $500 million – provides loans of $25,000 to $5 million to help small and medium-sized enterprises adopt AI responsibly, with a preferential interest rate for organizations choosing Canadian AI solutions. Consultants help SMEs determine where AI investment makes sense before the loan is deployed.
ISED’s Voluntary Code of Conduct on Advanced Generative AI Systems is explicitly described as applying to organizations of all sizes, with measures that are “broadly applicable” across Canada’s AI ecosystem. Signing the Code provides a structured commitment framework even for organizations not building frontier AI systems.
ISED launched an AI Risk Management Guide in early 2025, based on the Voluntary Code, providing implementation-level guidance for organizations.
The National Research Council of Canada’s Industrial Research Assistance Program (IRAP) provides advisory services and, in some cases, funding support for SMEs pursuing digital innovation including AI adoption.
In the United States, NIST’s AI RMF Playbook explicitly states that the framework is designed to be scalable and adaptable, and the Colorado AI Act’s safe harbour for NIST AI RMF compliance is accessible to organizations of any size.
A Practical One-to-Two-Person Governance Setup
For an SME with limited resources, a functional minimum governance posture looks like this:
- An AI inventory spreadsheet, updated quarterly, covering all AI tools in use and their primary risk level (low/medium/high)
- A named governance lead (this can be the COO, CTO, or senior HR manager – it does not require a new hire)
- A one-page AI use policy covering approved tools, prohibited uses, and how employees should report concerns about AI outputs
- A vendor questionnaire template sent to all AI vendors before onboarding
- A brief annual review of the inventory and policy
This is not a comprehensive program. It is the foundation without which no further governance can be built – and it is achievable for any organization.
Insurance and Audit Considerations
Cyber insurance underwriters are increasingly asking about AI governance practices as part of application processes. A documented AI inventory and a basic vendor due diligence process are defensible answers to underwriter inquiries. Organizations that cannot demonstrate basic AI governance may face coverage limitations or exclusions as AI-specific policy language becomes more common. External auditors, particularly for organizations subject to financial statement audits, are similarly beginning to raise questions about AI use and related risk management.
