AI Policy Guidelines Every Company Should Put in Place

AI is now in your workflows, whether you planned it or not. Employees paste data into chatbots, vendors ship features powered by machine learning, and departments test AI to speed up content, coding, or customer support. Without clear guardrails, that activity can create legal, privacy, and security risks. The good news is you can manage it with an AI policy that turns experimentation into a responsible, auditable practice. Here is how you can get started.

Anchor Your Program to Credible Standards

Start by mapping your policy to a recognized framework. NIST’s AI RMF is a practical guide to identify, measure, and mitigate AI risks across the lifecycle. It is voluntary, widely referenced by industry, and emphasizes trustworthy AI outcomes like safety, privacy, and explainability. ISO/IEC 42001 goes a step further by defining a management system for AI, similar in spirit to ISO 27001 for information security, so you can formalize roles, processes, and continual improvement. Aligning to these references keeps your policy current as the technology evolves.

Know the Rules That Already Apply to You

In Canada, privacy law governs AI use. PIPEDA and guidance from the Office of the Privacy Commissioner emphasize transparency, appropriate purpose, safeguards, and meaningful explanations when automated systems affect people. The government’s proposed Artificial Intelligence and Data Act adds obligations for “high‑impact” systems.

What Your AI Policy Needs to Cover

Here are the core elements every AI policy should include to balance innovation with responsibility:

Purpose and Scope

State where AI can be used in your company and where it cannot. Tie every approved use to a legitimate business purpose that aligns with privacy principles and your risk appetite.

Roles and accountability

Assign an executive owner and define duties for IT, security, legal, and business teams. You can have the tool owners to document use cases, data sources, and performance metrics. ISO/IEC 42001 provides a template for roles, documentation, and continual improvement.

Security and Vendor Controls

Treat AI providers like any critical SaaS vendor. Align technical controls to your existing security standards and to NIST AI RMF functions for measuring and managing risk throughout the lifecycle.

Accuracy, Bias, and Performance Testing

Define acceptance criteria before deployment. Test models for accuracy on your data, monitor drift, and document limitations. Require human review for material decisions about people. The EU AI Act and OECD guidance both push for transparency and human oversight, which your policy should reflect.

Acceptable Use and Employee Training

Give employees clear rules: approved tools, prohibited inputs, secure prompt practices, and how to handle output verification. Train on privacy, intellectual property, and prompt hygiene. Require citing sources for AI‑assisted content and mandate human fact checking for public materials.

Recordkeeping and Audits

Maintain a register of AI systems, use cases, data categories, risk ratings, and sign‑offs. Schedule periodic audits against NIST AI RMF or ISO/IEC 42001 controls so you can show due diligence to regulators, customers, and partners.

Where To Start

Begin with a short inventory of AI use across teams. Identify quick wins like training and prompt rules, then tackle higher‑risk items such as vendor due diligence and a data input policy. In parallel, draft your AI policy mapped to NIST AI RMF sections and add an implementation checklist. This approach delivers guardrails fast while you build toward ISO/IEC 42001 alignment.

AI works best when guided by strong policies. ManagePoint Technologies helps you create practical frameworks that build trust, protect your business, and unlock new opportunities. Schedule a consultation and move forward with confidence.