Guardrails that let people use AI productively while protecting the company.
AI Policy Development
Book A CallPOLICIES THAT TEAMS ACTUALLY FOLLOW.
We help companies develop internal AI policies that actually work. Practical frameworks that guide how teams can use Al tools responsibly, securely and effectively. From data governance to output quality control to risk management, we create policies built for real-world implementation.
This isn't about restrictive policies that kill innovation. It's about creating guardrails that let people use AI productively while protecting the company. Clear guidelines. Practical frameworks. Training that builds understanding. Policies that teams actually follow.
Al policy isn't a one-time project. It's ongoing. We help you build the governance structures, documentation and cultural foundations needed to manage Al use at scale.
BUILT FROM HOW YOUR TEAMS ALREADY WORK.
Understanding Where AI Lives in Your Business
Effective Al policy starts with understanding. Where are your teams already using AI? What tools? What processes? What risks?
We conduct comprehensive Al audits across your organisation. We identify all the places Al is being used. We map how it’s being used. We identify the risks, the opportunities and the policy gaps.
DATA GOVERNANCE. ACCEPTABLE USE. RISK MANAGEMENT.
Framework Development
Based on that understanding, we develop comprehensive Al policy frameworks. Data governance. Output quality and review. Security and compliance. Acceptable use. Risk management. Training and capability development.
Each policy is practical and actionable. Not vague principles. Clear guidelines that teams can follow. Documentation that's easy to understand. Examples that make implementation clear
TRAINING THAT ENSURES ADOPTION.
Training and Implementation
Policy is worthless if teams don't understand it or don't follow it. We develop training and implementation support that ensures adoption.
We create training materials tailored to different roles. Executives. Managers. Individual contributors. Frontline team members. Each group gets the training they need to understand the policies and implement them.
A POLICY NOBODY FOLLOWS IS WORSE THAN NO POLICY AT ALL.
Usability Is Non-Negotiable
A policy nobody follows is worse than no policy at all. It creates false confidence while the real risks continue unchecked,
We obsess over usability. Clear language, not legal jargon. Practical guidance, not vague principles. Real examples that help people understand what the rules mean in practice.
Common Questions
What goes in an AI policy?
Acceptable-use rules, data-handling requirements (especially around customer data and PII), approved vs prohibited tools, vendor and procurement review process, IP and output ownership, disclosure rules for AI-generated content, escalation and review process.
Why do AI policies fail?
Because they're written in the abstract and don't reflect how the team actually works. Teams already using AI quietly route around policies that don't map to reality. Mooning starts from observed usage so policy lands.
Does Mooning's AI policy work cover legal compliance?
Mooning frames AI policy from an operational and risk perspective and works alongside the client's legal counsel for jurisdiction-specific compliance language (GDPR, EU AI Act, Australian Privacy Act, etc.).
How long does an AI policy engagement take?
Typically 4–8 weeks: 1–2 weeks of discovery, 2–3 weeks of drafting and review, 1–3 weeks of rollout and training.
Should every company have an AI policy?
Any company where employees are using AI tools to do their jobs, which is essentially every company today. Without one, you carry data, IP and reputational risk you can't see.
