AI policy development that teams actually follow
Your teams are already using AI. The question is whether they have guidance. Mooning helps companies develop internal AI policies that work in practice: frameworks that guide how teams use AI tools responsibly, securely and effectively. From data governance to output quality control to risk management, we write policies built for real-world implementation.
This isn't about restrictive rules that kill innovation. It's about guardrails that let people use AI productively while protecting the company. That means clear guidelines, practical frameworks, training that builds understanding, and policies that get followed rather than filed.
AI policy also needs upkeep as the tools change. We help you build the governance structures, documentation and cultural foundations needed to manage AI use at scale.
Understanding where AI lives in your business
Effective AI policy starts with understanding. Where are your teams already using AI? Which tools? Which processes? What risks?
We conduct AI audits across your organisation. We identify all the places AI is being used, map how it's being used, and surface the risks, the opportunities and the policy gaps.
Starting from observed usage matters. Policies written in the abstract fail, because teams already using AI quietly route around rules that don't match how they work. We build from what your teams already do, so the policy lands.
Data governance, acceptable use and risk management
With that picture in place, we develop a complete AI policy framework. It typically covers:
- data governance and data handling, especially around customer data and personal information
- acceptable use, including approved and prohibited tools
- output quality and review
- security and compliance
- vendor selection and procurement review
- IP and output ownership, and disclosure of AI-generated content
- risk management, escalation and review
- training and capability development
Each policy is practical and actionable. Not vague principles, but clear guidelines teams can follow, documentation that's easy to understand, and examples that make implementation clear. We frame the policy from an operational and risk perspective, and work alongside your legal counsel on jurisdiction-specific compliance language such as GDPR, the EU AI Act and the Australian Privacy Act.
Training and implementation
A policy is worthless if teams don't understand it or don't follow it. We develop training and implementation support that makes adoption happen.
Training materials are tailored to different roles: executives, managers, individual contributors and frontline team members. Each group gets the training it needs to understand the policy and apply it in its own work. A typical engagement runs four to eight weeks, from discovery through drafting and review to rollout and training.
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 rather than legal jargon, practical guidance rather than vague principles, and real examples that help people understand what the rules mean in practice. And because the tools keep changing, we help you set up review cycles and vendor governance so the policy keeps pace with how your business uses AI.