AI use policy and training should give staff practical answers: which tools are approved, which information may be used, who reviews outputs and how concerns are reported. A policy becomes useful when people can apply it during real work.
If employees are already experimenting, delayed guidance creates uncertainty. Clear boundaries can protect the business while giving staff a legitimate way to learn.
Quick Answer: What Should an AI Use Policy Include?
An AI use policy should define approved tools, prohibited data, permitted tasks, human review, accountability, incident reporting and training. It should use plain language, match actual workflows and be reviewed as tools and risks change. Staff need examples and practice so the policy actively guides everyday behaviour.
Ask Intelligence Me. to facilitate a practical policy and training workshop.
What Are the Essential Policy Sections?
An AI use policy and training program needs seven essential sections, from purpose and scope through to a regular review schedule.
- Purpose and scope.
- Approved tools and accounts.
- Data and privacy boundaries.
- Human review and accountability.
- Accuracy, bias and copyright checks.
- Incident reporting and escalation.
- Training and review schedule.
The National AI Centre adoption foundations say organisations remain accountable for how and where AI is used and recommend policy guidance on risks and management.
What Should the Policy Say About Data?
The policy should set a default treatment for each data type, from public material through to confidential client information. Staff then know what to do without guessing.
| Data type | Default treatment |
|---|---|
| Public, approved information | Use within the approved workflow |
| Internal business information | Use only under policy and tool controls |
| Personal information | Assess privacy obligations first |
| Confidential client information | Do not use without explicit authority and safeguards |
The OAIC guidance advises organisations to consider privacy, security, server location and possible overseas disclosure when using cloud AI products.
How Should Training Support the Policy?
AI use policy and training should demonstrate allowed and disallowed scenarios, show staff how to review outputs and explain where to ask questions. Digital.gov.au staff-training guidance provides a strong public-sector example of aligning training with responsible-use expectations.
What I See Working in Practice
The best AI use policy and training programs are short enough to use and specific enough to answer common questions. Staff should be able to recognise a safe task, a risky input and the person to contact within minutes.
What Does a Simple AI Use Policy Look Like in Practice?
A simple AI use policy works best as a short list of yes, no and ask-first examples that staff can apply in seconds. Abstract principles matter, but concrete examples are what change everyday behaviour.
Yes: approved and low risk
Drafting an internal summary from public or approved material, rewording a standard email template, or brainstorming headings for a blog post in an approved tool.
No: outside the rules
Pasting customer records, contracts, health details or staff files into a personal account, or publishing AI output without a human review.
Ask first: depends on context
Summarising a client document, analysing sales data or connecting an AI tool to email or file storage. These tasks may be fine with the right account, settings and approval, so staff should check with the accountable owner before starting.
Pair the list with a one-page summary of approved tools and a named contact for questions. Review the examples every few months, because new tools and features will create new grey areas for your AI use policy and training program to cover.
Who Needs AI Use Policy and Training?
AI use policy and training suits any organisation where staff use public or commercial AI tools for work. Highly regulated or high-risk environments should involve legal, privacy, security and industry specialists.
For related reading, see Using Business Data in ChatGPT Safely: A Plain-English Guide and Introduce AI to Your Team Without Creating Chaos: 6 Practical Steps, or browse every article in Responsible AI & Data Safety.
Frequently Asked Questions About AI Use Policy and Training
Can we use a policy template?
A template is a useful starting point for AI use policy and training. Adapt it to your tools, information, contracts, roles and risk profile.
How often should the policy be reviewed?
Review it when tools, features, laws, risks or workflows materially change, and schedule a regular governance review.
Who should approve AI tools?
Assign accountable leadership with input from privacy, security, legal, operational and user perspectives appropriate to the business.
Is training mandatory?
The business should decide based on risk and obligations, and most find that AI use policy and training work best together. Staff cannot follow a policy they do not understand, so training is a practical control.
What are the legal restrictions on AI use in Australia?
Australia has no single AI-specific law for businesses. Existing laws still apply to AI use, including the Privacy Act 1988, Australian Consumer Law, copyright and workplace laws, and the government has published voluntary guidance. Check current obligations with a legal adviser because the rules continue to evolve.
What To Do Next
Start your AI use policy and training work by listing the tools staff are using and the information those tools receive. Intelligence Me. can facilitate the first policy workshop and turn it into role-based training.
Book an AI policy and training session before informal use becomes an unmanaged system. Prefer to compare options first? See the Intelligence Me. training options.
About Crom Salvatera and Jono Smith of Intelligence Me.
Your staff are already using AI. Clear rules and practical training let them keep the benefits while you keep control of your data and your risk.
Intelligence Me. is practical AI training and advisory for Australian business owners, professionals and teams. We teach you to put AI to work on your real tasks, in weeks, without becoming a tech expert, so you get hours back, produce better work and spend more of your week on the parts of business and life that matter to you.
Crom Salvatera, co-founder, has spent 22 years in marketing, 14 of them in senior digital roles. He has worked across more than 500 advertising and marketing accounts, helped generate more than $650 million in revenue for employers and clients, and led work for brands including LEGO, Hasbro, JB Hi-Fi, Optus and Crimson Education. He created the TLC Method (Tech, Links, Content) for search and AI visibility and uses AI every day to deliver paid client work. Connect with Crom Salvatera on LinkedIn.
Jono Smith, co-founder, is a founder and operator with more than two decades of experience building service and technology businesses across Australia, the Philippines, the United States and Asia. He founded Shore Solutions and grew it to more than 2,500 staff and over US$22 million in annual revenue before its acquisition, and he restructured a 1,100-person operation to profitability within five months. Today he advises business owners and leadership teams on practical AI adoption, from choosing the right tools to embedding them in everyday workflows.
Together, you get a rare combination in AI training: a marketer who uses AI on paid work every day and an operator who has scaled and turned around large teams. Your training is built around how your business really runs, with results you can measure in hours saved, quality gained and growth. Talk to Crom and Jono about your business.
