Your people are already using AI.

GIST is the methodology Tracy uses with corporate boards. It stands for Guardrails, Intent, Strategy, Practical Training. The sequence matters. Guardrails come first because your people are already using AI, and they need to know what stays in-house and what goes out. Intent comes second because tools without purpose are noise. Strategy comes third because the plan has to hold up at board level. Practical Training comes last because adoption only sticks when people know what to do on Monday morning.

AI governance is the set of decisions a business makes about how, where and when AI is used. It covers what data goes near AI tools, who is accountable when AI is wrong, what your people are allowed to do, and what gets escalated. In Australia, governance has to align with the Privacy Act, sector-specific obligations and your organisation’s own values. Good governance is not a brake. It is a permission slip. It tells your people exactly what they can do, which means they stop guessing and start using AI properly.

Start with guardrails. Not tools. Before anyone in your business touches another AI platform, sit down and decide three things. What data is off limits. What outputs need a human review. What happens if something goes wrong. Then pick one practical use case where AI saves your team an hour a week, and run a small pilot inside your guardrails. Most businesses skip this and end up with shadow AI everywhere. The boring step is the one that protects you. Take the AI Readiness check on this site for a structured starting point.

Shadow AI is the AI your people are already using without telling you. Tools in their browser. Copilot in their email. A free transcription tool on a client call. Most leaders assume it isn’t happening in their business. It is. Recent surveys put unsanctioned AI use at over 90% of organisations globally. Shadow AI is not a discipline problem. It is a governance gap. Your people are trying to do good work faster, and they are reaching for whatever helps. The fix is not banning tools. The fix is guardrails.

Start with three sections. Scope: who it applies to and which tools it covers. Use: what your people can and cannot do, what data is off limits, what outputs need a human review. Accountability: who owns AI decisions, who escalates when something goes wrong. Align it with the Privacy Act 1988, any sector-specific obligations and your existing IT and information-security policies. Keep it short. Keep it readable. Keep it living. Review every six months because the tools and the law both move fast.

Automation is a rules engine. It does the same thing the same way every time. AI is a probability engine. It produces an answer that is most likely correct based on patterns it has learned. Automation works best for repeatable tasks with clear rules: scheduling, invoicing, data entry. AI works best where judgment is involved: drafting, summarising, finding patterns, answering questions. Most modern systems combine both. The two are tools for different jobs, and knowing which job you have in front of you is half the battle.