The Readiness Check
AI spending is accelerating across Australian mid-market companies. But most are spending without the fundamentals in place—which means they're burning money on projects that will underdeliver or fail.
Before you authorise another AI project, run your team through these five questions. They're a acid test for whether you're actually ready.
1. Do we have clean, accessible data for the problem we're trying to solve?
AI is only as good as the data it learns from. If your customer records are scattered across three CRMs, your inventory data is updated manually in spreadsheets, or your operational metrics live in managers' heads—AI won't help. It will expose every data weakness you have. Fix your data foundation first.
2. Can we measure the current cost of the problem we're trying to solve?
If you can't quantify the cost of the problem you're solving—whether it's customer churn, manufacturing defects, or scheduling inefficiencies—you can't prove AI delivered value. Every AI investment needs a baseline. If you don't have one, you're not ready to spend.
3. Do we have executive sponsorship beyond the IT team?
AI projects that live in IT die in IT. You need a business unit sponsor—a COO, CFO, or operational MD—who owns the problem and the outcome. If your only champion is the IT Director, the project will lose momentum the moment budget season arrives.
4. Are our processes standardised enough to codify?
AI automates decisions. But it can only automate decisions that are consistent. If your operations vary wildly based on which manager is running things, which client is involved, or what mood someone's in—AI will struggle. Standardise before you automate.
5. Can we commit to the change management required?
The hardest part of AI isn't the technology—it's getting people to use it. Your team will need to change how they work, trust AI recommendations, and adapt to new workflows. If you're not prepared to invest in training, communication, and transitional support, the best AI system in the world will gather dust.
The Pattern
Notice what these questions have in common: they're not about technology. They're about operational discipline, data maturity, and organisational readiness. Those are the things that actually determine AI success.
If you can answer all five confidently, you're ready to invest. If you can't, that's okay—but don't spend money on AI until you've built the foundation. The technology will still be there when you're ready. The difference is you'll actually get value from it.