Every week I hear from another Australian business that got burned on an AI vendor selection. The stories are depressingly similar: impressive demo, big promises, signed contract, then months of integration headaches and a product that doesn’t quite do what was demonstrated.

Here’s how to avoid that. I’ve distilled this from conversations with dozens of Australian businesses that have been through AI procurement, including the ones that got it right.

Start With the Problem, Not the Technology

This sounds obvious. It isn’t, apparently, because most businesses I talk to started their AI journey by looking at vendors rather than looking at their own operations.

Before you talk to a single vendor, document three things. What specific business process are you trying to improve? What does success look like in measurable terms? What’s your budget including implementation, not just licencing?

If you can’t answer all three clearly, you aren’t ready to evaluate vendors. You’re ready to do more internal analysis.

The Australian-Specific Questions

Here’s where local context matters enormously. Most AI vendor evaluation guides are written for US businesses. Australian businesses face different considerations.

Data sovereignty. Where does your data go? Many AI platforms route data through US or European servers for processing. Under the Privacy Act 1988 and the evolving Australian Government Data Sovereignty Framework, this may create compliance obligations. Ask every vendor: where is data processed, where is it stored, and can you guarantee it stays within Australian jurisdiction?

Local support. An AI system that breaks at 2 PM Sydney time shouldn’t require waiting until San Francisco wakes up for support. Ask about Australian-based support teams, response time guarantees in AEST, and whether you’ll have a dedicated account manager in-country.

Australian industry compliance. Depending on your sector, you may need AI systems that comply with APRA guidelines (financial services), TGA requirements (healthcare), or state-specific regulations. International vendors often don’t understand these requirements until you explain them, and then they need time to adapt. Factor that into your timeline.

The Technical Evaluation Checklist

Skip the polished demos. Instead, ask for these five things.

Proof of concept on your data. Not sample data. Not anonymised data that vaguely resembles yours. Your actual data, processed in a controlled environment with your team present. Any vendor that refuses this is hiding something.

Integration documentation. How does the system connect to your existing tech stack? What APIs are available? What’s the typical integration timeline for businesses of your size? If the answer involves “custom development” or “professional services engagement,” multiply your budget estimate by two.

Reference customers in your industry and region. Not references from US enterprises ten times your size. Australian businesses in your sector who’ve been live for at least six months. Talk to them without the vendor present. Ask what went wrong, not just what went right.

Model performance metrics on Australian data. AI models trained primarily on American data may perform differently on Australian data. Language models struggle with Australian English idioms and place names. Computer vision models trained on Northern Hemisphere conditions may not handle Australian lighting and landscapes. Ask for Australian-specific performance data.

Exit strategy. What happens if you want to leave? How do you extract your data? What format is it in? How long does it take? Vendor lock-in is a real risk with AI platforms, and you need to understand the exit path before you enter.

Red Flags to Watch For

Vendors who demo with canned data and resist using yours. Vendors who can’t provide Australian references. Vendors who quote licencing costs but are vague about implementation costs. Vendors who promise results in weeks for problems that realistically take months. Vendors who can’t explain how their AI makes decisions in terms your team understands.

Any of these should give you pause. Multiple red flags should send you elsewhere.

The Selection Process That Works

Run a structured evaluation with scoring criteria agreed before you see any demos. Include technical team members, the business process owners, your compliance/legal team, and someone from finance. Weight practical factors (integration effort, local support, data sovereignty) at least as heavily as feature comparisons.

For most businesses, working with specialists in this space who understand both the technology and the Australian regulatory landscape can save months of trial and error. External expertise is especially valuable for your first major AI procurement, when you don’t yet have internal benchmarks for what good looks like.

The best AI vendor decisions I’ve seen took longer than expected upfront and saved enormous time and money in implementation. The worst ones were rushed. Take the time to get it right.