Industry update · 5 min read

Industry update: AI pilots stall on governance, not technology

The AI conversation has shifted. Twelve months ago clients asked what the technology could do. Now they ask who approved it, what data it touched, and what happens when it is wrong. That is a governance question, and it is where most stalled pilots are stuck.

Brisbane, QLD ·

Classify the data before you connect it

The fastest way to end an AI project is to discover that a pilot indexed a folder containing employee records or client contracts. Decide which classifications of data may be processed, by which system, and in which region, before anything is connected.

Keep a human in the loop where the cost of being wrong is real

Drafting, summarising and triaging are strong early use cases because a human reviews the output. Decisions that affect a person's money, employment, health or legal position need explicit human sign-off and a record of it.

Log prompts and outputs like any other system of record

If you cannot reconstruct why an automated decision was made, you cannot defend it to a customer, an auditor or a regulator. Treat prompt and output logs as business records with a defined retention period.

Start with the process, not the model

The successful deployments we have delivered replaced a specific, measurable piece of manual work: quote preparation, ticket triage, document extraction, first-line customer response. They had a baseline before they had a model.

In short

Write the data classification, access, logging and human-review rules first. Projects that do this ship; projects that skip it get paused at the first hard question.

Let's scope your next project

Tell us what you are trying to fix or grow. You will speak with an engineer, not a salesperson, and leave the call with a clear view of scope, timeline and cost.