Insights from the field: data platforms, AI delivery and APRA compliance

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AI Consulting

AI consulting in Australia: the local constraints that decide whether a project lands

Four constraints specific to Australian organisations shape every AI consulting engagement here: named regulators with specific artefacts, data residency as a multi-part design decision, an estate with a recognisable local shape, and panel procurement. What fifteen years in this market buys, and the three cases where a global firm is the better call.

By RUBIX · 24 September 2026

AI Consulting

What AI consulting actually delivers

"AI consulting" covers at least five different kinds of work with different deliverables, prices and risk. What each one gives you, and how to tell which one you are actually buying.

By RUBIX · 23 September 2026

Platforms

Build or buy your data platform: how to decide

Build versus buy is usually asked too broadly. Which layers of a data platform you should buy almost always, the one layer worth building, and the cost model that decides the rest.

By RUBIX · 22 September 2026

AI Readiness

Are you AI ready? Seven questions that decide it

Maturity models score ambition. These seven questions test whether your organisation can actually put an AI system into production, what a failing answer looks like, and what to do about each one.

By RUBIX · 22 September 2026

AI Readiness

What happens after an AI readiness assessment

A readiness assessment that ends in a scored report has failed. What the output should commit you to, who does the work next, and how the first AI engagement gets scoped in Australia.

By RUBIX · 21 September 2026

AI Delivery

Where AI agents do not work yet

AI agents genuinely run work in Australian organisations - and genuinely fail in four recurring places. An honest map of the line, and how to tell which side your use case sits on.

By RUBIX · 18 September 2026

AI Consulting

What an AI consulting engagement actually looks like

Cost and shortlist guides tell you who to hire. This is the shape of the work itself: the four phases, what each one must produce, and the five clauses that decide whether you get a system or a slide deck.

By RUBIX · 15 September 2026

AI Consulting

AI Consulting in Melbourne: What Local Actually Buys You

Proximity is the most oversold variable in choosing an AI consultant. The three things a Melbourne-based team genuinely changes, the three it does not, and the questions that tell them apart.

By RUBIX · 10 September 2026

Compliance

AI governance for founders: notes from EO Melbourne's AI in Action

Notes from EO Melbourne's AI in Action session, where Dylan spoke on data strategy, governance and scalable platforms - why governance is what lets a founder move fast on AI, and the five decisions that do the work of a framework at founder scale.

By RUBIX · 2 September 2026

Compliance

Who owns the knowledge your AI creates

Data residency answered the easy half of sovereignty. The question that matters now is who controls the institutional knowledge AI captures through prompts, evaluation sets and correction logs - and under CPS 230 a foundation model is a material service provider.

By RUBIX · 24 August 2026

AI Readiness

How to run an AI readiness assessment

Most AI readiness assessments score ambition, not readiness. What a real one measures across data, use cases, skills, technology and governance - and how to run one in weeks.

By RUBIX · 17 August 2026

Platforms

Why AI needs a governed data platform

Most stalled AI programs are not model problems, they are platform problems. What makes a data platform governed, the four failures of an ungoverned one, and the order to build it in.

By RUBIX · 14 August 2026

AI Delivery

Agentic AI for mid-size Australian businesses

Who builds agentic AI automation for mid-size Australian businesses? RUBIX, for organisations of 200 to 2,000 people - and why the mid-market ships agents that stick.

By RUBIX · 3 August 2026

Compliance

Asserted vs observed compliance

For twenty years, compliance in Australian financial services has been a documentation discipline. CPS 230 quietly breaks that model: the supervisory question is no longer "show me the policy" but "show me the signal."

By Dylan Smith · 1 August 2026