Latest Industry Insights

Australia faces a projected shortfall of 60,000 AI professionals by 2027, and the gap is widening. With only around 2,000 AI graduates entering the workforce each year, the maths simply doesn’t work.

AI product managers sit at the intersection of business strategy and technical AI execution. They’re the person who translates what the organisation needs into what the AI team builds — scoping what’s feasible, prioritising what matters, and making sure the thing that ships actually solves the problem it was designed for.

“AI engineer”, “data scientist”, “ML engineer” — if these titles all sound like the same job described three different ways, you’re not alone.

Machine learning engineers are the people who take models out of notebooks and put them into production. If data scientists ask “what can we predict?”, ML engineers answer “how do we make that prediction reliable, fast, and maintainable?”

According to CSIRO’s National AI Centre, 68% of Australian companies have now integrated AI into at least one business function. Government investment is growing, enterprise spending is up, and the business case for AI has never been more widely understood.

Every AI initiative starts with data. Before your data scientists can build models or your ML engineers can deploy them, someone has to design the pipelines, build the infrastructure, and make sure clean, reliable data flows where it needs to go. That someone is a data engineer — and they’re one of the most in-demand technical roles in Australia right now.