Latest Industry Insights

In 2026, the most useful career question is no longer “Will AI take my job?” It is: what tasks can AI do alone, what tasks can I do better with AI, and what work should remain uniquely human?

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 the National AI Centre’s AI Adoption Tracker, 43 to 45 per cent of Australian SMEs are now using AI in some form. Government investment is growing, enterprise spending is up, and the business case for AI has never been more widely understood.