Six months ago, "do you use AI?" was still a reasonable interview question for a technology hire. It isn't anymore. Every candidate I speak with uses AI in some form. The question that actually separates candidates now is whether they can point to a measurable outcome they created with it.
That shift has happened fast, and a lot of Australian hiring processes haven't caught up.
Who owns AI risk? No one agrees
Source: PwC 2026 Financial Services Workforce AI Survey. US sample of 1,000+ executives, used here as a governance signal, not an Australian market read.
What changed in the brief
For the past year, most tech briefs I've taken have listed AI exposure as a nice-to-have, somewhere below the core stack and the years of experience. That's now backwards. On the roles I'm currently working, AI fluency sits alongside the technical fundamentals, not after them. Hiring managers are asking me to screen for it specifically, and candidates who can't demonstrate it are dropping down shortlists regardless of their other experience.
This isn't limited to engineering and data roles either. I'm seeing it in project delivery, in business analysis, in leadership appointments. The bar has moved for the whole technology function, not just the people writing code.
The governance gap nobody's screening for
Here's what most Australian hiring processes are still missing: governance. A recent PwC survey of more than 1,000 US financial services executives found that while almost 9 in 10 say AI accountability exists somewhere in their organisation, there's no consensus on where. Roughly a quarter point to the CEO and board, others to technology leaders, risk and compliance, or business unit heads, and a smaller group say it falls to the employee actually using the tool.
That's a US financial services sample, not an Australian technology one, so I wouldn't lean on it as a direct market read. But it names a problem I see constantly on this side of the Tasman too: organisations hire for AI skill and assume governance will sort itself out. It doesn't. The same PwC data found 90% of leaders believe employees using personal AI tools outside approved systems creates regulatory risk, and in my conversations with Australian technology leaders, shadow AI is already a live concern, not a hypothetical one.
The organisations that win the next five years won't just have the best AI tools. They'll have people who know how to use them responsibly, and leaders who've actually decided who owns that responsibility.
What this means for hiring
If you're building a technology team in this market, three things are worth building into your process now:
-
Screen for applied AI outcomes, not tool familiarity. Ask what someone built or fixed, not what platforms they've clicked through.
-
Ask governance questions in interviews, even for individual contributor roles. Where a candidate has seen AI decisions go wrong tells you more than where they've seen it go right.
-
Extend the bar beyond technical teams. AI literacy is becoming a baseline expectation across delivery, analysis and leadership roles, and your screening process should reflect that.
Where this is heading
AI capability stopped being a differentiator the moment everyone claimed to have it. What's scarce now is the combination of technical fluency and the judgement to use it accountably. That's a harder thing to hire for, and it's exactly the kind of brief I'd rather spend time getting right than filling fast.
If you're building out a technology team and want to talk through what good looks like in this market, I'm always happy to have that conversation early.
-1.png?width=214&height=214&name=Darren%20(1)-1.png)