One of the quieter signals in the OECD’s latest data on technology and talent is this: we’re not drawing equally from the full population when it comes to technical capability.The numbers are clear, but they don’t shout. They simply show that across the OECD, and in Australia, men are still far more likely to code, more likely to work in ICT-heavy roles, and more likely to occupy AI-specific positions. And while the trend lines are slowly shifting, the gaps remain consistent.
The Early Divergence
Among 16–24-year-olds in Australia, young men are still nearly twice as likely to know how to code. That’s not unusual; the OECD average shows a similar pattern, but it’s worth paying attention to. These aren’t senior professionals. These are students and early-career talent. Which means that even before the job market comes into play, a meaningful divide has already formed.
This isn’t about ability. It may not even be about interest. It’s more likely about exposure, confidence, and who gets encouraged early on.
This is an industry supply issue. We’ll never get Gender Equality if the Genders aren’t equally represented. I think this is pretty simple logic.I wrote about this ~18 months ago. The article was called Is Australia Sleepwalking Towards A Tech Talent Crisis?, and it all sounded a bit dramatic to some people (I had calls from people telling me so). But the underlying data around supply won’t have changed drastically, and these OECD numbers back this assertion up.
🧠 The Digital Workload
The gap continues in the workforce. ICT task-intensive jobs, not just traditional IT roles but any job where digital capability is core to the function, are still more likely to be held by men. In Australia, men hold around 18% of these roles. Women, closer to 12%.These aren’t niche or obscure positions. These are the types of jobs that are growing, evolving, and shaping the future of work. Which makes the gap worth noticing, even if it’s no longer surprising.
The Shape of AI Talent
When it comes to AI-specific roles, measured here by LinkedIn profiles with engineering or machine learning skills, Australia tracks just below the OECD average: 24% women, compared to 26% across the board. That’s not a dramatic drop. But it is a reminder that even in the most in-demand, high-profile segments of tech, representation is still skewed. Again, it’s not just about fairness. It’s also about what perspectives are being built into the systems we use to get young people into the industry, and whose voices are influencing how those systems evolve.
Bridging School and the Workforce:
There’s been a growing conversation, one echoed in schools, households, and LinkedIn threads, about whether our current education system is preparing students for the future they’re entering.
The data here doesn’t answer that outright. But it does suggest something important: by the time students finish school, many have already been sorted, often unconsciously, into tech-confident and tech-uncertain paths. If we want a more equitable, adaptable workforce, maybe the question isn’t just “how do we get more women into AI?” but “how do we make sure more students, full stop, see this as a space they belong in?”
It might mean:
- Making programming and AI concepts more visible and less intimidating in secondary school
- Embedding work experience programs that expose all students, not just those already interested, to ICT roles
- Building stronger pathways between the university, TAFE, bootcamps, and industry for hands-on experience.
We won’t fix the future of education in one newsletter, but we can start paying closer attention to how early these divides begin, and how much potential we might unlock if we made the on-ramps broader.
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