By: Masego Mosala - Solutions Engineer, Cloudera

Here's a statistic that happily surprises people: Africa has the world's largest proportion of women graduating in STEM fields, coming in at 47% according to UNESCO. But the less encouraging follow-up statistic is that despite producing the graduates, only about one-quarter of core technical roles in Africa end up being held by women.

Female representation falls to between 23% and 30% by the technical executive level. At the top, the gap is even more pronounced: women hold fewer than 12% of technology leadership positions and only one in 10 CEO roles at African tech startups, the same research shows. 

Often, ‘women in tech’ conversations focus on getting more girls and women into STEM. But there’s little value in producing more female STEM graduates if these qualifications never lead to sustainable careers in technology or the other STEM fields.

This drop-off is especially concerning with the rapid rise of artificial intelligence (AI). If Africa wants to participate in the global AI conversation, the continent cannot afford to lose (or leave untapped) any tech talent. In South Africa, for example, organisations are accelerating AI integration across all areas of business, but a lack of technical skills threatens to undermine meaningful impact and growth. A recent report from Pnet found that demand for AI-related skills in South African job postings grew by 352% between 2019 and 2025. 

Where is the disconnect?

Calling this a 'pipeline problem' misses the point. The pipeline exists, but it's leaking. What's missing is an ecosystem ready to employ and invest in the women who make it through in the first place.

Building that ecosystem means paying attention to what happens after graduation, not just before it. One place to start is understanding why top graduate talent doesn't automatically translate into strong candidates and successful hires.

Studying at South African universities and then entering the job market taught me how wide that gap between academic theory and workplace readiness really is. The modern workplace demands a blend of hard and soft skills that university training rarely covers. Graduates need to code, yes, but they also need to pitch an idea in a meeting, defend a technical decision to a non-technical stakeholder, and work a room. Most degrees don't teach any of that, so even technically excellent graduates can struggle the moment they're handed a real deliverable with a deadline attached.

More practical, project-based coursework would help address that – work that mirrors how AI-influenced workplaces operate, where speed and applied judgement count for more than pure recall. Curriculum reform is slow, though, and universities can't fix this on their own.

The private sector needs to carry its share of this too, through vocational training, internships and learnerships that go beyond being framed simply as compliance. Technology moves fast enough that a single training intervention early in someone's career won't carry them for the next fifteen years – this has to be continuous, and organisations that treat it as a line item rather than an investment will get exactly the return they put in.

There's also a 'hidden curriculum' to the job market that nobody teaches explicitly – it covers things like how to handle multiple rounds of technical interviews, how to use LinkedIn deliberately rather than just have a profile on it, and how to make sure your work gets noticed instead of assuming it will speak for itself. Graduates are left to work this out alone, usually by trial and error, and often later than peers who pick it up through informal networks that already skew toward historically privileged demographics. If organisations are serious about retention, this can't be left to chance – it's something a graduate programme or early-career mentorship structure can teach directly, the same way you'd teach someone a new part of the platform.

I've experienced what that kind of structure looks like when it's built deliberately, not relegated to the metaphorical roll of the dice. At Cloudera, that's meant mentors who share what they've learned the hard way, sponsors who've opened doors I couldn't open myself, and a career coach who keeps me accountable and honest.

Solving this challenge like a solutions engineer

As a Solutions Engineer, I default to a structured framework whenever I hit a roadblock. I don't have all the answers to this particular challenge, but here's how I'd think it through using that same engineering mindset – less a personal to-do list, more a way of framing the problem that organisations serious about this could actually use.

Step 1: Define the challenge

Before you can design a solution, you need clear requirements. That starts with refusing to treat 'more women in tech' as a single problem. Is the barrier a skills gap, a shortage of roles, or a mismatch between what graduates learn and what employers need? Each cause demands a different fix, and treating them as one problem is usually how well-intentioned interventions miss the mark.

Step 2: Gather information

In solutions engineering, you never build in a silo – you lean on documentation, forums, your team's collective experience. Applied here, that means the industry needs better source data than it currently has. A good starting point: organisations talking directly to women who completed STEM degrees but never entered tech, and asking exactly when they walked away, and why. That's a different dataset to the usual graduate survey, and a far more honest one.

Step 3: Deploy, track and iterate

Eventually, an idea has to leave the whiteboard – a mentorship pilot, a revised graduate programme, an audit of where a hiring process filters women out without anyone flagging it. Whatever the intervention, the same principle applies: track it properly, by cohort, and be willing to say it isn't working rather than waiting for next year's diversity report to confirm it. Your first attempt doesn't need to be perfect. If it fails, you diagnose the error, learn from it, and try again.

This final step is something I have learnt many times over the course of my tech career – and grounded in one of the core principles of engineering itself. Being in the trenches of this industry has taught me to fail fast and embrace that failure as a stepping stone. For an industry that is losing women before they even get started, the message is the same. If Africa wants to be an active participant in the tech race, it cannot leave half of its talent behind. The continent has already proven its capacity to educate world-class women in STEM; the next frontier is ensuring we retain, elevate, and empower them to lead.