By Belma Ibrahimović, Head of AI, saas.group
AI is no longer a future concept or a niche technical experiment. Today, it’s firmly embedded, from the tools we use to the decisions we make and the services we rely on. From finance and healthcare through to marketing and design, AI is reshaping the landscape of almost every industry – and it’s only getting smarter.
Yet, like every major technological leap, AI comes with risks alongside its enormous potential. Among the most pressing are questions of bias and fairness. Ultimately, any algorithm is only as good as the people who built it, how it’s developed and how it’s used.
This means that if an algorithm is, say, developed by a group of males of similar ages with similar backgrounds it will most likely integrate some form of unintentional bias based on their commonalities. When those same groups also control how outputs are interpreted and used, the risk of structural bias increases further.
Despite this, the global share of women in AI roles remains alarmingly low – often somewhere in the low 20% range – and drops even more sharply in senior AI leadership. A more recent global talent study found that although AI is now the most sought-after skill, the vast majority of workers who say they’re skilled in AI are men (71%), while just 29% are women. The reality is that until this stark gender gap is addressed, these imbalances will continue to echo through the AI ecosystem and perpetuate discrimination – even unintentionally.
A growing problem
From my own experience too, the figures are reflective of what is becoming an increasingly profound industry issue. I remember ten years or so ago, when I started my career as a software engineer in my hometown of Sarajevo it felt the gender gap in tech, while still present, was finally beginning to close. Of course, that’s not to say working as a woman in tech wasn’t without its challenges, but I genuinely felt valued, respected and was able to advance quickly in my career.
Today, from a global vantage point, the picture looks very different. If anything, I would argue that the gap is widening. As Head of AI at saas.group, I am fortunate to work in a company that is diverse and inclusive with over a third (34%) of the group – far above the average – female. Yet in my role, which involves evaluating SaaS startups many now built around AI, around the world, I see firsthand just how male-dominated the sector remains.
Across development teams and leadership structures, men continue to occupy the majority of roles – particularly in areas that shape technology such as model design, data strategy and deployment. At any given meeting with an up-and-coming tech firm, chances are the overwhelming majority of the team will be male.
Representation and visibility
Why, you might ask, does this disparity exist – and what can we do about it? While there is no single explanation, I believe much of the answer begins in the classroom. Despite the progress made, the number of women choosing to pursue STEM subjects remains depressingly low.
Of course, there is an element of chicken and egg at play. How can young women and other underrepresented groups envision careers in tech, or AI in particular, when these industries appear overwhelmingly male? Conversely, when women do enter the field and encounter heavily male-dominated workplaces, those environments can reinforce feelings of exclusion, making retention and career progression even more difficult.
But the education system is only part of the story. There is also a lot more tech businesses, especially those operating in the AI space, can do to help tackle the gender imbalance. From equitable hiring practices and mentorship programs to promoting inclusive workplace cultures and policies that support career advancement, there are a range of tools companies can use to create an environment where women and all underrepresented groups.
Among these efforts, visible female role models are crucial for making a career in AI feel attainable. By placing more women in senior technical and leadership roles, creating opportunities for them to speak at industry events and sharing the stories of successful women in the field, companies can challenge entrenched norms and inspire the next generation to pursue careers in tech.
Commercial advantage
Aside from being a moral imperative, closing the AI gender gap also makes commercial sense. Yes, we must break down barriers and create a fair and diverse tech economy where there is equal opportunity for all. Equally, companies must bring diverse voices into AI – not just because it’s fair, but because teams that reflect a wider range of experiences make smarter decisions, spot blind spots faster and build better technology.
Beyond that, research shows again and again that having a more diverse and inclusive workforce can help achieve a higher return on equity and better returns. This is because it can strengthen an organization’s intellectual capacity, breeding the ability to innovate and adapt in our fast-changing environment, with studies showing a critical mass of women in senior positions can have the maximum positive impact on a company’s performance.
There’s no doubt that current developments are just the tip of the AI iceberg, as tech giants continue to develop new AI models and our reliance on them grows. With this, it becomes vital that businesses address the ethical risks associated with their use and ensure they have the right procedures and policies in place to support a broader skillset and a greater diversity of perspective than ever before.
The risk is that if we don’t start to close the gender gap now, we could be left with an AI-first world that is less fair, less innovative and, ultimately, less effective for half the population.
