Women lead nations, pilot planes, and engineer groundbreaking technologies. Yet, when it comes to artificial intelligence, a recent Capgemini report reveals a startling perception: many men still deem these crucial skills ‘masculine.’ In 2025, are we still grappling with such outdated biases?
While society celebrates advancements, it often simultaneously encodes old prejudices into new systems. Women in tech have long faced marginalization, whether through overt exclusion or subtle biases. As artificial intelligence reshapes leadership paradigms, this pattern persists, subtly disguised. It appears the patriarchy has merely adapted, going digital.
The Paradox of Progress: Confidence Without Conviction
The Capgemini Research Institute’s latest report, ‘Gender and Leadership: Navigating Bias, Opportunity and Change,’ starkly highlights this contradiction. Surveying 2,750 leaders across 11 countries, the findings initially suggest significant progress: 77% of both men and women now acknowledge that female leaders are equally effective. Confidence levels are nearly identical, with 58% of women and 59% of men reporting self-assurance. Furthermore, 68% of respondents believe that greater female representation in senior roles boosts business performance.
However, lurking beneath these encouraging statistics is a persistent, underlying bias. Nearly half of all male respondents continue to categorize essential future skills—such as artificial intelligence, automation, innovation, and data analytics—as ‘inherently masculine.’
These figures reveal a truth often obscured by politically correct corporate discourse: a belief in equality doesn’t necessarily translate to equitable perception. Bias hasn’t disappeared; it has merely modernized, cloaked in the sophisticated language of technology.
In contrast, most women surveyed perceive these skills as gender-neutral, with over a third even identifying innovation as ‘inherently feminine.’
The Masculinization of the Machine
It’s telling that AI—a domain defined by logic, precision, and immense power—is frequently conceptualized in masculine terms. This mirrors the societal reflex that often portrays CEOs as men in power suits and coders as solitary male figures. The historical link between intelligence and masculinity hasn’t faded; it has simply migrated to the digital realm.
While Capgemini’s study confirms that most women view AI and innovation skills as gender-neutral (with some even considering innovation ‘inherently feminine’), the prevailing perceptions among male leaders continue to dictate opportunities. When technological proficiency is unconsciously gendered, it erects an invisible barrier, creating a leadership filter that favors ingrained perceptions over actual competence.
This isn’t a flaw in the algorithms themselves, but rather a reflection of the biases embedded by those who train them. When leaders responsible for shaping the future perceive leadership through a traditionally masculine lens, they risk hardwiring existing hierarchies into the very fabric of tomorrow’s digital systems.
The Silent Reprogramming of Leadership
Modern workplaces often boast of transcending bias, equipped with catchy slogans, diversity statements, and ‘equity strategies.’ However, perception bias, particularly in tech-driven sectors, operates with a subtler, more insidious impact.
When AI and data analytics are implicitly labeled masculine, women in leadership roles are subtly relegated to the sidelines. They’re often expected to manage human resources rather than complex machines, to nurture rather than to innovate. Their empathy is praised, but their technical expertise is questioned. This cumulative effect is profoundly corrosive.
Technology is undeniably reshaping leadership, but this transformation isn’t unfolding equally for everyone. If digital proficiency becomes the ultimate criterion for leadership, and this proficiency is filtered through gendered assumptions, women risk being excluded from the future they actively help create. The Capgemini report explicitly warns that this perception bias could ‘reinforce the leadership divide’ at a time when technology is fundamentally redefining what it means to lead.
The Digital Ceiling: A New Glass, Harder to See
The proverbial glass ceiling hasn’t shattered; it has merely become transparent. This modern iteration doesn’t present as overt exclusion but rather as a gradual erosion of credibility, fostering a subtle perception that women are less attuned to the technological future.
Even as women excel in data science, head innovative labs, and formulate AI policies, they often remain outliers in a narrative predominantly authored by men. Patriarchy, once celebrated in traditional societies, now thrives with similar enthusiasm within the digital economy.
Rewriting the Leadership Algorithm
If technology truly represents the new language of power, then ensuring equitable access to speak it is a moral imperative. Organizations cannot simply automate their path to equality. Instead, they must actively dismantle the cultural structures that mistakenly link intellect with aggression and innovation solely with masculinity.
Authentic digital leadership extends beyond mere code proficiency; it demands a critical examination of the underlying assumptions that often obscure true potential. This necessitates a rich diversity of perspectives, particularly from those voices historically excluded from these vital discussions.
The Capgemini report is more than just a statistical analysis; it’s a sobering reflection on our contemporary illusions. It reveals that progress is far from linear, and we are still wrestling with deeply ingrained prejudices.
The Final Question: Who Codes the Future?
The future will undoubtedly be programmed and continuously evolve. But the crucial question remains: by whom, and for whose benefit? If the individuals shaping tomorrow’s world continue to believe that power, logic, and innovation are exclusively the domain of one gender, then AI will not usher in an era of liberation; instead, it will merely automate and entrench our existing, outdated hierarchies.
Women are not victims of AI itself, but rather of the narratives we perpetuate about who is deemed suitable to work alongside it. Until we collectively commit to rewriting this story—in our boardrooms, classrooms, and, crucially, within the very code we create—we will remain ensnared in a web of limiting stereotypes.
Ultimately, intelligence, whether artificial or human, will inherently carry bias as long as its creators and shapers are not diverse and free from prejudice.