AI’s gender gap: The blind spot in media innovation

Over the past two years, Luminous Power’s #WomenInEnergy campaign has made a significant impact, sparking critical conversations about women in STEM and the energy sector. With over 77.4 million impressions, 55.6 million reach, and 6.9 million views, the campaign’s global reach is a testament to its resonance.

This year’s film, focused on a young girl defying stereotypes with her solar energy model, is a celebration of women’s leadership in technical fields. The film challenges stereotypes by depicting a girl's solar project, initially attributed to her father, as being guided by her mother, a Luminous Solar engineer. It captures the growing influence of women in STEM and challenges the ingrained notion that men dominate technical expertise.

Talking about why Luminous Power Technologies came up with this campaign, its chief strategy transformation and marketing officer, Neelima Burra, said, “We’ve reached a turning point where conversations around feminism and changing gender roles are not only possible—they are essential. Instead of fearing potential backlash, our strategic approach has been to actively engage with and garner support among consumers, thereby broadening the scope of the conversation to a wider audience.”

Yet, even as progress is being made in some areas of STEM, the AI revolution poses new challenges. AI is transforming industries at an unprecedented pace, and its influence on media, advertising, and creative sectors is profound.

However, the gender imbalance in AI leadership and operational roles remains a glaring issue. This isn’t just an equity problem; it’s a strategic imperative. The absence of diverse perspectives in AI development risks reinforcing biases, limiting innovation, and reducing the effectiveness of AI-driven applications in media and advertising.

The strategic advantage of diverse AI teams  

Diversity of thought within AI teams is a critical factor in driving innovation and enhancing the effectiveness of AI-driven solutions in media technology. Srividhya Srinivasan, co-founder and chief customer success and innovation officer, Amagi, underscores this point.

“Ensuring diversity in AI development stands crucial as it helps mitigate bias, enhances system performance, and ensures inclusive representation, leading to fairer, more effective, and widely applicable AI solutions. W When people from different origins, cultures, experiences, and perspectives come together, they bring unique approaches to problem-solving.”

ph

Photo: Srividhya Srinivasan, co-founder and chief customer success and innovation officer, Amagi

This diversity contributes to creativity, helps teams think beyond standard solutions, and ultimately leads to more reliable and effective AI-driven solutions. Chandni Shah, chief operating officer of FCB Kinnect, reinforces this by highlighting how women’s perspectives improve AI applications. According to her, when a company brings a woman’s perspective into the mix, they get richer insights, fewer blind spots, and way more inclusive outcomes.

“In media and advertising, that means AI-powered content that genuinely connects with diverse audiences rather than missing the mark. Women bring fresh takes on consumer behaviour, emotion, and storytelling, which are key ingredients for predictive analytics that truly understand what makes people tick,” she added.

Today, more than ever, championing DEI is not just a ‘good to do’—it’s a ‘fundamental business imperative’, and smart companies understand that excluding any significant demographic is a strategic failure, one that leaves no winners.

Shirin Rai Gupta, director—marketing at upGrad Enterprise believes it is important for brands to acknowledge that maintaining faith with users requires organisations to actively honour commitments to diversity and inclusion, regardless of global obstacles. When development lacks diversity, biased outcomes are inevitable, leading to the continuation and worsening of existing societal inequalities.

She alludes to the AI hackathon on 2 March 2024, when social media lit up with posts showcasing Gemini’s image generation tool depicting historical figures—ranging from popes to America’s founding fathers, and most controversially, German World War II soldiers—as people of colour.

The backlash was swift and widespread. While tech billionaire Elon Musk seized on the controversy as another battle in the ongoing culture wars, criticism wasn’t confined to usual suspects. Even Google’s CEO, Sundar Pichai, weighed in, calling some of Gemini’s generated responses “completely unacceptable.” Adding fuel to the fire, the chatbot’s ambiguous takes on historical culpability—wavering between libertarians and Stalin as the greater source of harm—only deepened the outrage, turning an experimental showcase into a PR crisis.

“Many of us have grown up seeing this, with women, queer people, and differently abled people often relegated to stereotypical roles in film and advertising. Genuine connection requires the incorporation of authentic, lived experiences – whether it is in technology, media or any other field,” Gupta adds.

The data backs this up. AI systems trained on narrow datasets often fail to capture the full complexity of human behaviour. This can lead to skewed advertising campaigns that misinterpret audience segments, reinforcing outdated stereotypes rather than engaging consumers meaningfully.

The risks of gender imbalance in AI development

As AI increasingly shapes consumer interactions, the risks of developing media and adtech solutions without strong female representation are profound. Shah warns that if women aren’t in the room, AI in media risks becoming an echo chamber, churning out content and ads based on a narrow worldview. That means missing out on key nuances in female consumer behaviour and, worse, reinforcing outdated stereotypes.

Moneka Khurana, CEO of MMA Global India, emphasises how this silencing can leave the long-term business risks in its wake. "When women's voices are absent, AI systems can perpetuate existing biases, leading to products that fail to meet the needs of half the population. This underrepresentation can result in AI tools that overlook or misinterpret women's preferences and behaviours, leading to ineffective targeting and potential brand alienation,” she noted.

Beyond the ethical concerns, companies ignoring diversity in AI development risk alienating large consumer segments and damaging brand trust. The tech’s growing role in media and advertising comes with a major pitfall—built-in bias. As algorithms learn from existing data, they often reinforce societal inequalities.

This isn’t hypothetical; it manifests in audience targeting, where marginalised groups risk exclusion. Research on the ‘excoded’ highlights the urgent need for ethical intervention.

Photo: Rajesh Ghatge, CEO of Wondrlab Technologies and founding team member of Wondrlab

Rajesh Ghatge, CEO of Wondrlab Technologies and founding team member of Wondrlab, outlines the challenge. "Beyond the well-documented issue of algorithmic bias, the absence of female perspectives leads to homogenised content, diminished user engagement, and a lack of robustness in handling diverse data. It narrows creative vision, stifles innovation in user experience, and leaves AI vulnerable to misinterpreting evolving social trends,” he explained.

An unintended consequence of skewed training data

Bias in AI is often an unintended consequence of skewed training data. Without diverse teams building these models, AI applications in media risk entrenching existing societal inequalities.

Srividhya Srinivasan, co-founder and chief customer success and innovation officer, Amagi explains, "A diverse AI team ensures that the systems are designed with a broad range of perspectives, helping to identify and rectify biases early on. By fostering diversity, organisations can create AI systems that provide fairer personalisation, more inclusive content scheduling, and a more equitable global media distribution, ultimately enhancing user trust and engagement."

Building AI with diverse teams brings a wealth of perspectives, allowing biases to be spotted and corrected early. This leads to fairer personalisation, inclusive content strategies, and balanced media distribution. The result? Greater user trust, stronger engagement, and a more equitable digital ecosystem—proving that diversity isn’t just ethical, it’s strategic.

Moneka Khurana points out that the unintended biases in AI can have real-world consequences. "For instance, studies have shown that facial recognition systems have higher error rates for women and people of colour, a disparity that diverse teams are more likely to identify and address. By ensuring that AI systems are trained on representative data, companies can avoid alienating segments of their audience and uphold ethical standards."

Diversity’s role in ensuring unbiased AI

With AI playing a larger role in curating news, moderating content, and shaping public narratives, female participation in AI development becomes an ethical necessity. Ghatge argues that women often exhibit a heightened sensitivity to nuanced social issues, crucial for navigating the complexities of online harassment, misinformation, and the potential for AI to amplify harmful stereotypes. “Their presence in AI development fosters a culture of critical inquiry, prompting consideration of ethical implications that might otherwise be overlooked,” he claimed.

Shah adds that AI is only as good as the data it learns from, so if the teams building it aren’t diverse, their models won’t be either. “More women in AI means better representation in datasets, smarter algorithms, and content recommendations that reflect real audiences instead of outdated norms."

Photo: Chandni Shah, chief operating officer of FCB Kinnect

Agencies and companies are taking steps to address gender disparity in AI by fostering mentorship programs and academic partnerships. Ghatge highlights early-stage interventions, like university workshops and seminars that aim to pique female students' interest in AI. Similarly, mentorship programs, often facilitated through platforms like LinkedIn and informal networks, are connecting aspiring professionals with experienced mentors.

A large media company partnered with upGrad Enterprise to run a Women’s Leadership Program, training around 50 women managers over a 22-hour program. The results? 20% of learners were promoted, 80% cited a significant increase in leadership skills, and 55% are now mentoring others—which highlights the tangible results that leadership programs can provide.

Outlining FCB Kinnect’s approach, Shah revealed that the agency has been actively training all its Kinnectors, including women leaders and rising talent, to build AI expertise. “Our in-house AI Army is leading the way in AI adoption across the agency, and we’ve made it a point to keep the team balanced—just as many women as men,” she added.

The AI-driven transformation of media and advertising presents both opportunities and challenges. Ensuring gender diversity isn’t just about fairness; it’s about making AI smarter, more ethical, and more effective. As companies invest in inclusive AI talent pipelines, diverse AI teams will be better equipped to create content that resonates across audiences, ensuring that media and advertising remain innovative, representative, and culturally attuned.

The industry must recognise that inclusion is not a checkbox exercise; it’s a business necessity. If AI is to shape the future of media, then women must play a central role in shaping AI.