Published 16 January 2025 in Technology • 10 min read • 
Audio available
Imagine a world where artificial intelligence reflects the needs, insights, and aspirations of all humanity – not just a select few. This future is within reach, but it will involve a seismic shift from women-centered AI initiatives to women-governed AI leadership.
This shift is taking shape. As we’ll see in a series of mini-case studies, women are leading breakthroughs in the responsible use of digital technologies. A key first step is to root out the gender and ethnic biases that often plague existing AI models. Other initiatives are aimed at greatly increasing the number of women involved with AI –including not only college-educated women but also those in poor or troubled parts of the world. In all cases, the movement is toward new forms of “fair AI” that will benefit all.
Such movement is needed because the stakes are high. AI’s global market is projected to surpass $1.5 trillion by 2035. New AI will reshape industries from healthcare to agriculture and entertainment to education. More than ever, we will need to prioritize societal well-being over unchecked profit. The time has come to ensure that equity and sustainability are foundational, not optional.
So, imagine what could happen if women governed even half of the innovation ahead. Intelligent digital medicine systems, designed not to overlook biological gender differences (as many now do), could save millions of lives. AI-driven climate change solutions, spearheaded by female leaders, could accelerate the race to mitigate environmental crises. Inclusive digital ecosystems could unlock $28tn in global GDP by fully integrating women into the tech economy.
These projections are more than pipe dreams. The foundations are being laid as you read. However, a core question arises, which should be addressed upfront: why are women essential to building a brighter AI future?
Given the massive influences that AI can exert, there are growing calls for oversight of the technology. However, along with oversight, responsible leaders must step forward to drive direct and inclusive participation in AI. Studies show that diverse leadership teams deliver up to 30% better outcomes in innovation and ethical decision-making. Multiple factors point to women emerging as key players.
Many people have long had an intuitive sense that women are especially well-suited to lead responsibly. Now, research is affirming this and documenting why it is true. A multi-firm study by a team at the University of Urbino Carlo Bo in Italy found that: “female leadership contributes to the promotion and implementation of environmental and social practices through several characteristics [including]: the ability to empathize and listen and the predisposition to sharing and collaboration [as well as] thinking systematically/holistically, managing complexity, and taking an inclusive approach to leadership.”
“Studies show that diverse leadership teams deliver up to 30% better outcomes in innovation and ethical decision-making. Multiple factors point to women emerging as key players.”
Let’s see how these characteristics can be valuable in AI’s development and use. The following sections outline both the dangers and possibilities of the new technologies. They then show how women are taking on lead roles in making our new age — the Intelligent Age — work for everybody.
The dangers of artificial intelligence extend far beyond the ability of generative AI to create deepfake images or misleading text. AI’s most common uses thus far consist of analyzing data to recommend actions, and often, the results turn out to be biased. A 2024 research paper by an international team summarized the pitfalls: “In AI, biases can originate in the data (pre-existing bias), in the design of AI algorithms and systems (technical bias), and in the organizational processes using AI models (emerging bias). Fairness in AI (or simply, fair AI) aims at designing methods for detecting, mitigating, and controlling biases in AI-supported decision-making, especially when such biases lead to (in an ethical sense) unfair or (in a legal sense) discriminatory decisions.”
Researchers at National Taiwan University demonstrated “the large and varied potential for AI to echo and even amplify existing human bias” — specifically, gender bias — and they point to the role that diversified leadership can play in ethical AI development.
Examples of harmful bias in AI have been tracked for several years. They have included:
There are no easy solutions. AI programs are trained by using massive data sets, all of which are from the past and may have past social biases built into them. Also, the algorithms designed to analyze data and churn out results are very complex. “Interrogating” the training data — for example, by having it independently audited — can help. Still, many experts believe a more fundamental solution is to involve diverse groups of people, particularly women, in AI development.
One prominent woman is setting a new standard in the field of medical data. The forms of health care you receive, from prescription medicines to surgeries and other therapies, are based to a large degree on data showing which treatments work best for the most patients in similar situations. But there is a catch. Women’s bodies are different from men’s and may respond differently to the same treatments. (Even women’s hearts are different.) These differences often are not accounted for in the data. For example, women tend to be under-represented in clinical trials of new medicines. Sylvia Thun and her colleagues are on a mission to ensure that the most reliable data is available to practitioners worldwide.
“Kibo (Knowledge in a Box) software can scan, digitize, translate, and generate audio versions of inputted text across 60 global and 13 Indian languages...Kibo is already used at the Indian Parliament Library ”
Dr Thun, a medical doctor with deep expertise in information technology, directs the digital medicine unit at the Berlin Institute of Health in Germany. She is also co-founder with Dr Christiane Gross of a global network called #SheHealth, aimed explicitly at meeting women’s needs. Their initiatives include bringing more female professionals into critical and high-ranking positions in digital medicine.
Broader efforts are being organized by women as well. One example is another global coalition, f<a+i>r (the Feminist AI Research Network), an ongoing project of The <A+> Alliance for Inclusive Algorithms. The women in this network are technologists, academics, and activists drawn from institutions in the Global South along with Europe and North America. Tecnológico de Costa Rica (TEC, the Costa Rica Institute of Technology) is a key university partner, while research leaders are based in locales ranging from Indonesia and the Philippines to African and South American nations. Geographic diversity is crucial, as women in many regions face inbred cultural challenges and forms of marginalization to a greater degree than women in more inclusive societies.
The f<a+i>r agenda consists of moving from “what’s wrong” with current AI to prototyping data methods and development models that can work better going forward. R&D is focused on removing gender bias and proactively addressing real-world problems that women encounter. The f<a+i>r members are far from alone in their mission. Global groups such as Women in AI are channeling female leaders and tech experts into other “fair AI” initiatives, and women are increasingly well represented in the teams assembled by governments and corporations.
A great potential upside lies in getting more women involved with AI. Here are several examples of women learning and applying advanced digital technology to create a positive societal impact:
A new Indian company Trestle Labs, founded by Akshita Sachdeva and Bonny Dave, produces inclusive digital technology for the country’s growing knowledge sectors. Their Kibo (Knowledge in a Box) software can scan, digitize, translate, and generate audio versions of inputted text across 60 global and 13 Indian languages. This makes the content accessible to people who are visually impaired or not fluent in the source language. Kibo is already used at the Indian Parliament Library and several universities in India.
I would further highlight two projects in which the World Woman Foundation (WWF), in collaboration with the US-India Strategic Partnership Forum (USISPF), is playing a major part. One is an initiative to train a million Indigenous women in AI, starting with a pilot in Mayurbhanj, Odisha, India. By equipping Indigenous women with AI skills, this program aims to address tech disparities — India has a pronounced digital divide between urban and rural regions — as well as promoting economic opportunities and preserving cultural heritage.
It is often assumed that only highly educated professionals can take part in developing and applying AI. We plan to show that this elitist assumption is wrong. Women around the world can participate and deliver widespread benefits by learning their way into the field gradually and then expanding their reach.
Training in the Mayurbhanj pilot covers data annotation, an entry-level skill that allows women from many backgrounds to contribute to AI development. The program further includes an intro to AI-powered agriculture — which can enhance crop productivity and resilience — and basic learning across a spectrum of other digital applications. Training in Natural Language Processing (NLP) will help to preserve Indigenous languages and cultural heritage. AI applications in health enable access to telemedicine and predictive care, which is essential for remote areas. And environmental monitoring merges Indigenous knowledge with technology for conservation efforts. Altogether, these skills empower Indigenous women to actively participate in the digital economy, shaping a more equitable and sustainable future in AI.
Wherever instability drives migration flows, bringing women into AI and advanced digital technology can help to turn members of so-called 'problem populations' into valuable human assets.
At the same time, a similar project is taking shape in Tijuana, Mexico. Together with the Mexican software firm ITJ, the WWF is launching an AI training initiative for women. The goal is to tackle critical challenges of mass migration and job insecurity in the Tijuana and Mexico-U.S. border regions. By current estimates, up to 75% of Tijuana’s working-class women lack access to formal tech education and high-paying job opportunities. Studies show that empowering women economically can reduce poverty rates by up to 30% in low-income areas, creating a ripple effect that benefits entire communities. This initiative — which brings together stakeholders from both sides of the border — provides women with marketable skills for the near term while preparing them for future jobs in sectors like AI, where demand is projected to grow by 25% annually.
Such collaborative, cross-border interventions offer a blueprint for addressing migration and economic challenges in other global border areas, such as the Mediterranean/Europe regions or the Indian subcontinent. Wherever instability drives migration flows, bringing women into AI and advanced digital technology can help to turn members of so-called “problem populations” into valuable human assets. As in other situations, the result should be richer, more fulfilling lives for all concerned.
As the Intelligent Age unfolds, women-led governance will be a cornerstone of creating an inclusive, equitable, and sustainable AI-powered future. This shift is not just a moral imperative but a strategic necessity in a world where AI could shape the destiny of humanity.
When women govern AI, they bring unique perspectives that balance innovation with compassion and equity with efficiency. This leadership can ensure AI evolves to solve humanity’s greatest challenges, from eradicating poverty to advancing human rights while unlocking untapped opportunities for prosperity.
Some trends seem to show that widespread female tech leadership is inevitable. There have been years of efforts to close the gender gap in STEM fields, and the efforts are starting to bear fruit. By 2030, the number of women in lead AI roles could grow by 50%. And by 2040, we could see women filling 40% of decision-making roles in global technology firms – a sharp increase from today’s 16%.
However, we cannot afford to take progress for granted. Governments and corporations must continue creating pathways for women to ascend. Policies like gender targets, mentorship programs, and inclusive education initiatives can help. The bottom line is that it’s no longer sufficient for women to merely contribute to AI; they must share the reins in governing it.
The future of AI is not yet written, but it has the potential to be a story of collaboration, fairness, and mutual benefits. It’s time for women to take the pen and author a new chapter in the human-AI narrative, where intelligence is guided by empathy, inclusion, and visionary leadership. The Intelligent Age belongs to everyone, and women will be its leading architects.
AI's true revolution isn't in chatbots but in transforming industrial operations through dark factories and predictive maintenance. This will require leaders to balance technological advancement with responsible societal impact. ...
In a world of deepfakes, hallucinations, and bias, we offer practical guidance on how you can trust your AI systems....
Audio available
Companies are rushing to embrace the game-changing opportunities to improve operations and scale that AI offers; yet many are unaware of the pitfalls. Test your knowledge of the risks here – and...
In an era defined by advanced AI and behavioral data, Apple’s 'Evil Steve' test exemplifies a proactive approach to ethical decision-making and responsible data governance....
Explore first person business intelligence from top minds curated for a global executive audience