by The Enlighten Ventures Team
The returns data has been sitting in plain sight for two decades. Female-founded companies generate 2.5 times more revenue per dollar of funding than the market average. That is not a social finding. It is an alpha signal — one of the most consistent, most documented, and least acted-upon performance differentials in the history of venture capital.
BCG measured it across thousands of companies: female-founded startups generate $0.78 in revenue per dollar of funding raised. Male-founded startups generate $0.31. The multiple is 2.5×. MSCI confirmed it from the board governance angle: companies with at least 30% female directors outperformed those without by 18.9 percentage points over five years. Russell Reynolds closed the loop from the fund side: seven in ten top-quartile US venture capital funds over the last decade included female decision-makers.
Mira Murati raised $2 billion at a $12 billion valuation — before Thinking Machines Lab had a product — the largest seed round in venture capital history.
The AI industry is where this signal is most pronounced — and most actionable — right now. Anthropic, the world’s leading AI safety company, is valued at $183 billion and led by Daniela Amodei as President. Scale AI, the data infrastructure company on which every major AI training programme in the world depends, was co-founded by Lucy Guo and is valued at $74.1 billion. Mira Murati raised $2 billion at a $12 billion valuation — before Thinking Machines Lab had a product — the largest seed round in venture capital history. Dr. Fei-Fei Li built ImageNet, the dataset without which there is no deep learning revolution, no ChatGPT, and no $5.9 trillion global unicorn market. Dr. Lisa Su took AMD’s stock up 100× while building the world’s primary alternative to Nvidia for AI chips. Gwynne Shotwell runs SpaceX. Dr. Swati Mohan landed a rover on Mars.
Dr. Lisa Su took AMD’s stock up 100× while building the world’s primary alternative to Nvidia for AI chips. Gwynne Shotwell runs SpaceX. Dr. Swati Mohan landed a rover on Mars.
This is who is generating the alpha, what they have built, and where the returns are coming from.
“Female-founded companies generate 2.5 times the revenue efficiency of the market average. The alpha is in the data. The opportunity is in acting on it before the crowd arrives.” — The New Titans of AI, April 2026
The AI Companies built by the New Titans commanding the frontier
The most valuable companies in artificial intelligence — foundation models, spatial intelligence, autonomous systems, enterprise platforms, and the infrastructure that makes AI possible — include organisations built by women who recognised the opportunity before the market fully understood it, and who moved decisively.
Foundation Models and Safety
Daniela Amodei co-founded Anthropic on a single, precise thesis: that building AI safely and building AI powerfully are not competing priorities — they are the same project. Anthropic raised $11.8 billion in 2024, reached a $183 billion valuation$183 billion valuation, and produced the Claude series of models deployed by enterprises, governments, and research institutions worldwide. As President, Amodei commands the business that funds the safety research that may determine whether transformative AI benefits humanity at scale. The capital confidence this has attracted is without precedent in the history of technology safety.
Mira Murati served as Chief Technology Officer of OpenAI, overseeing GPT-4 and the launch of ChatGPT — the product that introduced a billion people to what large language models could do. When she founded Thinking Machines Lab, the market placed a $12 billion valuation on the company before it had a product. The $2 billion seed round she raised in July 2025 is the largest in venture capital history. It is the market’s precise statement about what she will build next.
Spatial Intelligence
World Labs, co-founded by Dr. Fei-Fei Li, is building AI that comprehends three-dimensional physical space — the foundational layer powering the next generation of robotics, surgical systems, autonomous vehicles, and augmented reality. World Labs raised $230 million in 2024 and $1 billion in 2026. The company extends Li’s thirty-year research programme — from ImageNet, which made modern deep learning possible, to the spatial intelligence systems that will define the decade that follows.
Dr Fei-Fei Li is the inaugural Sequoia Professor in the Computer Science Department at Stanford University, and Co-Director of Stanford’s Human-Centered AI Institute
Platforms Builders Scaling
Melanie Perkins built Canva — valued at over $25 billion, used by 170 million people — on the conviction that professional design tools should be available at every level of scale and resource. AI is now embedded throughout every Canva product. May Habib’s Writer is the enterprise generative AI platform that global companies deploy at scale with the governance and brand consistency that general-purpose models cannot provide; it has raised $326 million including a $200 million Series C. Lucy Guo co-founded Scale AI — valued at $74.1 billion — providing the data infrastructure on which every major AI training programme in the world depends.
Autonomous Systems
Raquel Urtasun, former head of Uber’s autonomous vehicle programme, built Waabi on the thesis that autonomous driving requires a driver AI constructed from first principles — not sensors retrofitted onto human-designed vehicles. Waabi’s $200 million Series B in 2024 validated an approach the most rigorous researchers in the field now recognise as technically correct. Daphne Koller has built two institutions that applied intelligence to civilisational bottlenecks: Coursera for education, and Insitro for drug discovery — compressing the fifteen-year pharmaceutical pipeline through machine learning, with Gilead Sciences as research partner and over $100 million in Series A funding.
AI Companies Founded or Led by Women
The investors above represent the capital formation layer of the female AI leadership ecosystem. Below them, and equally consequential, are the women applying AI directly to financial services architecture — building the platforms, instruments, and infrastructure through which the intelligent economy will run.
Deep Tech, STEM and Space
Commanding the Toughfest Frontiers
The most technically demanding domains of artificial intelligence — large language models, space systems, climate science, and the life sciences — are where the decade’s defining breakthroughs originate. Depth of expertise, precision of execution, and clarity of vision separate the architects from the rest.
Large Language Models
The Falcon large language models — open-source systems competing on international benchmarks with the leading commercial models — were built under the leadership of Najwa Aaraj, CEO of the Technology Innovation Institute in Abu Dhabi. Aaraj commands one of the most ambitious applied AI research programmes outside Silicon Valley, spanning cryptography, quantum computing, and autonomous systems alongside AI. Open-source language models are the new infrastructure layer of the global AI internet. Aaraj is building it, and the benchmarks confirm she is winning. Dr. Manasi Vartak, founder of Verta.ai, built the MLOps infrastructure that makes enterprise AI deployment reliable at scale — the critical junction where research becomes operational revenue.
Gwynne Shotwell runs SpaceX — more mass launched to orbit than any national space agency, the Falcon 9 the most reliably flown rocket in history, and Starlink providing broadband across 6,000+ satellites. AI governs constellation management, trajectory optimisation, and autonomous landing. Shotwell has converted the extraordinary into the routine. Vanessa Wyche directs NASA’s Johnson Space Center — commanding the ISS, the Artemis lunar programme, and the AI systems sustaining human life in environments where no physician can be present. Dr. Swati Mohan led Guidance, Navigation and Controls for NASA’s Perseverance Mars rover — the AI system that executed autonomous entry, descent, and landing on another planet in seven minutes of complete radio blackout. The algorithm made every decision. The landing succeeded.
Climate, AI and Life Sciences
Bessie Schwarz and Beth Tellman’s Floodbase deploys satellite imagery and ML for real-time flood monitoring and parametric insurance pricing — building the data infrastructure that reprices climate risk across sovereign debt, infrastructure finance, and reinsurance markets. In genomics, female principal investigators at the Broad Institute, Wellcome Sanger, and Helmholtz Association are translating transformer architectures into breakthroughs in cancer treatment, rare disease diagnosis, and precision agriculture. The convergence of language model techniques with genomic data is among the most productive scientific developments of the decade.
The Scientists & Innovators
The Research That Commands the Field
Scientific leadership in AI is measured by the discoveries so foundational that the industry is built upon them. The researchers profiled here hold that distinction — and continue to extend it.
Dr. Daphne Koller Co-Founder & CEO, Insitro · Co-Founder, Coursera · MacArthur FellowTwo transformations. Coursera delivered university education to over 100 million learners. Insitro is compressing the pharmaceutical development pipeline using machine learning — identifying which molecules succeed before the billion-dollar trial phases that have historically consumed the industry. The same theorem governs both: intelligence, correctly applied, dramatically accelerates the rate at which human knowledge reaches the people who need it.
Dr. Rana el Kaliouby Founder, Blue Tulip Ventures · Former CEO, Affectiva · Executive Fellow, Harvard Business School
El Kaliouby built Affectiva — the first commercially deployed emotion AI company — from MIT Media Lab, developing technology now embedded in automotive safety systems, mental health platforms, and educational tools across three continents. Following its acquisition by Smart Eye, she founded Blue Tulip Ventures to back the next generation of human-centric AI. Her memoir, Girl Decoded, is the definitive account of building technology that centres human cognition and emotion in its design brief.
Kim Polese Executive Chairman & Co-Founder, CrowdSmart · Co-Founder, Common Good AI · Former CEO, Marimba
Kim Polese’s career runs through the central arc of Silicon Valley’s AI development. She began at IntelliCorp — the first AI company ever to go public — implementing expert systems for Fortune 100 clients, before leading the 1995 launch of Java at Sun Microsystems as its founding product manager: one of the most consequential technology launches of the decade. As co-founder and CEO of Marimba, she built the company to profitability, IPO, and acquisition by BMC Software — with its platform now delivering three billion endpoint updates annually across consumer devices, vehicles, and appliances worldwide.
At CrowdSmart, which she co-founded in 2015 and chairs as Executive Chairman, Polese is building the architecture for collective intelligence at institutional scale: AI that amplifies group decision-making, surfaces hidden insights across teams, and systematically reduces the cognitive biases that undermine high-stakes organisational choices. Her thesis — that the greatest potential of AI lies in augmenting human intelligence rather than replacing it — positions CrowdSmart at the frontier of how institutions will govern, invest, and compete. She simultaneously co-founded Common Good AI, applying AI to democratic civic engagement and institutional trust — among the most consequential deployments of intelligent systems in modern governance. A member of President Obama’s Innovation Advisory Board, an Aspen Institute Crown Fellow, and an adjunct faculty member at UC Berkeley, Polese is one of the few technologists whose influence spans from the original foundations of AI to its current frontier.
Technology Executive · Fintech and AI App Builder · Former Researcher, Xerox PARC
Xerox PARC is where the modern computing world was invented. The graphical user interface, Ethernet, the laser printer, object-oriented programming — all of it originated in the laboratories of Palo Alto Research Center. To have worked there is to have stood at the precise coordinates where the future was being assembled. Yvonne Espinosa is one of the women who held that ground — carrying the research rigour and systems thinking of one of technology’s most consequential institutions into the applied work that follows.
Espinosa’s focus is the intersection where AI meets financial services and consumer applications: the design and development of intelligent platforms that bring the power of machine learning and data-driven automation to how people and institutions manage, move, and grow capital. Financial services is among the richest domains for AI application — encompassing fraud detection, credit intelligence, personalised financial guidance, compliance automation, and the infrastructure through which trillions of dollars flow daily. Espinosa brings to this space the depth of a research background forged at one of Silicon Valley’s most demanding institutions, combined with the builder’s instinct for products that work at scale. Her work represents precisely the kind of pedigree — rigorous, applied, commercially grounded — that the AI century rewards.
Dr. Tatia Codreanu Teaching Fellow & I-X AI Affiliate, Imperial College London · Cooperative AI Researcher
At Imperial College London, Dr. Tatia Codreanu leads research on one of the most strategically important questions in AI deployment: how do AI systems build and sustain human trust at scale? Her programme on Cooperative AI and Polite AI examines how systems can be designed to embody cooperation, ethical reasoning, and social awareness — the properties that determine whether organisations and individuals adopt AI with confidence or resistance. Her research integrates behavioural economics, cognitive psychology, and human-computer interaction into frameworks addressing AI’s role in leadership, decision-making, and strategic transformation. Her 2026 Imperial seminar AI in Film and Media: A Dual Frontier — drawing on case studies from the Cannes Film Festival and landmark legal precedents — mapped the economic and governance implications of AI’s integration into creative production with forensic precision. An I-X AI in Science Affiliate, she also designs Imperial’s AI-Enhanced Storytelling and AI and the Humanities programmes — translating frontier research into practice for senior executives, physicians, and institutional leaders across industry and government.
Dr. Joy Buolamwini Founder, Algorithmic Justice League · Author, Unmasking AI (2023)
Buolamwini’s 2018 “Gender Shades” study revealed systematic performance failures in facial recognition systems deployed by IBM, Microsoft, and Amazon — directly prompting IBM’s discontinuation of its facial recognition product in 2020 and driving industry-wide product improvements. She founded the Algorithmic Justice League, testified before the US Congress, premiered the documentary Coded Bias at Sundance, and published Unmasking AI in 2023. She has built the accountability architecture that governs how the industry now operates.
Dr. Margaret Mitchell Chief Ethics Scientist, Hugging Face · Creator, Model Cards
Mitchell created model cards — the standardised documentation making AI systems’ capabilities and limitations legible to regulators, enterprise deployers, and non-experts. In an era of accelerating regulatory pressure from Brussels to Washington, this infrastructure is among the most practically consequential governance innovations in recent AI. At Hugging Face, she continues to define the industry’s standards for responsible model development and deployment.
Academic and Research Leaders — Selected
V — AI Titans of Fashion, Architecture, Music, Art and Media
The Creative Economy’s AI Revolution
The $1.5 trillion creative economy is undergoing an AI transformation of the same magnitude as finance and manufacturing. The executives and artists commanding it are building AI applications of extraordinary commercial power and cultural permanence.
Fashion: Commanding the Algorithm
Katrina Lake built Stitch Fix as an AI company that happened to ship clothing — her thesis being that personal styling could be amplified by machine learning at scale. The algorithm built individual taste profiles from millions of decisions. Stitch Fix’s 2017 IPO was one of the decade’s most studied technology offerings. The human-plus-algorithm model Lake established is now the framework every major fashion conglomerate is building toward. Jennifer Hyman‘s Rent the Runway applied AI to fashion’s most persistent structural inefficiency: inventory capital locked in product that never reaches the right customer. Machine learning predicts precisely which items will be requested when, by whom, and in what size — transforming the economics of luxury fashion from fixed-cost to dynamic and AI-optimised.
AI Policyl Architecture and Smart Cities
Dr. Jacqui Taylor, CEO of FlyingBinary and Principal Strategic Advisor to the UK Government on AI and Smart Cities, leads one of the most extensive AI implementation programmes of her generation. An aerospace engineer, Taylor directs FlyingBinary — one of only 119 companies globally delivering accredited AI services to the UK Government — and serves simultaneously as UN Expert Advisor on procurement innovation for 180 nations. Generative AI is producing a new discipline of architecture: buildings and urban systems designed by algorithms that simulate structural performance, energy efficiency, and climate resilience before ground is broken. Female architects and urban technologists hold leadership positions across this discipline, deploying AI to determine how cities of ten million people will function in 2035.
Music: Owning the AI Frontier
Holly Herndon’s 2019 album PROTO established AI as a genuine compositional collaborator. Her subsequent project, Holly+, created an open-source platform allowing other artists to use her AI voice model under a licensing framework she controls — the first working model for artist-controlled AI licensing in the music industry. The frameworks the music business will need to adopt this decade are the ones Herndon built first.
Art, Museums and Cultural Infrastructure
Efsun Erkilic co-founded Refik Anadol Studio and architected Dataland — the world’s first museum dedicated to AI art, 20,000 square feet in Los Angeles, built in collaboration with Google. Erkilic built the institutional framework that transforms AI-generated work into permanent, collectible, exhibitable cultural form. At Christie’s, Sotheby’s, and the major auction houses, female curators and research directors are deploying AI for provenance research — tracing ownership histories across centuries of digitised records in hours instead of months.
Dr. Marsha Lipton: The Quantum Steward of Human Heritage
As the CEO and Co-Founder of Numeraire Future Trends, Dr. Marsha Lipton is pioneering the “verifiable identity layer” for the world’s most precious physical assets. While most tech titans focus on building digital worlds, Lipton is focused on securing the physical one—using a sophisticated blend of quantum physics, AI, and cryptography to protect the integrity of art, artifacts, and cultural heritage.
The Academic Foundation of a Polymath
Dr. Lipton’s approach to technology is defined by a rare level of academic rigor. She earned her Ph.D. in Physical Chemistry from the University of Chicago (specializing in quantum chemistry and spectroscopy) while simultaneously completing her MBA at the University of Chicago Booth School of Business.This dual-track expertise allowed her to bridge the gap between microscopic physical properties and global market structures, a journey that led from the research labs of the James Franck Institute to a 20-year career as a Managing Director at JPMorgan and Bankers Trust.
AI-Powered “Object Fingerprinting”
Under her leadership, Numeraire Future Trends has developed a non-invasive, optics-based AI solution that eliminates the need for physical tags, RFID chips, or stickers.
- Surface Biometrics: Just as humans are identified by fingerprints, Lipton’s AI analyzes the microscopic, inherent physical properties of an object—such as pigment distribution, surface texture, and material composition.
- Non-Invasive Verification: Using a portable digital microscope or even a mobile device, the system captures these “Object AI Fingerprints” to create a permanent, unique identity for any physical item.
Blockchain and the Digital Product Passport (DPP)
Lipton integrates these AI fingerprints with blockchain-anchored Digital Product Passports. This creates an immutable link between the physical object and its digital record, solving the “oracle problem” (the difficulty of ensuring that a digital record actually refers to the correct physical item).
- For Nations and Museums: Numeraire provides a framework for sovereign nations to secure their cultural patrimony, ensuring that stolen or looted artifacts can be identified and reclaimed with scientific certainty.
- For Emerging Artists: Lipton empowers creators to “sign” their work at the moment of creation, securing their legacy and ensuring secondary market royalties are protected through verifiable provenance.
- Cultural Stewardship: Her mission is to future-proof the cultural ecosystem. By providing a foundation of trust, she enables museums to engage in secure international loans and allows collectors to invest in emerging talent without the fear of AI-generated forgeries.
“A digital entry has little meaning if it is not immutably connected to the physical object it represents. At a time when technology makes deception easy, we must build an infrastructure of truth.” — Dr. Marsha Lipton
Policy and Governance
Writing the Rules of the AI Century
Policy Architects and Governance Leaders — Global
The Investors Shaping AI’s Financial Future
The investors directing capital toward female-led AI companies span every stage from angel to institutional. Their portfolios contain the companies that will define the next decade. Their track records command the attention of every serious allocator.
Among the most consequential architects of this capital landscape is Gillian Muessig — a figure whose career spans three decades of technology building and whose investment philosophy has consistently sat a decade ahead of the institutional consensus.
Gillian Muessig anaging Director & General Partner, Mastersfund™ · CEO, Outlines Venture Group · Co-Founder, Moz · Tech Advisor, Bill & Melinda Gates Foundation
Gillian Muessig has been one of the most consistently prescient voices in technology and venture capital for over three decades — building companies, funding founders, and redesigning the investment instruments through which capital reaches the people building the future. She co-founded SEOMoz, which became Moz — the world’s most widely used digital marketing software platform and the global hub for digital marketers. She pioneered the SEO discipline that launched household names including Zillow and Philips Lifeline onto the web, and built the world’s largest consortium of digital marketing agencies. That background gave Muessig something unusual in venture capital: the operational depth of someone who had actually built a market category from first principles.
In 2018, she launched the Sybilla Masters Fund — named for Sybilla Masters, the first American to hold a patent, whose 1715 invention was registered under her husband’s name because women were legally barred from patent ownership. The parallel to the venture capital industry was exact and deliberate. The fund invests in technology and innovation companies with women at the helm, applying over 25 years of independent research demonstrating that women-led companies return an average 35% higher ROI to investors than the market baseline. That finding — sustained across market cycles and company types — is the thesis. The fund now operates as Mastersfund™, with Muessig as Managing Director and General Partner.
What distinguishes Muessig’s approach from conventional gender-lens investing is the integration of machine learning directly into the investment process itself. Mastersfund is actively building an open-sourced ML platform to gather and analyse data on emerging startup companies at a scale and speed that traditional due diligence cannot reach — using AI to identify patterns in company assets, growth trajectories, and inflection points across thousands of early-stage companies simultaneously. The thesis is not that human judgment should be replaced; it is that AI-augmented diligence reveals the opportunities that crowded conventional markets systematically miss. In Muessig’s framing: the quiet field is where the unicorn stands.
Muessig serves on boards of directors on four continents and has advised the Bill & Melinda Gates Foundation on technology. Over the course of her career she has helped more than one thousand companies to launch, grow, pivot, and thrive. She is a global keynote speaker on the future of work, gender-lens investing, and the redesign of venture capital instruments — including revenue share, royalties, and venture debt models that expand the range of companies that can access institutional capital. With Outlines Venture Group, the firm she co-founded with Anne Kennedy, she invested $4.8 million in early-stage internet companies over a decade and generated $475 million in portfolio revenue — with four exits. That capital efficiency ratio is precisely the kind of performance record that every serious allocator should be examining.
Investment
The Sovereign Architects: Women-Led Family Offices Shaping the AI Frontier
While venture funds often chase the latest hype cycle, these ten women-led family offices and private investment groups are deploying permanent, generational capital to build the bedrock of the AI era. These leaders prioritize long-term “Deep AI” infrastructure over short-term exits.
1. Emerson Collective (USA) – Laurene Powell Jobs
The single-family office and impact vehicle of the Powell Jobs family is a titan of “Spatial Intelligence.”
- Major Investment: World Labs (AI Spatial Intelligence)
- The Impact: Part of a $1 billion Series C (2024/2025); Emerson typically provides high-conviction checks to companies blending design with AI-driven 3D environments.
2. Olayan Financing Company (Saudi Arabia) – Lubna Olayan
Olayan manages the private wealth and industrial holdings of the Olayan family, focusing on the integration of AI into global supply chains.
- Major Investment: Ma’aden (AI-driven autonomous mining and industrial tech)
- The Impact: Strategic allocations often exceed $100M for technology that modernizes traditional heavy industry.
3. Exor N.V. (Netherlands/Italy) – Suzanne Heywood
As COO of the Agnelli family’s holding company, Heywood treats AI as a vertical necessity for luxury and industrial assets like Ferrari and Stellantis.
- Major Investment: Wayve (Embodied AI/Autonomous Driving)
- The Impact: Participated in a $1.05 billion Series C (2024). Exor’s tech-specific checks often range from $25M to $100M+.
4. Eyal Ofer Family/Global Holdings – Olivia Ofer
Leading the family’s tech strategy, Olivia Ofer focuses on maritime, logistics, and real estate AI.
- Major Investment: Captain’s Eye (Maritime AI/Safety)
- The Impact: Family office participation in niche deep-tech infrastructure usually ranges from $5M to $15M.
5. Al Gurg Group (UAE) – Muna Al Gurg
Muna Al Gurg leads the retail and tech arms of this conglomerate, prioritizing regional AI sovereignty in the Middle East.
- Major Investment: G42 Partnership (Regional AI Infrastructure)
- The Impact: As a strategic partner, Al Gurg Group participates in consortium-style investments often exceeding $50M.
6. Sofina (Belgium) – The Boël Family (Maité de Formanoir)
Operating as the primary vehicle for the Boël family’s generational wealth, Sofina is a major backer of European “Sovereign AI.”
- Major Investment: Mistral AI
- The Impact: Part of a €600M Series B (2024); Sofina’s high-conviction growth checks typically range from €20M to €50M.
7. EastOne Group (UK/Ukraine) – Elena Pinchuk
The family office of Victor and Elena Pinchuk focuses on dual-use technology, cybersecurity, and information integrity.
- Major Investment: Palantir Technologies (AI/Data Analytics)
- The Impact: While specific entry sizes are private, family office allocations into category-defining AI infrastructure typically start at $25M.
8. Toscafund (UK) – Savina Rizova
Directing strategic research for elite investment circles, Rizova has pioneered “Factor-Based AI” for complex market analysis.
- Major Investment: Plend (AI-driven Credit Scoring)
- The Impact: Toscafund frequently leads or anchors rounds with check sizes ranging from £10M to £40M.
9. Swiss Future Institute (Switzerland) – Katrin J. Yuan
Yuan manages portfolios for ultra-high-net-worth European families with a focus on AI governance and “Heritage Tech.”
- Major Investment: DeepL (Neural Machine Translation)
- The Impact: Private Swiss family office allocations in late-stage European AI giants like DeepL usually range from $10M to $30M.
10. RHL Ventures (Malaysia) – Rachel Lau
Backed by her family’s multi-generational wealth, Lau focuses on the burgeoning ASEAN AI ecosystem.
- Major Investment: Coffee Meets Bagel (AI Matching Algorithms)
- The Impact: Through private family capital and the Hibiscus Fund, check sizes typically range from $500k to $5M.
Venture Capital Firms Backing Female-Led AI
The following leading venture capital firms have invested in female-led AI companies across stages — from the record-setting rounds of 2025 to seed investments that will define the next five years. This represents the institutional capital infrastructure behind the AI leadership profiled in this report.
The Institutions Building the Next Generation
Every sustained wave of innovation is built on the institutions that train the people who carry it forward. The organisations below are not support structures. They are the talent pipeline of the AI century — and the future of the field runs directly through them.
Research and Technical Communities
Women in Machine Learning (WiML) is the technical home for practising ML researchers and data scientists. Its annual workshops at NeurIPS and ICML — the world’s premier AI research conferences — are among the most attended satellite events in the entire programme. The papers presented, the collaborations formed, and the career trajectories launched at WiML workshops have shaped a generation of AI researchers whose work now appears in the most-cited venues in the field. Black in AI, co-founded by Dr. Timnit Gebru, has achieved research visibility and conference presence at NeurIPS and ICLR that exceeds its institutional scale — demonstrating what happens when a community builds with rigour and refuses to be peripheral. Latinas in AI is building rapidly, with a research agenda focused on AI’s impact on Latin American and Latina communities — one of the largest and fastest-growing technology markets in the world.
Education and Pipeline
AI4ALL, co-founded by Fei-Fei Li and Melinda French Gates, operates across 16 university partnerships with a singular focus: reaching young people before university, at the secondary school level where the decisions that determine who becomes an AI scientist are actually made. The founders, researchers, and investors of 2040 are in school right now. AI4ALL is making sure the best of them encounter the field early enough to choose it. Girls Who Code operates at the same critical pipeline stage — K-12 education — and has reached over 670,000 students globally, building the largest computer science education community in the world.
Global Networks
Women in AI (WAI) is the largest global network in the field — over 19,000 members across 150 countries — with an increasingly prominent focus on AI governance and policy alongside its technical community. As AI becomes the subject of international regulatory frameworks, WAI’s ability to place informed voices in those conversations is becoming one of its most consequential functions. Women Leading in AI operates at the apex of that policy work: its community’s sustained engagement with the UN process directly shaped the Global Digital Compact signed in September 2024 — the agreement between all UN member states on the governance of digital technology. That is not influence at the margins. That is authorship of the global framework.
Enterprise and Leadership
Women in Cloud has built a global network of 150,000 women in technology across 1,200 organisations — a platform through which enterprise AI adoption, leadership development, and commercial partnership are happening at scale. AI-Powered Women (MIT) equips executives and institutional leaders with the skills and frameworks for responsible AI adoption across their organisations — translating frontier research into operational practice for the people making deployment decisions at the largest companies in the world.
Investment Access
How to Access This Ecosystem — Across Every Stage
The capital infrastructure for investing in female-led AI spans from individual accredited investors to sovereign wealth funds. The question is not whether the opportunity exists. It is which entry point aligns with your mandate.
Seed / Early Stage
- The Helm — early-stage VC for women founders across sectors
- BBG Ventures — invests in startups with at least one female founder; Fund IV active
- Backstage Capital — underrepresented founders; strong AI track record
- SoGal Ventures — global early-stage; diverse founding teams across US and Asia-Pacific
- Portfolia Funds — thematic (health, fintech, AI); open to accredited individuals
Growth Stage
- Rethink Impact — largest US VC investing in female leaders deploying technology for impact
- Acrew Capital (Theresia Gouw & Lauren Kolodny) — fintech, cybersecurity, enterprise AI
- Outlander VC (Leura Craig) — top-decile returns; 62% diverse founders
- Bond Capital (Mary Meeker) — late-stage, high-conviction technology bets
- Pear VC (Mar Hershenson) — seed to Series A; transformational technology companies
Institutional / Multi-Strategy
- Goldman Sachs Launch With GS — $1B strategy targeting diverse entrepreneurs
- Point72 Ventures (Tara Stokes) — AI-focused within a $30B+ multi-strategy platform
- Hypatia Capital — women-founded companies; proprietary returns thesis
- Level Equity (Sarah Sommer) — $4.5B AUM; software-focused growth equity
Education and Network Access
- Goldman Sachs 10,000 Women — global education, mentorship, and capital access
- Springboard Enterprises — accelerates growth-stage companies led by women
- WiML Fellowship Programme — research funding and access to NeurIPS, ICML, ICLR
- AI4ALL — 16 university partnerships; pipeline from secondary education onward
Reshaping the World. Solving What Matters. Generating Alpha.
This is the complete picture. The women profiled in this report are building the most important technology in human history — commanding its intellectual foundations, directing its capital, writing its governance architecture, and solving the problems that define civilisational progress. The returns these achievements generate are extraordinary. The scale of what they are building is without precedent.
On the problems they are solving: Fei-Fei Li gave machines the ability to see, and is now building the systems that will teach them to comprehend three-dimensional space. Daphne Koller is compressing the pharmaceutical pipeline from fifteen years to a fraction of that — with direct implications for millions of patients awaiting treatments that the old system moved too slowly to deliver. Kate Ryder is deploying AI across a healthcare gap the traditional system has never closed. Bessie Schwarz and Beth Tellman are repricing climate risk across sovereign debt and reinsurance markets. Gwynne Shotwell has made commercial spaceflight routine and is blanketing the planet in connectivity. Dr. Swati Mohan landed a rover on Mars. These are not incremental improvements. They are structural advances in what human civilisation can do.
On the alpha they are generating: Female-led companies produce a 2.5× revenue efficiency multiple versus the market average per dollar deployed — documented by BCG across thousands of companies and corroborated across independent datasets. Boards with meaningful female representation deliver an 18.9-percentage-point return premium over five years. Seven in ten of the top-quartile US venture capital funds of the past decade included female decision-maker— a finding that has sustained across market cycles and forms the analytical bedrock of Mastersfund’s investment thesis. The alpha is in the record: Anthropic at $183 billion. Scale AI at $74.1 billion. Thinking Machines Lab raising $2 billion at a $12 billion seed valuation before a product existed. These are not projections. They are realised, audited, historical outcomes.
On the world they are reshaping: Margrethe Vestager wrote the legal framework governing AI across every European jurisdiction — now the global reference standard. Dr. Ivana Bartoletti embedded AI accountability into the UN Global Digital Compact. Najwa Aaraj is producing the open-source language models that power the global AI internet. Dr. Jacqui Taylor is engineering the AI infrastructure of 90 nations. Kim Polese is building the collective intelligence platforms that will determine how institutions govern and decide in the age of AI. Dr. Tatia Codreanu is building the trust architecture that will determine how broadly AI is adopted with confidence rather than resistance. Yvonne Espinosa is carrying the research rigour of Xerox PARC — where the modern computing world was invented — into the applied frontier of AI in financial services. Dr. Lisa Su built the hardware the entire industry runs on. The world these leaders are constructing is more capable, more precisely governed, and more intelligently organised than the one they found.
“The New Titans of AI are not building at the margins of the field. They command its intellectual foundations, its most valuable companies, its governance architecture, and its most consequential research programmes — solving the problems that define the limits of human capability while generating returns that dwarf the market average.” — The New Titans of AI, April 2026
The story of artificial intelligence, told completely and accurately, has their names at the centre of it. Every chapter. Every frontier. Every breakthrough. Every return. These are the architects of the AI century — and the architecture they are building is the world we will all inhabit fur us to thrive and prosper.