March Is for Marching Women Into AI Governance
If AI is the new enterprise infrastructure, then Women’s Month is a governance meeting, not a greeting card.
AI Is the New Infrastructure — And Women Must Govern It
AI is fast becoming the operating system of the global economy, with AI and data‑center infrastructure spending already in the hundreds of billions and projected to reach into the trillions over the next few years. At the same time, women hold roughly 25–30% of AI‑related jobs, only about 18% of C‑suite roles in AI startups, and as few as 10–15% of top tech and AI leadership positions globally. Studies continue to find that many AI systems show measurable gender and intersectional bias in hiring, credit, healthcare, policing, and more.
So what we elevate in March is not just sentiment; it’s a proxy for what we’re willing to encode into the next decade of products, policies, and power structures. When our feeds overflow with inspiration while the models deciding our credit, careers, healthcare, and creative visibility are trained on incomplete, biased, or outdated data, celebration becomes a glossy distraction from structural neglect. Women were never meant to be the edge case in someone else’s model; we are the architects of the systems — and the AI governance frameworks — that will define the next decade.
Women currently represent roughly one in four AI professionals and only about 12–15% of women in AI reach executive or top technical roles. The technology redefining power is still being built, funded, and governed without women in most of the decisive seats. If AI is going to rewrite the future, we are here to reprogram the operating system.
Power, Not Praise
Every March, the world applauds women — and then ushers many of us back into rooms where we still earn less, own less, and hold fewer decision rights over the technologies running our lives.
In the U.S., women working full time, year‑round were paid about 81 cents for every dollar paid to men in 2024, and across all earners (including part‑time and seasonal workers) that drops to around 76 cents. For women of color, the gap is even more severe: in 2024, white non‑Hispanic women earned about 73 cents, Black women around 63 cents, and Latinas about 54 cents for every dollar paid to white non‑Hispanic men. Recent analysis shows the gap has widened, with full‑time women’s earnings slipping from roughly 83 cents on the dollar in 2023 to just under 81 cents in 2024.
In AI‑heavy organizations, women hold only about 26–30% of data and AI roles and roughly 10–15% of CEO or top technical and AI leadership positions. So the question for March is simple: Who is this month changing?
If you’re a woman, March is a reminder to treat your expertise like equity — an asset that sets terms, not just a story that earns applause.
If you control budgets, boards, product roadmaps, policy, or venture capital, March is your audit.
- Are you moving money?
- Are you moving seats?
- Are you redesigning systems?
If your Women’s Month strategy fits in a social media calendar but not in a capital allocation memo, that’s not allyship; it’s branding. International Women’s Day began in 1910 as a coordinated strategy for labor rights, political power, and legal equality, not a campaign theme.
From Performative Celebration to Real Power Shifts
The real test of March isn’t how many posts go live — it’s how many pay bands, promotion slates, board seats, and governance committees actually shift. If Women’s Month doesn’t show up in your budgets, product roadmaps, and AI governance charters, it’s ornamental, not structural.
The Contradiction We’re Living In
Organizations publish inclusion statements while AI systems increasingly decide who gets approved, promoted, flagged, or filtered. Women remain underrepresented in AI research, technical architecture, and governance, and are statistically less likely than men to be named as authors or inventors even when they contribute comparable work. Women now represent roughly 25–30% of AI‑related jobs, but only about 18% of C‑suite positions at AI startups and 10–15% of top tech roles in major AI‑driven organizations.
If women are not shaping the data, the tools, and the rules, the data and the tools will shape women. AI does not become equitable by intention; it becomes equitable through authority. Inclusion without governance is theater.
When AI Systems Decide Who Gets Seen, Funded, and Promoted
Today’s AI systems influence who passes a resume screen, who is flagged for risk, whose face is recognized correctly, and whose work is surfaced or buried. When women are missing from the rooms where these systems are designed, trained, and governed, bias doesn’t just persist — it scales.
Three Moves That Turn March Into Infrastructure
1. Put Women in Load‑Bearing AI Roles
Research shows that companies with more women in senior leadership often see stronger financial performance, better governance, and more risk‑aware decision‑making. Yet across AI‑heavy organizations, women hold only around 30% of overall leadership roles and about 10–15% of CEO and top technical roles, with women still a small minority of CTOs and chief AI officers worldwide. AI systems mirror their makers; when women are missing from product, data, research, and policy teams, blind spots scale with every deployment.
Load‑bearing roles mean women leading product, data, and AI governance with real veto power — not just holding HR, comms, or “culture” titles while others set the model’s rules. This looks like women chairing AI governance committees, owning critical AI P&Ls, and writing the technical and ethical standards that products must meet before they ship.
2. Fix Systems, Not Women
Studies on leadership and promotion show that when women receive equal sponsorship, stretch assignments, and clear promotion paths, the so‑called “ambition gap” largely disappears. What often gets labeled as disengagement is a rational response to systems that devalue caregiving, reward visibility over value, and gate power through informal networks.
As AI restructures workflows and metrics, there’s a documented risk that invisible labor — organizing, documentation, emotional support — is automated in name and reassigned to women in practice, while algorithms still credit others for the visible outputs. The constraint is system design, not women’s capability. Fixing systems means redesigning promotion criteria to account for impact, assigning explicit ownership and recognition for AI and “glue work,” and ensuring AI‑driven performance tools do not quietly penalize caregivers or those doing critical but less visible work.
3. Use March as a Decision Window
For leaders, March should trigger real decisions and deadlines, not just campaigns.
- What pay and promotion decisions are being finalized in the next 90 days?
- Who is setting and governing your AI strategy — and how many of them hold true veto power?
- What measurable shift will exist by next March that does not exist right now?
- And by next March, which women leaders in your organization will hold real authority over AI governance, not just AI adoption?
Gender and intersectional bias have been documented in AI across hiring, healthcare, finance, and justice — from skewed risk scores to misdiagnosis, misidentification, and discriminatory credit decisions. AI becomes an equalizer only when women are present and empowered at every stage: data, design, deployment, evaluation, and governance. By next March, if your organization cannot point to specific shifts in who is paid, promoted, funded, or governing AI, then Women’s Month was performative theater, not infrastructure.
What Empressa Is Building
At Empressa, we’re not waiting for legacy systems to catch up. We’re building parallel infrastructure where women’s wisdom is the engine, not an afterthought — because AI is always shaped by whose knowledge it is trained on and who gets rewarded when that knowledge scales.
Our Empress Community
Before women lead with AI, they need spaces where they can breathe, experiment, and be seen as leaders. At Empressa, we’ve intentionally built a multifaceted global community of women across functions, sectors, regions, and generations — from early‑career talent to C‑suite executives — who are learning and leading with AI together. There are intimate C‑suite rooms for strategic conversations, peer circles for early‑ and mid‑career women building confidence and skills side by side, and main‑room gatherings where everyone comes together to exchange ideas, test tools, and be visible in the same space.
This structure means women can connect at their current stage of career, build peer networks that boost advancement, and also mentor, collaborate with, and gain direct access to experts and senior leaders across other layers of the ecosystem. Research shows that psychological safety and strong peer networks are critical for women’s progression into leadership and for inclusive AI adoption; when women can question, test, and co‑design AI in trusted rooms, they are far more likely to shape how it is used rather than have it imposed on them. In our rooms, ambition is normalized, questions are welcome, and AI is treated as a strategic tool in women’s hands.
The Empressive Book of Women
For generations, women’s expertise has powered institutions without being fully credited, archived, or compensated — a pattern documented across STEM, tech, and creative industries. In an AI era, that invisible work doesn’t just disappear; it risks becoming anonymous training data for someone else’s model.
At Empressa, our experts are not the ghostwriters of someone else’s algorithm. Our bias‑aware GPT is trained on attributed insights from real women — founders, operators, executives, creatives, and community builders — whose wisdom powers the platform and is preserved with attribution and a royalty model that pays them when their expertise is used. Their contributions become the source of guidance for women using the platform, and their names remain attached to their ideas as the system scales.
This March, we’re turning what we built internally into something the world can see. The Empressive Book of Women is a thoughtfully curated “little golden book” of Empressa AI’s women leaders — spotlighting each woman’s brand, services, stats, and how to reach her as a trusted expert shaping the age of AI across sectors, generations, and geographies. Your expertise doesn’t vanish into the model; it sits on our digital shelf as equity.
Empressa AI25
Across history, women have written code, discovered particles, mapped galaxies, and built institutions — only to watch their names vanish from the record or appear as a footnote under someone else’s. This “Matilda Effect” is not a metaphor; studies show women in research teams are significantly less likely than men to be credited as authors or inventors, even when doing the same work.
In AI, women account for only about 30% of professionals, roughly 18% of C‑suite roles in AI startups, and as few as 12% of AI research positions globally. The risk is clear: women are helping build the systems shaping our future, but their contributions can still be diluted or erased.
Empressa AI25 is our annual editorial canon recognizing 25 women whose decisions, systems, policies, and capital allocation choices are materially shaping the present and future of artificial intelligence — founders, regulators, operators, and capital allocators across sectors and regions. We’re introducing Empressa AI25 this March so history does not repeat itself — and instead, HERstory is written into the future of AI in real time, with women’s names, leadership, and impact etched into the record rather than erased from the credits.
Nominate yourself (or a peer) by March 13
AI Foundations for Women
AI Foundations for Women is where women learn to build with AI, not just consume it. Powered by Empressa’s royalty‑based, women‑trained GPT — where lived expertise becomes paid, attributed intelligence — the program equips women with skills, confidence, and ethical grounding to shape AI from the inside out. Inside Empressa Playground, a bias‑aware AI lab designed for experimentation and psychological safety, our inaugural experience in November 2025 brought together 166 women across 33 global cohorts, supported by 57 expert facilitators selected from more than 250 applicants, with scholarships offered to women worldwide. The program ran again in January with function‑specific and Spanish‑language cohorts and will run once more to the broader public on March 27 before it becomes part of our Enterprise Solutions portfolio.
These experiences are seeding a pipeline of women who are already using AI to ship new products, policies, strategies, and playbooks inside their institutions — not just reacting to someone else’s roadmap.
Learn more and register for our final event here
Writing Women Into the Code
Across Women’s Month, Empressa is modeling what it looks like when women shape AI — and the systems around it — end to end:
- Through community that normalizes ambition.
- Through preserved expertise that is credited, compensated, and showcased.
- Through an evolving canon that documents women’s leadership in AI.
- Through capability‑building that equips women to govern, not just use, emerging tools.
Women’s Month was never meant to be decorative. It was designed to rebalance power. AI is the infrastructure of the next decade — economically, politically, culturally. If you are redesigning the future with AI and women are not central to the blueprint, you are leaving value, resilience, and possibility on the table.
We are not asking to be included in the AI era.
We are building it.
This March, let’s not just celebrate women, let’s MARCH women — into budgets, into seats, into systems, into AI governance — and together build an equitable future worth celebrating.
#AINeedsWomen
FAQ: Women, AI Governance, and Empressa
Q1: What is AI governance and why does it matter for women?
AI governance is the set of people, policies, and processes that decide how AI systems are designed, trained, deployed, and monitored. When women are underrepresented in AI governance, the systems that shape hiring, credit, healthcare, safety, and visibility are more likely to reflect existing gender and intersectional bias instead of correcting it.
Q2: How underrepresented are women in AI and tech leadership today?
Women currently make up roughly one in four AI professionals and hold an even smaller share of C‑suite and top technical roles in AI‑driven organizations. In many companies, women are almost absent from the most powerful seats in AI strategy, architecture, and governance, which limits whose perspectives are encoded into the next generation of tools and policies.
Q3: Why isn’t a Women’s Month campaign enough on its own?
Women’s Month posts and events can raise awareness, but they do not change power unless they are tied to decisions about budgets, pay, promotion, hiring, and governance. If Women’s Month activity lives only in marketing calendars and not in capital allocation, org design, or AI oversight, it functions as branding rather than structural change.
Q4: What are “load‑bearing” roles for women in AI?
Load‑bearing roles are positions where women’s decisions materially shape how AI is used. Examples include chairs of AI governance or risk committees, leaders who own AI product P&Ls, and executives who can delay or block deployment until ethical and technical standards are met. When women are in these roles, their judgment directly influences how AI impacts employees, customers, and communities.
Q5: What does it mean to “fix systems, not women” in the context of AI?
“Fix systems, not women” means recognizing that gaps in representation and outcomes are driven by structures, not a lack of ambition or skill. In AI‑rich environments, organizations need to redesign promotion criteria, recognize invisible and AI‑related “glue work,” and audit AI‑driven performance and hiring tools for hidden penalties that disproportionately affect women and caregivers.
Q6: How is Empressa helping women shape AI governance?
Empressa builds parallel infrastructure where women’s expertise is the engine of the AI system, not an afterthought. Through the Empress Community, AI Foundations for Women, the Empressive Book of Women, and Empressa AI25, women gain community, capability, visibility, and real economic participation in how AI is designed, taught, and governed.
Q7: What is AI Foundations for Women?
AI Foundations for Women is a cohort‑based program where women learn to build with AI instead of just consuming it. Inside Empressa Playground, a bias‑aware AI lab, women experiment with tools, apply AI to real work, and develop the skills and confidence to influence AI decisions and governance inside their organizations.
Q8: How can leaders turn Women’s Month into lasting AI infrastructure?
Leaders can use March as a decision window: commit to moving money, seats, and systems, not just messaging. That means setting specific targets for women in AI governance roles, revising policies and incentives, funding women‑led AI initiatives, and being able to point to concrete shifts in pay, promotion, and AI oversight by next March.
Sources & Further Reading
- Federal Reserve; AlixPartners; Energy & infrastructure analyses on AI and data‑center spending
- SheAI 2026 report; LinkedIn “Statistics on AI risks for women and girls”
- World Economic Forum, Global Gender Gap and AI workforce/leadership data
- Russell Reynolds, “The Case for More Women Leaders in AI”
- UN Women; UNDP; AI fairness and gender bias research
- AAUW; U.S. Census Bureau; USAFacts – U.S. gender pay gap data
- National Partnership for Women & Families – wage gaps for women of color
- “Women are credited less in science than men” – PNAS
- “Invisible Women: Data Bias in a World Designed for Men” – Caroline Criado Perez
- Matilda Effect literature; National Geographic on overlooked women scientists
- McKinsey / Lean In women in leadership data and summaries
- People Management – psychological safety in the age of AI
- Indiana University – research on AI, household work, and gendered labor
- World Economic Forum – “How an AI-Driven Future Can Include More Women in Leadership”
- Forbes – “AI Development Needs More Women” and related women-in-leadership impact pieces
- UN Women – history and purpose of International Women’s Day
- Empressa, Women in AI Quarterly Index: The Rise of the Digital Riveter