I want to talk about something real for a minute.
When I started in cybersecurity — 19 years ago, fresh out of a world where being a woman in Special Forces Cyber meant you had to be twice as prepared, twice as precise, and ready to prove yourself in rooms that weren't built with you in mind — nobody handed me a roadmap. There was no "Women in AI Cybersecurity" blog post waiting for me. There was just the mission, and the question of whether I was going to get it done or not.
I got it done. And I kept getting it done — through 10+ years of Army Special Forces Cyber Electronic Warfare, through building Outpost Gray from scratch, through speaking at RSA in front of thousands, through launching this entire AI education brand. Not because the industry made it easy. Because I figured out how to move through spaces that weren't designed for me and build something worth having on the other side.
This post is for every woman who's standing at the edge of cybersecurity or AI and wondering: Is there a place for me here? How do I get in? How do I stay in? And how do I build something that's actually mine?
Here's what I know.
Let's not sugarcoat it. Women make up roughly 24% of the cybersecurity workforce globally. In AI research and engineering, the numbers are even more stark — somewhere around 22% by most estimates. Leadership positions? Worse. These aren't numbers I'm happy about. They're numbers I think about constantly.
At the same time, I've watched the conversation shift in the last five years in ways that actually matter. Not just "diversity initiative" noise — actual change in who's getting hired, who's getting promoted, and who's getting funded. It's happening unevenly and not fast enough, but it's happening.
More importantly: I've watched individual women with the right skills and the right strategy build extraordinary careers in this space regardless of what the aggregate numbers look like. The industry is imperfect. Your career doesn't have to be.
I get asked this constantly, and I want to give you the answer I wish I'd had earlier rather than the generic "get certified and network" advice you've already heard.
The biggest mistake I see women make in tech careers — and I've made this mistake myself — is spending enormous energy on credentials and preparation before putting work out in the world. Certifications matter. Degrees matter. But what gets you the job, the contract, the speaking slot, the opportunity is visible proof of what you can do.
Build a GitHub repository. Write a Medium post about something you figured out. Set up a personal lab. Document your projects. The people who move fastest in this industry aren't the most credentialed — they're the most visible about the work they're doing.
Cybersecurity is enormous. AI is enormous. "I want to work in cybersecurity" or "I'm interested in AI" is not a career plan — it's a starting point. The women I know who built real careers in this space found a specific intersection and went deep. Cloud security. AI red-teaming. Threat intelligence for critical infrastructure. AI-powered fraud detection in financial services. Pick something that genuinely interests you and become the most credible person in that corner.
Niches have less competition than broad categories. And in a field that's growing as fast as AI+cyber, being the specialist is almost always more valuable than being a generalist.
I've been in rooms where I was the only woman. I've been in briefings where someone assumed I was the administrative support. I've had my technical contributions talked over and then repeated back by someone else five minutes later as if they originated them. Every woman in tech has a version of this story.
Here's what I've learned: the energy you spend shrinking yourself to make others comfortable is energy you don't have for the work. Stop spending it. Be precise. Be confident. Repeat yourself if you have to. The people who can't handle that aren't your people — and your time is too valuable to spend performing smallness for them.
"The energy you spend shrinking yourself to make others comfortable is energy you don't have for the work. Stop spending it."
Breaking in is one challenge. Staying in — and advancing — is a different one. I've watched brilliant women leave cybersecurity not because they couldn't do the work, but because the culture made the cost of doing the work too high.
Sustainable career growth in this space requires three things that nobody tells you upfront:
This is the part that genuinely excites me about 2026, and why I built an entire brand around AI education for professionals.
AI tools — specifically AI agents — are creating a capability equalizer that didn't exist five years ago. Here's what I mean by that.
In every organization I've worked in, informal power came partly from access: access to information, access to senior leaders, access to resources that let you move faster and do more. That access wasn't evenly distributed — it followed existing networks, which in tech and security skewed heavily toward men who'd been in the industry longer.
An AI agent doesn't care about those dynamics. It gives you research capabilities that used to require a team. It helps you produce at a volume and quality that used to require years of institutional support. It handles administrative overhead that used to eat your time while colleagues with more support got to focus on high-visibility work. It levels the output gap that informal inequality creates.
I'm not naive enough to think AI tools solve structural problems. They don't. But they do give individual women a lever they didn't have before. And I've seen it work in practice — women in my community who used to feel perpetually behind, drowning in operational tasks, who learned to use AI agents and suddenly had capacity to do strategic work, write, speak, build. That's real.
I put together a complete free guide to getting your first AI agent up and running — built specifically for professionals who aren't engineers but want the same capabilities. No coding required.
The title of this post includes "building your own path" — and I want to end there, because it's the thing I feel most strongly about.
The traditional model of career advancement in cybersecurity and AI was built by people who aren't you, optimized for people who aren't you, and evaluated by criteria that often undervalue what you bring. You can work within that model — and sometimes you have to — but don't mistake it for the only model.
Some of the most impressive women I know in this space built their credibility outside traditional institutions. They started podcasts. They built consulting practices. They published research independently. They grew communities. They spoke at conferences before they had permission to. They created the visibility first and let the opportunities follow.
I did that. It worked. Not immediately — nothing in this industry works immediately — but it compounded. The audience I built, the reputation I built, the relationships I built outside formal institutional channels became more valuable than anything I had inside them.
You don't have to wait for someone to give you a platform. Build one. You don't have to wait for a company to recognize your expertise. Document it publicly. You don't have to wait for the industry to become what it should be before you start having the career you want. Start now, with the tools you have, and iterate.
AI tools are part of that toolkit now. Use them. The leverage is real and it's available to everyone — but the people who move first get the most out of it.
That's why I'm here. That's why Zara exists. That's why I spent 19 years in this industry and I'm not done yet.
If you're a woman standing at the edge of this space wondering if there's room for you — there is. Make the room if you have to. And reach out. I built this community for exactly this reason.
The Fire Your To-Do List course is for professionals — especially women building careers in cyber and AI — who want to use AI agents to operate at a level that used to require a full team. Built from real-world experience, not theory.
One-time investment · No subscription · Built by someone doing the work