The Hidden Gender Rules of AI Agents

Six years ago, I was nervously awaiting my turn to give a TEDx Talk and listening to my friend Emily Liu talk about a topic that’s stuck with me ever since. 

Emily’s talk was centered on the feminization phenomenon of voice assistants and how the tech giants all chose female traits, names, and/or personalities. Whether it was Apple with Siri, Amazon with Alexa, or Microsoft with Cortana, they were all feminized, designed to tell you the weather, play your music, and turn on your lights. Even Google Assistant didn’t have a female name in 2019, but it of course had a female voice. Emily’s argument was that these naming choices reflected something we'd internalized without questioning: support is a female task.

At the time, it felt like a sharp observation about consumer tech but I didn’t think about the talk much up until a few weeks ago. During one of my deep work “sourcing” days at my firm, I was scrolling through deck after deck looking for companies I was deeply excited about when I had a realization.

The new generation of AI agents isn’t just smart, it’s quietly becoming male. I review hundreds of early-stage AI pitches every quarter, and once I noticed it, I couldn’t unsee it. 

The data from these calls backs this up. Across the most recent 200 decks we reviewed, among the teams who gave their AI agent a human name, 70% chose male names, 20% female, and 10% neutral. You can see it in the products themselves: Harvey, your legal advisor. Claude, your conversationalist. Devin, your engineering co-pilot. Jasper, your content creator. These are real products with real traction, and they're all coded male.

Not every AI gets a human name: ChatGPT and Gemini are notable exceptions. But the founders I see who are building agents are largely choosing to personify them, and when they do, the pattern emerges. 

The agents doing specialized knowledge work tend to get male names. Richard will help you with all things fundraising. Michael is your investment analyst on standby. Henry is your commercial real estate analyst, generating underwriting memos and deal decks on command. Meanwhile, the products built for invisible labor like scheduling, coordination, wellness, personal support, etc still overwhelmingly get female names. There’s Siena or Sierra who will handle your customer support inquiries. Phia who will shop for you. Clara will schedule meetings for you.

Once you see the pattern, it’s impossible to unsee.  And it raises a question: What changed? This isn’t about political correctness, it’s about the subconscious choices shaping how we interact with intelligence.

📈 The Shift From Retrieval to Reasoning

The gender flip tracks two shifts happening at once: the products are getting smarter and the business model for selling them is shifting toward enterprise. 

The early voice assistants like Siri, Alexa, and Cortana were retrieval engines. They could pull up information, set timers, play songs. They had narrow, well-defined tasks and predictable boundaries. They were helpers, not thinkers.

Today's AI agents are doing something different. They synthesize information, generate code, draft legal arguments, make strategic recommendations. They're capable of reasoning, analyzing, and mimicking expertise. They're positioned as professionals who do knowledge work, not just assistants who complete simple tasks.

This shift in capability has coincided with a shift in market. AI helpers went from products living on your phone to enterprise software priced in the thousands or tens of thousands, sold to businesses and positioned as specialized technologies that CFOs will approve and CTOs will trust. Naming isn’t just branding, it’s a growth strategy. These choices aren’t aesthetic; they’re conversion tactics built to accelerate trust and adoption.

Somewhere along the way, we started marketing enterprise-grade intelligence as male. 

We talk a lot about bias in AI models, but almost no one talks about bias in AI go-to-market. In a world where most engineers, most lawyers, and most C-suite buyers are still men, naming your AI agent "Devin" instead of "Diana" might genuinely feel like the safer bet. It might even be the safer bet. Product names are the type of things founders A/B test. Whether it's data or assumptions guiding people toward masculine agent names isn't clear. But the pattern is undeniable.

🔤 Naming Intelligence

When we name our products after people, we project our beliefs about people onto them.

Naming a SaaS product never carried that weight. Salesforce, Slack, Asana, these are just words. They don't imply gender, personality, or identity. But AI agents are conversational. They have voices, literal and metaphorical. They're designed to feel like collaborators, not just tools.

So when you name an AI agent, you're not just picking a label. You're creating a persona, and that persona shapes how people perceive competence and authority.

Right now, for enterprise AI agents, expertise apparently sounds male. For support and wellness AI, it sounds female. And while many factors might go into those choices, they're not neutral. These naming patterns risk encoding decades of occupational gender stereotypes into the software layer that will increasingly mediate how we work.

⚖️ No Easy Answers

I don't have a manifesto here or a call to action to change what’s happening. But it’s worth considering the defaults we’re setting because defaults become culture faster than we think. How can we encourage founders to choose the right name, not just any name?

Maybe the real question isn’t why AI agents are male. Maybe it’s what future we’re normalizing when we name them this way. The products we’re building right now will define how intelligence sounds, who it serves, and what we believe about it. If we’re building the future, we should be brave enough to question what we’re building and the ramifications it may have.

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