When I was offered the CEO role at Smart Communications, a digital customer experience company, my instinct was to say no. I thought I wasn’t qualified, lacking depth of experience in product or engineering. I believed a CEO needed a background in every department, and by that standard, I didn’t measure up.
Thankfully, the people I trusted convinced me otherwise. They helped me see that the perspective I brought – having spent my career in marketing and strategy, obsessed with how customers experience a product rather than how it gets built – was my strength, not a gap.
I’ve thought about that moment many times since. But never more than when I started looking closely at how women experience AI.
What the data told me about my own career
Every year, my company surveys thousands of consumers across healthcare, financial services, and insurance about their experiences and expectations. Over the past two years, I’ve noticed a recurring trend in how women respond to questions about AI.
Women aren’t less interested in AI than men. But they are more cautious about its risks. Across every industry and geography we surveyed, women expressed higher levels of concern about AI than men and lower levels of confidence in AI-powered tools. The gap was widest in healthcare and financial services, exactly the sectors moving fastest to deploy AI in consequential customer interactions.
The standard read on data like this is that it represents a problem to solve. Women need more education, more reassurance, and better onboarding. Close the confidence gap, and adoption will follow.
But, as a female CEO, I read it differently. Women’s caution about AI is not a gap in understanding. It is a considered response to real questions about accountability, transparency, and what happens to the person on the receiving end when something goes wrong. The same questions that I have spent my entire career learning to ask.
The question nobody is asking
The industries we support are making consequential decisions about how AI will interact with their customers. How much of the claims process gets automated, how a benefits change gets communicated, and how a financial decision that affects someone’s family gets delivered. These interactions carry real emotional and financial weight. And the people shaping those decisions are, more often than not, optimizing for speed and cost.
The question of how it lands for the person on the receiving end gets less airtime. So does the question of who is accountable when it goes wrong. Women who have spent careers being told that their instinct toward empathy and relational thinking is a liability rather than a skill are exactly the people equipped to ask these questions. But those women are rarely in the rooms where AI strategy gets made. According to the World Economic Forum, women hold just 15% of executive AI roles worldwide. This is a significant strategic blind spot, not just a pipeline gap.
This isn’t about innate differences
I am not arguing about the innate differences between men and women. I’m making an argument about what happens to your perspective when you spend years navigating a culture that treats relational thinking as soft. You get very good at holding two things at once: the business requirement and the human one. You learn to ask not just whether something is efficient but whether it’s right. You also develop an instinct for the gap between how a decision looks on a slide and how it feels to the person it affects.
That instinct is the foundation of every AI strategy.
Trust is the obstacle nobody is measuring
Consumers are genuinely open to AI playing a bigger role in their lives. But trust is the consistent obstacle. People want to know that someone is accountable for the decisions being made about them. They want to feel known, not processed.
We’ve gotten good at measuring what AI saves. Time, cost, headcount. We’re less good at measuring what it costs when a communication lands wrong, when a customer feels like a case number, and when trust erodes quietly across dozens of small interactions. Those costs are real. They show up in churn, in complaints, and in regulatory scrutiny. They’re just harder to put in a slide. And they’re exactly what you miss when the people designing your AI strategy aren’t oriented toward the human on the receiving end of it.
The two problems are connected
I accepted the CEO role because people I trusted told me my skills and experience were enough. That the perspective I’d been quietly undervaluing was exactly what the role required.
I recognize that I am fortunate. Too many women lack someone in their corner making that case. And in most organizations, that’s not a personal failing. It’s a structural one. Companies are investing heavily in AI tools while underinvesting in the talent mix needed to deploy them well. Women are being brought in to manage AI outputs, but rarely to shape the strategy behind them. That’s a career pipeline problem as much as it is a business one. And most AI strategies don’t have someone in the room asking the questions that need to be asked.
Those two problems are connected. The same instinct that makes women more cautious consumers of AI is the instinct that makes them valuable architects of it. And solving the second problem starts with recognizing that the first one isn’t a problem at all.
