Artificial intelligence is rapidly reshaping the workplace. Employees are using AI to streamline administrative tasks, generate ideas, analyze information, and accelerate work that previously required far more time and effort. As organizations continue to integrate these tools into daily operations, a growing body of research suggests that women may be approaching AI differently than men, raising important questions about what causes this gap and how it may impact future leadership and advancement in the workplace.
A recent Lean In study found that men are more likely than women to regularly report on the use of AI in the workplace. The study also found that women are less encouraged to use AI by their managers and are less well-received when they do. While much of the debate surrounding these findings focuses on access, training, and representation, another important factor is worth noting. It’s confidence. More specifically, the lessons many high-achieving women have learned to build and protect trust throughout their careers may be shaping the way they approach AI in the workplace today.
confidence and reliability
In my work as a leadership coach, I have often seen women hesitate in situations where there is no clear roadmap, established expertise, and virtually no guarantee that things will work out right away. Many women have spent years building a professional identity based on preparation, reliability, and thoughtful execution. They succeeded because they learned how to minimize mistakes, anticipate challenges, and demonstrate competency before moving forward. These strategies often worked well in traditional work environments, where expertise and precision were closely tied to credibility and promotion.
AI changes these dynamics in important ways. The people who are the first to take advantage of AI tools are often not the ones with the most technical expertise or understanding of the technology itself. They are often the people most willing to experiment, test incomplete ideas, and learn through trial and error. AI rewards curiosity, repetition, and adaptability in ways that may feel unfamiliar and uncomfortable for women, who have traditionally been valued for sophistication and certainty.
This distinction is important because hesitancy toward AI can be interpreted as resistance to change or lack of interest in the technology. In reality, this problem can be much more subtle. A recent 2026 academic study examining gender differences in generative AI adoption found that women’s lower adoption rates were less related to technical ability and more to broader concerns about the ethical, social, and workplace implications of AI, including privacy, labor disruption, and abuse. These findings suggest that attention to AI may reflect thoughtful evaluation rather than a lack of readiness or ability.
The role of workplace culture
Workplace culture also plays a big role. To begin with, culture influences who is comfortable working with new technology. Employees are more likely to experiment if they believe the learning process itself will be supported rather than valued. Research published earlier this year found that psychological safety plays a key role in AI adoption, with employees who feel safer taking interpersonal risks more willing to engage with AI tools. Experimentation becomes even more difficult in workplaces where employees fear appearing uninformed, making mistakes, or undermining credibility.
This is especially important for women, who may already feel pressure to continually prove themselves in environments where they are still underrepresented in leadership and technical roles. AI can create a particularly risky level of ambiguity if there is an expectation that people understand before they speak. Many AI tools still produce inconsistent results, need refinement, and require continuous learning. Using them effectively often means asking questions publicly, trying approaches that may not work, and working around uncertainty in real time.
the price of hesitation
As organizations increasingly value AI fluency, these dynamics can have far-reaching implications for leadership visibility and advancement. Employees who engage early with emerging technologies often have the opportunity to shape workflows, influence strategy, and establish themselves as innovative contributors. Over time, small differences in your willingness to experiment can add up to big differences in your exposure, confidence, and career momentum. The Financial Times research has already highlighted concerns that patterns of AI adoption could reinforce existing inequalities in the workplace if access, encouragement and visibility remain uneven.
Leaders have a critical role to play in shaping how employees experience this transition. While organizations often approach AI adoption primarily as a technical training issue, the challenge also has deep cultural and behavioral dimensions. Employees need more than just access to tools. They need an environment where learning is normalized, experimentation is encouraged, and uncertainty is treated as part of the process rather than evidence of incompetence.
Because of this, leaders may need to rethink how confidence is defined and rewarded within their organizations. Historically, trust in the workplace has often been associated with certainty, decisiveness, and expertise. Confidence in the AI era may increasingly depend on adaptability, openness, and a proactive attitude before feeling fully prepared. The professionals most likely to succeed may not be those who always have the right answer right away, but those who remain proactive as they learn, adjust, and evolve with rapidly changing technology.
Conversations about women and AI often focus on whether women are falling behind. A more productive question may be: What work environments allow people to participate confidently enough in moments of great change and uncertainty? AI is transforming the way we work, but it’s also revealing deeper truths about workplace culture, psychological safety, and how professionals learn to avoid risk throughout their careers.
This article originally appeared on Forbes.com
