> ## Content Index > Fetch the complete content index at: https://www.leadingwithempathy.blog/llms.txt > Use this file to discover other available public pages before exploring further. # Access Is Not Enough: Women in Tech and the AI Opportunity Gap - URL: https://www.leadingwithempathy.blog/access-is-not-enough-women-in-tech-and-the-ai-opportunity-gap/ - Published: 2026-09-29T06:30:33.000Z - Updated: 2026-09-29T06:30:32.000Z - Description: Giving everyone the same AI tool may look like equal opportunity. But access means far less without encouragement, mentorship, and the chance to do work that will be seen. - Author: Megan Tipps - Tags: Women in Tech, Artificial Intelligence, AI at Work, Engineering Leadership, Mentorship, Sponsorship, Career Development, Inclusive Leadership, Imposter Syndrome, Workplace Equity, Technology Leadership It is easy to describe access as progress. Give everyone the same AI tool. Add the link to the team channel. Arrange a demonstration. Perhaps provide a short course. Then step back and trust that opportunity has been distributed evenly. On paper, everyone has access. In practice, some people will be encouraged to experiment. They will be invited into the interesting conversations, given room to try things, and reassured that getting it wrong is part of learning. Their early attempts will be noticed. Someone will mention their name when an AI-related project needs an owner. Others will receive the login details and be left to their own devices. I have often been one of the people left to figure things out. Fortunately, I enjoy it. Give me an unfamiliar tool and a problem worth solving, and I will happily disappear down the rabbit hole until I understand how the pieces fit together. Being left alone can feel like a challenge, and sometimes I like the challenge. But enjoying the puzzle does not make the absence of support irrelevant. There is a difference between being trusted to explore and being overlooked. From the outside, the two can look remarkably similar. Both involve independence. Both may end with someone teaching themselves something new. Only one comes with the quiet knowledge that somebody is paying attention to where that learning could lead. That difference matters as AI becomes part of more jobs and more decisions about people’s futures. We talk about access as though the tool itself creates an equal starting line. It does not. People arrive with different levels of confidence, time, organisational influence, and support. Some are already accustomed to being encouraged towards new opportunities. Others have learnt to wait until they are completely certain before putting up a hand. This is particularly complicated for women in technology. I do not want to turn this into a simple story about men against women. Most workplace dynamics are more tangled than that, and lack of encouragement is not something only women experience. I have seen people of different backgrounds sink further into self-doubt while more confident or better-supported colleagues move ahead. Still, technology remains a male-dominated field, and informal support often follows familiar relationships. Men may encourage, recommend, and advocate for other men without making a conscious decision to exclude anyone. They recognise potential in somebody who reminds them of themselves. They share an opportunity in a casual conversation. They give someone a nudge towards a promotion before that person feels entirely ready. None of those moments looks dramatic. Together, they shape careers. Women do not lack ambition, technical ability, curiosity, or the willingness to experiment. We have all of those things. What we do not always receive is the same steady reinforcement that tells a person their ability has been seen and that somebody expects it to grow. The latest [Women in the Workplace report from McKinsey and LeanIn.Org](https://www.mckinsey.com/capabilities/people-and-organization/our-insights/women-in-the-workplace?ref=leadingwithempathy.blog) gives this concern an uncomfortable shape. Among entry-level employees, only 21 percent of women said their managers encouraged them to use AI tools, compared with 33 percent of men. Employees who received that encouragement were more than 50 percent more likely to use the tools. That finding stayed with me because the difference is not access. It is encouragement. A manager does not need to possess every answer to provide it. Encouragement can be as simple as saying, “I think you would be good at this.” It can look like making time for someone to learn during the working day, checking in while they experiment, or giving them a real problem on which to build their confidence. It can mean pairing them with someone who has more experience instead of quietly assuming they will ask for help if they need it. Mentorship adds something equally important: somewhere safe to bring unfinished thinking. AI arrives wrapped in so much confidence and noise that admitting uncertainty can feel like admitting that you are already behind. A mentor can make room for the questions people are reluctant to ask publicly. They can help someone distinguish between a genuine skills gap and the ordinary discomfort of learning something new. Without that support, people who already feel confident tend to move fastest. They experiment visibly, talk about what they are building, and become associated with the new technology. Their confidence attracts more opportunity, and each opportunity gives them more reason to feel confident. Soon, they are not only using the tools. They are leading projects, shaping decisions, and receiving recognition for being ahead of the curve. Meanwhile, someone equally capable may still be experimenting quietly, unsure whether their work is ready to be seen. If nobody asks what they are learning or invites them into a meaningful project, imposter syndrome has plenty of space to fill in the silence. The gap widens without anyone having deliberately designed it. This is how an AI opportunity gap can grow inside a company that believes it has given everyone the same chance. The answer is not to assume that women need rescuing or special permission to be technical. That would replace one limiting belief with another. Nor is the answer to push every person towards AI with the same enthusiasm, regardless of their role or interests. Fair opportunity should not become compulsory excitement. The work is more attentive than that. Leaders need to notice who is receiving encouragement, who is being trusted with visible work, and whose experiments are recognised as potential. They need to look beyond the people who are already comfortable announcing what they can do. They need to offer guidance without taking away autonomy and mentorship without suggesting that capability was missing in the first place. They also need to remember that access is a beginning, not an outcome. A licence can open a tool. It cannot create confidence. A training session can introduce a feature. It cannot make someone feel that their contribution is wanted. An open invitation can technically include everyone while still favouring the people who already feel entitled to walk through the door. The hopeful part is that encouragement is not a scarce resource. A leader can change the direction of someone’s career with a conversation, a stretch opportunity, an introduction, or a little well-placed confidence. Teams can make experimentation safer. Organisations can pair access with mentoring, protected learning time, and fair pathways into visible work. Colleagues can become more deliberate about whose names they mention when opportunities appear. AI may change the work itself, but people will still shape who gets to grow through it. If we want this technology to widen opportunity rather than repeat old patterns, we have to pay attention to what happens after access is granted. Not because women lack anything, but because talent should not have to thrive in spite of being overlooked. Sometimes the door is already open. What changes a future is hearing someone say, sincerely, “I can see you doing something with this.” --- ## Building great software starts with how we lead people. I write about engineering leadership, team culture, AI, psychological safety, and the lessons I've learned from nearly two decades of building software and leading teams. Join Email sent! Check your inbox to complete your signup. New essays in your inbox. No spam. Unsubscribe anytime.