Women in STEM are navigating a deeply unfair reality. The same AI tools that earn male colleagues praise and promotions are quietly working against women who use them. Research confirms what many have already felt: women get penalised for using AI, while men get rewarded for doing the exact same thing.
In Episode 043 of the Lunch with Leaders podcast, Adaeze Iloeje-Udeogalanya names this double standard directly, backs it with hard data, and gives women in STEM a clear, actionable strategy for pushing through it. This episode is not about waiting for the bias to disappear. It is about learning to navigate it without shrinking back.
Listen to Episode 043: Breaking the AI Double Standard for Women in STEM
The Reality Nobody Is Talking About Loudly Enough
Adaeze opens the episode with a personal story that will feel uncomfortably familiar to many women in STEM. She built an exceptional tool at work, something genuinely high-impact and innovative. Her manager completely ignored it. Shortly afterward, a male colleague presented a basic, low-impact tool and received significant praise from the same manager.
That experience is not an isolated incident. It reflects a documented, measurable pattern. A study cited in the episode reveals that female engineers receive ratings 9% lower in perceived competence when they use AI to produce work, even when that work is identical to work produced by male peers using the same tools. Furthermore, only 21% of entry-level women receive encouragement from their managers to use AI, compared to 33% of men.
These numbers reveal two things clearly. First, the double standard is real and quantifiable. Second, most women are navigating this without organisational support, which means the responsibility for managing it falls on the individual, not the institution.
Why This Happens and Why It Is Not About You
Understanding the root cause of the double standard matters before addressing the strategy for overcoming it. Adaeze is precise on this point: the penalty women face for using AI has nothing to do with their actual competence, the quality of their work, or the sophistication of their AI use.
Instead, it stems from unconscious bias embedded deeply in how performance gets evaluated in STEM environments. Performance evaluation systems were largely built around assumptions that do not centre women, and certainly do not centre women of colour. Those assumptions shape what gets noticed, what gets credited, and who gets the benefit of the doubt when new tools or methods are introduced.
Consequently, a man who uses AI signals innovation and forward thinking. A woman who uses the same tool in the same way risks being perceived as cutting corners or relying on assistance she would not otherwise need. The work is identical. The perception is not. That gap is bias — not personal failure.
Recognising this distinction is essential because it shifts the framing entirely. The problem does not require women to work harder, perform better, or use AI more carefully. It requires women to control the narrative around how their AI use gets perceived and credited.
Hear Adaeze break down the research and the strategy: Listen to Episode 043 of Lunch with Leaders
How to Break Through the Double Standard: Four Strategic Steps
Rather than waiting for organisations to address their own bias, Adaeze gives women four concrete strategies to navigate the double standard actively and position themselves as forward-thinking AI leaders.
1. Use AI Intentionally and Track the Metrics
Random AI use produces random results. Strategic AI use produces a story. The difference lies in intentionality and measurement.
Focus your AI adoption on tasks with clear, measurable outcomes: increased efficiency, reduced costs, faster turnaround, improved accuracy. Then track those outcomes rigorously. When you can walk into a room and say “I used AI to reduce reporting time by 40% over the last quarter,” you shift the conversation from perception to evidence. Bias thrives in ambiguity. Data cuts through it.
Do not use AI simply because it is available. Apply it where the return on investment is visible, specific, and communicable to the people who evaluate your performance.
2. Teach AI to Your Peers
One of the fastest and most effective ways to reposition yourself from AI user to AI leader is to become the person who teaches others. Write internal guides. Walk your team through a tool that is producing results. Host a short informal session where you share what you have learned and how it applies to your shared work.
Teaching does something that simply using a tool never can: it publicly establishes your expertise. When your colleagues and managers watch you explain AI to others, they stop seeing you as someone who relies on a tool and start seeing you as someone who commands it. That shift in perception is significant, and it happens through visibility rather than performance alone.
3. Find Your Internal Advocate
You need at least one senior person in your organisation who knows what you are building with AI and understands its impact. That person cannot advocate for you if they do not have the information to do so, which means you need to actively create opportunities to give them that information.
Have a direct conversation with your manager or another key leader. Share specifically what you have been doing with AI, what outcomes it has produced, and where you see potential for broader application. Do not wait for a performance review to surface this. Create the conversation yourself, frame it around business impact, and make it easy for your advocate to repeat what you tell them to the people who matter.
If your manager does not encourage your AI use, recognise that you are among the 79% of women in that position. That reality does not mean you stop building. It means you work harder to find the advocate who will.
4. Control the Narrative Through Strategic Framing
How you talk about your AI use shapes how others perceive it. Framing matters enormously in environments where bias already tilts the playing field against you.
Instead of mentioning AI incidentally or defensively, introduce it proactively and confidently in the context of results. Lead with the outcome. Follow with the method. “I developed a solution that cut our analysis time in half” lands differently than “I used AI to help with the analysis.” Both are accurate. Only one positions you as a leader who drives results.
Strategic framing is not about hiding your AI use. It is about ensuring that the story people walk away with is the right one: that you are someone who leverages every available resource to deliver exceptional outcomes.
The Broader Stakes: Why Staying Quiet Is Not an Option
Some women respond to the AI double standard by pulling back. If using AI attracts scrutiny, the logic goes, perhaps it is safer not to use it publicly. That response is understandable. It is also costly.
As Adaeze explored in Episode 041: Why Are Women Adopting AI at Lower Rates Than Men?, women already adopt AI at 25% lower rates than men. Pulling back further in response to bias does not protect you. It widens the gap between where you are and where the opportunities are concentrating. The professionals who build visible AI fluency now are the ones who will lead AI initiatives, earn the high-visibility projects, and shape how AI gets used in their organisations.
Moreover, as Christelle Mombo-Zigah powerfully demonstrated in Episode 042: Christelle Mombo-Zigah: Bridging the Gap, AI Governance and Cultural Representation, the women who refuse to step back from technology are the ones who ultimately get to shape it. Staying quiet cedes that ground to people whose experiences and priorities do not reflect yours.
The double standard is the obstacle. Moving through it strategically, not around it, is the path forward.
What You Can Do Right Now
If this episode resonated with you, here are your immediate next steps:
- Track your AI wins: Start a simple document today and record every outcome your AI use has produced in the last 30 days. Be specific about the impact.
- Identify one teaching opportunity: Think of one colleague or team that would benefit from understanding an AI tool you already use well. Offer to walk them through it this week.
- Schedule the conversation: Identify the senior leader in your organisation who needs to know about your AI work. Put the meeting on the calendar before the end of this week.
- Take the Leadership Edge Diagnostic: Complete the free five-minute assessment at link.africanwomeninstem.com/leadership to identify your visibility gaps and understand exactly how to position yourself more effectively.
- Book a Strategy Call: If you are a senior woman in STEM ready to stop second-guessing and start strategising, book a complimentary Authority Shift Strategy Call with Adaeze through the link in the show notes.
Also, revisit Episode 040: Dwain Robinson: Bridging the Gap in Special Education for a powerful reminder of what becomes possible when you stop trying to fix broken systems from the inside and start building solutions from your own experience and expertise.
Conclusion
The AI double standard is real. The research confirms it, the lived experiences of women across STEM industries reinforce it, and the career consequences of ignoring it are serious. However, the existence of the double standard does not make the path forward impossible. It makes strategic navigation essential.
Stop waiting for your organisation to fix its own bias before you act. Start using AI with intention, measuring its impact rigorously, teaching what you know, finding the advocates who will speak for you in the rooms you are not yet in, and framing your work in language that positions you as the leader you already are.
The double standard is the enemy. You are not the problem. And the strategy for winning is already in your hands.
Listen to the full episode and start breaking through: Episode 043: Breaking the AI Double Standard for Women in STEM
Join the African Women in STEM Membership
Visit the African Women in STEM Website
Watch Adaeze Iloeje-Udeogalanya’s TEDX Talk on YouTube
