Cheyenne Dominguez & Farida Khalaf: Author Interview #16, AI Everywhere, Volume 1
AI Everywhere, Vol. 1, Ch.13: Why Women Must Get AI Savvy Now. Why upskilling for women matters and how women can thrive by seizing current opportunities.
Welcome back to the She Writes AI interview series, where we talk with the authors behind AI Everywhere, Volume 1 exploring their personal journeys and professional expertise to understand how we can build a future for AI that is truly ethical, responsible, and human-centered.
This is the 16th episode in our series, and today I am joined by Cheyenne Dominguez | M(AI)VENS. Her Chapter 13: Why Women Must Get AI Savvy Now challenges the passive strategy of waiting for technology to “stabilize”. Cheyenne argues that for women, waiting for the dust to settle means missing the critical moment when the actual power structures, frameworks, and norms of the AI era are being set.
Cheyenne Dominguez | M(AI)VENS brings a sharp strategic lens to this conversation, drawing on her background as a business consultant to exclusive leadership networks and her experience building niche communities where women can thrive. As the founder of M(AI)VENS, a newsletter and network for “non-techy” women, she is on a mission to ensure that the AI revolution doesn’t leave women behind. Her work moves the conversation beyond just “using” tools and into the realm of strategic influence. She reveals that the real risk isn’t just a lack of technical skill, but the danger of women remaining in execution roles while the decision-making layers of companies are shaped by others.
In this conversation, Cheyenne Dominguez | M(AI)VENS explores the fundamental difference between being a mere consumer and being “AI savvy,” how to navigate the “competence penalty” through transparent ownership, and why human judgment must remain the ultimate line that no algorithm can cross. Whether you are a professional in a non-technical role or a leader looking to perform an inclusion audit on your team, Cheyenne’s insights offer a practical roadmap for moving from private experimentation to visible participation.
Below is Cheyenne Dominguez | M(AI)VENS’s full interview response to Farida Khalaf’s questions on Why Women Must Get AI Savvy Now from AI Everywhere, Volume 1.
Topic: Why Women Must Get AI Savvy Now (Chapter 13)
Intended Audience: For women and non-technical professionals seeking a strategic roadmap to move from “AI anxiety” to “AI agency,” and for leaders seeking a disciplined framework to transition their teams from execution-based tasks toward visible participation and strategic influence in the decision-making layers of an AI-driven workforce.
Part 1: The Professional Path & The Urgency
The Expert Perspective: Cheyenne Dominguez | M(AI)VENS, your chapter is titled “Why Women Must Get AI Savvy Now.” What was the specific “spark” or observation in the tech landscape that made you realize waiting for AI to “stabilize” was a strategy that would disproportionately hurt women?
Cheyenne: The spark was watching when AI shifted from a technical tool to now a popular set of consumer-facing products and a decision-making layer inside companies. Hiring, marketing, budgeting, product development. AI is now shaping all of it. In many organizations, those early conversations are being led by small, often male-dominated groups. I see familiar patterns forming where women are present in execution roles but not shaping how the tools are being selected, used, monitored, and measured. Waiting for AI to “settle” means arriving after the frameworks, norms, and power structures are already set. We can’t let that happen.
Defining “Savvy”: You emphasize upskilling rather than just “using” tools. In your view, what is the fundamental difference between being an AI consumer and being “AI savvy,” and why is that distinction a requirement for career survival today?
Cheyenne: Using AI is task-based. Being AI savvy is strategic. An AI consumer asks, “Can this tool help me?” An AI-savvy professional asks, “How is this tool changing how decisions are made, and where do I need to be in that process?” That distinction is important because careers are not built on task completion alone. They’re built on influence, judgment, and proximity to decision-making.
Part 2: Upskilling & The Competence Penalty
The “Competence Penalty”: The sources mention that women are sometimes penalized more severely for using AI than men are. How can a woman build “AI savviness” in a way that demonstrates her expertise rather than making her look like she is outsourcing her thinking?
Cheyenne: I think the key is transparency paired with ownership. So, instead of presenting AI-assisted work as output alone, show your strategic thought process. For example, share how you structured a prompt and why, what/how you refined, what you rejected, and why. That signals expertise. AI becomes part of your workflow, not a shortcut. The goal is to be seen as someone who can direct the tool, not someone dependent on it.
Beyond the Degree: The book notes that “no computer science degrees are needed” to benefit from these insights. For women in non-technical roles, what are the top two “AI-first” skills that offer the highest return on investment for their time right now?
Cheyenne: Across reports from McKinsey & Company, Microsoft, and LinkedIn, two AI-first skills consistently rise to the top:
AI-augmented decision-making — Using AI to think through problems, compare options, and arrive at stronger recommendations. This is where companies are seeing the biggest gains. It moves you closer to strategy and leadership conversations.
Embedding AI into your daily workflows — Applying AI to the work you already do in a repeatable way. Reports, planning, communication, analysis. The advantage comes from consistency, not occasional use.
These two stand out because they directly improve how decisions get made and how work gets delivered, which is typically how performance is judged.
Seizing the Gap: You talk about thriving by seizing current opportunities. What are the specific hidden opportunities in AI that women are uniquely positioned to lead, which the male-dominated narrative typically overlooks?
Cheyenne: There are opportunities in areas that require context, empathy, and real-world application. Internal communications, ethical implementation, client experience design, education and training, and community building around AI adoption. These are often dismissed as “soft” areas, yet they determine whether AI actually works inside an organization. Women are already leading in these spaces. With AI layered in, they can own the bridge between technology and people.
Part 3: Systemic Impact & Leadership
The 12% Crisis: Celeste Garcia (Chapter 1) points out that only 12.4% of women reach the C-suite in AI. How does your strategy for getting “savvy” provide a roadmap for women to break through that “locked and loaded” bias at the executive level?
Cheyenne: Getting AI savvy is about positioning, not just skill-building. Women who understand how AI impacts revenue, efficiency, and risk can enter conversations at the executive level with relevance and confidence. It shifts them from being seen as functional to strategic. The roadmap is this: learn enough to ask good questions, connect AI to business outcomes, and speak about it in the language leadership already values.
The Global Baseline: As part of a collective representing five continents, how do you see the “upskilling” requirement differing for women in the Global South versus those in Western tech hubs?
Cheyenne: The fundamentals are the same, but access changes everything. In Western tech hubs, the challenge is not access to AI. It’s sorting through too many tools, updates, and opinions, and knowing where to spend time so it actually enhances your work. In the Global South, it’s more likely to be access to tools, infrastructure, or training.
The “Ecosystem Tax”: Rebecca Mbaya (Chapter 2) mentions the “Ecosystem Tax” for innovators. Do you believe women pay a similar “tax” in the workplace when trying to learn AI, and how can they collectively burden-share to reduce that load?
Cheyenne: Yes, women often pay some version of this tax. Learning AI is happening on top of existing workloads, without always having support. Collective burden-sharing could look like small peer groups, shared prompts, shared workflows, and open conversations about what is and isn’t working. It reduces duplication and accelerates confidence. Also, I believe women who participate in peer networks and shared learning environments can experiment and learn faster, regardless of geography.
"Waiting for AI to 'settle' means arriving after the frameworks, norms, and power structures are already set. We can’t let that happen."
— Cheyenne Dominguez
Part 4: Governance & The Human Signal
Accountability in Learning: If a woman is using AI to accelerate her work, where should she draw the line to ensure she doesn’t lose her professional identity or her human signal to the algorithm?
Cheyenne: The line is judgment. AI can support thinking, but it can’t replace human judgment. Women should stay anchored in their voice, their point of view, and their standards. If you can’t explain or defend the output, it probably shouldn’t be used. The “human signal” is discernment and responsibility for the final product.
The “Savvy” Audit: If a tech leader wants to perform an “Inclusion Audit” on their team’s training programs, what is the first red flag that indicates their upskilling efforts are actually excluding women?
Cheyenne: The first red flag is when AI training is self-directed only. That tends to favor those who already have time, access, and confidence. If upskilling is not structured, supported, and tied to real business use cases, it could quietly exclude many women.
Part 5: Actionable Awareness & Future Vision
The Substack Connection: As a member of the SheWritesAI community, what is one upskilling tip or resource you’ve shared recently that helps women move from “AI anxiety” to “AI agency”?
Cheyenne: One shift I’ve been sharing is to avoid treating AI as something you need to “learn first” before using. Instead, use it in parallel with your work. Think of it as you would any “learning on the job” type of situation. Bring AI into something you already own, like a project or campaign, even if it feels imperfect. Confidence builds through use and experience.
The Final Message: After reading Chapter 13, if a woman takes only one action this week to ensure she is not left behind, what do you hope that action is?
Cheyenne: Do one visible thing with AI this week. Not behind the scenes. Share an insight with your boss. Start a quick conversation with a coworker about improving a clunky process. Bring a more thoughtful, better-prepared recommendation into a meeting. It doesn’t have to be big. But it has to be seen. The shift is from private experimentation to visible participation. That’s how people begin to associate you with the future. Over time, those small moments build and enhance a reputation. You become someone who is thinking ahead and contributing in a new way. That can be what keeps you in the conversation and at the forefront as the AI transformation unfolds.
"The shift is from private experimentation to visible participation. That’s how people begin to associate you with the future."
Why This Matters
Cheyenne Dominguez | M(AI)VENS ’s perspective is a vital call to action because she identifies AI not just as a productivity booster, but as a new layer of corporate governance that is currently being "locked and loaded”.
Closing the Adoption Gap: With studies showing only 37% of women using generative AI tools compared to 50% of men, Cheyenne’s framework addresses a critical gender gap in adoption and confidence.
The 60% Premium: She highlights the high stakes of this transition, noting that professionals with AI skills can command up to 60% higher salaries. Upskilling is not just about keeping a job; it’s about significant economic opportunity.
Strategy Over Tasks: Cheyenne clarifies that while using AI is task-based, being “AI savvy” is strategic. To thrive, women must move closer to how decisions are made, using AI-augmented decision-making to influence high-level strategy, rather than just completing reports faster.
Judgment as Sovereignty: She reminds us that the “human signal” is ultimately judgment. By maintaining ownership over the “why” and “how” of AI output, professionals protect their identity and ensure they are directing the tool rather than being dependent on it.
Thank you, Cheyenne Dominguez | M(AI)VENS, for your empowering and deeply practical contribution to this conversation. For readers looking to secure their place in the AI-driven workforce, her chapter in AI Everywhere, Volume 1 offers a clear-eyed guide on how to seize the gap where context, empathy, and strategic judgment meet.
Don’t miss her newsletter and community, M(AI)VENS, where she provides weekly AI news curated for women, “quick wins” to leverage AI, and personal stories of women across industries. Her advice is a powerful reminder: confidence isn’t built by studying the tech in isolation, but by using it in parallel with your work and making your contributions seen. I personally highly recommend joining her “Prompt Parties” and “Monthly Book Club” to move from anxiety to true agency.
And if you’re interested in more conversations like this, consider subscribing to She Writes AI. I’ll continue sharing insights from the voices shaping the future of AI, including contributors from AI Everywhere, Volume 1, where 26 women from across five continents explore how artificial intelligence is changing the world we live in, and how we can change it for the better.
References
Book purchasing information
Buy the ebook on Amazon (now also available in paperback and hardcover) - special intro pricing will expire at the end of May, so don’t wait!
Tips from our publisher on how to buy an Amazon ebook from a non-KDP-marketplace country, and how to read it without a Kindle device (free)
Purchasing and review links (we’re on Amazon, Goodreads, and Storygraph)
For more insights on the book, see aiEverywhereBooks.com - our beautiful book series website created by Blessing Okpala, PhD:
Thanks for reading She Writes AI Community! Subscribe (free) to receive new interviews, weekly digests, & book news and to support our work:
 | A guest post by
|
Thank you for having me! I’m passionate about helping non-techy women become AI-savvy, especially to increase influence and opportunity. 🥳