Alexis
Macías
AI Architect/ Senior Managing Data Scientist at IBM
"The AI Work Women Do That No One Sees"
"The AI Work Women Do That No One Sees"
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Session: The AI Work Women Do That No One Sees
AI is often presented as a story of breakthrough models, cutting-edge algorithms, and rapid innovation. But in the real world, AI succeeds-or fails-because of work that rarely makes it into keynote slides.This talk shines a light on the invisible AI work women disproportionately do: translating business problems into technical reality, aligning stakeholders, designing governance, managing risk, and holding systems together when hype meets production.
Drawing from real enterprise AI programs deployed at scale, this session reframes what it truly means to “build AI that works.” The most critical AI contributions aren’t always writing models, they’re designing systems of trust, accountability, and decision-making. And too often, these contributions are labeled as “soft,” overlooked, or taken for granted.
Through personal experience leading complex AI initiatives across industries, this talk challenges the narrow definition of technical impact and reclaims system leadership, orchestration, and governance as core AI architecture skills.
Attendees will leave with a new language to describe their work, a clearer understanding of why AI fails in the real world, and the confidence to recognize, and advocate for, the value women bring to building AI systems that actually deliver results.
Because if we want better AI, we must first see the people doing the work that makes it possible.
Key Takeaways
- Understand why AI success depends on system design, governance, and leadership-not just models and algorithms.
- Recognize the invisible AI work women often do and why it is foundational to building AI that works in the real world.
- Learn how to reframe so-called “soft skills” as core AI architecture and leadership capabilities.
- Gain language and confidence to clearly articulate technical impact beyond coding or model building.
- Walk away with a new perspective on how women can shape the future of AI through trust, accountability, and systems thinking.
Bio
Alexis Macías is a Senior Managing Data Scientist and AI Architect specializing in enterprise AI systems that move from experimentation to real-world impact. She has led large-scale AI programs across regulated and complex environments, focusing on governance, operating models, and production-ready AI delivery.With a background in applied mathematics and years of experience bridging business, data, and technology, Alexis is passionate about redefining what “technical leadership” looks like in AI. She advocates for visibility, accountability, and systems thinking as the foundation for responsible and effective AI.
