AI Talent, Strategy, and AGI: What is the New Edge?
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I support AI growth at Bank of America, building on earlier work on Google Assistant with Accenture and my studies at the University of Chicago.
My long-term vision is to shape the next generation of AI, turning advanced intelligence into experiences that people trust, adopt, and rely on at scale.
I care most about AI that benefits humanity: grounded in strong governance, attuned to culture, and designed to help people make better decisions in an increasingly complex world.
This site brings together my work across the business and technical sides of AI, with selected experiences spanning technology, strategy, and execution. I write about responsible AI, the future of leadership, and my experience working at the intersection of business and technology.
Career
Currently focused on enterprise AI strategy, governance, and AI product delivery at one of the world’s largest financial institutions.
Erica for Employees · Enterprise Virtual Assistant · Web & Voice
Google Assistant · Multilingual Conversational AI
Writing
Field notes from the AI industry, published on Medium.
Coming Up Next
Governance makes AI safe; monitoring makes it beneficial. This piece breaks down the two disciplines every leader needs to get right, with practical frameworks and the questions worth asking before the next initiative goes live.
Published
Everyone knows technical and business teams struggle to communicate, but that framing undersells the problem. In enterprise AI, the gap between these two worlds creates friction, derails projects, erodes trust and, most importantly, produces AI systems that never quite deliver what they promised. This article offers practical insights on what each side actually needs, where things tend to break, and what it takes to hold it all together.
For years, the value of AI was measured by information access. Could the system retrieve the right information fast enough? Could it summarize, search, or surface what a human needed?
That question has lost most of its weight. The question now is whether the AI capability has the right scenarios and assumptions to make the best decision. That's a different bar than simply having the right information to describe one.
Before checking model outputs, the foundation has to be right. So as leaders, what are the foundations of a stable AI strategy?
Speaking
Panels, talks, and conversations at the intersection of AI, data science, and human-centered technology.
ChatADS is the official podcast of UChicago's MS-ADS program, featuring candid conversations on how data science, machine learning, and AI are applied to solve real-world problems. Topics span industry applications, career trajectories, emerging tech trends, and ethical data choices.
Listen on Spotify →Panelist in a moderated discussion for UChicago's Kappa Theta Pi winter workshop series. Joined 5–6 professionals across product, engineering, data science, and strategy to share career journeys and advice for students navigating tech recruiting, followed by student Q&A and open networking.
Invited guest speaker for the ADSP program, sharing industry perspective on enterprise AI, NLP, and the path from engineering into AI product leadership.
One of a select group of judges chosen for exceptional professional experience in tech. Evaluated 13 project submissions across a 24-hour sprint with 150+ undergraduate and graduate participants from across the US. Provided technical feedback, asked probing questions, and contributed to final prize deliberations.