Business Analyst at McKinsey & Company specializing in AI’s impact on software development. MIT Media Lab graduate (MEng & BS in Computer Science) who brings unique perspective combining AI research, human-computer interaction, and organizational transformation.
Current Work
At McKinsey, Natasha contributes to research and consulting on AI’s transformation of software development practices. She co-authors research on post-Agile methodologies and advises enterprises on AI-native workflows. Her work includes “Unlocking the value of AI in software development” and “How open source AI solutions are reshaping business.”
Background
As a graduate student in the Fluid Interfaces group at MIT Media Lab, Natasha developed MemPal, a multimodal AI system helping older adults with independent living. Her research focused on wearable devices for cognitive support and human-centered AI design. Paper available on ACM Digital Library.
Philosophy on AI and Software Development
Natasha’s approach reflects her dual background in technical AI research and management consulting:
Human-Centered Transformation - Technology adoption requires understanding organizational dynamics, not just technical capabilities.
Research-Grounded Practice - Large-scale empirical studies provide evidence for how AI reshapes work, enabling more informed strategic decisions.
Beyond Agile - AI agents fundamentally change task allocation, sprint cycles, and team structures—requiring new methodologies, not tweaks to existing frameworks.
About McKinsey & Company
McKinsey is a global management consulting firm conducting large-scale research on AI’s organizational impact. Through QuantumBlack (McKinsey’s AI practice), the firm advises leading companies on AI adoption, software development transformation, and organizational restructuring for the AI era.
Conference Appearance
Event: AI Engineering Code Summit 2025 Date: November 20, 2025 Time: 11:20 AM - 11:40 AM Session: Moving away from Agile - What’s Next?
Co-presented with Martin Harrysson, exploring how organizations should reorganize development practices in the AI era. Drawing on McKinsey’s research across thousands of developers, the session examined emerging AI-native roles, post-Agile methodologies, and practical change management strategies for enterprise adoption.