Ksenia Se is a strategic advisor and author focused on artificial intelligence adoption and organizational transformation. She is recognized for contributions to discourse on AI-native business models and the operational integration of machine intelligence into organizational workflows.1)
Se's work centers on understanding how organizations transition toward AI-native operational models. Her research and writing explore the strategic implications of integrating machine intelligence into core business processes, moving beyond traditional software adoption patterns. She examines how companies restructure workflows, decision-making processes, and competitive strategies when machine learning systems become embedded in ordinary operational work rather than serving as supplementary tools.
Her contributions to the “Age of AI” series emphasize the distinction between organizations that adopt AI as an enhancement to existing processes and those that fundamentally reimagine business models around machine intelligence capabilities. This includes analysis of how startups can be structured from inception with AI as a primary operational component, rather than bolting AI onto traditional business architectures.
A central theme in Se's work is the definition and characteristics of AI-native startups. These organizations are conceptualized as companies where machine intelligence participates in ordinary work—meaning AI systems are embedded into routine operations, decision-making, and value creation processes. Rather than viewing AI as a specialized function or separate department, AI-native approaches integrate machine learning into the fundamental business model.
This framework contrasts with traditional technology adoption, where new tools are layered onto existing organizational structures. Se's analysis suggests that successful AI-native organizations require different approaches to talent acquisition, organizational design, data infrastructure, and capital allocation.
Through her writing and strategic advisory work, Se contributes to broader conversations about artificial intelligence's role in organizational transformation. Her perspective bridges strategic business thinking and technical AI capabilities, examining how companies assess AI readiness, navigate implementation challenges, and measure returns on AI investments.
Her work addresses practical questions facing enterprise organizations: how to identify use cases where AI creates competitive advantage, how to structure teams for AI integration, and how to develop organizational cultures that effectively leverage machine intelligence.