Eliza Cabrera is a principal AI product manager at Smarsh, leading development of Discovery Agent for compliance investigations and electronic discovery in regulated financial services. She builds enterprise products that apply artificial intelligence to sensitive workplace information, financial operations and legally consequential investigations.
At Workday, Cabrera developed generative features for Workday Help, including tools that converted lengthy employee-policy documents into usable guidance, translated content and maintained consistent organizational language. These features kept human reviewers involved and integrated directly into existing knowledge-management workflows.
She subsequently led early-access work on Workday Assistant, extending context-aware assistance across human resources and finance. Because the assistant operated across multiple products and potentially handled compensation information and other sensitive employee data, its development required coordination among product teams and careful attention to privacy. Cabrera also led go-to-market work for Workday’s policy agent and helped build its financial audit agent before joining Smarsh to develop Discovery Agent.
How she approaches enterprise AI
- Integrated product strategy: Cabrera rejects AI features built primarily to advertise technical sophistication. Her account of building enterprise AI products emphasizes established customer problems, existing workflows and experiences that remain useful without requiring users to understand the underlying technology.
- Incremental agent development: Her Workday projects progressed from document generation and translation to context-aware assistance and increasingly autonomous agents. Each stage introduced new requirements for product integration, sensitive-data handling and coordination across enterprise platforms.
- Governance as product design: Employee policies, compensation data, financial audits and regulated investigations demand controlled access, human oversight and defensible outcomes. Cabrera treats those constraints as fundamental product requirements.
- The Product Orchestrator: In her framework for modern product leadership, Cabrera argues that domain expertise and industry-specific judgment matter more than adopting a generic AI-product-manager identity. Product leaders must coordinate people, agents, tools and partnerships around concrete business problems—a position she has also articulated in a public professional post.
Cabrera also founded and led AI in Product, a Colorado community for product professionals exploring generative AI, multimodal experiences and changing product-management responsibilities. Through AI in the Rockies, she continues writing about AI product leadership and professional judgment.
