Selena Singh,

AI Product Strategy & Human-Centered AI

I operationalize AI-enabled decision systems that help organizations move from fragmented workflows to scalable, governance-aligned operations. My work is grounded in human–computer interaction and cognitive science, enabling me to design AI systems that account for how people actually think, decide, and build trust.

With a background in UX research and enterprise operations, I specialize in translating complex AI capabilities into real-world systems that improve decision quality, reduce risk, and support long-term adoption.

What I Bring to the Table

  • Human-Centered Decision Strategy: Expertise in qualitative + quantitative research that informs how decisions are made and operationalized within complex, regulated environments.

  • AI Systems & Responsible Deployment: Experience integrating AI capabilities (predictive modeling, real-time insights) into operational systems while ensuring transparency, fairness, and auditability.

  • Operational Impact: Proven track record in logistics, finance, and technology where AI-enabled systems improved decision speed, efficiency, and organizational trust.

  • Mentorship & Enablement: I enable teams to adopt structured, governance-aligned workflows and build confidence in human–AI decision-making.

Core Competencies

  • AI Product Strategy & Discovery

  • Responsible AI & Governance-by-Design

  • Product Analysis & Decision Support

  • Cross-Functional Leadership & Enablement

  • Organizational Change & AI Adoption

Industry Experience

  • Logistics & Supply Chain Operations

  • Financial Services & Risk-Sensitive Environments

  • Enterprise AI & Data Platforms

  • Global Operations & Distributed Systems

Technical & Creative Skills

  • User Discovery, Behavioral Analysis & Human–Computer Interaction

  • Workflow & Decision System Design

  • Data-Informed Product Strategy

  • Knowledge Systems & Documentation Design

  • Team Mentorship & Stakeholder Communication

Approach to AI Enablement & Decision Systems

Across projects, I apply a consistent approach to building AI-enabled systems:

  • Understand how decisions are made in real-world environments

  • Structure AI outputs into usable, auditable decision flows

  • Embed human-in-the-loop validation and oversight

  • Align systems with governance, risk, and compliance requirements

  • Enable adoption through training, workflows, and operational integration

This approach ensures AI systems are not only technically effective, but trustworthy, usable, and scalable.