Nitin Kumar
Marriott International, Director Data Science
Dallas, Texas, United States
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Nitin Kumar is the Director of Data Science and GenAI at Marriott International, where he leads large-scale AI initiatives spanning marketing, customer engagement, and operational excellence. His work focuses on bringing Generative AI and intelligent agentic systems from concept to enterprise deployment, enabling real business impact across diverse functions. He is also an active speaker and contributor at leading AI and data science forums, sharing insights on innovation, governance, and the future of AI in business transformation.
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Augmenting the Agentic Workforce: From LLM Creation to Human-Centered Evaluation
As organizations adopt large language models (LLMs) to automate content creation, summarization, and communication tasks, the need for thoughtful oversight becomes critical. This session introduces a scalable framework for building agentic workforces—semi-autonomous teams powered by LLMs that generate, evaluate, and translate content under structured human guidance. The proposed pipeline includes LLM-based content generation, self-evaluation through LLM-as-a-judge techniques, and dynamic human-in-the-loop (HitL) checkpoints that ensure factual accuracy, alignment with organizational values, and contextual appropriateness.
We’ll explore how this architecture can be extended to multilingual use cases, where translation and translation evaluation are managed through a blend of automated scoring and human quality review. Attendees will learn practical patterns for building these hybrid workflows, including evaluation criteria, escalation logic, and feedback integration for continual improvement. By fusing machine efficiency with human discernment, agentic workforces offer a responsible path forward for deploying generative AI in content-rich, high-stakes domains.
Bridging the Gap: Operationalizing AI Agents from Innovation Labs to Enterprise Scale
Enterprises are awash with AI agent prototypes—but few make it past the pilot phase. The gap isn’t ambition; it’s architecture, governance, and trust. This session presents a structured, framework-driven playbook for moving from experimentation to execution.
We’ll introduce a two-layer decision framework that connects reasoning strategies (how agents think) with architectural patterns (how they’re built), enabling teams to match the right design to their risk tolerance, data maturity, and operational context. Alongside it, we’ll unpack the four non-negotiable pillars of production-grade agents:
Data Integrity & Lineage – ensuring every response is grounded in authoritative sources.
Hallucination Prevention – using validation and grounding to guarantee reliability.
Compliance & Auditability – embedding controls and traceability by design.
User Trust & Adoption – achieving confidence through transparent automation and human oversight.
The session outlines concrete metrics, testing workflows, and phased deployment models that emphasize augmentation over replacement. Attendees will leave with actionable frameworks to help their AI agents graduate from lab experiments to enterprise assets.
Nitin Kumar
Marriott International, Director Data Science
Dallas, Texas, United States
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