Ayan Putatunda

Unlocking Intelligence through Data

Abstract- Every enterprise has data. Few have AI that works. Despite decades of investment in warehouses, lakes, and BI, roughly 80% of AI project time is still spent on data preparation, plumbing, and access — not on the model. The bottleneck is no longer intelligence; it is whether our data platforms are ready for intelligence to consume them.

This keynote presents a practitioner's maturity model for AI-ready data, drawn from building and operating petabyte-scale platforms in production: from Ground data (raw and ingested), through Curated (modeled and trusted — where most enterprises stop), to Intelligent (semantic layers, embeddings, and feature stores that give data machine-consumable meaning), and finally to Agentic-Ready — self-describing data, tool-shaped access, context provisioning, and guardrails for a new kind of consumer that plans, calls tools, and acts autonomously. Along the way, we examine how AI actually consumes the platform today — BI, ML serving, RAG, and emerging agent protocols such as MCP — and the failure modes at each stage, including real lessons from deploying skills-driven agentic workflows that cut delivery time ~2.5x at enterprise scale.

Attendees will leave with a concrete framework to assess their own platform's AI readiness — and a roadmap for closing the gaps that matter most, because readiness is not a milestone; it is a continuous property of the platform.

Brief Profile- Ayan Putatunda is a Staff Data Engineer at Zendesk, where he leads Agentic Analytics for the Zendesk Data Platform — the data backbone behind a platform that resolved 4.5 billion service interactions for over 100,000 organizations in 2025. With 15+ years of experience building large-scale data and AI platforms across enterprises including Zendesk, Achieve, and Noodle.ai, his current work pioneers skills-driven agentic data engineering: governed libraries of AI skills that automate the analytics-engineering lifecycle with humans in the loop, delivering ~2.5x faster time-to-production. He is an IEEE Senior Member, a speaker at dbt Summit 2026 and the Applied AI Summit, a judge for the ACM Fremont Chapter's NextGen Hackathon 2026, and an active mentor to data and AI engineers worldwide. He holds an M.S. in Data Science from the University of Illinois Urbana-Champaign.