Agentic AI: How to Build Autonomous Data Workers That Don’t Go Rogue

Imagine creating an AI worker that not only does the heavy lifting of data engineering but actually drives revenue for your organization — while you sleep. In this full-day hands-on workshop you’ll learn how to build autonomous data agents that connect data, analytics and business decisions, unlocking new income streams, cost savings and strategic advantage in the AI race. We’ll cover the architecture behind these revenue-enabled agents: how to structure them to follow business rules, track performance, generate measurable ROI, and avoid the trap of becoming just another “expensive toy.” Participants will walk away with a clear blueprint to deploy agents that: Automate data workflows, free up human engineers and reduce costs. Generate business value by feeding insights, making decisions and executing tasks (e.g., identify new opportunities, market segments, or operational inefficiencies). Monetize their activity via pricing models (usage-based, outcome-based, seat-based) that tie your architecture to income rather than just “cool tech.” Split into two sessions (4 hrs each): Session 1 (Morning): Foundations of agentic data systems — autonomy, memory, decision logic, value-tracking, business alignment. Session 2 (Afternoon): Hands-on building of an agentic data worker from ingestion to insight to action — including how to instrument it for monetizable outcomes like cost savings, lead generation or process optimization. By the end of the day you’ll walk away not just with code, but with a monetization map: how to position your agentic system for profit, how to communicate its business case, and how to stay ahead in the evolving AI race.
Who is this presentation for?
This workshop is designed for data engineers, AI/ML practitioners, analysts, solution architects, product leaders, and innovators who want to turn autonomous AI systems into real business value. It’s ideal for professionals aiming to automate workflows, reduce costs, and discover new revenue opportunities with AI. No prior experience in AI agents or coding is required. The session starts from first principles and builds up step-by-step, guiding attendees through concepts, architecture, and live demonstrations using simple, accessible tools. Whether you’re technical, strategic, or just AI-curious, you’ll walk away ready to build or lead your own agentic AI initiatives.
Prerequisite knowledge:
No prior experience with AI agents, coding, or data engineering is required. The workshop is designed to be fully self-contained, starting from foundational concepts and gradually moving into implementation. All examples, demos, and exercises will be explained from scratch. The speaker will ensure that participants face no roadblocks, even if they come in without understanding a single prerequisite. Every concept will be broken down in plain language, with guided walkthroughs, visuals, and take-home resources to help every attendee keep pace and succeed.
What you'll learn?
How to design and build autonomous AI data workers that can fetch, clean, analyze, and act on information without constant supervision. The core building blocks of agentic AI systems — reasoning loops, memory, decision logic, and safety guardrails — explained in human language. How to connect agents to real-world data pipelines and workflows to automate repetitive tasks and free up human engineers. Proven frameworks to keep agents aligned, transparent, and accountable so they don’t “go rogue.” Techniques to measure and monetize agent performance through cost reduction, speed, and new revenue opportunities. How to future-proof your career or business by understanding the next wave of AI infrastructure — systems that think, act, and learn. By the end of the workshop, you’ll not only understand how agentic AI works, but also how to make it work for you — turning cutting-edge autonomy into tangible business impact

Sakshi Naik is an AI researcher, data architect, and IEEE leader recognized nationally for her work on building ethical and reliable AI systems. She currently chairs the IEEE USA Agentic AI Subcommittee, where she helps shape U.S. policy positions on responsible automation and intelligent systems. With over five years of industry experience at Walgreens, Sakshi has engineered large-scale data and AI platforms on Azure Databricks, driving analytics modernization and end-to-end automation across enterprise environments. Her technical expertise spans data engineering, AI fairness frameworks, and scalable ML infrastructure. Beyond her professional roles, Sakshi is a speaker at global AI and data conferences including ODSC West, PASS Data Summit, AI Infra Summit, and the C# Software Architecture Conference, where she has addressed thousands on the future of trustworthy AI. She also mentors students and early-career technologists through IEEE and her YouTube series “AI with Sakshi.” Sakshi’s mission is to make AI both powerful and principled — systems that help people, not replace them.