IDUG NA 2026

Discover how AI coding assistants transform DB2 development. This live demonstration showcases Bob, an AI-powered tool that automates schema design, generates optimized SQL queries, debugs complex issues, and tunes performance—all through natural language. See real-time examples of migration planning, query optimization, and troubleshooting that reduce development time by 60%. Learn practical integration strategies for your DB2 workflows.

In this session we'll take a look at the capabilities that have been added to Db2 over the past years to prepare Db2 to meet client demands of today and the future. This will include modern deployment options such as cloud and containerized deployments - but - we'll spend more time on modern workloads such as data virtualization, multi-model support, NoSQL support, how to handle mixed workloads and, of course, AI. Many clients are using Db2 for traditional OLTP, operational and analytic workloads - but - are you getting the full value of your Db2 investment and footprint ? All these high value capabilities are there and included in your current license base. Lets unpack what they are.

Enterprises are under pressure to deliver faster insights, streamline operations, and reduce the complexity of managing large Db2 environments. Generative AI is emerging as a practical accelerator across development, administration, and performance engineering. This session will show how teams can harness AI to translate natural language questions into accurate Db2 queries, explore schemas and dependencies without digging through documentation, and diagnose performance issues with recommendations that mirror seasoned experts. We will walk through real use cases that demonstrate how GenAI can simplify workloads, cut troubleshooting time, and improve SQL efficiency, giving developers, DBAs, and performance analysts a powerful new set of tools to boost productivity and unlock the full value of Db2.

When a Db2 or IMS issue occurs, resolution often relies on time-critical manual analysis. This session explores how agentic AI is evolving the operational model for IMS and Db2—moving beyond scripted automation toward more adaptive, AI-assisted approaches for handling complex runtime scenarios. Through a live demo grounded in real client feedback from a large financial services organization, we demonstrate how these approaches can reduce time to resolution and improve operational efficiency. We also examine how AI-assisted decisioning can support routine maintenance, ensuring actions are recommended within defined rules, governance boundaries, and measurable value.
Co-presented with Anshul Agrawal, this technically focused session will also be submitted to IBM TechXchange.

I have a passion for all things mainframe especially Db2 for z/OS.
I like to tell non-technical folks what I do is make the mainframe & its databases a little easier to work with—and maybe a little less intimidating for the next generation of users.”
“honestly—when people hear ‘mainframe,’ they don’t always think modern, developer-friendly, and easy to integrate with.
But that’s exactly what we’re going to challenge today.”
“What I’m hoping to show you is that modernization isn’t about replacing the mainframe—it’s about unlocking more value from it, making it easier to use, and integrating it seamlessly into how we already build and deliver applications today.”
“So whether you’re deeply familiar with the platform, or just curious about how it fits into a modern development lifecycle—there should be something useful here for you.”

AI agents are moving beyond chatbots and code suggestions. The next frontier is agentic AI — systems that autonomously plan multi-step tasks, invoke tools, handle branching logic, and execute end-to-end workflows with minimal human intervention. This session shows how that capability applies directly to Db2 for z/OS operations today, using tooling already available in your environment.
The architectural foundation is simpler than it appears: a well-documented CLI is already an agent interface. The Zowe CLI ecosystem — including its Db2 plugin and the richer vendor-supplied extensions published to the Zowe conformance catalog — gives an AI agent a complete, auditable means to act on the mainframe. The agent does not wait for step-by-step instructions; it reasons over the task, selects the right tool from its available plugin set, chains the necessary operations, and executes.
This session presents a layered agent architecture purpose-built for Db2 workflows in production environments:
Execution layer: A base skill encoding the Zowe CLI interface — translating agent intent into exact, logged commands with safe defaults enforcedDomain layer: A Db2-specific reasoning layer encoding your object model, naming conventions, environment topology, and operational runbooks — the institutional knowledge that typically lives in a senior DBA's headGuardrail layer: Explicit constraints on what the agent executes autonomously versus what requires human sign-off, scoped by environment, subsystem, or operation classWe will demonstrate this using vendor-supplied database management plugins available in the Zowe ecosystem. By exposing operations like DDL generation, schema comparison across subsystems, validation, deployment, and object migration through a CLI interface, an agent can autonomously execute workflows that previously required manual expert coordination — generating DDL for a target object, comparing it against a reference subsystem, validating dependencies, and staging the deployment artifact as a single orchestrated task.
We will also show how the compounding architecture scales across your full mainframe stack. Institutional knowledge encoded once — for Db2, for your SCM tool, for your CICS or MQ environment — becomes a reusable agent capability. Each domain layer builds on the same execution foundation, and the agent chains them together as the workflow demands.
Attendees will leave with a concrete architecture for deploying agentic AI on Db2 z/OS, practical guardrail patterns that make autonomous execution safe in production, and a clear understanding of how the depth of the Zowe plugin ecosystem — open-source and vendor-supplied alike — becomes a direct multiplier for what an AI agent can accomplish.

IBM Db2 offers a wide range of AI features, both built-in and external tools, for creating AI systems and solutions. These include over 200 built-in AI stored procedures and tools that work seamlessly with open-source AI ecosystems. In this workshop, participants will explore Db2’s AI support and use a selection of these features to implement practical AI models. The workshop consists of two parts. In the first module, participants will learn how to develop a supervised AI model using Db2’s built-in AI stored procedures. The entire model development and usage will be done using SQL within the database. In the second module, participants will learn how to create a Python model using popular Python packages outside of the database, and then deploy that model back into a Db2 database. By the end of the workshop, participants will have gained fundamental skills and hands-on experience in utilizing these AI capabilities. They will be able to apply these skills to their future AI projects. This workshop is designed to be beginner-friendly and does not require participants to have extensive knowledge in AI. Basic SQL skills and some Python programming skills are sufficient for attending and benefiting from this workshop.

As AI capabilities expand on IBM Z, database operations are evolving from manual, expertise-driven practices to more automated, simpler, and faster management. This hands-on lab session provides experience with Database Assistant capabilities which transform Db2 administration through agent-assisted intelligence.
Experience how the solution combines AI-driven system insights, context-aware dashboards, and AI agents to enable:

Faster understanding of system behavior
Accelerated troubleshooting
Clearer assessments of operational impact
More confident decision-making

The benefit is reduced manual effort, improved consistency, faster issue resolution, and enhanced operational efficiency across complex enterprise environments.
Make sure to bring your laptop!

Are you ready to move beyond managing infrastructure and start innovating with your data? This hands-on workshop provides a deep dive into migrating and modernizing IBM Db2 workloads using Amazon RDS for Db2. Participants will gain practical experience in executing seamless migrations from platforms like Linux, AIX, or z/OS while ensuring high availability and optimized performance.Beyond the migration, you will explore how to unlock the value of your data by integrating AWS AI/ML services. You'll learn to build intelligent applications using Amazon Bedrock powered by your live RDS for Db2 data. By the end of this session, you will have a clear blueprint for transforming your legacy databases into a modern, AI-ready data foundation.

This hands-on lab will explore how Db2 integrates vector data with structured relational data to support AI-driven use cases. Through guided exercises, attendees will combine unstructured text-derived vectors with traditional data and apply similarity search across both. The lab shows queries that merge SQL filtering with vector similarity to enable semantic search, recommendations, and intelligent data retrieval.