2026
AI Executive
AI now shapes conversations across every industry. With new tools launching constantly, it’s hard to know which ones matter and how to use them. This track helps leaders cut through the noise and learn how to evaluate and integrate AI tools effectively.
AI Ops & Technology Management
AI projects are moving from experiments to production. As they scale, managing models, infrastructure, and workflows becomes more complex. This track features engineering and ops leaders who share practical strategies for MLOps, AIOps, deployment, monitoring, and resource management.
AI Strategy, Case Studies & Success Stories
Hear from teams who have already built successful AI programs. They’ll explain what worked, how they measure success, which users they focus on, and how they drive real organizational change.
Machine Learning, Models & Architectures
Experts in research and development share best practices for training predictive models, using transformers effectively, and working with modern data analysis techniques.
AI Frameworks, Tools & Applied AI
Developers will learn how to build agentic apps, bots, and other AI-enabled software. Sessions cover customizing LLMs, using RAG, writing better prompts, working with frameworks like LangChain, and integrating AI directly into development workflows with AI co-pilots.
Data Access, Data Management & Operations
Data engineers will share how they manage AI workloads on-prem and in the cloud. Topics include streaming data, vector databases, data cleaning, and building efficient pipelines using MLOps and AIOps best practices.
AI Enterprise Dev
Build and integrate AI into enterprise-grade applications, systems, and workflows with a focus on scalability, reliability, and real-world use.
Fintech
From enhanced fraud protection and data analysis to real time predictions to autonomous agent-enabled payments, it’s clear that AI’s effect on the financial industry promises to be nothing short of revolutionary.