AI for Technical Professionals
Explore the technical depth shaping the future of enterprise AI
Built for the People Building AI
For the engineers, data scientists, and technical architects turning AI ambition into production reality, this is where the real work gets discussed. Explore the architectures, infrastructure decisions, and data foundations that determine whether an AI system actually scales and performs under real-world pressure.
From next-generation research to data excellence practices and hands-on masterclasses, the Summit is built to meet the challenges you face head on.
Where the Technical Work Happens
Two stages, built for the teams solving the hardest problems in AI. From the research pushing the boundaries of what is possible to the data foundations that make production systems reliable, these stages are where technical depth meets practical application.
The Next Generation Stage 🚀
The Next Generation Stage explores the cutting edge of AI, focusing on forward-thinking applications, infrastructure, hardware and emerging technologies.
Leading innovators will showcase the latest thinking, prototypes, models in use and recent breakthroughs through engaging use cases, demonstrations and technical presentations.
The Data Excellence Stage 💻
Enterprise AI is only as strong as the data behind it.
The Data Excellence stage explores the foundations required to build reliable, scalable and production-ready AI, from AI-ready data architectures and governance to real-time activation, observability and operational resilience.
As organizations move beyond pilots, the focus shifts from simply collecting data to creating trusted, AI-ready environments.
Key Sessions to Attend
Discover the must-attend sessions for engineers, data scientists, and technical architects at The AI Summit New York, featuring expert insights on the architectures, infrastructure decisions, and data foundations behind production AI systems, navigating the engineering trade-offs of scaling AI, and measuring true performance and risk across enterprise deployments.
Multi-agent AI is the next frontier. Unpack the engineering decisions behind orchestration, communication, and conflict resolution as organizations tackle coordination, scalability, and evaluation at scale.
AI is becoming an active participant in building and maintaining software. This panel examines how engineering workflows, architecture, and human judgment evolve as AI takes on more ownership.
AI is moving beyond centralized cloud to edge devices and distributed environments. Discover how engineering teams design for resilience, recovery, and security as these systems scale and fail.
From lakehouses to vector databases, organizations face growing complexity in enterprise data design. Leaders weigh the trade-offs shaping data strategies built to support the next generation of AI.
Most AI failures get blamed on data, but the root cause is architecture. A simulated autonomous enterprise reveals how two overlooked architectural choices transform cost, trust, and speed.
As data platforms standardize, advantage shifts to how organizations design and own their capabilities. Leaders share how to balance bespoke builds with commercial platforms without added complexity.
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