The Data Architecture Gap Facing AI – AI’s growth has surpassed its original data architecture. Systems built primarily for reporting on a periodical basis and overnight batch processes are currently being used to generate real-time actionable intelligence that needs to respond to changing conditions within seconds. This has created a growing divide between what organizations expect their AI applications to accomplish versus what the current data platform technology supports.

In this Keynote presentation we will discuss the existing technology divide; evaluate how decisions regarding data ingestion, processing and coordination affect the response time and reliability of AI enabled systems and explain why moving from batch-based designs to continuous always-on, event driven architectures is no longer an option for those working at high volume. We will compare legacy data architecture technologies with modern ones to illustrate how continuously operating data platforms turn delayed insights into real-time operational intelligence. Audience members will be able to understand better the design principles, trade-offs and examples of how to build scalable data platforms supporting AI based solutions.

2nd International Engineering Data analytics and management Conference (EAMCON 2026)
https://eamcon.in/keynote_speakers/gajendra-babu-thokala/