The News
Starburst announced AI & Datanova 2025, an in-person summit taking place October 9, 2025, at The Westin New York Times Square. The event will gather senior data and technology leaders to explore strategies for turning enterprise data into AI-driven outcomes, alongside the launch of the 2025 Data Visionary Awards. Read the press release here.
Analysis
As enterprises push toward AI-native applications, the quality, accessibility, and governance of underlying data has become the defining challenge. theCUBE Research has observed that data readiness is the single most cited barrier to scaling AI projects, with organizations struggling to unify data across fragmented clouds, SaaS platforms, and on-premises systems. Events like AI & Datanova underscore how industry conversations are shifting: from experimenting with models to establishing the data infrastructure that sustains AI in production.
Enterprise Agents and the Future of AI Workflows
One highlight of Starburst’s program is CEO Justin Borgman’s keynote on the “emerging era of Enterprise Agents.” These are autonomous, AI-powered systems capable of orchestrating multi-step tasks across business units. For developers, this represents both opportunity and complexity. Applications are likely to increasingly depend on federated data access, governance frameworks, and real-time responsiveness to enable agents to function reliably. While the concept is still in early adoption, the direction aligns with broader industry momentum toward agentic AI workflows, where data pipelines and models converge into more dynamic, enterprise-scale applications.
Custom Pipelines and Patchwork Data Access
Developers have tried to meet AI and analytics needs by piecing together custom pipelines, such as ETL tools, APIs, and database connectors, that often created data silos and latency bottlenecks. This approach worked for dashboards or batch analytics but struggles under the demands of real-time AI inference and reasoning agents. We find that fragmentation across tools adds friction for developers, slowing their ability to move from proof-of-concept to scalable deployments.
Shifting Toward Federated and Governed Data Architectures
The focus of AI & Datanova reflects a pivot toward federated query, governed access, and real-time integration as pillars for AI success. This could mean more emphasis on platform-level solutions and standardized protocols rather than ad hoc data engineering. While each organization will face its own adoption hurdles, the trajectory shows that AI outcomes will increasingly hinge on how well enterprises can expose trusted, governed data to intelligent applications. Conferences like AI & Datanova aim to give practitioners visibility into both the technical strategies and peer benchmarks shaping this shift.
Looking Ahead
The market is entering a phase where data infrastructure is inseparable from AI strategy. We project that enterprises will accelerate investments in unified data access, real-time integration, and governance to meet the requirements of agentic AI. AI & Datanova 2025 serves as both a showcase of customer best practices and a bellwether for how the industry envisions this transition.
For Starburst, the event doubles as a platform to showcase its role in the evolving AI-data ecosystem. For developers and architects, the broader takeaway is that the era of AI-driven enterprises is moving from theory to practice, with data readiness as the deciding factor in who can compete effectively.
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