Future-Ready Data Foundation: From AI Pilot to Production Value
Watch the on-demand webcast on building a future-ready data foundation that enables trusted, scalable, and AI-ready data, with a practical roadmap for moving AI from pilot to production value.
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View RecordingAgenda / Topics Covered
Why AI pilots stall
Understand why AI initiatives often struggle when data is fragmented, inconsistently defined, or owned by disconnected teams.
Future-ready data foundation
Learn the core data readiness capabilities required for trusted, consistent, scalable AI programs.
Roadmap from pilot to production
Review a practical 60-90 day roadmap for prioritizing gaps, use cases, and follow-up action plans.
Assessment and next steps
See how an AI Data Readiness Assessment can identify what to fix first before scaling production AI.
Speakers
Stewart Bond
Research VP, Data Intelligence and Integration Software at IDC
Stewart Bond leads IDC’s Data Intelligence and Integration Software research, focusing on emerging trends in data movement, ingestion, transformation, mastering, cleansing, and consumption in the digital era.
Srinivas Poddutoori
Co-founder and COO at Artha Solutions
As COO and co-founder of Artha Data Solutions, Srinivas Poddutoori drives global data-driven innovation across enterprises through data engineering, master data management, data governance, and AI initiatives, including AI governance.
Madhav Nalla
Enterprise Intelligence Architect at Qlik Partner Ambassador
Madhav works at the intersection of data strategy, digital transformation, advanced analytics, and AI, focusing on trusted, scalable data ecosystems that power intelligent automation and decision-making.
Sidney Drill
Product Marketing Director at Qlik
Sidney Drill is a product marketer at Qlik specializing in integration and analytics, known as an enthusiastic presenter, data for good advocate, and former Solution Architect.
Data Readiness for AI
Learn how to fix fragmented ownership, inconsistent definitions, and disconnected systems so AI can scale with trust.
/resources/webinarsKey Takeaways
Understand why AI success depends on trusted, well-governed, and consistently defined enterprise data.
Learn how to identify the data readiness gaps that keep AI pilots from reaching production.
Use a practical 60-90 day roadmap to prioritize fixes, use cases, and operating-model changes.
Connect data governance, integration, quality, and ownership to measurable AI production value.
