The AI-Ready Data Core: Creating the Foundation for Intelligent Systems

As AI becomes a central pillar of business decision-making, enterprises face a new challenge, and that is making their data AI-ready. It’s no longer enough to collect and digitise information. For organisations, data must be structured, contextualised, discoverable, and usable—both by humans and intelligent systems.AI can only deliver if your data is truly ready, but most enterprises are drowning in fragmented, incomplete, or slow-to-update data. In this episode of Don't Panic, It's Just Data, host Doug Laney and Sushant Rai, Vice President of Product of AI and Data Strategy at Relito, explore how modern data unification strategies are changing enterprises, enabling AI to deliver faster, more reliable insights. They focus on the shift from traditional Master Data Management (MDM) to next-generation AI-ready data cores, uncovering the risks of fragmented data and the strategies to overcome them.Why AI-Ready Data MattersAI, especially large language models (LLMs), is changing how people interact with data. Analysts, executives, and frontline teams now expect natural language queries and instant, actionable insights.Sushant explains:AI performs at its best when it has full context, empowered with the right data. This allows AI agents to make decisions and take actions on behalf of your business.When you embed intelligence into your data layer, AI can help you manage and scale your data without drowning your teams in manual work. This will only work if your data is structured, clean, governed, and constantly updated, everything that makes it truly AI-ready.The Data Scale ChallengeThe volume of data being turned over daily is staggering. As Sushant notes:The amount of data getting generated every single day is so massive that there’s no way to keep up without AI. Even the largest organizations, with massive data stewardship teams, can’t catch up manually.This gap is driving the change in the modern data platforms, where AI automates stewardship, enriches data continuously, detects anomalies, and maintains quality in real time.Want to learn more about modern data unification and AI-ready platforms? Visit Reltio.com for insights, resources, and case studies.TakeawaysData unification provides a trusted, real-time view of key business elements.Organizations must balance speed and trust in data management.Classic MDM is evolving into modern data unification platforms.Real-time data access is crucial for AI and analytics.AI can enhance data quality and governance processes.Successful data initiatives require clear business outcomes and ownership.Data unification should be viewed as a business platform, not just an IT project.AI agents will play a significant role in automating data governance.Organizations need to focus on both structured and unstructured data.The future of data management involves continuous unification and...

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