Digital Transformation Leader, Data & Analytics, Business Development, Strategic Innovator in Consumer Products and Retail- Nestle, Procter & Gamble, Walmart, Amazon Web Services
Data is the oxygen that fuels AI acceleration. I know this is a bit of a cliché, but here's the reality...most enterprise data strategies weren't built for the AI era. Over 62% of organizations believe the lack of data governance is the main challenge inhibiting AI initiatives. Organizations are hitting roadblocks not because they lack data governance, but because their current frameworks can't handle AI's demands. Traditional governance models were designed for predictable, batch-processed data flows. AI requires something fundamentally different: dynamic, real-time data management that can adapt as quickly as the models consuming it. The companies winning with AI are building governance systems that respond dynamically to changing requirements. They're implementing intelligent data validation that learns and evolves, creating reusable data assets that accelerate model development, and establishing oversight mechanisms that scale with automation. I'm curious about your experiences: How is your organization adapting its data management for AI workloads? What tools are you finding valuable in your Data-AI Governance journey? How have you evolved your data platform and architecture to be AI-ready? This is complex territory where shared insights benefit everyone. #Data4AI #DataGuy #AIGovernance #DigitalTransformation
The AI revolution is transforming businesses, but it also brings complex challenges. As organizations adopt AI-first strategies, they're faced with new data governance issues, complex AI interpretations, and emerging quality concerns. Our latest paper explores how organizations can thrive in this new landscape by balancing intelligent systems with ethical oversight. https://bit.ly/3VnaKe1
