Building a strong data infrastructure for AI agent success

AI agents are only as effective as the data supporting them, and most companies scaling AI fail not because AI models are weak, but because they lack proper data architecture and governance. The key to success is delivering business context along with data (not just collecting more data), and overcoming 'trust debt' by ensuring data has shared definitions, semantic consistency, and reliable operational context across the many data sources and cloud systems companies use.