{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"The AI Briefing","title":"The Data Quality Crisis Killing 85% of AI Projects (And How to Fix It)","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/52dea63e\"></iframe>","width":"100%","height":180,"duration":543,"description":"85% of AI leaders cite data quality as their biggest challenge, yet most initiatives launch without addressing foundational data problems. Tom Barber reveals the uncomfortable conversation your AI team is avoiding.\n\nThe Data Quality Crisis Killing 85% of AI Projects\nKey Statistics\n\n85% of AI leaders cite data quality as their most significant challenge (KPMG 2025 AI Quarterly Poll)\n77% of organizations lack essential data and AI security practices (Accenture State of Cybersecurity Resilience 2025)\n72% of CEOs view proprietary data as key to Gen AI value (IBM 2025 CEO Study)\n50% of CEOs acknowledge significant data challenges from rushed investments\n30% of Gen AI projects predicted to be abandoned after proof of concept (Gartner)\n\nThree Critical Questions for Your AI Initiative\n1. Single Source of Truth\n\nDo we have unified data for AI models to consume?\nAre AI initiatives using centralized data warehouses or convenient silos?\nHow do conflicting data versions affect AI outputs?\n\n2. Data Quality Ownership\n\nWho owns data quality in our organization?\nDo they have authority to block deployments?\nWas data quality specifically signed off on your last AI launch?\n\n3. Data Lineage and Traceability\n\nCan we trace AI decisions back to source data?\nHow do we debug AI failures without lineage?\nAre we prepared for EU AI Act requirements (phased in February 2025)?\n\nThe Real Cost of Poor Data Governance\n\nOrganizations skip governance → hit problems at scale → abandon initiatives → repeat cycle\nTech debt compounds from rushed implementations\nStrong data foundations enable faster AI scaling\n\nAction Items for This Week\n\nAsk for data quality scores on your highest priority AI initiative\nIdentify who owns data quality decisions and their authority level\nTest traceability: can you track wrong outputs to source data?\nEnsure data governance is a budget line item, not buried assumption\n\nKey Frameworks Mentioned\n\nAccenture: Data security, lineage, quality, and compliance\nPwC: Board-level...","thumbnail_url":"https://img.transistorcdn.com/l4TTMAx4d27sGdvCOPP-6vIhh7U0b5J5SpAWtYmxkvs/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS8yN2U2/ZWY1ODg4MTgwMjk3/MjVmZmZjODNmMjVh/YzFjNS5wbmc.webp","thumbnail_width":300,"thumbnail_height":300}