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8 Ways to Build AI Governance That Actually Works ๐๐ฒ๐ฐ๐ผ๐บ๐ฒ ๐ฏ๐ฒ๐๐๐ฒ๐ฟ ๐ฎ๐ ๐๐ ๐ถ๐ป ๐ท๐๐๐ ๐ญ ๐บ๐ถ๐ป๐๐๐ฒ ๐ฎ ๐ฑ๐ฎ๐. ๐๐ฒ๐ ๐๐ต๐ฒ ๐๐ ๐ป๐ฒ๐๐๐น๐ฒ๐๐๐ฒ๐ฟ ๐๐บ๐ฎ๐ฟ๐ ๐น๐ฒ๐ฎ๐ฑ๐ฒ๐ฟ๐ ๐ฟ๐ฒ๐ฎ๐ฑ. ๐ฆ๐ถ๐ด๐ป ๐๐ฝ ๐ณ๐ฟ๐ฒ๐ฒ ๐ป๐ผ๐ โ aiforleaders.com Original post: __________ 82% of SMEs haven't documented their AI systems. And yet, the EU AI Act hits full enforcement on August 2, 2026. Fines up to โฌ35M or 7% of global revenue. Governance sounds like a 6-month enterprise project. It's not. It comes down to 8 things: 1. AI Inventory: Know every AI system your business actually uses. 2. Data Lineage: Track where data flows and what transforms it. 3. Data Quality: Bad data in, bad decisions out. 4. Data Security: Encrypt it, anonymize it, log it. 5. Access Control: Not everyone needs the keys to everything. 6. Human Oversight: AI decides nothing alone. 7. Compliance Tracking: Map your systems to the rules that apply. 8. Audit Logs: If you can't prove it, it didn't happen. Most companies skip straight to compliance. But compliance without the other 7 layers is just paperwork. Start with an AI inventory. List every tool your team uses. Every chatbot. Every auto-scorer. Every copilot. Most leaders discover 3x more AI systems than expected. That one step changes the conversation from "we should do something" to "here's exactly what we need to govern." Which of these 8 is the biggest gap in your organization? โฌ๏ธ Let me know in the comments Credit to Alex Miguel Meyer. Follow him for more.