Ai Risk

Most teams rush into AI governance. → Guardrails → Monitoring → Human override → Compliance checks All fine. But it assumes something that usually isn’t true: → Clear data ownership → Stable definitions → One agreed …

Data governance is all about the inputs. AI governance handles the outputs. Both are critical, and neither works alone. 👉 𝗗𝗮𝘁𝗮 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲: 𝗣𝗿𝗼𝘁𝗲𝗰𝘁𝘀 𝗪𝗵𝗮𝘁 𝗚𝗼𝗲𝘀 𝗜𝗻 👉 𝗔𝗜 𝗚𝗼𝘃𝗲𝗿𝗻…

The 10 most important AI topics for senior leaders AI is no longer an IT experiment. It’s a board-level risk. Across industries, I see executives circling around the same themes. Different context. Same pressure. Here…

I made a decision to move the majority of my workloads away from OpenAI to Anthropic! Not because of performance. Not because of features. But because of something far more important: 🎯Trust 🎯 This surprises most, be…

AI risk doesn’t start where people think. It’s not just the model. It’s everything around it. Here are the 3 levels where things quietly break 👇 𝗟𝗲𝘃𝗲𝗹 𝟭 - 𝗠𝗼𝗱𝗲𝗹 𝗿𝗶𝘀𝗸 (𝘄𝗵𝗮𝘁 𝘁𝗵𝗲 𝗔𝗜 𝘁𝗵𝗶𝗻𝗸𝘀)…

🤖 What fails first in an AI environment? The model—or the data systems that quietly determine what the model can see, retain, and leak? According to Cloud Security Alliance’s Data Security within AI Environments, the r…

🧠🤖 When AI Becomes the Default Decision-Maker New findings from Wharton School of the University of Pennsylvania reveal a powerful behavioral shift: people tend to defer to AI far more than expected. In a study of 1,3…

Most executives learned AI too late. You still have 90 days. Your board asks about AI governance. You either demonstrate judgment or watch them hire someone who can. Most leaders don't have an AI literacy problem. They…

AI risk isn’t the model. It’s the data no one truly owns. ⚠️ Many AI failures don’t happen because of weak algorithms. They happen because the underlying data is inconsistent, unclear, or poorly governed. Think about …