AI & Data·5 min read
Data Questions to Ask Before Funding Your Next AI Initiative
Investment committees approve AI projects with a value case that ignores data risk. A short checklist prevents the post-mortem finding.
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AI & Data.
AI agent deployment, data governance, and enterprise AI risk from practitioners who build these systems.
AI & Data·7 min read
AI Governance as an Operating System, Not a Policy PDF
Most organizations have AI principles. Few have controls that execute at runtime. The gap between policy and enforcement is where incidents happen.
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AI & Data·6 min read
What Shadow AI Means for Your Risk Register
If your risk register treats AI as one line item under technology risk, it is out of date. Shadow AI touches four risk categories at once.
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AI & Data·6 min read
Before You Secure AI, Fix Your Data Map
Only 35% of organizations have full visibility into unstructured data. Without data discovery and classification, AI security controls have no foundation.
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AI & Data·7 min read
Shadow AI Is Already Inside Your Organization. Here Is How To Find It.
78% of employees bring their own AI tools to work. Only 36% have governance policies. A 10-day sprint closes the gap.
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AI & Data·7 min read
Claude Mythos Preview: Anthropic Built Its Most Powerful Model and Chose Not to Release It
Anthropic built Claude Mythos Preview and chose not to release it. The first frontier model withheld for cyber risk reshapes AI governance playbooks.
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AI & Data·8 min read
The End of Single-Vendor AI Stacks: Why Enterprises Need a Model Portfolio
Single-vendor AI stacks create concentration risk enterprises don't yet see. A portfolio approach across cloud, open-source, and edge models is overdue.
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AI & Data·7 min read
Trust Shockwaves in AI Platforms: Why Vendor Risk Now Includes Political Exposure
AI platform loyalty can fracture overnight. The ChatGPT-Claude shift shows why vendor evaluation must now include political and reputational risk.
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AI & Data·7 min read
AI Data Governance: The Same Problem Enterprises Already Solved
Enterprise AI data concerns mirror cloud migration fears of 2010-2016. The governance discipline is identical, only the processing engine changed.
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