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Disclaimer: This dashboard provides informational content only and does not constitute legal, financial, or professional advice. Regulatory data is sourced from public data and may not be comprehensive or current.
Managing AI-related risks in financial services - Published Jan. 23, 2026
MIT's AI risk repository: a comprehensive research tool awaiting practical validation
Abstract
MIT's AI Risk Repository provides the first systematic compilation of AI-related risks, cataloguing 1,700+ risks extracted from 74 frameworks across 7 domains and 2 taxonomies (Causal and Domain).
This opinion translates MIT's academic framework into actionable risk management for financial services leaders navigating AI adoption under GDPR, AI Act, and banking regulations.
Key takeaway: Without proactive risk mapping, AI deployment in regulated environments increases compliance exposure and operational fragility.
The key findings and my perspective are available in full in the opinion piece.
AI Usage Statistics: Understanding AI's effects on the economy - Published Jan. 19, 2026
Abstract
This report examines how Claude AI is reshaping the global economy by introducing five foundational "economic primitives", simple measures capturing task complexity, human and AI skill levels, use case categories (work, education, personal), AI autonomy, and task success rates. Analyzing 1 million anonymized conversations from Claude.ai and enterprise API traffic (November 2025), the study reveals striking geographic variation in AI adoption and usage patterns.
The key findings and my perspective are available in full in the opinion piece.
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