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8 articles
While high-risk AI rules were pushed to 2027, the EU AI Act’s transparency duties for chatbots, synthetic content and deepfakes already apply. This playbook explains who is affected and how to implement disclosure and marking in practice.
AI agents that plan and act across systems break the assumptions behind traditional AI governance. This article lays out a practical control framework, drawing on Singapore’s agentic AI governance model and emerging enterprise practice.
US model risk guidance was rewritten in April 2026 and EU high-risk AI rules for credit scoring now apply from December 2027. This guide explains what changed and how lenders should govern machine learning credit models in the meantime.
The March 2026 Basel III endgame re-proposal lowers expected capital for the largest US banks but raises the bar on exposure data, classification and calculation systems. Here is what credit risk teams should prepare now.
Almost every company now uses AI, yet few can show it in their earnings. This playbook explains why value stalls between pilot and P&L, and how to build a portfolio, metrics and operating model that close the gap.
AI can make Lean and Six Sigma faster and more continuous, but only if it is applied with discipline. This playbook shows where AI fits across DMAIC and daily management, what to avoid, and how to start.
As AI agents take on real operational work, operations leaders need to manage them alongside people: allocating work, controlling quality, planning capacity and tracking cost. This playbook adapts proven operational excellence methods to the hybrid workforce.
AI coding agents are tempting companies to build what they once bought. This guide explains what has really changed in the build-versus-buy equation, what has not, and offers a practical scoring model for 2026 decisions.
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