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Make responsibility work
AI Governance Is Becoming an Operating System Problem
Connect policies to permissions, review points and decisions people can explain.
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Better questions. Better AI decisions.
Ideas, evidence and practical ways forward—for the people putting AI to work.
IN FOCUSTrust & governance
From regulation to everyday practice
EU AI Act Readiness Is Not the Same as Operational AI Governance
Turn AI Act readiness into clear responsibilities, usable controls and evidence of what actually happens.
Read the analysis 9 min readNext step: talk to Sten Franke
Bring your question. Together you agree the next step and its scope.
Explore the thinking
16 articles · English
What may an agent do?
Your Agent Has Tools. Who Gave It Authority?
Define the boundary between a useful recommendation and an action with real consequences.
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Look behind the claim
AI Vendors Make Claims. What Can You Actually Prove?
Read product claims alongside their sources, scope and unanswered buying questions.
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What result are we protecting?
The Missing Question in AI Governance: What Business Outcome Are We Protecting?
Start governance with the business outcome, then choose the controls that matter.
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Change the way work happens
What an AI-First Organization Actually Has to Change
Build the roles, operating habits and feedback loops that make AI useful beyond a pilot.
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Commit with clear conditions
Can We Trust AI — and Still Go All-In?
Separate confidence in a technology from the evidence needed for your next commitment.
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Buy a capability, define its limits
Buying an AI Agent Is Not the Same as Trusting It
Compare agent capabilities with permissions, failure handling and operating costs.
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An inventory is a starting point
The AI Governance Gap: Why Inventories, Policies and Leaderboards Don’t Govern Agents
Follow an agent from recorded identity to permitted action, review and recovery.
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Make the next stage repeatable
AI Does Not Scale by Itself
Test the workflow, human effort and ownership before extending a promising pilot.
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Measure margin and customer trust
Retail AI in 2026: Dynamic Pricing and Personalisation, From Promise to Proof
Distinguish pricing from personalisation and design a test with meaningful commercial measures.
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Make synthetic media recognisable
Synthetic Faces and Voices in 2026: From VASA-1 to Deepfake Rules
Trace consent, disclosure and responsibility across the production and distribution workflow.
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Find the right shortlist
How to Navigate 961 AI Offerings: A Buyer's Guide to the 2026 AI Landscape
Use tasks, evidence and operating conditions to narrow a research inventory. The live catalogue has its own scope.
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From forecast to a stock decision
AI in Inventory and Logistics 2026: What the Evidence Measures
Compare forecast quality with service levels, stock costs and the consequences of being wrong.
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Read the measure behind the number
AI Growth Facts 2026: What the Evidence Shows Across Industries
Separate adoption, spending and realised value before using market statistics in a decision.
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Turn principles into choices
10 Ethical AI Issues in 2026: From Principles to Dated Rules
Make fairness, accountability and human judgment concrete in the way an AI system is used.
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