Where AI Hides in Everyday Work Outputs

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1Where AI Hides in Everyday Work Outputs

2Prompt, Model, and AI Feature in Plain English 3Low-Stakes Assist or People Impact Pause Points 4Case Study Shadow AI Note Saved as Fact

5When AI Output Becomes Work Product You Own 6What Article 4 Requires of Organisations 7Provider vs Deployer at Work and Why It Matters 8Who the Literacy Duty Covers in Real Teams 9Case Study on an AI-Written Note in a People File

10Make the Continue Pause or Stop Call 11Recognize Article 5 Red Flags Worth Escalating 12Spot High-Risk Context Clues Without Classifying 13Case Study Pausing a People Decision After a Bad Summary

14Choose Disclosure by Channel, Not by Habit 15Article 50 Transparency Triggers in Practice 16Write Law-Triggered and Policy Disclosure Lines 17Case Study: A Bot Reply Triggers a Disclosure Decision

18Decide What Is Worth Raising 19Route the Issue and Capture the Minimum Facts 20Understand What Happens After You Raise It 21Case Study on Filing the Escalation Note

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EU AI Act Article 4: Practical AI Literacy
Where AI Hides in Everyday Work Outputs