AI Governance
AI governance is the set of policies, processes, and technical controls an organization uses to manage the risks of deploying AI systems. This includes deciding which use cases are appropriate for AI, how models are evaluated before deployment, who is accountable when they fail, and how you handle data privacy, bias, and regulatory compliance. The EU AI Act, which took effect in 2024, made governance a legal requirement for companies operating in Europe—classifying AI systems by risk level and imposing obligations that scale accordingly. But governance is not just a compliance exercise. Organizations without clear AI governance end up with shadow AI: employees using ChatGPT to draft contracts, analyze customer data, or make recommendations with no oversight, no audit trail, and no idea what the model was trained on. Governance is how you use AI aggressively without using it recklessly.
Related terms:
WWGPTD
WWGPTD began as internal Slack shorthand to remind teams that using AI isn’t cheating but the essential first step. It reframes strategy by asking how AI.
Context Window
A context window is the maximum amount of text a language model can process in a single call—input and output combined—measured in tokens.
Chain-of-Thought
Chain-of-thought prompting, introduced by Google Research in 2022, transforms AI from an answer machine into a reasoning partner by explicitly modeling the...