AI Capability Framework
AI capability is the ability to use AI thoughtfully, critically, and effectively in real situations.
Core dimensions
1. Curiosity
Asking why, exploring alternatives, and continuing beyond the first answer.
2. Communication
Giving context, expressing goals, refining questions, and making expectations visible.
3. Verification
Checking claims, identifying uncertainty, comparing sources, and recognising hallucinations.
4. Reflection
Using AI output to examine one’s own assumptions, reasoning, and blind spots.
5. Collaboration
Treating AI as a thinking partner rather than a one-shot answer machine.
6. Context Building
Providing relevant knowledge, examples, constraints, personal history, and domain information.
7. Workflow Design
Turning repeated work into dependable human–AI processes without losing oversight.
8. Responsibility
Protecting privacy, understanding consequences, and knowing when human judgement must remain decisive.
Human intelligence and AI capability
Traditional intelligence tests may measure parts of reasoning, pattern recognition, memory, or processing speed. AI capability measures something different: how effectively a person thinks and acts with AI over time.
It is not a replacement for intelligence, education, or experience. It is a new layer that can amplify—or expose—the way a person already thinks.
Evidence of capability
Capability should be demonstrated through real behaviour, not only through multiple-choice questions. Useful evidence may include:
- Improving an AI answer through several rounds of dialogue
- Detecting errors or missing assumptions
- Building reusable context or knowledge
- Creating a transparent workflow
- Explaining AI output to another person
- Knowing when not to rely on AI