AI autonomy
AI autonomy is how much an AI system is allowed to act on its own — from only observing, to proposing actions, to acting within limits, to leading a process. Higher autonomy means less human involvement per action; responsible systems make the level explicit and adjustable.
Key characteristics
- Observe — the teammate watches only; no auto-runs and no proposals (maximum control)
- Propose — it reads and explores on its own but asks before any change (the default)
- Act — it creates new in-lane work on its own, but asks before changing anything you've already touched
- Lead — broad in-lane authority, including updating its own in-lane work, for high-trust roles
- Higher autonomy needs stronger guardrails and logging
- Sensitive actions (sending, posting, paying, publishing) stay gated regardless of level
- The control that lets you trust an AI teammate with real work
Example
A business sets its AI teammate to 'propose' for client emails — it drafts every reply for review — but allows 'act' for internal status updates it has come to trust, while sending payments stays gated no matter what.
How it relates to Kuvai
Every Kuvai teammate has an explicit autonomy level — it defaults to Propose (it drafts, you decide), and you raise it only where you've built trust. Sensitive actions like sending email, posting to a ledger, or paying are never-autonomous regardless of level, and every action is logged with its reason. Autonomy you control is how AI becomes safe to trust with real work.
Related terms
Agentic AI is artificial intelligence that plans and takes multi-step, autonomous action toward a goal — rather than just generating a single piece of text in response to a prompt. Where a standard generative model answers what you ask, agentic AI decides what needs to happen, breaks the goal into steps, uses tools to carry them out, and adapts as it goes, working with limited human input.
AI agentAn AI agent is software that perceives its environment, decides what to do, and takes action toward a goal — often autonomously and over multiple steps — by using tools, calling APIs, and reasoning with a language model. Unlike a chatbot that only generates text in reply to a prompt, an agent can act on the world: it can search, read, write to systems, and chain steps together to complete a task rather than just answer a question.
AI teammateAn AI teammate is a software colleague that owns a defined job end-to-end — grounded in a business's own documents and data, connected to its tools, and running on a schedule. Unlike an AI assistant you prompt, a teammate works continuously, accumulates your context, and drafts actions for your approval rather than waiting to be asked.
Self-learning AISelf-learning AI describes an AI system that improves at a job over time from feedback and experience, rather than performing identically forever. In Kuvai, self-learning is operational, not model retraining: after completed work, a teammate reviews how it went, captures durable facts, and proposes refinements to its own instructions that you approve. It improves from your corrections — it does not change on its own or 'get smarter.'
Compounding delegationCompounding delegation is the idea that work you hand to an AI teammate gets easier and more valuable to delegate over time — because the teammate accumulates context, improves from your corrections, and can take on more autonomy as it earns trust. It's the Kuvai term for what happens when memory, curiosity, self-learning, and autonomy stack: the more a teammate works with you, the less you have to repeat yourself.
AI memoryAI memory is an AI system's ability to retain information across sessions — your preferences, your business's facts, decisions, and summaries of past work — instead of starting from a blank slate every time. In Kuvai, each AI teammate keeps its own private notebook of how your business works, so it stops asking you to re-explain the basics and gets more useful the longer it works with you.