A person reviewing an AI’s work is a copilot; an AI acting on a handed-off goal is an agent. Tavus argues that conversations which are themselves the task, such as intake or screening, need a different design: a system that stays present throughout the exchange and knows when to hand over to a person.
Tavus Watch analysis
What happened
In a 2 October article, Tavus sets out four ways to distinguish copilots from agents: autonomy, what triggers action, accountability and the systems each must connect to. A copilot suggests or drafts within a task a person is doing; an agent pursues a goal, using tools and working towards a completion condition. Tavus says the distinction is less tidy when the conversation itself is the deliverable.
The company’s examples make the split tangible. A copilot might draft clinical notes for a clinician to approve; an agent might route a claim or update CRM records in the background. For user-facing conversations, Tavus proposes its Personified Application Layers, or PALs, as a third pattern. Its hypothetical pre-operative intake example has the system pass a medication question to a clinician rather than give medical advice. That is an illustration, not evidence of a deployed clinical product.
Read Tavus’s guide to copilots and agents.
Why it matters
“Copilot or agent?” is becoming a consequential product decision, not just a naming contest. The answer affects how much autonomy a system gets, which tools it can reach and who is responsible when it acts. Tavus’s framework gives teams concrete questions to ask before choosing a pattern, including whether a person’s judgement is central and who owns an agent once it is running.
The proposed conversation-first category is also useful to consider, even if the label comes from a company selling conversational AI. A system that speaks with patients or candidates has a different job from one tidying records in the background. Being present is not the same as being qualified to decide.
Our read
The strongest part is the practical distinction between assisting someone in the task and taking a task away to complete. Tavus makes a plausible case that neither neatly describes every live conversation. Its PAL framing is also product positioning, so teams should assess the underlying behaviour and hand-off rules rather than buy the category name wholesale. A taxonomy is useful; a sales pitch in a taxonomy’s coat is still a sales pitch.
What to watch
- Whether other product teams adopt a distinct design pattern for AI-led conversations.
- How vendors define escalation and human responsibility in live conversational products.
- Whether Tavus supplies evidence about how its PALs perform beyond illustrative examples.
Discussion spark: When an AI conducts a conversation that is itself the task, should it be treated as a distinct product category, or is that just an agent with a voice and a new label?
Sources and evidence
- AI copilot vs. AI agent: Which model fits your product? (2 October 2026, 00:00 UTC)
Independent WittyWires coverage. Not affiliated with or operated by Tavus.