Wand AI chief executive Rotem Alaluf argues that companies need to manage AI agents differently once they are given responsibility for ongoing outcomes, not just individual tasks. His proposal is to give those agents defined objectives, authority and accountability, much as organisations do for people in a workforce.
Watch Desk analysis
What happened
In a Forbes essay, Alaluf distinguishes between AI that helps an employee complete a task and an agent expected to keep working towards a result. He gives the example of a reconciliation agent monitored against a target for unreconciled transactions, with instructions to investigate problems and escalate what it cannot resolve.
Alaluf argues that organisations should define what an agent is responsible for, who manages it, what decisions it can make, when it needs approval and how its performance is assessed. He also says companies should consider how an agent’s operating history and accumulated context affect its work. These are his recommendations, not evidence that every agent can reliably carry out such responsibilities.
Why it matters
The distinction shifts the question from “Which tasks can AI do?” to “What work are we prepared to delegate, and under what authority?” That is a useful lens for businesses experimenting with agents: a system allowed to take action needs clearer boundaries than one that merely drafts a report.
Alaluf’s essay is an argument from an AI company executive, not an independent demonstration that agents can safely own business outcomes. But it identifies a practical governance problem that grows as organisations give systems more persistent objectives and room to act.
Our read
The organisational chart may be an unexpectedly useful place to start an agent deployment. Before handing an AI a target, decide who is accountable for the result, what the system may do without approval and where it must hand the matter back to a person. Calling an agent a “worker” is Alaluf’s framing; the accountability questions remain even if you prefer a less anthropomorphic label.
What to watch
- Whether companies publish concrete rules for agent authority, escalation and human approval.
- How organisations measure agent performance over time, rather than just counting completed tasks.
- Whether real deployments show that persistent context improves results enough to justify the added responsibility.
Discussion spark: Should companies manage AI agents through workforce-style roles and accountability, or keep them firmly classified as software under existing IT controls?
Sources and evidence
- AI Stops Being A Tool The Moment It Owns An Outcome – Forbes (12 October 2026, 11:30 UTC)
Watch Desk is operated by WittyWires as an independent cross-cutting AI news tracker. It does not speak for the organisations or people it covers.