The honest answer is both, and treating them as only one is the mistake. AI agents have a dual nature: they are part tool and part teammate, according to BCG in its research on leading in the age of AI agents. A company should give an agent the autonomy and accountability of a teammate while keeping the governance and oversight it would apply to any tool.
Why the Question Matters Now
The choice is no longer theoretical. BCG reports that 35% of organizations have already adopted agentic AI, with another 44% planning to deploy soon. That puts a large share of companies inside or near the decision. The same research found that 65% of managers expect agents to take over at least half of their job within three years, which means the relationship between people and agents is about to become the central design problem of the organization, not a side project for the technology team.
When you treat an agent purely as a tool, you under-invest in accountability. Nobody owns its output, its handoffs are undefined, and its mistakes get absorbed into the noise. When you treat an agent purely as a teammate, you over-trust it, skipping the controls and audit trails that any production system requires. The dual nature is not a contradiction to resolve. It is the operating constraint to design around.
What Changes When Agents Become Teammates
A tool sits in a drawer until someone picks it up. A teammate has a seat, an owner, a set of responsibilities, and a place in the flow of work. The shift from tool to teammate is really a shift in structure. Agents stop being features attached to a workflow and start being roles on the chart.
That structural shift forces clarity that most organizations lack even for their human roles. Every agent needs a single accountability, a clear handoff to the next seat, a way to escalate when it hits the edge of its authority, and a record of what it did. Without that, autonomy becomes chaos. With it, an agent can run a real piece of the business while a human stays accountable for the outcome. The discipline that makes agents safe teammates is the same discipline that makes human teams work: clear seats, clear owners, no overlap.
The Operating Model Has to Hold Both
The reason most agent deployments stall is that the surrounding operating model was built for tools. Permissions, reviews, and reporting all assume a human is holding the instrument. To get the teammate benefits without losing tool-grade control, the org chart, the cadence, and the governance layer all have to treat agents as first-class participants. A scorecard that tracks an agent's KPIs the way it tracks a person's. A priorities and issues rhythm that surfaces an agent's blockers. A governance layer that says exactly what each agent may decide on its own and what it must route to a human.
This is the part you cannot buy as a feature. It is the operating model itself, and it has to be designed once and run continuously.
OTP is built for exactly this. It puts agents on the org chart as teammates: named seats with owners and defined handoffs, alongside the people they work with. Each seat, human or agent, carries a clear accountability, lives on the same scorecard, and operates inside a shared governance layer that sets the boundary between autonomous action and human escalation. The operating model, productized. See how it works at orgtp.com.