How to manage AI teammates at work
An AI teammate needs what a new hire needs: a defined role, clear limits, a probation period and a manager. The controls vendors offer differ more than their marketing suggests.
Contents
Most managers have never managed software that answers the phone. The habits that work for a new hire, a clear role, limits on what they may commit to, closer supervision early on, carry over, but the tools for applying them differ by product, and some of the most useful controls sit on enterprise plans.
Leaders expect this to become part of the job. In Microsoft's 2025 Work Trend Index, 36% of leaders said they expected to manage AI agents as part of their role within five years, against 21% of employees; 28% of managers were considering hiring AI workforce managers, and 32% planned to hire AI agent specialists within 12 to 18 months1. Gartner, for its part, predicts that more than 40% of agentic AI projects will be cancelled by the end of 2027, citing rising costs and unclear business value2. Management is the difference between those two outcomes.
The controls vendors offer
The products we reviewed offer four kinds of control. Not every product offers all four.
| Control | What it does | Examples from vendor pages |
|---|---|---|
| Approvals | Holds chosen actions until a person agrees | Lindy holds anything with outside impact3; OpenLazarus lets the company decide what runs automatically and what needs approval4; Artisan offers approvals and escalation rules5 |
| Limits by value or type | Lets a teammate act alone below a threshold and ask above it | OpenLazarus gives the example of a material order over $20,000, or a change to a promised ship date, waiting for a person6; Artisan locks tone and calls to action5 |
| Access | Limits what records and projects a teammate can see | Asana teammates follow existing Asana permissions, and admins choose who can create and change them7; Relevance AI offers role-based access8 |
| Logs and oversight | Shows what a teammate did and why | OpenLazarus logs every action where staff can see it6; Relevance AI offers tracing and audit logs8; Microsoft's Agent 365 lets IT observe and manage agents in one place9 |
Two cautions follow from the table. Audit logs are often a premium feature: Lindy lists them on Enterprise only10 and Asana on Enterprise+11. And some products describe routing and handoffs without a step that holds messages before they go out; 11x's site, for example, describes when agents hand over to human reps but no pre-send approval12.
Relevance AI frames the progression explicitly, as four levels of autonomy from assisted, through copilot with human review, to autopilot and self-driving8. The framing is useful whichever product a company uses: every teammate sits at a level, and the manager's job is to decide when it moves up.
A management routine that works
The routine below adapts ordinary people management to AI teammates. Each step can be done with the controls in the table above.
- Write a job description. One role, the queue it owns, the records it may read and write, and how customers or colleagues reach it.
- Set three lists. What it may do alone, what it must ask first, what it must always pass to a person. Put money thresholds and commitments on the second and third lists.
- Give it what a new hire would read. Price lists, policies, templates, past replies. Sintra's helpers, for example, draw on a shared knowledge base built from the owner's documents and tone of voice13.
- Start on probation. Run the first weeks with approvals on for everything outside-facing, and read every escalation.
- Review weekly. Read a sample of completed work, every escalation and every error. Correct the guidance, then decide whether to widen a limit.
- Track two numbers. The size of the queue it owns, and the share of its work that a person had to correct.
- Name an owner. One person is accountable for each teammate's limits and reviews, as they would be for a direct report.
- Plan the exit. Know how to revoke its access and what happens to the records it created. OpenLazarus, for instance, states that the code and data belong to the customer and can be hosted elsewhere4.
Where the teammate's work should live
Management is far easier when a teammate's actions sit in the same records as everyone else's. An assistant that works inside one manager's inbox leaves the rest of the team without a view of what it did. A teammate with its own inbox and phone number, working on shared records, can be reviewed like any colleague: its emails, calls and changes are where the team already looks. OpenLazarus describes its teammates this way, each with an inbox, a phone number and limits the company sets, working on the same records staff use14.
For companies already committed to a suite, the equivalent is to keep agents inside it. Asana's teammates act on the same plans as the people in Asana7, and Microsoft's agents work across Microsoft 365 data under Agent 3659.
What good management looks like after three months
A well-managed AI teammate is unremarkable. Its queue is cleared daily, its approval list is shorter than on its first day because its work earned it, its escalations reach the right person with the context attached, and its owner can show, from the log, what it did last week and how often it was corrected. That is the standard our ranking of AI teammates for business uses when it weighs approvals, limits and logs, and the cost guide shows how supervision time enters the budget.
Questions buyers ask
Who should manage an AI teammate?
The person who manages the work it takes on. A teammate that answers calls belongs to whoever runs the front office, and one that chases invoices to the finance lead. That person sets its limits, reviews its work and decides when to widen what it may do alone.
Should an AI teammate need approval before it acts?
At the start, for anything that leaves the company or commits money. Lindy, for example, holds actions with outside impact for approval until a job is handed over in full. As its work holds up in review, the approval list can shrink.
What should an AI teammate never be allowed to do?
Each company draws its own line, but common examples are committing to prices or discounts outside a set range, changing promised delivery dates, making legal or contractual commitments and deleting records. Those belong on the list of actions it must always escalate.
Sources
- 2025: The year the Frontier Firm is born (Work Trend Index). Microsoft WorkLab, 23 Apr 2025. Accessed 8 Nov 2026.
- Over 40% of agentic AI projects will be scrapped by 2027, Gartner says (Reuters). The Star / Reuters, 25 Jun 2025. Accessed 8 Nov 2026.
- Lindy: your AI employee. Lindy. Accessed 8 Nov 2026.
- Frequently asked questions. OpenLazarus. Accessed 8 Nov 2026.
- Artisan full product guide (llms-full.txt). Artisan. Accessed 8 Nov 2026.
- OpenLazarus for manufacturing. OpenLazarus. Accessed 8 Nov 2026.
- AI Teammates. Asana. Accessed 8 Nov 2026.
- The home of the AI Workforce. Relevance AI. Accessed 8 Nov 2026.
- Agents in Microsoft 365 Copilot. Microsoft. Accessed 8 Nov 2026.
- Pricing. Lindy. Accessed 8 Nov 2026.
- Pricing. Asana. Accessed 8 Nov 2026.
- Revenue agents for frontier revenue teams. 11x. Accessed 8 Nov 2026.
- Sintra: AI employees for business owners. Sintra. Accessed 8 Nov 2026.
- AI employees for your business: ready-made teammates. OpenLazarus. Accessed 8 Nov 2026.
Updated 8 Nov 2026: First published.