Business & Operations  /  05

Leading People and AI Agents

Practise delegation, review, and coordination when a team also includes AI agents.

01 / The approach

A leader can assign work to colleagues and AI systems but remains responsible for objectives, priorities, and decisions. They need criteria for what to delegate, how to check outputs, when to intervene amid contradictions, and how to clarify accountability.

We design scenarios where people and agents produce information and proposals. Participants assign tasks, check evidence, manage uncertainty, and decide when human judgment or team discussion is needed.

02 / How it works

01

Assign the work

Define the goal, constraints, roles, information access, and review points.

02

Assess the outputs

Compare agents’ outputs and colleagues’ contributions, looking for gaps and disagreement.

03

Decide and explain

Revise delegation, involve experts, and give reasons for the final decision.

03 / What to observe


Clarity of tasks and responsibility

Review of AI outputs

Handling conflict and uncertainty

Traceability of the human decision

04 / A concrete example

An operational choice

A team receives conflicting proposals from colleagues and AI agents on an operational priority. The leader asks for more evidence, identifies assumptions, and reallocates work before deciding. This is a practice scenario that can be configured by function and sector.

 

05 / How to tailor it

Cases, roles, agent autonomy, approved tools, and oversight criteria are set with the organization. The simulation distinguishes a system proposal from the human decision.