By function
Executives do not need another dashboard. They need a decision packet that is ready when the question is live.
Decisions wait because the context is in five systems and three inboxes. The agent should assemble the evidence. The executive should still make the call.
12%
of CEOs report both higher revenue and lower cost from AI. Fifty-six percent report neither.
PwC, 29th Global CEO Survey1
How I see it
Executive and decision agents
An executive agent is a research-and-exception system with a very clear owner. It prepares the weekly operating picture, flags the cases that need a decision, and drafts the options. It does not quietly decide for the company.
This is where COOs feel the job. Newly hired leaders need a visible win. Established leaders need a result that advances them. Long-tenured leaders need to show they can lead the next chapter. A decision agent can support that only if it is tied to a real operating workflow.
The failure mode is a daily memo nobody asked for. The success mode is a shorter time from question to decision on a recurring class of calls: pricing exceptions, capacity, vendor issues, account risk.
Common mistakes
What teams usually get wrong.
A general executive assistant with no decision class
Open-ended briefing has no baseline.
Removing the decision-maker
Accountability cannot be delegated to a model.
More slides, faster
If the meeting does not change, the agent did not create leverage.
A useful diagnostic
Five questions before you fund the work.
Which recurring decision is delayed by missing context?
That is the first executive-agent use case.What does a good packet contain in two pages?
If you cannot say, the process is the first fix.How often does the same decision type appear?
Rare decisions should stay fully human.Will the executive use the packet in a real meeting?
If not, do not build it.Is there a larger workflow win underneath the decision?
Sometimes the better project is the operations agent that feeds the packet.
Economic model
Decision speedrecurring decisions × hours of packet assembly × loaded executive and analyst cost
The larger value is often the operating result of a faster call, but start with the assembly cost you can measure.
Three credible paths
How far should you go?
Do not force one solution. Choose the path the economics, the risk, and the organization can support.
Improve the work you already have
Keep the process mostly intact and use AI on the bottlenecks that create delay, rework, or follow-up.
The workflow is already sound and a few steps create most of the friction.
Gains are usually incremental. The operating economics do not change much.
Redesign the workflow around AI
Question every handoff, queue, and duplicate step, then rebuild the process around what AI can now do.
The process grew over years and coordination now costs more than the work itself.
Requires process change, clearer ownership, and a willingness to retire old steps.
Put an agent on a high-value outcome
Give an agent responsibility for one valuable result across systems, with humans at the control points that require judgment, authority, or risk acceptance.
The workflow is high-value, variable, multi-step, and worth engineering for production.
Needs stronger architecture, evaluation, controls, and monitoring. This is not a prompt project.
When this is the wrong next step
Do not fund an agent here.
- The executive wants a companion, not a decision class.
- The underlying data is not trusted and nobody will fix that.
- The real need is a weekly operating review discipline, not software.
A useful next step
Bring one workflow. Get guided into production.
We guide the implementation, go deep on the technical path, and stay hands-on through operations — or tell you when a simpler answer is better.
Discuss an AI opportunity