The executive office is becoming a systems job

The appeal of an AI chief of staff is easy to understand. You want something that already knows what's going on. It remembers the decision from last week, notices the project that has gone quiet and brings you the information you need before you think to ask for it. Ideally, it can move some of the work forward too.

You'd like to stop carrying quite so much of the business around in your head.

That is an attractive promise. It helps explain why the chief of staff label is appearing on software, personal AI setups and even new job descriptions for people hired to build these capabilities.

I think there's a meaningful change underneath the marketing. More of the work surrounding an executive can be supported by connected systems that retain useful information and act on it. Deciding how those systems should work is becoming part of the job itself.

“AI chief of staff” can mean very different things

These examples shouldn't be treated as interchangeable. Together, though, they show different attempts to address a similar ambition: having more of the coordination around a business handled deliberately, with less dependence on someone remembering to initiate every step.

Why this idea is getting attention now

The underlying problem is familiar. Information about the business lives in different places, and someone has to make sense of it.

A project tool can tell you that a deadline is Friday. An email may explain why the deadline matters. A conversation may reveal that the person responsible is waiting for a decision. Looking at any one of those gives you part of the answer.

Executive support has long involved putting that picture together. What makes the current AI opportunity interesting is the ability to work with information in the form people produce it: messages, documents, conversations and incomplete requests.

Connected AI can, depending on its access and tools, retrieve relevant material, interpret it and take steps in other software. Saved context and reusable instructions can give that work continuity. AI-assisted building also gives people more ways to adapt a tool to their own needs, as Kupp's example illustrates.

That combination makes a different kind of support imaginable. A system can be configured to check for a particular condition, gather the relevant information and prepare the next action. The person using it doesn't have to begin every interaction by explaining the business again.

My reading of the enthusiasm is that people want relief from constantly reassembling the picture. They want help staying oriented and following through. “Chief of staff” is an appealing name for that, even when the software covers a much narrower part of the actual role.

The title promises a relationship, while the product needs a design

When someone says, “I want AI to be my chief of staff,” they're describing an expectation: understand what matters to me and help me stay on top of it.

To build something useful from that expectation, someone has to make it specific.

What counts as important? Which information is current? What should happen when a request arrives? What can the system do independently? How does it recognize that an issue was resolved in a conversation it couldn't access?

Those choices shape the service the executive receives. They determine whether an alert is helpful, whether a recommendation has the right background and whether the system knows when to stop following up.

Designing and managing how information, software and people work together around the executive.

That includes choosing what to automate, but it extends to how the whole arrangement behaves over time. Someone needs to make sure yesterday's exception doesn't become tomorrow's standing instruction. Someone needs to decide which problems deserve attention and which notifications can be removed.

The executive might own that work themselves. It could sit with an executive assistant or chief of staff, or be shared with operations and technical colleagues. The title matters less than whether someone understands both the business need and the system being used to meet it.

Some professional judgment becomes part of the system

This is where the work gets interesting for people already in executive operations.

You may know that a certain customer's requests need an earlier review because of an upcoming renewal. You know which internal updates are useful to the executive and which simply repeat information they already have. You know when a missed deadline needs a conversation rather than another reminder.

Some of that knowledge can be expressed as instructions, examples or conditions that software can use. Some will remain situational and require a person. Figuring out the difference is part of the design.

For example, “keep track of important customers” gives AI very little to work with. A more useful setup identifies which customers are in scope, where the current relationship information lives, what kinds of changes deserve attention and who reviews the findings. As priorities change, that setup needs to change with them.

There is a technical term for part of this: context engineering. In plain language, it means arranging for AI to have the information and instructions it needs for the job at hand. Anthropic's guidance describes this as ongoing work involving tools, retrieved information and history, rather than relying on the wording of a prompt alone. It also warns that supplying more information can make relevant details harder to use. Anthropic's explanation↗.

Executive operations adds the business judgment behind those choices. Which details matter? Who should have access? When has the situation changed enough that the old approach no longer fits?

An experienced practitioner can make a substantial contribution here without writing every integration themselves. They do need enough understanding to specify the behavior, test real situations and recognize when technical help is needed.

The executive office can develop shared foundations

One difficulty with executive support is how personally the role is defined. Different leaders need different things. Even two executives with the same title can work very differently.

That makes a single universal system a poor fit. It doesn't mean every arrangement needs to be invented from scratch.

Keeping a current record of priorities is a recurring need. So is tracking commitments, preparing for decisions and carrying useful context from one conversation to another. These functions can have reusable structures, with room for the executive's preferences and the company's circumstances.

This is where I see a bigger opportunity for the field. We can develop ways of working that people can adapt, explain and maintain. An executive's preferences can sit within that structure, alongside agreed responsibilities and appropriate AI assistance.

It could also change what a handover looks like. The next person inherits the current priorities, the reasons behind important choices and an understandable account of what the tools do. They still need to build relationships and exercise their own judgment. They have a better starting point.

Prepare a handover someone can use shows one way to put that continuity into practice.

That is a more useful ambition than expecting every incoming assistant or chief of staff to create their own private collection of workarounds.

The hype can help or distort this shift

There's a commercial appeal to the title too. “Chief of staff” suggests proximity to leadership, broad awareness and initiative. A product borrowing that name is asking to be trusted with a much bigger part of the working day. I would read the label as an ambition and a positioning choice. The functions underneath it still need to earn that trust.

The chief of staff label can make the software sound more complete than it is. It can also flatten a role that may involve resolving disagreements, representing a leader and influencing decisions across the business.

Those responsibilities don't disappear because a system has access to the calendar. Nor should every executive-support professional suddenly be expected to run company-wide AI implementation alongside a full existing workload. The technical role GC AI describes is a particular hiring choice, and not a new minimum standard for everyone in the field.

But dismissing the entire idea would miss something useful too. People are trying to make continuity, anticipation and follow-through available through software. That creates room for practitioners to help define what good support looks like, and how much of it can be delivered reliably in this way.

I think the strongest version of this shift gives executive operations a clearer place in designing how the business runs around its leaders. It recognizes the work of choosing the approach, configuring the tools and keeping the arrangement useful as the company changes.

An executive assistant might take ownership of a few well-defined workflows. A chief of staff might coordinate a broader set across the leadership team. The scope should fit the person, the organization and the support available.

The future of this work will partly be shaped by the people building the software. It should also be shaped by the people who understand the job well enough to tell them what it needs to do.

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