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Agentic workspace management: AI that runs the office
4 min read
Introduction
Hybrid work has made a lot of things easier, but not the organization behind it. Who is in the office when, which desk stays free, whether the meeting room fits eight people, and why half the booked desks end up empty: all of that costs someone in the company time, usually on top of their actual job.
Agentic workspace management is the approach of handing exactly this work to an AI. In this article, you’ll learn what’s behind it, how it differs from traditional desk booking tools, which organizations it pays off for, and how anny puts it into practice.
In short: what is agentic workspace management?
Agentic workspace management describes the management of desks, rooms, and shared resources by an AI that doesn’t just answer requests but handles bookings and admin tasks on its own.
“Agentic” is the technical term for AI systems that act instead of only answering. An AI agent gets a goal, fetches missing information, decides based on the rules you set, and sees the task through.
Applied to the workplace, that means:
An employee writes, “I need a desk on the third floor on Thursday, ideally next to the design team,” and gets the booking, not a list of options.
A team lead says, “We need a room for twelve people with video conferencing next Wednesday from 10 a.m. to 4 p.m.,” and the room is booked.
And on the admin side: “From January, the fourth floor is closed. Move the desks to floors two and three” gets done without anyone rebuilding booking rules by hand.
Why traditional desk booking tools hit their limits
Most companies have a desk booking tool by now. Still, the effort stays high, for three reasons.
The interface is a hurdle. Every tool has its own interface, its own logic, its own menus. Someone who comes into the office twice a month has forgotten the steps by the third time and ends up not booking at all.
Administration stays with people. Adding new spaces, closing floors, changing quotas, setting rules for teams: these are configuration tasks that someone with admin rights has to do, often office management or IT.
The systems know too little about each other. The desk is in one tool, the meeting room in a spreadsheet, and an event gets organized over chat. Anyone who needs all three books in three places.
What makes agentic workspace management
Three traits belong together:
The AI gets things done instead of only showing them.
It takes a request, checks availability and rules, books, reschedules, or cancels, and confirms. No step is left for later.
It works in both directions.
For employees, it’s the go-to contact for everything about desks, rooms, and resources. For administrators, it’s an agent that sets up spaces, quotas, and rules by message.
It draws on a single source of truth.
The AI reads directly from the booking system. So it can’t assign a desk that’s blocked or promise a room that was booked long ago.
The difference at a glance
Traditional desk booking | Chatbot on top of the tool | Agentic workspace management | |
|---|---|---|---|
Requests in your own words | No, a form | Yes | Yes |
Completes the booking | Manually by the user | No, refers you elsewhere | Yes, on its own |
Combines several resources | Usually separate | No | Yes, in one step |
Sets up spaces and rules | Through an admin interface | No | By message |
Data source | Its own database | Separately maintained knowledge | The booking system itself |
Effort for office management | Stays | Stays | Largely goes away |
Who agentic workspace management pays off for
It fits best when several things come together: there are more people than assigned desks, attendance changes, and administration happens on the side.
Typical situations:
Companies with hybrid work models, where desks, meeting rooms, and parking spaces are assigned anew every day
Organizations with multiple locations, where different rules and quotas apply to each building
Coworking spaces that serve external members and day guests in addition to internal administration
Universities and public institutions, where many people share limited study, work, and advising spaces
Companies with space projects, such as a move, downsizing, or renovation, where rules change often
The approach matters less if everyone has an assigned desk and nothing changes. Then there’s simply little to coordinate.
What the AI takes off your plate
For employees
Booking works through what’s already open: a chat window, a message, soon MS Teams, too. Nobody has to open a tool they use twice a month.
The AI also understands vague requests. “Something quiet for Thursday morning” is enough if the system knows which areas count as focus zones.
For administrators
This is the bigger lever, because this work never goes away, it only gets spread around. With the anny Agent, you describe changes in your own words instead of configuring them:
add new spaces, floors, or locations
block desks, for example for renovations or events
set quotas for teams or departments
change rules, such as how far in advance people can book
adjust prices or internal cost allocation where relevant
Because the agent works directly in the booking system, changes apply immediately to every request that comes in afterward.
With analytics
Which spaces are used, which sit empty, which days are full? These questions drive lease and space planning decisions. Instead of building reports, you ask anny AI and get concrete suggestions.
Why an API isn’t enough
The obvious idea would be to connect an AI assistant to an existing desk booking tool through an API. Many providers take exactly this route.
But then you still have two systems that only half understand each other. The assistant sends a request and works with whatever just arrived. In practice, this shows up in three places:
The data lags behind. There’s a sync between request and response, and right then the desk may already be gone.
The rules get lost. A workspace system knows dozens of special cases: team zones, quotas, lead times, access permissions. Usually only a fraction of that makes it through an API.
Errors surface late. Nobody notices a double booking when it’s confirmed, only at 9 a.m. when two people are standing at the same desk.
That’s why agentic workspace management starts deeper: communication and booking logic are one system, not two connected ones.
The question that always comes up: what about the data?
An AI that manages workspaces knows a lot. Who is in the office when, who sits next to whom, how often someone comes in. That’s personal data, and in many companies it’s not just IT that has a say, but also the works council.
So two things are decisive:
Where the data is processed. Many solutions rely on large models from international providers. anny runs a custom-tuned AI model on infrastructure in Europe, with no data shared with third parties.
What is analyzed and what isn’t. You can analyze space usage meaningfully without building attendance profiles of individuals. Decide deliberately how far the analysis goes before you roll out a system.
Where the term comes from and what role anny plays
“Agentic” is the buzzword the AI industry is using to describe its next stage. After assistants that answer come agents that act. Agentic workspace management applies this principle to managing desks and shared resources.
At anny, we’re actively driving this development. Since 2020, we’ve been building booking software that more than 1,500 companies and organizations use today, many of them with hybrid work models, along with coworking spaces, universities, libraries, and public institutions.
Over that time, we’ve built something that can’t be copied in a few months: a platform that reflects how organizations actually allocate their resources, with quotas, zones, permissions, subscriptions, and special rules for each location.
That’s the prerequisite for agentic AI. An AI agent can only act as well as the logic it works in. That’s why we didn’t put the AI next to our platform. We built it in:
Externally, the AI takes requests by phone and chat and sees them through to a finished booking. WhatsApp, Instagram, email, and MS Teams will follow.
Internally, the anny Agent handles administration, from setup to day-to-day changes, all by message.
Underneath runs a custom-tuned AI model, operated in Europe.
Try agentic workspace management with anny
For a long time, workspace management was a tool you first had to learn how to use. Agentic workspace management changes that: you say what you need, and the system does the rest.
In anny, you can do that right away with the anny Agent. Describe how your office works in your own words, for example “Three floors, 40 desks, two meeting rooms, bookings up to two weeks in advance, third floor for the engineering team only.” In a few minutes, your booking system is ready, including spaces, rules, and permissions.
No training, no setup call, no configuration menu. And whether you’re testing or live, your organization’s data is processed by a custom-tuned AI model in Europe, with no data shared with third parties.
👉 Set up your workspace for free
Prefer a walkthrough to getting started yourself? In a personal demo, we’ll show you what agentic workspace management would look like for you, with your spaces, your rules, and your workflows.
