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An AI operating model is a target operating model in which AI carries out a fixed share of the work: which tasks AI performs, who decides, which data and systems sit underneath and how it is governed. We help mid-sized organisations design it and build it.
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Definition
An AI operating model is the way an organisation is set up when AI carries out a fixed share of the work: which tasks AI performs, which people make the decisions, which data and systems sit underneath, and how it is all governed and improved.
Start with the concept itself.
An operating model describes how an organisation delivers its strategy in practice: which processes run, who does what, which systems and data sit underneath and how the organisation is managed. The target operating model (TOM) is the desired future state: the design of how your organisation will work. The gap between today and that TOM is your change agenda.
An AI operating model is the AI version of that target operating model.
It adds a new kind of worker: software that reads, decides within set limits and finishes the job. AI is not a separate discipline alongside the rest; it touches every part. Processes are redesigned around what AI does well, roles shift from doing the work to checking and improving it, and data has to be in order because AI acts on it directly.
Without that design, you end up with isolated pilots that never scale.
That is why we start small and concrete: one process, one team, a measurable result. From there we build layer by layer, until AI is a natural part of how the business runs. At Burgstate we have worked this way since late 2025, month by month, on an ongoing AI programme that now spans four departments.
Building blocks
The same building blocks as in any target operating model, with AI as a new kind of worker. Together they decide whether AI stays an experiment or becomes a fixed part of how you run the business.
What AI contributes to: which goals, which processes and how you measure the return. Without this, you get isolated experiments.
Work redesigned around what AI does well: what AI carries out, where a person checks and where the exceptions go.
Who owns it, which roles shift from doing the work to checking and improving it, and which skills that requires.
Connected systems and reliable data, so AI can work with your own information. This is the layer that is missing most often.
Agreements on use, data and human oversight, a register of AI applications and the obligations under the EU AI Act.
Measuring what AI delivers, adjusting course and extending it. An AI operating model is never finished: it grows with what the technology can do.
Comparison
How an AI operating model differs from the traditional operating model most organisations work with today, and from simply rolling out tools.
| Traditional operating model | Rolling out tools | AI operating model | |
|---|---|---|---|
| Who does the work | People, supported by software | People, with standalone AI tools alongside | AI carries out the work, people steer and check |
| Processes | Designed around manual work | Unchanged, with a tool added | Redesigned around what AI can do |
| Data | Scattered across systems | Per tool, often copied | Connected, one source of truth |
| Governance | Line management | Often not arranged | Ownership, an AI policy and a register |
| Growth | More work needs more people | Scattered time savings, hard to measure | Growth without a matching rise in headcount |
In practice
Three engagements, each showing a different building block: setting direction, putting the data layer in place and extending AI month by month.
5,000+
Mental-health-care organisations mapped
Read how Ecare went from growth plan to a working system4
Departments benefit
Read how Burgstate extends AI month by monthThe short definition is in the glossary: what is an AI operating model? The technical layer underneath it is an AI Operating System.
Our services
Know where AI truly pays off, in two weeks.
In 14 days we map where AI delivers concrete time, money or quality in your business. No hype, no generic tips. Just a report with prioritised opportunities, a live presentation and a clear next step.
Custom AI software that runs in your work straight away.
We build web apps, automations and agents that fit your business context. No standalone plug-and-play tools, but software that connects to your processes, your data and the people who use it. Human at the wheel, AI does the groundwork.
One layer on top that brings everything together.
Moneybird, AFAS, HubSpot, Google, a planning tool. All fine systems, and yet no overview. We build an AIOS that sits on top and connects your business into one brain. We started it for ourselves and are now building it for the Dutch SMB market. The first pilots are running.
Smart workers that take repetitive work off your team.
An AI agent is not a chatbot. It is a piece of software that carries out a task on its own: triaging email, following up leads, summarising reports, comparing documents. We build agents that work in your business context, with the right boundaries and human control.
Repetitive work that does itself.
Processing invoices, reading documents, handling customer questions, syncing data between systems. We automate the processes where time and errors sit, with AI agents and integrations on top of your existing software. No more manual work, more time for the real work.
Thinking along, making choices, giving direction.
Not every AI question starts with building. Sometimes the question is which direction, which tool, which path. We are a strategic sounding board for owners and management teams who want to get clear on where AI should land for their business. Practical, honest, and without jargon.
Where to start
You do not reorganise around AI in one go. We start with an AI audit or a strategy engagement, choose the process with the most value and build out from there. Fixed scope and price for each step.
A target operating model (TOM) describes how an organisation needs to work in the future to deliver its strategy: the processes, the organisation and roles, the systems and data, the locations and suppliers, and the way it is managed. The current operating model is the starting point. The gap between the two determines which changes are needed and in what order you make them.
The Operating Model Canvas, developed by Andrew Campbell, Mikel Gutierrez and Mark Lancelott, is a widely used way to describe an operating model on a single page. It starts from the value proposition and works it out in six building blocks, summarised as POLISM: processes, organisation, locations, information, suppliers and the management system. For an AI operating model you record, for each building block, what AI does: which process steps AI carries out, which roles change as a result, which information and systems AI needs and how it is governed.
A target operating model describes how your organisation needs to work in the future: processes, people, systems and governance. An AI operating model is a target operating model that includes AI as a worker. AI does not get a corner of its own; it has a place in every layer: which tasks AI takes over, how people work alongside it, which data and systems sit underneath and which agreements that requires.
Start with the question of which processes deliver the most value, not with the tools. Make sure the data and systems for those processes are accessible, appoint an owner for each process, agree how staff use AI and start with one process that shows results within weeks. From there you scale up, team by team.
You see the first step, one process with a measurable result, within weeks. An organisation-wide AI operating model grows over months to years, layer by layer. At Burgstate we have been working month by month since late 2025 on an ongoing AI programme that now spans four departments.
Ultimate accountability sits with senior management, not with IT alone. For each process you appoint an owner from the business who decides what AI does and checks that it works. Larger organisations often appoint a Chief AI Officer or a similar role; in mid-sized organisations an external partner can partly fill that role.
Work shifts from doing to checking, improving and dealing with customers. Repetitive tasks decrease, and the roles that remain call for more judgement. That takes explanation, training and honest communication about what is changing. The aim is usually to grow without a matching rise in headcount, not to cut jobs.
Yes, especially then. Tools such as Copilot and ChatGPT make individual employees more productive, but they do not change the way the organisation works by themselves. An AI operating model makes sure the gain does not stay with individuals: processes, data and agreements are set up so that AI takes over work structurally.
The AI operating model is the organisational side: how you work, decide and govern. An AI Operating System is the technical layer underneath, which connects your data, systems and knowledge so AI can work with them. One you design, the other you build; together they make AI a fixed part of how the business runs.
That depends on the size of your organisation and the pace you choose. We work in steps with a fixed scope and price for each step, starting with an AI audit or a strategy engagement. Book an intro call for an estimate for your organisation.
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