Every office search starts with the same six questions. How many employees? How many square metres? Which city? How many parking spaces? What is the budget? When do you need to move in? These are sensible, practical questions, and answering them correctly still matters enormously. But there is a seventh question that rarely gets asked early enough, and it may be the most important one of all: how will your organisation actually work in three years? In an era where AI is reshaping business processes faster than most companies can track, finding the right commercial property is no longer simply a matter of matching headcount to floor space. It is a question of understanding the organisation you are becoming, and then searching for a building that can keep up.
We Sign Leases for Years in an Economy That Changes by the Month
A standard commercial lease in the Netherlands typically runs for five years, often with an option to extend for another five. That is a long commitment in any business environment. But in today's environment, it is an extraordinary one. The pace at which AI tools are being integrated into everyday business operations means that the organisation signing a lease in 2026 may look and work quite differently by 2029, let alone 2031.
Eurostat data confirms that AI adoption among European enterprises has been accelerating meaningfully. In the Netherlands, the share of companies using AI technologies has grown consistently in recent years, with larger enterprises leading adoption but smaller companies closing the gap. Gartner forecasts that global enterprise AI spending will continue to rise sharply through the latter half of this decade, while McKinsey research consistently points to an acceleration in the integration of AI capabilities into core business workflows, not just as pilot projects but as operational infrastructure.
These are not forecasts to be taken lightly. But they also require careful interpretation. There is an important distinction between what has been measured and what is projected. The fact that AI adoption is growing rapidly is a measurable reality. Exactly how many Dutch companies will have structurally integrated AI into their core processes by 2029 remains a scenario, not a certainty. A plausible scenario based on current adoption curves suggests that the majority of medium and large Dutch enterprises will have moved beyond experimental AI use toward embedded AI workflows within three to four years. Whether that plays out precisely as projected is unknowable. What is clear is that the direction of travel is set.
The Deeper Change: From Tool to Infrastructure
The most common way to discuss AI in a business context is to focus on adoption rates. How many companies use it? How often? For what tasks? These are reasonable metrics, but they miss the more fundamental shift that is already underway in many organisations.
Today, a typical employee might use an AI tool to draft a document, summarise a meeting, or generate an image. That is AI as a productivity tool, discrete, optional, and largely peripheral to core operations. The more significant change is what happens when AI moves from the edge of a workflow to its centre. When AI capabilities are embedded in a company's CRM, its financial processes, its HR systems, its customer service operations, its cybersecurity stack, its planning tools, and its data analysis pipelines, AI stops being a tool that people choose to use and becomes infrastructure that the business depends on.
That distinction matters enormously for property decisions. When AI is a tool, the building it runs in is largely irrelevant. When AI is infrastructure, the building becomes part of the question. Connectivity, digital resilience, power capacity, and the overall technical quality of a space all move from nice-to-have to operationally relevant. As we explored in our earlier article on IT infrastructure as the new scarcity factor, the gap between what different buildings can deliver digitally is wider than most tenants realise.
"The real change is not how many people use AI. It is how many business processes will no longer function the same way without it."
What Does This Mean for the Physical Workplace?
The relationship between AI and office space is not straightforward, and anyone who tells you it is should be treated with scepticism. There is a persistent narrative that AI will inevitably reduce the demand for office space by automating work and shrinking headcount. There is another narrative that AI will create so many new roles and so much new growth that companies will need more space, not less. The honest answer is that both effects are plausible, and the outcome will vary considerably by sector, by organisation size, and by the specific nature of the work involved.
What is less debatable is that AI changes how organisations work, and how an organisation works has direct implications for what it needs from a physical space. Consider a few concrete possibilities:
- Organisations with more automated back-office functions may need fewer individual workstations but more collaborative and project-based spaces.
- Companies running data-intensive AI workflows may place higher demands on connectivity and digital infrastructure than their square-metre footprint alone would suggest.
- Fast-growing AI-native businesses may require maximum spatial flexibility, with lease structures that can accommodate rapid expansion without penalty.
- Organisations restructuring their teams around AI-augmented roles may find that the composition of their workforce changes faster than expected, altering both the size and configuration of the space they need.
None of these outcomes is universal. But all of them illustrate why a conversation about future office needs that stops at headcount and square metres is leaving important variables on the table.
What the Research Tells Us About Buildings and AI
Research from Cushman and Wakefield on AI and commercial real estate consistently points in the same direction: AI is not simply a force that shrinks real estate demand. Its more nuanced effect is on the quality of space that organisations are willing to accept. Buildings with strong digital infrastructure, flexible floor plates, high energy efficiency, and robust connectivity are attracting greater interest from occupiers with sophisticated technological requirements. Buildings that lag on these dimensions face more challenging leasing environments, regardless of their location or headline rent.
Knight Frank's research on corporate real estate and AI adoption reinforces this picture. Their work on what they describe as a defining phase in workplace evolution notes that the three years between now and the end of the decade are likely to be the period in which AI moves from experimentation to embedded operation across corporate real estate functions. Their research on AI adoption in corporate real estate also highlights that the collaboration between CRE teams, HR, and IT is becoming a critical factor in how companies make property decisions, because the workspace strategy can no longer be designed without understanding the technology strategy.
The question this raises is deceptively simple: if companies are reorganising themselves around AI capabilities between now and 2029, why would we still determine their property needs using only the parameters of 2026?
The Traditional Search Question Is Not Wrong. It Is Incomplete.
A conventional office search query looks something like this: 100 employees, approximately 70 workstations, 1,500 square metres, central Amsterdam, 50 parking spaces, budget of X euros per square metre. That search query is not wrong. Every one of those parameters matters and will still matter in five years.
But it is incomplete, because it says nothing about the organisation behind those numbers. Two companies can both need 100 employees and 1,500 square metres and be looking for entirely different buildings, because they work in fundamentally different ways.
Consider two organisations searching for office space in Amsterdam with near-identical footprints:
- Company A is a traditional professional services firm with stable processes, moderate cloud usage, and no current plans for AI integration beyond basic productivity tools.
- Company B is a scale-up running AI-powered services, with developers, data scientists, real-time collaboration workflows, and a technology stack that places heavy demands on network reliability and digital continuity.
Same city, same surface area, same headcount. Different buildings. Not because one company is more important than the other, but because their operational profiles are genuinely different. As we discuss in our article on what a building can handle digitally, the variation in digital capability across otherwise comparable commercial properties is substantial, and it is a variable that a traditional search query does not capture.
"Square metres tell you how much space an organisation needs. They do not tell you how that organisation works within those square metres."
Searching for 2029, Not Just 2026
A tenant signing a five-year lease in 2026 will still be bound by that contract in 2031. That is not an abstract observation. It means that the building chosen this year needs to remain a workable environment not just for the organisation as it exists today, but for the organisation as it may exist in three, four, or five years.
Mapping that trajectory requires asking different questions at the start of the search process:
- How does the organisation work today, and how is that likely to change?
- Which AI tools are already in use, and which are planned for integration in the next one to two years?
- Which processes are candidates for automation, and what will that do to team composition?
- How important is digital continuity to daily operations, and how dependent is the business on cloud infrastructure?
- Does the organisation need maximum spatial flexibility, or is stability more important?
- What connectivity and network requirements will the business have in 2028 or 2029?
These questions do not replace the traditional ones. They add a second layer of analysis that makes the eventual property match more durable. An organisation that thinks through these questions before beginning its search is far less likely to find itself in a building that felt right in 2026 but no longer serves its operational needs by 2029. Our guide to what makes an office AI-proof goes deeper on the specific building characteristics worth examining.
Introducing the Digital Usage Profile
At RE-SEARCH, we think of this second layer of analysis as the digital usage profile of an organisation. It sits alongside the traditional programme of requirements and adds a dimension that is increasingly relevant as AI becomes embedded in more business processes.
A digital usage profile addresses questions like: How bandwidth-intensive are the organisation's daily workflows? How critical is network redundancy to operations? What are the cybersecurity requirements? Does the organisation need smart building integrations? How important is mobile coverage quality? What is the expected growth in data consumption over the lease term?
The value of building a digital usage profile before searching for property is that it allows the search to be oriented around what an organisation actually needs from a building, rather than simply what the building offers on paper. It also creates a meaningful basis for comparing properties that look identical on a standard search but differ significantly in their ability to support the organisation's operational future.
This is where the connection to building-side assessment tools becomes relevant. RE-SEARCH works with IT-Label (it-label.com) to make the digital delivery level of commercial real estate visible and comparable. The logic is straightforward: RE-SEARCH investigates what the user needs digitally; IT-Label maps what the building can deliver digitally. Where those two assessments align, you have a digital match, not just a spatial one.
A Different Role for the Property Adviser
None of this reduces the role of the property adviser. If anything, it makes that role more important, and more demanding. When organisations are changing rapidly, the value of asking the right questions before a search begins is greater than ever. A good adviser does not start with the available listings. A good adviser starts with the organisation.
That means asking not only "how many square metres do you need?" but also "where will your organisation be in three years?" Not only "what is your budget per square metre?" but also "what does your business depend on digitally, and is that going to grow?" Not only "which district do you prefer?" but also "how much flexibility do you need to build into this commitment?"
Technology is making it faster and easier to search property databases, compare buildings, and surface relevant listings. But the faster and more capable search technology becomes, the more important it is to formulate the right search question in the first place. As we put it elsewhere: AI can search better and better. But someone still has to investigate what we are actually searching for.
"Technology helps us search faster. Research helps us choose better."
For logistics operators making similar long-term commitments, the same principle applies. Whether evaluating warehouse and logistics space in Rotterdam or distribution facilities elsewhere, the question of how operations will evolve over a five-year lease term is just as critical as the square meterage itself.
From Search Engine to Research Engine
There is a growing volume of commercial property data available online. Platforms can surface listings faster, filter by more criteria, and compare buildings across a wider range of attributes than was possible a decade ago. RE-SEARCH is part of that evolution, and we believe in its value.
But we also believe that more data and faster search tools place a premium on one thing that technology cannot do automatically: understanding the organisation behind the search. The name RE-SEARCH is not an accident. RE stands for real estate. Search stands for finding. But search, in its most useful form, begins with research. Researching the organisation. Researching the direction it is moving. Researching what it will actually need from a building, not just today, but across the full term of the commitment being made.
AI does not need to occupy a single square metre of floor space to change which square metres a company needs. That is the central insight of this article, and it is the insight that should inform how property searches are structured as AI becomes a more fundamental part of how businesses operate.
Frequently Asked Questions
Does AI automatically mean companies need less office space?
Not necessarily. AI can automate certain tasks and reduce the need for individual workstations, but it can also accelerate growth, create new roles, and increase the value of high-quality collaborative space. The relationship between AI and office demand is more nuanced than a simple reduction in square metres.
What is a digital usage profile and why does it matter?
A digital usage profile captures how an organisation works digitally: its bandwidth requirements, cloud dependencies, network redundancy needs, cybersecurity requirements, and expected growth in data consumption. It sits alongside the traditional programme of requirements and helps identify buildings that can genuinely support the organisation's operational needs, not just its physical footprint.
How far ahead should a company think when searching for office space?
A five-year lease signed in 2026 runs to 2031. Given the pace of AI adoption and organisational change, it makes sense to model at least three years forward when assessing property requirements. That means considering not just how the organisation works today, but how it is likely to work in 2028 and 2029, and whether the building under consideration can support that trajectory.
What is IT-Label and how does it relate to office search?
IT-Label is a framework that assesses and communicates the digital delivery level of commercial real estate, covering aspects like connectivity, redundancy, smart building systems, and network infrastructure. RE-SEARCH uses IT-Label assessments to match the digital usage profile of an organisation with buildings that can actually deliver what is needed. You can find more information at it-label.com.
Should a logistics or warehouse tenant ask the same forward-looking questions?
Yes. The same logic applies to any long-term property commitment. An organisation evaluating warehouse and logistics space in Venlo, for example, should consider how automation, robotics, and data-driven supply chain management will affect its operational requirements over the lease term, not just the dock doors and floor load capacity it needs on day one.
What is RE-SEARCH's approach to future-proofing office searches?
RE-SEARCH starts the conversation before the search. Rather than beginning with available listings and filtering by surface area and location, we first investigate how the organisation works, how it is likely to evolve, and what it will need from a building across the full term of its commitment. That research-first approach is what the RE-SEARCH name reflects, and it is what we mean when we say: search begins with research.
Your next lease will last for years. So investigate not just where you want to work today. Investigate how you are going to work tomorrow.
