Almost every organisation today uses artificial intelligence in some form, from ChatGPT and Microsoft Copilot to automated customer service, real-time translation and AI-driven building management. But behind every AI prompt, every automated workflow and every cloud-based model lies an enormous volume of data traffic. The question is no longer whether AI will transform commercial real estate. That transformation is already underway. The real question is whether the digital infrastructure of our office buildings, warehouses and retail premises can actually handle what is coming.
AI Is Becoming Core Infrastructure for Businesses
A few years ago, AI tools were the preserve of large technology companies. Today they are embedded in the daily operations of firms of every size and sector. Sales teams use AI to summarise meetings and draft proposals. Marketing departments generate images and videos in seconds. Logistics operators run predictive analytics to optimise routes and inventory. Customer service platforms resolve queries without human intervention. Architects and engineers use generative design tools that crunch thousands of variables simultaneously.
Each of these applications has one thing in common: they are hungry for bandwidth. Unlike a browser loading a webpage or an email client syncing a mailbox, AI tools engage in continuous, bidirectional data exchange with cloud infrastructure. They stream inputs, receive processed outputs and update models, all in real time, all day long. When an entire floor of employees runs these tools simultaneously, the cumulative demand on a building's network becomes significant.
- AI assistants and copilots continuously query cloud servers
- Real-time translation tools process live audio streams
- Image and video generation transfers large files repeatedly
- AI-powered meeting tools upload, transcribe and summarise in parallel
- Smart building systems generate constant sensor data that must be processed and acted upon
This is a qualitatively different kind of network load from what commercial buildings were designed to accommodate even five years ago.
The Gap Between Traditional and AI-Driven Workplaces
The contrast between a traditional office network and one configured for AI-intensive work is stark. Consider the difference in what the network must support:
| Traditional office | AI-driven office |
|---|---|
| Email and document storage | Continuous cloud processing and model queries |
| Web browsing | Real-time AI assistants running across all workstations |
| Video calls | AI meeting assistants transcribing and summarising live |
| Manual file search | AI generating and indexing content continuously |
| Occasional large file transfers | Large dataset processing as a routine daily task |
The implications extend beyond internet speed. Buildings need robust fibre connections, Wi-Fi infrastructure dense enough to handle simultaneous high-demand devices, scalable network architecture that can grow with usage, redundant connections to prevent downtime, professional patch rooms and cable management, and cybersecurity frameworks that can handle the expanded attack surface AI tools introduce. Many commercial buildings, including relatively modern ones, fall short on several of these points.
Is the Commercial Real Estate Market Actually Prepared?
This is the uncomfortable question that landlords, asset managers and investors need to sit with. A building completed in 2015 may have been considered fully equipped at the time. In 2026, with AI embedded in standard business operations, that same building's network infrastructure could be a genuine bottleneck, and a reason tenants choose to go elsewhere.
The checklist for digital readiness is not complicated, but it is often overlooked during property assessments:
| Question | Why it matters for AI-intensive use |
|---|---|
| Is fibre broadband present and scalable? | The baseline for high data throughput |
| Can the network architecture grow with demand? | AI usage will increase, not plateau |
| Is Wi-Fi capable of supporting intensive simultaneous use? | Underperforming Wi-Fi is the most common complaint in modern offices |
| Are redundant internet connections in place? | Downtime costs more when operations depend on cloud AI |
| Is cybersecurity architecture fit for purpose? | AI tools expand the threat surface considerably |
| Is the building capable of meeting tomorrow's standards, not just today's? | Long-term asset value depends on it |
It is worth noting that network congestion in commercial buildings is already a documented problem, separate from AI entirely. Articles examining network congestion as a scarcity factor in commercial real estate make clear that connectivity constraints are affecting tenant decisions right now, before AI adoption has even peaked.
Smart Buildings Add Another Layer of Digital Demand
The challenge is compounded by the fact that it is not only office workers who are driving up data demand. Buildings themselves are becoming AI-powered. Modern smart building systems use artificial intelligence to manage climate control, predict maintenance needs, optimise energy consumption, control access and analyse occupancy patterns. All of these systems communicate continuously across digital networks. A fully instrumented smart building is, in effect, running dozens of IoT devices and AI applications simultaneously, quite apart from whatever the tenants are doing.
For a deeper look at how these technologies are reshaping building infrastructure, the topic of smart building systems and future-proofing commercial real estate offers a useful foundation. The convergence of tenant-side AI usage and building-side AI management means that digital infrastructure is no longer an optional upgrade, it is load-bearing.
Digital Infrastructure as a Real Estate Value Factor
For decades, commercial property valuation focused on a familiar cluster of variables: location, floor area, parking ratio, energy efficiency, fit-out quality and lease terms. Digital infrastructure rarely featured in due diligence beyond a basic check that internet was available. That model is outdating itself quickly.
| Historically decisive factors | Increasingly decisive factors |
|---|---|
| Location and accessibility | Digital connectivity and fibre availability |
| Floor area and layout | Network capacity and scalability |
| Parking provision | Redundant internet infrastructure |
| Energy label | IT delivery level and infrastructure quality |
| Fit-out and finish | Smart building systems and IoT readiness |
Tenants seeking office space in Amsterdam or office space in Rotterdam are increasingly factoring connectivity and digital infrastructure into their requirements, not as a bonus, but as a non-negotiable. For logistics operators considering warehouse and logistics space in Venlo, where AI-driven supply chain management is standard practice, the same principle applies to industrial premises.
The parallel with sustainability is instructive. A decade ago, an energy label was a nice-to-have. Today it is a legal requirement in many segments of the Dutch market, and buildings that fail to meet minimum standards face functional obsolescence. Digital infrastructure is on the same trajectory. The firms that recognise this early, whether as landlords investing in upgrades or as tenants specifying requirements precisely, will be better positioned than those who treat it as peripheral.
The IT-Label: Measuring What Currently Goes Unmeasured
If the energy label answers the question "how energy-efficient is this building?", the IT-Label answers the question "how digitally capable is this building?". It assesses the quality of a building's IT delivery level (cabling, network architecture, fibre connectivity, Wi-Fi infrastructure and overall digital readiness) and translates that into a standardised rating that landlords and tenants can use in decision-making.
The logic is straightforward: you cannot manage what you do not measure. Without a structured framework like the IT-Label, tenants have no reliable way to compare the digital quality of one building against another, and landlords have no objective benchmark against which to position investment decisions. Given that IT infrastructure is already emerging as a scarcity factor in commercial real estate, the absence of standardised measurement is a genuine market inefficiency.
RE-SEARCH believes that within a few years, the IT-Label will be as standard a feature of commercial property listings as the energy label or the NEN measurement. The trend is clear: tenants are not just asking how many square metres are available or what the rent per square metre amounts to. They are asking whether their AI environment can run seamlessly in that building, whether hybrid working is properly supported, and whether the digital infrastructure will remain adequate not just today but over the full term of a five- or ten-year lease.
What Landlords, Investors and Tenants Should Do Now
The practical implications differ depending on where you sit in the market.
For landlords and asset managers, the priority is audit. Understand the current digital delivery level of your portfolio. Identify buildings where network infrastructure is lagging and model the cost of upgrading fibre, cabling and Wi-Fi against the risk of increased vacancy as AI-ready tenants look elsewhere. For those managing properties in competitive markets, digital infrastructure may already be influencing leasing outcomes more than the rent-free incentives on offer.
For investors, digital readiness should enter due diligence as a standard line item. A building with poor IT infrastructure in a market where tenant demand is shifting toward AI-intensive workplaces carries a risk premium that is not always reflected in the current valuation. Conversely, buildings that have invested in scalable network infrastructure, fibre connectivity and smart building systems are better placed to attract and retain tenants at stable rents.
For tenants, the message is to ask harder questions before signing a lease. Review the delivery level of the office or warehouse space you are considering, and make sure the digital specification is part of that conversation. What is the available internet bandwidth? Is fibre in place? What is the Wi-Fi architecture? Is the network infrastructure shared with other tenants in ways that could create congestion? These are not technical niceties, they are operational essentials for any business running AI tools as part of its daily workflow.
The Buildings of Tomorrow Are Being Chosen Today
Commercial real estate has always been shaped by the demands of the economy it serves. Industrial expansion created demand for warehousing. The knowledge economy created demand for flexible, collaborative office environments. The AI economy is creating demand for digitally robust, future-proof buildings, and that demand is not a future scenario. It is present in every lease negotiation happening right now.
The question worth sitting with is this: are the offices, business premises and retail spaces that make up today's commercial real estate stock digitally strong enough to keep pace with this shift? For some buildings, the answer is yes: they were built or refurbished with scalable infrastructure and are ready to support AI-intensive tenants. For many others, the honest answer is not yet.
What is certain is that digital infrastructure quality is moving from the margins of property assessment to its centre. The organisations (landlords, investors, developers and tenants alike) that treat this shift seriously today will be the ones occupying and owning the most valuable commercial real estate tomorrow.
