Proptech (property technology) is the umbrella term for technology and digital services that help the real estate industry own, manage, let and use buildings. AI is currently the most talked-about part of proptech, and the question many property owners ask is whether AI in real estate is hype or real business value. The short answer: AI already delivers measurable value in a few well-defined areas, such as energy, administration and customer service, but it solves nothing on its own. Without organised data and clear processes, the result is usually a pilot that never scales.
What is proptech?
Proptech covers all digital solutions aimed at property and buildings, from sensors in the ventilation unit to letting platforms. The term is sometimes used interchangeably with real estate technology, and you will also hear contech (construction technology) and smart buildings. A simple way to map the market is by which part of the property life cycle a solution supports:
| Area | Example solutions | Who uses them |
|---|---|---|
| Operations and energy | Energy optimisation, building automation, sensors, predictive maintenance | Facility technicians, property managers |
| Management and finance | Lease administration, invoice flows, reporting | Property managers, controllers |
| Tenant experience | Fault reporting, tenant apps, access control, meeting room booking | Tenants, customer service |
| Letting and transactions | Advertising, matching, digital signing, valuation | Leasing teams, transaction teams |
| Planning and construction | BIM, digital twins, project tools | Project managers, developers |
Most of the value in proptech comes not from individual tools but from their ability to share data. That is why standards and integrations have become a topic of their own in the industry.
Proptech in Sweden
Sweden has an active proptech scene, driven by both startups and large property owners. A few reference points:
- PropTech Sweden, founded in 2019, is a network and membership organisation for players in property and construction technology. Property companies, tech companies and investors meet there through events, workshops and competitions.
- RealEstateCore is an open, shared data language for buildings launched in 2018 by Vasakronan, Akademiska Hus, Willhem, RISE and Jönköping University, among others. It connects BIM, control systems and sensor data, and is an example of Swedish property owners driving standardisation themselves.
- Larger companies lead. The Swedish property sector training board notes that the larger property companies lead the adoption of new technology and new roles, while smaller companies often lack the resources.
It is a recurring pattern: the technology exists, but the ability to adopt it varies widely between companies.
AI in the real estate industry: where does it stand?
Use is growing fast. According to Statistics Sweden (SCB), 35 percent of Swedish companies with at least ten employees used AI in 2025, compared with 25 percent the year before. In SCB's report on AI use in companies 2025, real estate is one of the sectors where the share grew most.
But the depth is limited. In a Hifab survey (January 2026), around 70 percent of property companies said they use AI to a limited extent, mainly for personal productivity such as editing text, analysis and planning. Around 23 percent use AI broadly across the business, for example to analyse utility consumption, in customer service, for scenario simulations and to code invoices. The biggest obstacle according to the same survey is a lack of skills and a generally low level of digitalisation.
Where AI delivers real business value
1. Energy and operations
This is where the clearest results are. AI-based control can adjust heating, cooling and ventilation to weather forecasts, occupancy and historical patterns, and analytical models can detect anomalies in consumption or alarms before they turn into expensive faults. The prerequisite is that the building has metering points and a control system that can be connected. More on building technology in our article on smart offices and buildings.
2. Administration and finance
Coding supplier invoices, reconciliations and compiling reports are repetitive tasks with clear rules, which suits AI well. The benefit is rarely spectacular but easy to measure in time saved, and it reduces vulnerability when key people leave.
3. Leases and documents
Language models are good at reading long documents and extracting information. For a property owner, that can mean going through a portfolio of leases and summarising notice periods, indexation clauses and amendments. The output needs checking, but the work goes from weeks to days.
4. Customer service and fault reporting
AI can sort and prioritise incoming cases, suggest replies and answer simple questions around the clock. It works best as support for staff, not as a replacement. The EU AI Act also requires that people chatting with an AI system are told so.
5. Letting
AI can help interpret what a tenant is really looking for and match it against available space. This is one of the areas where Shace works: companies describe their office needs, and property owners receive qualified enquiries instead of broad mailings. Vacant premises can be published directly from your own system via API, so the details do not need to be entered by hand.
Where it is still mostly hype
- Fully automated rent setting. Commercial rents are negotiated, and the data is thin and often confidential. AI can support the decision, but it takes market knowledge.
- "AI platforms" without data. A tool that promises insights across the whole portfolio is only as good as the data it is fed. If leases, areas and operations data are not structured, the insights are guesses.
- Digital twins without a use case. A detailed 3D model of the building is impressive, but the value only appears when someone uses it to make operating or investment decisions.
- Vacancy risk forecasts for individual tenants. It sounds appealing but often relies on too few data points to be reliable within a single portfolio.
Hype or business value: five questions before you buy
- What concrete problem does it solve, and what does that problem cost today?
- What data does it need, and do we have it in the right format?
- How will we measure the result after six and twelve months?
- Who owns the solution internally once the vendor has moved on?
- Can it integrate with the systems we already have, or does it become a new silo?
If the vendor cannot answer these clearly, that is a signal to wait.
Data first, AI second
The biggest misconception about AI is that the technology itself creates the value. In practice, the ability to collect, structure and use the business's data is what decides the outcome. That is why most successful AI initiatives in property companies start with a duller project: getting the core data in order. We describe how in the article on moving from Excel to real-time property data. For AI from the workplace perspective, read AI and automation in the office of the future, or see our overview of the real estate industry's challenges.
Frequently asked questions
What does proptech mean?
Proptech is short for property technology and means technology for the real estate industry. It covers everything from energy control and sensors to digital services for property management, tenants and letting.
How is AI used in the real estate industry today?
Most property companies use AI for personal productivity, such as writing and analysis. More advanced users apply AI to energy optimisation, invoice handling, customer service and consumption analysis. Broader use is held back mainly by skills and data quality.
Which proptech organisations exist in Sweden?
PropTech Sweden, founded in 2019, is a network and membership organisation for property and construction technology in Sweden. In addition, industry bodies and individual property owners run their own initiatives, such as the open data standard RealEstateCore.
Is AI in real estate worth the investment?
It depends on the use case. Energy optimisation and automating administrative flows often deliver measurable results quickly, while broad platforms without structured data rarely do. Start with a well-defined problem and one metric to improve.
Want qualified enquiries for your vacant premises, straight from your own system? Learn more about Shace for landlords.