AI in the property sector is no longer just an experiment

Just a few years ago, artificial intelligence (AI) was seen primarily as a technology of the future, used mainly by the IT sector and the world’s largest technology corporations. Today, it is having an increasingly significant impact on the residential, commercial and investment property markets.

The growing volume of data, the development of analytical tools, cost pressures and the need for faster decision-making mean that AI is becoming one of the most important elements of the real estate industry’s transformation. The application of artificial intelligence now extends beyond marketing and customer service to include advanced investment analysis, automated property valuation models (AVMs), building management and the optimisation of operating costs.

At the same time, the property market remains a sector heavily reliant on expert experience, local knowledge and risk analysis. Therefore, the key question today is not whether AI will replace property market specialists, but how it will change their role and the decision-making process.

AI in property valuation — from data to value forecasting

One of the areas in which artificial intelligence is developing most rapidly is property valuation. Automated Valuation Models (AVMs) – which use machine learning algorithms and big data analysis – are becoming increasingly important.

Systems of this type simultaneously analyse hundreds of factors affecting property value, including, amongst others:

• historical transaction prices,
• location,
• availability of infrastructure,
• public transport,
• demographic data,
• spatial planning,
• level of supply and demand,
• rental market trends,
• building standard and energy efficiency.

In practice, this means that preliminary valuations and analyses of a property’s investment potential can be prepared much more quickly. Solutions of this kind are already widely used in Western markets by platforms such as Zillow and Redfin, which build their own predictive models based on millions of data records.

On the Polish market, the development of this segment remains more limited, mainly due to:

• limited availability of high-quality data,
• market fragmentation,
• restricted access to comprehensive transaction databases,
• differences in quality between local markets.

Nevertheless, the importance of data analytics and predictive models is steadily growing, particularly in the investment sector and the private rented sector (PRS).

It is worth noting, however, that even the most advanced AI models do not eliminate the role of property market experts. Algorithms can significantly speed up data analysis, but they still have a limited ability to assess qualitative factors, such as the specific characteristics of a micro-location, legal risks or the individual features of a property.

AI in property sales and customer service

Artificial intelligence is also having an increasingly significant impact on the property sales process and customer relationship management.

Modern property platforms use AI for a range of purposes, including:

• personalising offers,
• recommending properties tailored to the user’s preferences,
• analysing customer behaviour,
• automatically segmenting sales leads,
• predicting the likelihood of a purchase.

Chatbots and virtual assistants that provide 24/7 customer support are also becoming increasingly popular. Tools of this kind can answer questions about properties, arrange viewings, or carry out initial customer screening.

AI is also used in property marketing.

Algorithms support:

• generating product descriptions,
• analysing the effectiveness of advertising campaigns,
• dynamic price adjustment,
• optimising ad placements.

For large property developers and sales platforms, this means the opportunity to boost sales efficiency and make better use of marketing budgets.

At the same time, the importance of so-called predictive marketing – that is, predicting customer behaviour based on historical data and current user activity – is growing.

Artificial intelligence in building management and asset management

One of the most promising areas for AI development remains commercial property management and smart buildings.

Modern AI-powered systems enable:

• monitoring of energy consumption,
• analysis of the operation of technical systems,
• failure prediction,
• optimisation of operating costs,
• improvement of buildings’ energy efficiency.

Predictive maintenance – the process of anticipating potential faults before a breakdown occurs – is becoming particularly important. By analysing data from sensors and BMS (Building Management System) systems, it is possible to reduce maintenance costs and minimise the risk of operational downtime.

AI technologies are also playing an increasingly important role in the implementation of ESG strategies and the decarbonisation of property. In practice, this means:

• optimisation of energy consumption,
• reduction of CO₂ emissions,
• monitoring of environmental parameters,
• support for ESG reporting,
• analysis of buildings’ energy efficiency.

For commercial property owners, this can have significant implications not only in operational terms but also in terms of investment. This is because an increasing number of funds and financial institutions are taking ESG factors into account when assessing asset quality and investment risk.

to be continued