AI in the property industry.
At a time when technological innovations are radically changing our everyday lives and the world of work, artificial intelligence (AI) has long since assumed its role as a key factor for transformation.
Raphael Gielgen, Trendscout Future of Work Life & Learn, Vitra – What was considered a vision of the future just a few years ago is now a reality in the first business models - and the pace is accelerating. The property industry is no longer at the beginning, but in the middle of a profound transformation: from selective application to structural integration. The challenge is no longer whether AI will be used, but how consistently, how scalable and how responsibly.
The development of AI - exponential and ubiquitous
According to OpenAI, ChatGPT had one million users just 5 days after its launch in November 2022. In comparison: Instagram took around 2.5 months to reach 1 million downloads. And it took Netflix around 3.5 years to reach 1 million users. The development of AI - exponential and ubiquitous. Today, hundreds of millions of people around the world use AI-supported tools every day - often without realising it.
The number of available applications has literally exploded: The ‘Future Tools’ database alone now lists over 20,000 specialised AI solutions. At the same time, the market environment has become more diverse - with strong players such as Anthropic, Mistral, Google (Gemini), Meta (LLaMA), Cohere and xAI.
In a recent survey by Bitkom, over 70% of German companies see AI as the most important competitive factor in the next five years. The dynamics are clear: AI is no longer the topic of the future - but of the present.
Generative AI - universal, scalable, highly dynamic
Studies such as the Harvard Business Review show that Generative AI is as versatile as the world of tasks in the modern knowledge society. Its applications range from customer service to strategic decision support.
Six dominant application clusters have now emerged, which will continue to characterise most use cases in 2025:
- technical support & automation
- content creation & media production
- administrative & personal assistance functions
- knowledge transfer & on-demand learning
- creative processes & idea generation
- data analysis & decision support
The boundaries between these categories are becoming increasingly blurred - because the new generation of multimodal AI can process and generate text, images, sound and video simultaneously. This makes the technology a universal tool in almost all professions, especially where thinking, planning, communicating and decision-making are involved.
Source: R. Gielgen MIT
Property industry: from potential to practice
The potential of AI in the property industry is no longer just theoretical - initial projects show how efficiency, precision and user orientation can be increased along the entire value chain. According to an analysis by McKinsey & Company, AI can generate over 180 billion US dollars in added value for the global property industry every year - and the trend is rising.
What is needed is no longer imagination, but the courage to realise it. Whether project developer, architect, owner, operator or user - AI-supported tools are already changing decisions, processes and business models. And it is becoming clear that it is not the size of a company that determines its AI success, but its strategic approach to transformation.
Looking at the entire value chain in the property industry, the following fields of action and activities emerge in which AI or generative AI offers great potential. These encompass the entire life cycle of a property, from planning and development to construction, operation and management. The following eight fields of action are examples of how broad and effective the potential applications are today:
1. property search and valuation
Data analysis and forecasts: Use of AI to analyse large amounts of data to identify potential properties based on location, price trends and environmental factors.
Geodata and satellite imagery: Use of AI to analyse geospatial data and satellite imagery to assess the suitability and potential of properties.
Market analysis: Automated market analyses and forecasts of property prices and demand trends.
2. project planning and design
Generative design: Use of generative AI to support architects and engineers in the creation of construction plans and to generate optimal designs based on predefined parameters.
BIM (Building Information Modelling): Integration of AI into BIM systems to enable more accurate planning and predictions over the entire life cycle of a building.
3. financing and investment
Risk assessment: Use of AI to analyse and assess investment risks using historical data and market trends.
Automated financial advice: AI-driven advisory systems for investors to optimise financing strategies and portfolio management.
4. development, design & construction
Construction monitoring: Use of AI for real-time monitoring of construction progress using drones and cameras to meet time and cost schedules.
Optimisation of construction processes: Use of AI to optimise construction processes, material usage and logistics to increase efficiency and sustainability.
Quality control: Automated quality control and error detection using AI to recognise construction defects at an early stage.
5. letting & occupancy
Smart buildings: Implementation of AI in building technologies to enable smart and efficient management and personalised experiences for residents.
Rental pricing: Using AI to dynamically adjust rental prices based on market trends and demand.
6. operation and maintenance
Predictive maintenance: Using AI to predict maintenance needs and schedule maintenance work to minimise downtime and costs.
Energy management: AI-supported systems to optimise energy consumption and reduce operating costs through intelligent control of heating, ventilation and air conditioning systems.
7. property management and customer service
Virtual assistants: Use of chatbots and virtual assistants to improve customer service and respond quickly to tenant and user enquiries.
Data analysis for administration: use of AI to analyse tenant data and administrative processes to increase efficiency and satisfaction.
8. marketing and sales
Target group analysis: Use of AI to analyse target groups and create customised marketing campaigns.
Virtual tours: Development of virtual tours and viewings using generative AI to give potential buyers and tenants a realistic picture of properties.
Source: R. Gielgen MIT
Realisation
The various players in the property industry can integrate AI and generative AI into their business models in a variety of ways in order to increase efficiency, reduce costs and make better decisions. The integration of AI into the property industry is not just a technology project - it is a strategic transformation process that affects leadership, culture and structure. Successful companies follow five principles:
1. courage to pilot - but with the intention of scaling: introducing AI solutions in pilot projects to test their benefits and efficiency before deploying them on a larger scale. Those who experiment with AI early on will recognise the levers and hurdles more quickly.
2. building expertise at all levels: AI is not an IT issue - it is an organisational issue. Companies need an understanding of AI in management, tool expertise in the specialist departments and new roles such as AI Product Owner or Prompt Engineer.
3. co-operations and partnerships: Collaboration with technology companies and start-ups specialising in AI to develop and implement tailored solutions.
4. understanding and cultivating data as a raw material: Build a solid data infrastructure to collect, store and analyse relevant data needed for AI applications. No data, no AI.
5. agility in the AI strategy: AI technologies change on a monthly basis. Successful companies do not rigidly anchor AI in 5-year plans, but think in terms of learning systems that evolve with technology and the market.
As in many other industries, the implementation of an AI strategy in the property industry can be hindered by various challenges and hurdles. No AI without data - no impact without courage
Many companies fail not because of the technology, but because of the implementation. Above all: insufficient data quality, a lack of structures, too little clarity in the approach. But this is precisely where the opportunity lies: those who start to structure their data in a targeted manner, clarify responsibilities and understand AI as a strategic tool today will create a real competitive advantage.
The tools are there. Now it's up to us.
Sourve: R. Gielgen MIT
AI co-operation partners
For companies that want to implement AI projects, cooperation with specialised partners or AI consulting companies offers numerous advantages.
These partners have expertise and many years of experience, which facilitates the development and implementation of customised solutions. They have access to the latest technologies and are often at the forefront of technological innovation, which gives projects an advantage, and they usually offer scalable and flexible solutions that meet a company's specific needs and growth objectives.
Working with professional AI consultants in particular minimises risk and ensures that all legal and ethical requirements are met.
Now is the ideal time to consider the integration of AI consistently, as the technology is mature and available, the competitive landscape is changing rapidly and companies that embrace AI early on can secure decisive competitive advantages.