Technical property management is a decisive factor in maintaining the value of buildings and ensuring their reliable and cost-effective operation. But with growing regulatory requirements, increasing technical complexity and rising expectations concerning sustainability and service quality, the traditional, manual management model is rapidly reaching its limits.
The pressure to modernise is particularly noticeable in areas where processes are still paper-based or fragmented. Artificial intelligence (AI) offers new opportunities here and marks the transition from reactive management to proactive, data-based facility management.
Challenges: Why there is growing pressure to act
Many technical management processes have evolved over time and lack structure. Information is often managed on paper, stored in decentralised Excel files or in unsynchronised systems. This causes a host of different problems:
- Processes are not transparent: Duplicate data entry, lack of traceability and media disruptions make it more difficult to work efficiently.
- Reactive operations management: Disruptions are only dealt with when their negative impact is already being felt.
- Increased coordination effort: Delays and queries regularly arise because relevant information is not available centrally.
In addition, external factors intensify pressure for change:
- Technological diversity: Buildings are becoming more technically sophisticated due to HVAC systems, sensors, building management systems and automation systems. As a result, manual monitoring is no longer adequate.
- Regulatory requirements: ESG criteria, energy saving regulations and the obligation to provide documentary evidence require precise, data-based action.
- Skills shortage: There is a lack of appropriately qualified personnel. Resources must therefore be used efficiently and routine activities automated.
Technical management
How digitally advanced is it already?
Our experts work with you to analyse the current situation and identify specific improvement measures.
The change begins with AI: New potential for technical management
Artificial intelligence offers practical solutions to the main challenges in technical facility management. The areas of application are diverse – from fault management to energy monitoring to maintenance planning.
1. Predictive maintenance: Predictive maintenance instead of expensive
Instead of operating according to fixed maintenance intervals or responding to acute failures, AI continuously analyses operating and sensor data, detects deviations at an early stage and predicts the optimal maintenance time. The risk of failure is therefore minimised, the service life of systems is extended and costs are reduced.
2. Far-sighted fault analysis: Address the causes, not the symptoms
Recurring technical problems, such as those relating to air conditioning or access control, can be reliably detected and analysed by AI systems. Instead of simply resolving symptoms, learning algorithms allow systemic causes to be identified and offer specific recommendations for action. This reduces the volume of tickets, improves response times and eases the burden on internal resources.
3. Smart building technology: Focus on energy efficiency and ESG goals
Thanks to AI-driven systems, energy management is not only more precise, but also more sustainable. Heating, cooling and lighting systems can be adapted in real time to actual demand. Analysis of past consumption data also enables continuous optimisation to lower operating costs and fulfil ESG requirements.
4. Intelligent help desks: Respond faster, solve problems more efficiently
AI-based support systems, such as modern chatbots or digital help desks, automatically record incoming troubleshooting reports, categorise them according to urgency and forward them to the responsible parties. Using Natural Language Processing (NLP), they also understand even unstructured input and reliably prioritise processes. This results in shorter wait times, more targeted escalation and a more professional user experience, round the clock.
AI in property management
Begin with a pilot project
Predictive maintenance can be tackled without embarking on a major project. We support you in selecting suitable application areas and technologies.
Digital process landscapes as the basis for smart management
AI can only realise its full potential in tandem with consistent, clearly defined business processes. An intelligent, networked infrastructure is the basis for sustainable process improvement in facility management – from maintenance and fault management through to strategic control of technical systems.
- Standardisation: Standard processes for maintenance, repair, reporting and escalation increase quality and reduce error rates.
- System integration: Interfaces between building management systems, CAFM solutions and ticket systems create a networked database.
- KPIs provide transparency: Real-time indicators and interactive dashboards enable fact-based control and continuous process optimisation.
In short: Digitalisation is the prerequisite for ensuring AI solutions can be used effectively and scalably.
Definitions in context
- Smart building technology refers to digitally networked systems, sensors and automation, which monitor, control and, in some cases, independently optimise the central functions of a building in real time, often with the aid of learning algorithms.
- ESG goals represent strategic guidelines in the areas of environmental, social and governance. These criteria are becoming increasingly important for the real estate industry in the valuation, financing and management of properties.
Connecting data pools
Breaking down silos with the Swiss LCDM Hub
AI can only be used effectively when the right data is available in good quality from all data sources. The Swiss LCDM Hub helps here.
Outlook: The future of real estate management is intelligent and predictable
The decision to use AI in technical property management is a step towards greater efficiency, transparency and sustainability. It opens up the possibility of proactively managing resources, minimising operational risks and ensuring compliance with regulatory requirements.
- Reduced downtime
- Greater operational reliability
- Targeted use of resources
- ESG-compliant documentation
- Increased user satisfaction
Change can be tackled without embarking on a major project. Many organisations are already benefiting from targeted pilot projects, for example, for introducing AI-based fault diagnostics or in the area of predictive maintenance. Such projects also form the entry point to strategic process improvement in facility management, increasing efficiency in the long term and ensuring operational reliability. Step by step, this leads to intelligent, data-driven control of the technical infrastructure – efficiently, resiliently and sustainably.
Data management for technical property management with the support of AI
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