Artificial intelligence is on the rise. Everywhere, it seems - except in the construction and property industry. At least that's what the statements of industry experts suggest. However, a comparison with reality shows that much more is happening than expected.
Baby-Steps despite omnipresence
The buzzword digital transformation has been buzzing around the construction and property industry for over a decade. Neither negative interest rates, the coronavirus pandemic nor the energy transition have seriously accelerated the digitalisation of the industry. Instead, it continues to babble like a gentle mountain stream. Then came Chat GPT and catapulted artificial intelligence (AI) into society's consciousness. Since then, experts and specialists have agreed: AI will disruptively change all sectors of the economy. And what does the construction and property industry have to say about this? One thing above all: don't rush things.
The hesitant assessment of artificial intelligence has a long tradition in the industry, as a look back at the results of past digital real estate surveys by pom+ shows. In 2022, 56% of the 200 or so managers and specialists surveyed still attested to its high or very high benefit. In addition, just over half of those surveyed stated that they do not use any form of AI in their day-to-day business, while 29% confirmed that AI applications are being developed or are already in use in their company. One year later, Chat GPT made its grand entrance - and paradoxically, the property industry immediately lowered its expectations: in 2023, only 52% still saw a high benefit in AI, 48% did not use it at all, and just 30% confirmed that it was being developed or used. Even today, only just under a third (32%) of respondents state that AI is being developed or used in their own company.
The market is likely to be further along
The timeline in the chart clearly shows the slow adoption of the technology: over the last three years, AI has only grown by 4% in the property industry. And this is despite the fact that hardly any other topic has been so present in the past 18 months. The placement of other innovations on Gartner's hype cycle (chart above) also shows a stagnation in their level of maturity for the sector and fits in with the picture of stalled digital maturity.
On closer inspection, however, it can be assumed that the current omnipresence of Chat GPT has an additional negative impact on positioning on the hype cycle. Due to the latent focus on generative AI, it is often forgotten that AI has not only existed for two years, but has undergone decades of development. Various solutions that can also be categorised as AI have already been in successful use for some time. One example is automated valuation models, i.e. models for the automated valuation of properties.
Another example is capturing solutions, which are used to create structured 3D models from scanned point clouds. A look at the solutions available on the market shows that AI-based approaches are available across the entire life cycle of properties and range from planning support tools to the optimisation of material flows. These examples underline the fact that AI is in practical use and is already helping the real estate industry to optimise processes and make them more efficient.
Reasons for the negative assessment
One reason for the industry's cautious assessment of AI is likely to be the often exaggerated ideas of what it can actually achieve. Most AI applications in the property sector are still limited to a supporting function, for example by being used in simulations or data analysis. However, the really significant efficiency gains from AI in the future are likely to come primarily from augmented and autonomous intelligence.
In other words, when AI acts as a decision-making aid by deriving insights from data and thus independently proposing new solutions. Or even decides independently which problems need to be solved and how in order to fulfil a given goal. The difficulties in differentiating between data analytics and AI are also likely to contribute to the pessimistic assessments. This is because AI is often viewed purely as an IT topic and less as an integral part of the core business. An additional obstacle is the need for training data and test scenarios, which are essential for the successful introduction of generative AI. Just as with the implementation of sustainability measures, the same applies here: No progress is possible without a sound database.
Rapid development
Generative AI is developing at a rapid pace. It feels like a new feature based on generative AI comes onto the market almost every day. It is therefore particularly challenging for small and medium-sized companies to keep track of the possibilities and not miss the boat. While large companies are currently focussing heavily on the use of generative AI for knowledge management and customer communication, the necessary investments are putting off smaller companies. However, it is essential for all companies to think about meaningful use cases for AI and to approach their implementation step by step. If this is missed, there is a risk that the catch-up process will be all the more costly later on - or that it will no longer be possible to catch up at all.
Broad «upskilling» required
Against this background, it is clear that AI is by no means just a technical challenge, but above all a management task that must be tackled strategically and operationally. The success of AI applications depends heavily on the quality of the input and the ability of employees to utilise this technology effectively. It is therefore crucial to systematically introduce specialists to AI and train them accordingly. This is the only way to realise the full potential of AI in the property sector.
The original version of this article first appeared in IMMOBILIA in August 2024.
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