Proptech: challenges and global trends


The mentality of the incumbent real estate is changing. If 2018 was the year in which PropTech hit the mainstream limelight in terms of knowledge and awareness, we must admit that it was, however, somewhat disappointing in terms of implementation. 

This was clearly outlined in reports by BPF and KPMG. The latter, for example, highlighted how the industry recognises the potential opportunities and challenges posed by PropTech, that don’t only concern technology, but that are also aimed towards the client, innovation and collaboration.

Real progress has been very slow. In fact even if a rather disconcerting 97% of those interviewed claimed that digital and technological innovation will have an impact on their businesses, over half (56%) described themselves as being below 5/10 as far as digital and innovation maturity is concerned.   

But, even in the field of proptech, this is easier said than done. For this reason, at the end of last year, I interviewed various start-ups in the United Kingdom, who confirmed that they had noticed a significant change in the mentality of real estate companies with whom they were dealing, and that everyone involved is expecting a big push this year in terms of the implementation of technology.  

Data, AI and Machine Learning at the core of the sector.

The three afore-mentioned concepts continue to be noted as the ‘hot topics’ for start-ups. In reality, access to data is probably still the biggest challenge for many start-ups in the PropTech sector.  Data-sharing is a fundamental principle, especially in the areas in which the public and private sectors intersect each other.

Artificial Intelligence and Machine Learning have been at the top of the list for a while now, and I would say that they are slowly becoming the planned modus operandi for all the technological solutions that look to the future.   On the other hand, and for this very reason, many start-ups tend to add “AI” to their name with the aim of increasing their visibility and potential interest. 

But the reality would appear to be somewhat different. One study, published last week by the London venture capital company, MMC Ventures, found no proof of the fact that artificial intelligence is a key part of the products offered by 40% of the 2,830 AI start-ups in Europe.

Investment growth continues. It may come as no surprise that investors expect to see continued growth in investment in PropTech. According to MetaProp’s most recent index, the ‘Global PropTech Confidence Index,’ 60% of the PropTech investors interviewed predict that they will make more investments in 2019 than in 2018, an all-time high and growing, compared to the 46% of some six months ago.

During my one-to-one interviews with investors, many of them expressed an expectation – or at least,  the hope – that the current value of $20 billion invested will be exceeded in 2019.

Proprietary investment funds. Another trend for 2019 – which started back in 2018, with, for example, JLL Spark and RET Ventures, but which is expected to grow further – are the real estate incumbents that create proprietary investment funds to implement their digital strategy.

Real Estate businesses are increasingly aware not only of the purchase value of products from start-ups, but also of having the chance to participate in the rise of successful start-ups and have ownership in order to make sure that the solutions they need are created. These very same companies have, on the whole, recognised the importance of allowing start-ups to be start-ups, and therefore keeping them at a safe distance outside of their own company structure. 

Smart Tech. The main trend that almost all the investors with whom I have spoken across the world share, both as an expectation and also as an investment objective, is that of the Smart Technologies.

In actual fact, the most immediate and impactful way to support the real estate market is to accompany the sector’s transition towards a world of services, in other words, Customer Experience Management, combined with a sophisticated analysis of data and technology – that will make it possible to implement these learning systems and therefore optimise resources and assets.