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How Artificial Intelligence is changing the Real Estate industry

March 06, 2018 - By James Boreham

Artificial Intelligence has been attracting serious attention for a number of years now and the impact that this technology will have is a very polarising subject. To quote a 2017 comment from Mark Zuckerberg, “if you’re arguing against AI then you’re arguing against safer cars and being able to better diagnose people when they’re sick.” By contrast, Stephen Hawking believes, “the development of full Artificial Intelligence could spell the end of the human race”. This article aims to highlight how AI is being utilised within a particular industry – real estate. It also aims to dispel certain myths and give a clearer sense of where this technology is at in 2018.

Commercial real estate is a few years out from having robotic brokers and automated deals, but everyone from technology vendors to large managing agents are paving the way for artificial intelligence to become the next revolution in the property industry and across professional services, in general. It is a shift that has the potential to put the power of leveraging data into the hands of landlords, as they have access to their own data just one click away rather than relying on servicers to provide details on request. Artificial Intelligence is expected to reach $36 billion in revenue worldwide by 2025. Deep learning is at the core of the new technology and is driving its potential as a real estate disruptor.

So, what is Deep Learning?

Similar to how a child learns a language, machines can ingest new rules and methods for processing information by repeated exposure to the data, rather than being given static rules. Which means that the more information the machine is exposed to, the smarter it gets. Deep learning allows data to be extracted, adapted and changed to suit different needs, languages and accuracy levels. For real estate, it allows for deals on a global level, improving liquidity and reducing transaction costs. Real estate brokers engaged in international deals and working with documents across multiple languages will not have to hire a translator or commit to paperwork in one language. The technology has the ability to extract and process the data from lease documents into the language of the recipient’s choosing, ensuring negotiation terms remain accurate and transparent.

Smart data platforms that make use of technologies such as AI and Deep Learning are much faster and more reliable than human data entry. Utilizing Deep Learning algorithms, these platforms can complete the same data processing normally reserved for manual input, saving time and money. These platforms can also notice when information is missing, needs a review or is important.

This technology is also being used outside of the real estate market; following the 2016 revision of the reporting standards by Financial Accounting Standards Board (FASB) and International Accounting Standards Board (IASB), the boards replaced the previous IAS 17 standard with IFRS 16, that distinguishes between operating and financing leases. Using Deep Learning platforms, organisations can easily and accurately comply with the impending IFRS 16 standards. These tools can be applied to consolidate all the relevant lease files, identify those files that need to comply with the new standards and structure relevant data for seamless liability accounting purposes. The relation between each piece of information is taken into account, rather than being considered individually, flagging repeat issues in the future.

Why use AI for this purpose?

This labour-intensive analysis also shifts the responsibility away from the employees, allowing them time to add value to less mundane tasks. While the fear is that with the success of these platforms, landlords will depend less on real estate brokers to manage their portfolios, firms have increasingly sought to merge human intuition with the precision of machine learning. Asset management companies who are increasingly adopting and implementing these technologies on a Global scale are quickly realising that rather than replacing their real estate brokers with artificial intelligence, these collaborations have strengthened the presence of brokers at their firms. They are now able spend more of their time servicing clients instead of being bogged down with paperwork. Commercial real estate has only scratched the surface of what artificial intelligence can offer. Beyond management of paperwork, the technology could revolutionize every step of the real estate process, from intelligent search engines to combining listings with automatic investment advice and image recognition. Perhaps most impactful has been the door it has opened for more egalitarian analysis of data. No longer locked into undecipherable spreadsheets, landlords and potential investors are now more informed than ever about their deals and portfolios, thanks to the power of artificial intelligence. There is also a massive risk reduction angle to this, humans make errors, particularly on repetitive routine tasks, AI’s ability to improve accuracy and reduce PI risk is sizeable. Lawyers commonly acknowledge that is you remove 80% of the onerous parts of document review, they can concentrate in the right places, this hybrid method is extremely powerful.

What does this all mean for transactional business?

Heightened liquidity. When trading any security or asset there is typically a large amount of due diligence done prior to the deal going ahead, streamlining this process using AI provides an exciting prospect for historically less liquid asset classes. This is massive for the vendor in a transaction, having full clarity on details of their lease asset portfolio will save renegotiated prices at a later stage.

What’s been discussed here is focused on a particular application of this technology but from this, broader conclusions can be drawn about how AI will change the way the industry evolves over the next 5-10 years. The key takeaway being, AI is not something to be feared, it is something to be embraced. AI may change certain business functions, but for the better. It will be the mundane routine tasks that get automated, not those where subjective judgement and reasoning is relied upon. There’s also another critical conclusion here – very few people remain doubtful about the adoption or utilisation of AI, so it’s up to organisations to be early adopters and use this technology to their benefit, forgoing this sees the risk of becoming increasingly obsolete over time.

The article was originally published in Lockton Real Estate & Construction's Market Watch Newsletter.

Author: James Boreham, Sales Executive, LEVERTON