Building consultancy has been among the slower corners of the real estate world to adopt artificial intelligence. Alex Herrmann, head of building consultancy at MAPP, suggests this hesitation stems from the nature of the work. The advice delivered by consultants arrives at critical moments during acquisitions, capital raises, and major capital expenditure planning. Despite the delay, Herrmann believes the tide is slowly turning as the sector begins to understand AI’s potential.
Unlike other real estate functions that rely heavily on data, building consultancy retains a critical reliance on the traditional site visit. However, AI tools are being tested to assist surveyors before they even arrive. These platforms can trawl through historical building records, interrogate drone surveys, or flag anomalies. Running lease documentation through an AI platform can reveal material obligations or break clauses, while an AI-informed location search aggregates data on neighbouring land uses, planning history, or environmental constraints. This preparation ensures a surveyor arrives better equipped to ask the right questions and look in the right places.
There is a clear distinction between what a machine can see and what a human must interpret. A tool might identify a crack in an external wall from a drone image or historical survey, but that judgment requires human experience to determine if the crack resulted from past settlement, live structural movement, or something more benign. Similarly, a drone can assess the general condition of a roof covering, yet it works in tandem with a human assessing whether a damaged section is caused by a bat roost, bird nesting colony, or another issue. AI will simply package poor information more efficiently if the underlying site observations are faulty.
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Human conversation remains a vital component of the process. Some of the most valuable intelligence gathered during a site visit comes not from any system or sensor, but from a quiet word with a location manager. Questions like how busy the site really is, or whether there are whispers about lease renewals, can fundamentally shape the advice given to a client.
Predictive Maintenance and Accountability
Despite the growing use of AI tools, surveyors are not yet experiencing meaningful reductions in timescales or costs. Client expectations, particularly during acquisitions, already demand near-instant turnaround. Given the interdependent relationship between a surveyor and their AI tools, the technology is augmenting rather than accelerating key tasks. There is one area where AI is demonstrably adding value, and that is predictive maintenance. Solutions that process historical maintenance records, cross-reference equipment age and service history, and populate planned preventative maintenance schedules are proving useful. Understanding when a boiler is likely to fail, or when plant equipment is approaching the end of its life, helps property managers forecast budgets and maintain compliance with health and safety legislation.
Looking ahead, the integration of AI into building consultancy faces a difficult balance. While tools can enhance a surveyor’s capabilities, they cannot yet replace the subtle understanding of a professional judgment. Future plans for a building—such as whether a tenant requires 24/7 occupation or specific heating and cooling requirements in a warehouse—are factors that can only be properly understood through human investigation and relationship management. AI cannot yet ask the right question of the right person at the right time.
