Animation by Vera van de Seyp
It’s all well and good Modus writing about the benefits and drawbacks of artificial intelligence (AI) for the surveying profession, but what do surveyors actually think of it?
New technology often has the potential to improve our lives and raise professional standards, but it also comes with challenges. Never is this truer than in the case of AI and how it is applied to the built environment.
Which is why the RICS Professional Standard Responsible use of artificial intelligence in surveying practice was published in September 2025 and comes into practice from 9 March 2026. As AI and automation continue to evolve and play a more significant role in valuation practices, clear and reliable standards are critical.
Modus spoke to four experts from across the industry spectrum – residential, commercial, building surveying and valuation – to find out how it is impacting the work they do.
Sector: Residential Ian McGuinness FRICS is a partner and head of analytics at Knight Frank.
What opportunities or challenges has AI brought with it?
On the opportunity side, the gains are significant. We’ve seen a step-change in how quickly professionals can synthesise insight. Language models like ChatGPT now support rapid cross-referencing of planning documents, consultation responses, and other unstructured datasets. What once took hours of manual review can now be triaged in minutes.
Machine vision has opened up new possibilities, especially in under-surveyed areas. Models like Meta’s Segment Anything can classify building form or land use even when structured data doesn’t exist – which is enormously valuable in early-stage site analysis.
It’s also helping professionals turn data into more persuasive, client-friendly narratives – a capability that’s already reshaping how we pitch, present, and advise.
That said, the hype can be misleading. AI is sometimes sold into the industry as a one-size-fits-all solution. In reality, the term ‘AI’ now encompasses a wide range of pre-existing capabilities. Without clarity, non-technical decision-makers can easily be oversold.
We’re still operating in a landscape of ethical and regulatory uncertainty. Some third-party use cases have fallen short when tested for explainability or auditability. For a profession built on trust, that’s a red flag and we need to stay vigilant about transparency.
What is the general sentiment in residential surveying towards AI?
There’s genuine interest in how AI can help with report writing, defect recognition, or valuation modelling – particularly given increasing client demands and cost pressures. But there’s also scepticism, especially where AI is presented as a magic wand without clarity on its provenance, limitations, or compliance with professional standards.
Can AI be combined with other newer technologies like drones to increase the scale/quantity of work a residential surveyor can do?
Absolutely, the potential here is enormous. Drones already extend a surveyor’s reach, allowing rapid, safe access to rooftops, large estates, and otherwise inaccessible areas. But when AI is applied to the imagery and spatial data those drones collect, our interpretation of the data becomes more intelligent.
AI systems can classify materials, flag structural anomalies, assess gradients, even detect signs of environmental stress – all in real time, and at scale. This not only accelerates the survey process but supports more consistent, repeatable decision-making across large portfolios.
To what extent can AI automate certain surveying processes without compromising RICS standards?
Clear opportunities for automation lie in routine valuation modelling, photo classification and tagging, template-driven report generation, and risk-flagging based on predefined indicators
However full automation of high-stakes professional opinion is unlikely to meet RICS standards without a human in the loop. AI should augment, not replace, surveyor judgment. Insight can be accelerated, but responsibility can’t be outsourced. The prize isn’t automation for its own sake. It’s amplified expertise.
Sector: Commercial Maria Wiedner MRICS is the founder and CEO of Cambridge Finance and a member of RICS’ Commercial Property professional group panel (PGP).
Is the commercial property sector embracing the potential uses of AI?
The commercial property sector is aware of AI’s potential – larger firms and forward-looking investors are experimenting with AI for valuations, asset management, and market analysis.
However, compared with sectors such as finance, commercial property has been slower to embrace AI due to fragmented data, confidentiality concerns, and cultural resistance to change. The sector risks falling behind unless adoption accelerates.
What opportunities and challenges has AI brought with it?
The opportunities include faster analysis of large datasets; automated valuations and cash flow modelling; improved forecasting of rents, yields, and market cycles; and enhanced decision support through scenario analysis and sensitivity testing.
However, there are challenges too, such as data quality and consistency, as well as concerns about transparency and ‘black box’ AI models (where the user isn’t able to see the internal workings of a system). Surveyors and analysts often lack AI and data science training, which creates a skills gap. Then there are ethical and regulatory questions, especially aligning outputs with RICS Red Book standards.
What is the general sentiment in commercial property towards AI?
Many surveying professionals recognise AI’s efficiency benefits but worry about accuracy, accountability, and the risk of being replaced. The sentiment is mixed: younger professionals are more open to AI, while senior surveyors are cautious, focusing on professional judgement and client trust.
Are companies finding the integration of AI challenging?
Yes. Integration is proving difficult because property data is siloed across different platforms, formats, and owners. AI requires clean, structured datasets to deliver value, but the industry still struggles with fragmented leases, valuation assumptions, and transaction data. Many companies also lack in-house technical expertise and must rely on external providers, adding to costs and integration challenges.
Is AI streamlining certain processes in the industry? And is it improving the quality of data received?
AI can automate repetitive and data-heavy tasks such as lease abstraction, rent roll analysis, comparable evidence collation, and initial valuation modelling. This can save significant time and reduce human error. However, interpretation, professional judgement, and compliance with RICS standards cannot be fully automated. AI should be viewed as an assistant that supports surveyors in making informed, compliant decisions, rather than as a replacement for professional expertise.
Valuations can be streamlined, particularly for standardised asset classes like residential, logistics, and retail portfolios. Automated valuation models (AVMs) speed up comparisons and produce indicative values. However, data quality is not necessarily improved by AI; rather, AI helps clean and structure existing datasets.
Sector: Building surveying Adrian Tagg MRICS is an associate professor in building surveying at the University of Reading and managing director of surveying firm Tech DD Ltd.
Are building surveying professionals embracing the potential of AI?
Building surveyors want to root out and establish the facts through evidence-based analysis epitomised by a physical site inspection. Why would they place their faith or trust in something that is untested in an environment where professional liability and client confidence is key?
Despite this, the role of the building surveyor has changed significantly since the formation of RICS in 1868. As well as reviewing documents before inspections or after a visit to corroborate the findings, there is a need to input survey findings into reports and present this to clients who often require a summary of the key information, risks, investment costs or other ‘red flag’ issues. Surveyors are certainly beginning to use AI for these administrative tasks or legal and technical analysis.
What opportunities or challenges has AI brought with it?
With clients paying fees that are often fixed for professional advice, AI that makes the process of document review or other administrative tasks more efficient is a real opportunity to get more work done.
It has proved effective with the review of lease clauses, such as those covering repair obligations or principal dates associated with break clauses or key terms. While this is still considered to be in its infancy, I spoke to a director at Savills recently who said: “It takes a fraction of a second to do what we used to do in an hour or so, and so far has been very accurate, even with crumpled old yellowing paper leases.”
How can predictive AI help in areas like building maintenance and is its use becoming widespread?
Predictive AI is probably a phrase that will worry most surveyors in a professional environment where they are liable for their advice. There have been instances where the use of the word ‘renew’ instead of ‘replace’ has resulted in thousands of pounds of damages being awarded. Can AI interpret such nuance?
Having said that, there is an attempt to utilise predictive AI for things such as the likely presence of mould to residential properties. Surely older houses are more prone to damp and therefore more likely to suffer mould? However, the variables in this assumption appear too great as building occupation, the presence of heating and ventilation as well as human activity such as drying washing on radiators can have wildly differing outcomes on the generation of mould. Despite this, there are surveyors actively developing AI to establish the likelihood of such events.
How can predictive AI help in areas like building maintenance and is its use becoming widespread?
While building surveyors are naturally cautious and suspicious, they are also inquisitive as well as pragmatic. AI is seen as being something that can be of benefit and certainly clients would welcome this if it reduced professional fees but the majority of surveyors appear reluctant to allow AI to interfere with the physical survey or site data collection process.
To what extent can AI automate certain surveying processes without compromising RICS standards?
This perhaps is the most challenging and thorny issue with the use of AI, as all professional members are obliged to adopt best practice or the rules of engagement stipulated within the professional standards.
In terms of client instruction, professional responsibility and liability there is no flexibility built into professional standards or professional liability insurance policies to accommodate AI. There still remains a need for surveyors and ultimately human intelligence to inspect, analyse, report and sign off on their advice.
Sector: Valuation Paul Aylott MRICS is head of valuations and lease advisory at Glenny LLP Chartered Surveyors
Is the valuation sector embracing the potential of AI?
The valuation sector is embracing AI and automation as much as, if not more than, other sectors of real estate. In general, valuation firms have been progressive yet measured in adopting automation, particularly in respect of collecting data and completing due diligence tasks.
What are the main opportunities or challenges AI has brought with it?
The main opportunities in this sector are around efficiency, faster data analysis and the ability to draw insights from large data sets. Reducing time on repetitive tasks, which allows surveyors to focus on professional judgement and client service, is a significant opportunity.
The main challenge is balancing this with ensuring that the professional service provided meets RICS standards and the clients understand the process and how conclusions are reached.
Is the change from AI mostly positive, negative or are you still undecided?
On balance, the change is positive. Automation and AI have the potential to enhance rather than replace professional expertise. There is of course caution about over reliance on technology without human oversight.
Valuation is not just about the numbers but about local knowledge, professional judgement and context, things that AI is not yet capable of replicating.
What is the general sentiment among valuation professionals towards AI?
There is an expectation, particularly among the younger generation of registered valuers that AI and automation should play a key part of the task, reducing the repetitive elements so that professionals can focus on judgement and client service. I believe that this will gather momentum as the next generation of valuers enter the marketplace and it might become a differential to candidates when considering career options and which firm to join.
Those businesses that invest in automation and AI are likely to attract the best quality candidates and the removal of many of the repetitive tasks in the valuation process might make the sector more appealing to real estate graduates entering the market. However, the importance of graduates and trainees understanding the process cannot be ignored.
Are there concerns around the transparency of AI in valuation and over-reliance on it?
Transparency is key in the valuation process. Businesses that are able to adopt AI and automation into their valuation practices but still ensure that transparency and professional service is at the heart of every step of the valuation process will see the benefits.
The ultimate responsibility for accuracy, compliance and professional judgement remains with the surveyor. AI and automation should be seen as a supporting process rather than a replacement.
Responsible use of artificial intelligence in surveying practice
A new RICS professional standard, effective 9 March 2026
