Artificial Intelligence in the natural and built environment sector

Artificial intelligence (AI) is a branch of computer science that looks at how machines make decisions based on data. AI does not refer to one single entity, but to a branch of computer science that incorporates machine learning (the development of algorithms that allow computers to learn and generalise from data) and data science (processes for organising and analysing data).

Unlike human decision-making, AI makes decisions based on data i.e. information in a format that computers can process. It is this decision-making capability that is the most revolutionary feature of AI.

AI is already used in some fields of surveying, such as in quantity surveying (e.g., for cost estimation and quantity takeoff) and valuation (e.g. automated valuation models are used to produce a valuation of property).

AI is less visible in the production processes of surveying work when it is integrated into existing applications, such as search engines, report summary creation, transcription and document processing.

Generally, AI can reduce human error by automating repetitive tasks like data collection and analysis, and it can identify patterns or anomalies that might otherwise be missed.

Like many complex or new tools, artificial intelligence requires new or adjusted skills and knowledge to use it effectively and competently. AI is different to other tools because it can make decisions, so it is important for members to continue to take ownership of their work to ensure that it remains of high quality and relevant for their clients and other stakeholders.

AI is already changing how surveying professionals carry out their work, and members and regulated firms need to respond accordingly by:

• adapting risk management and data safeguarding systems
• carefully considering their approach to governance
• creating rigorous procurement processes
• developing processes to scrutinise outputs.
   

Furthermore, clear communication with the client is vital in maintaining trust and confidence, particularly given the less visible role of AI and the use of client data in third-party AI systems is likely to be the norm. Transparency and clarity in terms of engagement are therefore essential.

Data security is managed through secure storage, management of access, training and protocols regarding the uploading of data into AI systems. Members and RICS-regulated firms will already have measures in place to comply with data protection regulations like the General Data Protection Regulation (GDPR) or local /international privacy laws – these measures will need to be reviewed considering the role that AI plays in their surveying practice.

To mitigate data risks, best practices should be followed. AI tools should anonymise sensitive data and comply with privacy standards to ensure stakeholders' information remains protected.

Yes, RICS is in the process of developing training in different formats to support members to meet the standard, as well as enhance their understanding and use of AI in surveying more generally.

Yes, the Standard will be translated into several languages, likely including: 

• Simplified Chinese (Mandarin)
• Spanish
• French
• German

The standard requires that members and RICS-regulated firms make clear in writing the processes to seek redress if a client feels they have been negatively affected using an AI system.