In the ever-evolving South African quantity surveying environment, keeping up with market trends and industry developments is essential to maintaining professional relevance. One of the most significant recent shifts has been the rapid integration of artificial intelligence into everyday professional work.
While AI as a concept has existed for decades, its practical application has changed dramatically in a short period of time. Tools that were once considered experimental are now being adopted at an unprecedented pace, reshaping how professionals across industries approach analysis, communication, and decision-making.
The release of generative AI tools such as ChatGPT in late 2022 marked a clear turning point. The platform reached one million users within days and one hundred million within its first two months, with adoption continuing to accelerate since then. Today, hundreds of millions of users globally rely on AI tools for both work-related and personal tasks. This rapid uptake highlights how quickly AI has moved from being a novelty to becoming an expected part of modern workflows.
For quantity surveyors, this shift is particularly relevant. Those who understand and apply AI effectively are increasingly better positioned to improve efficiency, enhance decision-making, and add greater value to clients. Rather than remaining an abstract concept, AI offers several accessible applications that can reduce evaluation time and limit repetitive document reviews when used appropriately.
That said, it is important to remember that AI tools are exactly that, tools. They are best used as a second set of eyes rather than a final authority, there to support professional judgment without replacing it.
The following examples highlight practical applications of AI that are already influencing how the profession engages with this technology. Rather than theory alone, these areas reflect real changes in practice, shaping how quantity surveyors approach analysis, decision-making, and professional advice.
1. Market research and benchmarking
With access to large and diverse data sets, AI can analyse current market information, material price trends, and labour cost fluctuations, helping quantity surveyors remain informed in an increasingly volatile economic environment. Recent research by the Association of South African Quantity Surveyors (ASAQS), which explored the use of AI to price a simple one-brick wall, provides a useful illustration of both the potential and current limitations of this technology.
While the exercise demonstrated that AI can generate indicative pricing based on available data, it also highlighted that such outputs cannot yet be relied upon without professional oversight and contextual adjustment.
Although still in its early stages, this application offers valuable insight into how AI could be used within the construction environment as a supporting tool rather than a definitive source. When applied in this way, it can be especially valuable in advising clients on timing, escalation allowances, and procurement strategies.
2. Cost planning and early estimates
AI-driven tools can support early-stage cost planning by analysing historical project data, regional cost benchmarks, and escalation trends derived from current and past BER indices. When provided with clearly defined project parameters – such as building typology, geographic location, gross floor area, anticipated quality and specification level, primary structural system, provisional allowances for finishes and services, and the intended procurement strategy – AI can generate indicative cost rates per square metre based on comparable developments.
When supplemented with a quantity surveyor’s own historical project data, including actual tender rates and final account outcomes, these estimates can more closely reflect real market conditions. This comparative approach enables AI to identify cost drivers, highlight anomalies, and produce more informed baseline rates. For South African quantity surveyors who frequently undertake feasibility assessments with limited design information, this can significantly improve both the speed and reliability of early-stage estimates.
While professional judgment remains essential to validate and refine outputs, this process provides a stronger foundation for early client discussions around affordability, scope alignment, and cost risk.
3. Tender analysis and procurement support
Building on the earlier reference to the ASAQS research, similar principles can be applied during the tender analysis process. When used as a benchmarking tool, AI-generated indicative rates can assist quantity surveyors in comparing tendered prices not only between competing tenderers but also against prevailing market expectations.
In this context, AI can help identify abnormal pricing, potential under- or overpricing, and flag items that warrant closer scrutiny. This additional layer of comparison supports a more informed tender evaluation process, particularly in volatile market conditions, while reinforcing the role of professional judgment in interpreting results. Consequently, quantity surveyors are better positioned to focus on the core purpose of tender analysis: effective risk management.
4. Cost reporting and forecasting
By tracking project expenditure, AI-based tools can assist in forecasting final account outcomes and identifying potential cost overruns at an earlier stage. Beyond basic forecasting, these tools are particularly effective at identifying trends and early warning indicators within project cost data. In the South African construction context, this may include preliminaries consistently exceeding allowances, provisional sums being eroded earlier than anticipated, escalation allowances becoming insufficient due to material price volatility, or certified progress not aligning with actual site productivity.
By reviewing both historical and live project information, AI can also highlight recurring issues such as repeated variations within specific trades, unexpected fluctuations in monthly valuations, or cost movement linked to programme delays. These indicators enable quantity surveyors to interrogate the underlying causes – whether arising from ongoing design development, procurement challenges, or site-related constraints – before they materially impact the final account.
When used in this way, improved forecasting supports earlier and more informed risk trend analysis, resulting in clearer, more accurate cost reporting and greater transparency for clients and project teams. More importantly, it enables quantity surveyors to provide timely, proactive advice and maintain effective cost control throughout the life of the project.
5. Claims and monthly valuations
AI can assist in the review of correspondence, payment valuations, and contract documentation by identifying patterns, potential risks, and missing or inconsistent information. This improves response times to clients and contractors in relation to claims and disputes, while reducing the likelihood of oversight. Month-to-month valuations can also be compared more effectively, enabling quantity surveyors to identify changes in measured work, variations, and provisional sums. By flagging unexpected movements or inconsistencies, these tools support more informed assessments and enable issues to be addressed proactively rather than reactively.
6. Professional writing and communication
Beyond basic grammar checks, AI can assist quantity surveyors with drafting reports, correspondence, and meeting minutes in a clear and professional tone. It can also transform brief, unstructured notes into well-articulated documents with clearly defined points presented in a logical order, saving time while maintaining consistency and quality. This allows professionals to focus more on the substance of discussions rather than the mechanics of note-taking.
This capability can be extended through tools such as Read.ai, which provide real-time meeting transcripts and automatically generate summaries. By capturing key discussion points, action items, and assigned responsibilities, these tools support more effective follow-up, internal coordination, and project tracking.
Appropriate caution is, however, essential, particularly in client-facing engagements. Considerations around confidentiality, data privacy, and professional ethics remain crucial. The use of such tools is disclosed upfront, with the necessary permissions obtained from all parties. Ultimately, responsibility rests with the practitioner and the firm to ensure that AI is used in a manner aligned with professional obligations and the intended objectives of the engagement.
A values-led approach to responsible AI use
Perhaps the most significant shift required is not simply the adoption of new technology, but a change in how we engage with it. Treating AI as a search engine and asking superficial questions only scratches the surface of its potential. The real value lies in experimentation, critical testing, and developing an understanding of how these tools can meaningfully support day-to-day professional practice. For those already on this journey, the opportunity lies in going deeper; for those who have not, AI literacy is increasingly becoming a necessary part of professional development.
Despite its growing capabilities, AI continues to rely on human input, context, and professional judgement. These tools are not a final authority, but a support mechanism. The true advantage, therefore, will not come from the technology itself, but from how effectively, responsibly, and collectively the profession chooses to use it.
As we at RLB continue to engage with AI, our core values provide a clear framework for how this technology should be applied in practice. Truth is reflected in using AI transparently, understanding its limitations, and ensuring that insights remain grounded in verified data and professional judgement. Trust is built by maintaining accountability, protecting client data, and ensuring that AI enhances confidence rather than undermines it.
Only by sharing knowledge across teams, in the true spirit of collaboration, will we succeed Together, using AI as a collective support tool rather than an individual shortcut. As we look to Tomorrow, embracing innovation allows us to strengthen decision-making, improve outcomes, and prepare the profession today for the challenges of the future.