Gareth Parker, Co-founder of N3 Technologies, explores how trusted, transparent and structured data can help property and construction businesses manage risk, improve decision-making and safely adopt Artificial Intelligence.
Success in today’s property and construction market is defined by resilience and cost efficiency and for developers, surveyors and funders, utilising data and making informed decisions has become increasingly critical against a backdrop of evolving market conditions, growing cost pressures and changing requirements across reporting, such as sustainability and ESG tracking.
In an industry fraught with uncertainties, the use of both historical and real-time data and predictive analytics can mitigate many risks, including potential delays and over-runs, while also helping with scenario planning. However, currently, while increasingly large volumes of project and building information are being generated across multiple systems and reports (site constraints, structural design decisions, sustainability strategies, building systems, development projects), insights aren’t being understood or utilised effectively. In fact, this information often isn’t even being distributed across planning documentation, consultant reports and internal reporting tools.
Companies need to get the right tools and a cohesive data strategy in place to remain competitive. Against a backdrop of rising costs, political uncertainty and a disrupted supply chain and labour market, developers need to make decisions based on reliable, current intelligence rather than assumptions or outdated information. It is only through access to trusted, real-time data that property teams can make better-informed decisions, manage risk and improve project viability across complex development programmes.
The power of data
Data is an incredibly valuable asset. The real value comes from being able to see what it’s telling you, and when utilised correctly, data is a game changer for decision-making, helping teams spot trends, understand context and visualise the bigger picture.
Businesses that don’t embrace real-time data intelligence are in real danger of being left behind as competitors capitalise on faster, evidence-based decision-making, where they see how individual project elements compare and identify where costs or performance are moving away from expectations. Teams need to use data to compare appraisals, predictions and similar projects across key cost and performance measures.
As buildings and development projects have grown more data-rich, the problem is no longer producing data, it’s making it trustworthy, accessible and actionable. In a pressurised industry, property professionals are struggling to defend their data-driven decisions due to a reliance on static datasets which are seen to be outdated and therefore inaccurate and not an appropriate benchmark for forecasting.
Rather than relying on archives or information that is out of date, teams need access to structured, real-time data from live projects that adapts with the market to inform decisions, stay agile and competitive. By centralising project data across developments into one single, trusted platform, teams can benchmark performance and cost against thousands of similar developments as well as monitoring risk and analysing trends in real time.
When relying on prediction and comparison data, teams need to ensure the information isn’t an estimate, inaccurate or hallucinated in any way. Vitally, all data must be verified to combat the growing lack of trust in the industry in the age of AI. Many tools on the market are not transparent about the source of data and how calculations have been made. Consequently, decision-makers feel this rationale can’t be trusted.
Building a trusted data foundation
A businesses Digital Transformation is only as strong as its data foundations. To build trust, data and AI tools for the property sector need to be transparent and show how data has been sourced and calculations have been put together. The most successful teams will rely on accessible, well-managed project data that is contributed by the people who create it, including surveyors, developers and funders across the UK. To ensure consistency and reliability, teams need to utilise data that is normalised and structured, not scraped or inferred.
For a sector as risk-averse as real estate, the rapid pace of change in AI tools and usage presents a threat to data quality, sustainability credentials, ethical principles and the workforce. To ensure data and AI is being utilised responsibly, transparency is critical. As the increase in AI-generated material grows and becomes more believable, it’s increasingly important that businesses disclose how and when they use AI in all deliverables. Without policies, trust and transparency, Generative AI will quietly fill data gaps with plausible, untraceable content while being undeclared and unchecked. If your team is currently utilising a data or AI tool which can’t answer questions around security, provenance or data sovereignty, it is worth asking whether you can truly trust the information it produces.
This is not to say AI has no place in construction, as the technology has the potential to further revolutionise efficiency and decision-making. However, for automation and new tools to deliver value safely and reliably, clear boundaries and policies need to be in place. For example, teams should use AI to interface data, not generate it, a human should be kept in the loop at all times and rather than layering AI onto unverified or untrusted data, teams should first ensure the underlying data is accurate, structured and traceable. Trusted data is defined by information where every value can be traced, in terms of where it came from, how it was produced and how it got to its current form. Data sovereignty is also an increasingly important consideration for compliance and teams should ensure that any platform they use is storing data in the UK/EU infrastructure and never training generative models outside of this domain.
In property and construction, success will not be defined by how much data or AI a business uses, but by how effective its tools and strategies are in identifying industry trends and encouraging intelligent decisions. By utilising secure, transparent and traceable data, property teams can improve resilience, manage risk and support long-term project viability and business competitiveness. It is only through ensuring a trusted, secure data foundation that new cutting-edge automation and AI solutions can be deployed with confidence to turn complex project information into faster, evidence-based decisions.
