The true value of a building increasingly depends on the quality of its data.

Ask any investor what drives property value today, and the answer might surprise you. Location and square footage, the traditional measures of value, are taking the backseat to a surprising new metric: data. Across the PropTech space, AI in real estate is turning buildings into self-reporting assets that describe their own performance. Every data point from energy use to tenant flow adds to a property's digital profile, making it easier to understand, optimise and finance.

At DO OK, I see this transformation firsthand as we help PropTech teams build the kind of reliable AI-ready systems that turn building data into real intelligence. In one recent project, we helped a Norwegian PropTech company scale a cloud-based HVAC optimisation platform to improve how its IoT sensors, air quality monitors and weather data feed into AI models that improve energy efficiency. We've learned from projects like this how the right data architecture turns everyday telemetry into insights that improve sustainability and value, as well as comfort for building occupants.

The same focus on data guides my work at Rankfor.ai, a company incubated within DO OK, now operating as an independent venture. PropTech platforms measure how buildings perform in the physical world, but Rankfor.ai measures how a brand or organisation performs in the digital space. We quantify visibility within large language models and AI ecosystems, providing a new kind of market signal that shows how clearly a company is understood by machines.

Similar principles drive building valuation: assets with clean, structured, discoverable data are easier for AI to interpret. Brands and portfolios now gain value through how clearly they're represented in AI ecosystems, and the question now for investors is how well their assets' data performs.

Real estate value was traditionally tied to physical factors like location, materials and comparable sales. Those still matter, but they only tell part of the story. The most competitive assets now are data-driven real estate: properties that generate, analyse and act on information about their operation and environment.

Data layers now shape how properties are evaluated:

• Operational data: energy use, occupancy, maintenance history

• Environmental data: temperature, air quality, building materials, sustainability metrics

• Market data: comparable transactions and demand trends

Connected systems (building IoT) record and relay this information into smart-building data pipelines that feed automated valuation models (AVMs). These systems move valuation from static appraisal to a continuous, data-rich feedback loop.

The change also mirrors wider market expectations. Tenants and investors want transparency and evidence of performance, and data has become a proxy for trust. A property rich in clean, contextual information can command a premium, the same as a well-indexed brand that stands out in search results. In both domains, visibility = value.

Over the past decade or so, PropTech AI has been changing valuation from an art informed by experience into a data-powered science. AI real estate valuation tools now process millions of signals, like maintenance logs and satellite imagery, to create faster, more objective appraisals.

New models help automate and predict value:

• Automated Valuation Models (AVMs) for instant price estimation

• Predictive analytics for forecasting yield, energy costs or repairs

• Computer vision for assessing condition from photos or video

These technologies reduce bias and allow dynamic property valuation, reflecting live conditions rather than past reports.

Behind every accurate valuation lies a robust real estate data infrastructure. Reliable pipelines, secure integrations and structured metadata determine whether AI can interpret a building's story correctly. DO OK's engineering approach adds value here, helping PropTech firms design systems that keep their data clean, connected and usable, creating true asset intelligence for buildings.

If AI can calculate a building's worth based on how it performs, can it also measure a company's or brand's value based on how it appears digitally? Answering that question connects PropTech and AI visibility analytics through solutions like Rankfor.ai, which I'm proud to be helping move toward full release after a successful PoC and fundraising round.

Rankfor.ai applies similar principles to digital assets that property valuation AI uses for physical ones. Instead of analysing maintenance cycles or energy usage, it measures semantic visibility, digital footprint and market perception across search engines and large language models (LLMs). It quantifies how discoverable, trustworthy and relevant an organisation appears within AI ecosystems.

For investors and analysts, this represents a new form of continuous valuation. PropTech systems measure a building's performance, and Rankfor.ai measures an organisation's performance in data space: how often it's surfaced, how coherently it's represented and how that visibility evolves.

Data maturity forms the foundation of both approaches. Clean, structured, well-governed data allows both valuation models and visibility algorithms to see the full picture. Data quality determines perceived worth for buildings and brands alike.

Assets are only as intelligent (and therefore only as valuable) as the information they can generate, structure and share.

In data-driven real estate, every connected meter and sensor contributes to a growing stream of smart-building data. When combined within a robust building IoT network, this information enables real-time optimisation, predicting energy use, scheduling maintenance and improving tenant comfort.

Here's what data maturity looks like in practice:

• Collection: sensors and systems that produce accurate, continuous data

• Structure: interoperable databases and metadata that connect them

• Governance: quality control and compliance build trust

The same principles power digital visibility. Rankfor.ai depends on well-organised metadata and content hierarchies that make organisations legible to AI. In both cases, the clearer the data, the more completely AI can "see" the asset.

Achieving that level of clarity requires deliberate, well-designed real estate data infrastructure, which DO OK helps build for PropTech and AI visibility platforms alike.

The next frontier for AI in real estate is how buyers and sellers perceive assets. Large language models such as ChatGPT, Gemini and Claude are proving their worth as research tools for analysts and investors, surfacing patterns and insights that previously took weeks of painstaking manual work.

That transformation makes visibility a new form of currency. A building's performance or certifications might live in databases, but if the data isn't structured for AI retrieval, its story remains hidden. The same is true for companies and PropTech platforms.

Rankfor.ai bridges that gap by measuring an organisation's AI visibility; how clearly its data appears and how coherently LLMs represent it across multiple surfaces. The platform tracks:

• Discoverability: how easily data is surfaced

• Coherence: how consistently it's represented

• Trustworthiness: how credible it appears to AI systems

This mirrors the predictive systems that forecast occupancy or maintenance for PropTech players. Visibility leads to foresight, helping decision-makers anticipate risk and opportunity before they appear on the balance sheet.

The intersection of PropTech AI and visibility analytics is reshaping how developers, investors, and technology providers create and measure value for all stakeholders.

Data infrastructure is now a strategic asset. IoT sensors, dashboards and sustainability metrics feed the real estate analytics platforms that underpin valuation accuracy and compliance. Mature, interoperable data improves operations and enhances market value.

Data-driven real estate and AI in property management tools provide constant performance insights. Portfolios can be rebalanced dynamically as new signals emerge, making valuation a continuous process rather than an annual one.

The opportunity lies in connecting the dots. Combining operational data from physical assets with digital visibility metrics, like those from Rankfor.ai, creates a complete picture of market performance.

At the same time, a new distribution and communication channel is emerging: large language models and conversational interfaces. These AI-driven environments represent a fresh way to surface assets, insights and reputations to investors and buyers in a competitive property market. Those who engage early will shape how property information gets discovered, discussed and valued in the years ahead.

Teams that treat real estate data infrastructure and AI visibility as complementary investments will gain a distinct edge. Chat-based and LLM-powered channels are just starting to take shape, and now is the time to establish presence and credibility within them. In a market driven by algorithms, data clarity and discoverability are the new curb appeal.

The trajectory of AI in real estate points toward assets that know their own value. As digital twin real estate models become standard, they will continuously simulate performance, and soon valuation itself.

Self-valuating assets will combine:

• Continuous operational monitoring

• Predictive market correlation

• Automatic valuation updates

Sensors and smart-building data will feed models that link operations with market conditions in real time, creating machine-verified transparency for lenders, investors, property owners, tenants and maintenance personnel.

But even a perfectly instrumented building still needs discoverability within AI ecosystems. Rankfor.ai adds that layer, translating performance data into recognition and trust in the digital marketplace.

The infrastructure behind this future, reliable data pipelines, governance and open standards, is what we build at DO OK every day. These systems working together holistically mark the beginning of an economy where assets constantly explain and justify their value through data.

AI in real estate is changing what we mean by "value." The assets that stand out tomorrow will be efficient and sustainable, but most of all they will be legible to AI. Worth will emerge from how clearly an asset's data tells its story to both people and machines.

Data maturity and transparency are becoming the new differentiators in the PropTech space. At the same time, Rankfor.ai shows how visibility itself is an asset, transforming perception into measurable advantage.

Companies like DO OK build the bridges that make this possible: the data infrastructure, pipelines and integrations that turn raw information into continuous insight. In this new real estate environment, visibility is fast becoming the purest measure of an asset's worth.