BIM and AI advance in real estate, but data sets the pace

With tools increasingly integrated into project workflows, the sector is gaining efficiency in market analysis and asset operations; experts point to the key factors needed to turn technology into decision-making

Ruben Millon, Global BIM Manager Program Presenter at Graphisoft

By: SiiLA News

06/18/2026

Architecture has been one of the fields most affected by digital advancement, with new ways of designing, building and developing projects. BIM, or Building Information Modeling, was not the only revolutionary tool to reshape the market. AI, or artificial intelligence, is here to stay, and the current challenge is to build solid data foundations to structure its operation.

According to FGV IBRE, BIM arrived in Brazil in the mid-2000s as a new 3D model. Twenty-four years later, it is now used by around 20.6% of companies in the sector, no longer limited to design visualization, but forming part of the structural foundation of projects by organizing data, processes, coordination and decision-making within a connected environment.

AI complements this process by strengthening the ability to process large volumes of data, run analyses, identify patterns and flag inconsistencies that can support decision-making. When these tools are combined, the operational gains are significant. A report by the Construction Industry Institute, or CII, shows that around 58% of construction activities, from design to operation, do not add value to the final result, a figure that can reach 90% in some cases.

These tools make organization easier, but market interpretation still depends on human assessment. In a practical example, a 24-year analysis makes it possible to evaluate the growth in the number of logistics condominium and office units within a historical comparison.

Offices and industrial properties new supply over the years

The tools support data processing and organization, but they still require context to assess which external factors may be affecting development trends. Although both markets reached a peak in the number of units in 2013, logistics condominiums saw a less intense gradual decline than offices, largely due to the asset profile and the contract models typically adopted. In practice, the tools may organize the data, but it is the professional behind the spreadsheet who explains the reasons behind the numbers.

When rework is reduced, efficiency multiplies. Ruben Millon, Global BIM Manager Program Presenter at Graphisoft, highlighted the key aspects shaping this transition period.

“The main points are process reorganization, information standardization and the development of mature digital environments. Technology alone does not solve structural problems. Without proper workflows, data governance and cohesive processes, even the most advanced tools end up delivering limited gains,” he said.

Despite clear progress, not all segments have a solid data foundation. Sectors such as industry and infrastructure are still lagging behind, while residential and commercial construction show more structured maturity, according to Márcia Doring, a consultant and manager of technology implementation in architecture. The lack of information, combined with confidential contracts, makes it harder to obtain a broad view of the market.

“In practice, many organizations are building extremely valuable knowledge bases, but this information remains restricted to their internal environments. As a result, market evolution is taking place more slowly than it could in a scenario with greater sharing and standardization,” she said.

Segment-level snapshots of the real estate market help fill this gap. Market Analytics indicators, for example, shed light on asset dynamics and absorption trends, supporting investors, tenants and developers in their decision-making.

For Millon, further progress still depends on clearer legislation and stronger cybersecurity frameworks.

“Construction projects contain strategic, operational and even critical infrastructure information. For this reason, data governance, information security and a clear understanding of how AI platforms use this data are becoming fundamental discussions within the sector,” he said.

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