New year, new technology: what to expect from AI’s evolution in the real estate market in 2026

In early stages, AI was seen as an unstable technology, often limited by imprecise answers. Today, the picture is different. For Paladino, the turning point lies in models being able to connect to real data sources and operate with greater reliability.

“Before, AI hallucinated; then it stopped hallucinating; now it can connect to document databases, retrieve answers, and even identify what it doesn’t know—calling a human when needed.”

This technical maturity opens space for more sophisticated use cases in real estate, especially across leasing cycles, asset management, due diligence, and back-office operations—with direct gains in productivity, standardization, and error reduction.

More than replacing professionals, the next stage of AI in commercial real estate is about collaboration. According to Paladino, the winning logic will be hybrid workflows, in which humans and intelligent systems work together.

“Today you already have flows where collaboration works better. AI generates a response, the human reviews it, and the process continues. This coexistence will work increasingly well and more fluidly.”

In practice, this means AI stops being a standalone tool and becomes embedded within work platforms, reducing the need for extensive training and accelerating adoption in teams’ daily routines.

With first-touch service automated and more efficient, a new challenge begins to emerge: managing the volume of qualified leads. “The next bottleneck is helping organize and improve the broker’s time efficiency. Once the first interaction is solved, this becomes the big challenge.”

The trend is for new AI solutions to focus on pipeline management, intelligent prioritization of opportunities, and automation of follow-ups—areas that still lack digital standardization in the Brazilian market.

Another field with strong potential is legal-commercial work. Although still in early stages, automating contract-related steps is expected to gain traction in the coming years.

Finally, AI evolution also changes the real estate customer journey. With increasingly autonomous systems, the market is likely to accept interactions at any time, including outside traditional business hours—expanding the pace and availability of negotiations.

More than a technological shift, the evolution of artificial intelligence in commercial real estate signals a structural transformation. By supporting decisions, organizing workflows, prioritizing opportunities, and integrating data throughout the entire real estate journey, AI frees up time for higher-value strategic activities and redefines how professionals relate to the business. For Real Estate, the debate is no longer about adoption, but about the quality of that integration.

The challenge for the sector is clear: turning increasingly intelligent models into more efficient, ethical, and scalable processes. In a market driven by data, speed, and precision, artificial intelligence stops being a promise and becomes competitive infrastructure.