BTR: AI Reshapes PropTech - Real Estate Sector Enters New Era of Intelligence, Integration, and Strategic Agility

Carla Hinson, MRI Software

SILVER SPRING, MD, UNITED STATES, July 30, 2025 /EINPresswire.com/ -- The property technology sector—PropTech—has entered a phase of accelerated disruption, driven by the convergence of artificial intelligence, legacy system modernization, and shifting economic pressures across residential, commercial, and industrial segments. What began as a fragmented landscape of point solutions is rapidly evolving into an interconnected ecosystem where strategic data access, automation, and predictive analytics define competitive advantage.

According to Fortune Business Insights, the global PropTech market is projected to grow from $40.2 billion in 2025 to $88.4 billion by 2032, reflecting a compound annual growth rate (CAGR) of 11.9%. This trend underscores the sector’s transition from basic digitization to advanced data-driven transformation.

Carla Hinson, Vice President of Solution and Innovation at MRI Software and a 26-year veteran of the sector, believes that AI offers a critical bridge between fragmented infrastructure and the integrated decision-making that will likely separate winners from the rest.

This next evolution of PropTech, she pointed out, is not just about deploying new tools—it’s about unlocking value from existing systems. For many organizations, the question is no longer “What can we digitize?” but “How do we extract intelligence from what we already have digitized?”

From Fragmentation to Function: Closing the Data Gap

Historically, PropTech has been defined by a siloed toolset. Separate systems handled leasing, facilities maintenance, finance, and tenant engagement—often without interoperability. This fragmentation led to inefficiencies and costly mistakes because technology decisions and tactical processes have not been effectively tied to overall business strategy.

“We’ve seen entire HVAC systems replaced just weeks before a lease was set to expire—simply because the facility and leasing teams weren’t aligned,” said Hinson in a recent executive vidcast interview for journalists. “These silos create friction, waste, and strategic blind spots.”

This structural problem is echoed in market findings. The Business Research Company estimates the global PropTech market will have risen from $36.1 billion in 2024 to $41.5 billion by the end of 2025, a 15.1% annual growth rate, fueled by the imperative to integrate operations by better leveraging AI and cloud platforms to tie together disconnected real estate ecosystems.

Artificial intelligence, explained Hinson, is reshaping the very definition of integration by moving beyond APIs and middleware that requires high level of technical expertise to a more adaptive framework, where systems can autonomously interact with and interpret data across platforms with much lower levels of human technical intervention.

“As a result, it is now increasingly clear that the first step in effectively integrating AI into your modernization strategy is to understand what data you already have,” Hinson said. “Organizations often don’t realize they’re sitting on decades of insights—cost histories, occupancy patterns, maintenance cycles—that haven’t been tapped because they’re locked in legacy systems.”

AI as Strategic Infrastructure, Not Just a Tool

It is in this context that AI is becoming central to how real estate professionals plan, operate, and optimize portfolios, from lease management to predictive maintenance.

“AI is allowing us to move beyond reaction into anticipation,” Hinson explained. “Whether it’s spotting a data irregularity before it becomes a costly mistake or forecasting an asset failure before it disrupts operations, the strategic implications are enormous.”

AI also enables natural language querying, reducing the need for specialized technical skills. “The tools are adapting to the user—not the other way around,” Hinson said.

This is particularly relevant in a market where real estate professionals are overburdened with reporting and compliance tasks. AI allows organizations to shift resources from data wrangling to decision-making. This improves both responsiveness and employee retention because, in the past, much of the data management work performed by staff was typically done after hours and on weekends, when workplace distractions are minimized.

Trust, Governance, and the Rise of Vertical AI Models

Despite enthusiasm, adoption is tempered by security and compliance concerns—especially around the use of public large language models (LLMs). This has triggered growing interest in domain-specific, small language models (SLMs) trained on proprietary or industry-specific data.

“Domain expertise in AI matters. You can’t apply a residential lease model to a commercial portfolio and expect clean results,” Hinson said. “The industry is quickly realizing that verticalized AI—trained for purpose—is essential.”

Consumers of PropTech, she added, who have a well thought out data foundation and an integrated perspective on the problems that they want to solve can generate clear operational returns quickly. Lease abstraction (the process of extracting key data and terms from lease documents and converting them into a structured, digital format that can be used for analysis, compliance, and operational decision-making) has traditionally been an intensely manual process. With AI, it can now be handled by models that extract detailed contract data in seconds. Facilities teams use AI to identify maintenance needs before systems fail. And real-time dashboards allow executives to monitor portfolio-wide performance metrics without waiting on end-of-month reports.

Studies show that knowledge workers in the sector spend between 20% and 30% of their time manually assembling data. AI is reducing that figure dramatically, while also improving the accuracy and utility of the resulting insights.

“It’s not just about productivity—it’s about reducing burnout, retaining talent, and giving people the tools to work smarter,” Hinson said.

AI is also enabling better financial planning, from net operating income to capital expenditure forecasting. With better data that is more effectively integrated across executive decision support systems, predictive models help avoid unplanned costs, while centralized data exposes opportunities to consolidate information and eliminate waste.

Strategic Inflection Point: AI as a Competitive Lever

For C-level executives and boards, AI is increasingly viewed as a strategic differentiator. Early adopters are leveraging intelligent tools to simulate investment scenarios, optimize leasing strategies, and drive portfolio-wide innovation.

“AI isn’t about automating everything. It’s about being intentional,” said Hinson. “Understanding your data, knowing your goals, and choosing tools that support them—that’s where the competitive edge lies.”

The industry’s top performers, she adds, aren’t simply deploying the most AI. They’re deploying it in the right places. As a result, they’re improving occupancy rates, extending asset life cycles, and unlocking insights from underutilized data assets.

And while full AI adoption will take time, the tools are maturing fast, especially in North America. The Business Research Company and Fortune Business Insights both cite markets in the United States and Canada as the largest and most advanced sources of demand accounting for almost 40% of the global PropTech share.

Building the Hybrid Workforce of the Future

Looking ahead, experts expect the emergence of new hybrid roles—where AI specialists collaborate with business leaders to define use cases, manage deployments, and monitor performance. These roles will be critical to scaling AI safely and effectively across complex property management operations.

“We’re moving toward a model where AI is a partner, not a process,” Hinson said. “The companies that succeed will be those that treat AI as part of the team.”

Click Here to Read a full Q&A of this Interview.

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