5. AI Moves into Real Estate

Although the stage of AI exploration and adoption varies widely across firms, the use of artificial intelligence applications is expanding across the real estate industry. With this in mind, the following are the types of tools in use by firms in 2025.

• Generative versus agentic AI. Today’s first wave of AI tools are predominantly generative applications (GenAI). GenAI can create content (text, media, or code) in response to a prompt. GenAI produces outputs using machine learning models trained on content sourced broadly from the internet (public web data) or narrowly on proprietary datasets selected by the application developer (internal company applications). Use cases include customer service chatbots, software development, routine administrative tasks or paperwork, research.

• Agentic AI picks up where GenAI leaves off. It can plan and act with minimal prompting, running continuous processes with limited supervision. Use cases for agentic AI include analyzing information to provide predictive analytics, executing financial market trades, recommending health treatments, managing inventories, and blocking malware.

Real estate firms are in the initial stages of exploring how AI could improve internal operations, typically in administrative or recurring tasks with consistent deliverables. Many larger real estate firms, however, have moved toward using AI for higher-value internal tasks and property operations.

As AI use expands further into research, underwriting, and reporting tasks, it is becoming a larger threat to hiring, particularly for entry-level roles. Increased adoption of these technologies has reduced entry-level employment across industries in the most exposed occupations by 13 percent, according to 2025 research from Stanford University, while employment for more experienced workers in the same roles has been stable or growing. The most exposed occupations include computer programmers, financial managers, accountants, and sales representatives.

While saturation on the scale where AI tools replace workers is rare in the real estate industry, it is occurring. Real estate use cases include data analytics,  leasing and investment recommendations, and price modeling. Real estate firms with operationally intensive property holdings, such as residential and health care–related assets, are using AI to improve customer services elements of their properties.

Our interviewees expect that tenant demand will be impacted by the increased adoption of AI tools, although these workforce impacts will take time to evolve. Analysis of AI adoption today shows a mix of impacts on existing employment from eliminating jobs or tasks to creating new forms of work. In this early stage (limited adoption in most firms and saturation at a few large firms), job transformation is more common than AI replacing employees.

However, entry-level positions are at risk of AI replacement today. Employment declines for entry-level workers are tied to automation rather than task augmentation alongside employees. Young college graduates in 2025 face a more difficult job market. The Burning Glass Institute reports that unemployment rates for young adults, (20 to 24 years old) are rising for those with a bachelor's degree or higher, while unemployment in the same age group with less education is falling. Separately, AI adoption to replace entry-level tasks is keeping more experienced employees in their roles, who themselves are using AI to gain new efficiencies around mundane tasks.

Nearly half of the skills in a typical U.S. job posting are poised to undergo a “hybrid transformation” due to AI adoption. Hybrid transformation means that human oversight remains critical to the work. AI applications are primarily changing administrative tasks for roles requiring in-person services, while more tasks can be automated in technical roles. Skill replacement by generative AI in 2025 remains small, at 0.7 percent of 2,900 skills analyzed, which is significant growth from zero skills replaced one year prior.

Consider the potential applications in nursing versus software development. GenAI creates efficiencies in both roles but is less transformative in nursing. Software development is among the roles most exposed to generative AI because the core skills are technical and routine. These tasks can be replicated by GenAI with humans directing work and providing quality control. In nursing, the opposite is true with core skills requiring a physical presence and real-time problem solving with technical and routine tasks required, but less central to the role. Both roles are transformed by the adoption of AI tools with different employment impacts. AI can reduce administrative tasks for nurses and shrink the software team.

Residential owners and operators are diving into AI tools for resident services to create efficiencies, while improving customer service. These use cases include providing tech-savvy renters with services delivered in a way they prefer, and health-tracking applications in assisted living or memory care facilities to improve emergency response times.

For traditional multifamily operators, the consolidation of onsite services under a dedicated chatbot for residents allows staff to serve multiple properties from a single office. Practitioners applying this use case find fewer staff members are required on site, but overall staffing has not changed due to the software team tasked with developing and updating the chatbot application. These multifamily operators also find their young adult residents prefer renting properties using a chatbot for basic communications over those with an onsite manager.

The most advanced operators in this space are developing fully AI-enabled properties—automated tours, leasing, and resident services—with fewer or no onsite amenities to provide high-quality rental units at a discount to comparable units in properties with full onsite amenities.

Overall, artificial intelligence adoption is in preliminary stages and showing promise in automating routine tasks, some of which reduce the need for full time employees. On the flip-side, the use of AI tools in company and property operations requires new skill sets, which could support more hiring. The real estate industry has much to consider when adopting AI tools and setting property strategy in the years to come. There may be fog, but once this clears, technology will continue to change the way we work.