Artificial intelligence continues to penetrate industries once defined by human relationships, and real estate is no exception. From automated property appraisals to chat-based listing assistants, the idea of an “AI realtor” is no longer speculative. However, new survey data suggests that when it comes to one of life’s biggest financial and emotional decisions — buying a home — many people remain confused. In particular, women seem significantly more cautious than men about replacing human agents with machines.
One last one survey by Home Marketing Services reveals a clear gender divide in attitudes towards AI-only real estate agents. While just over half of men (54.47%) said they do not want AI to replace human realtors, opposition rises sharply among women, with 74.81% preferring human guidance. Only about a quarter of women said they would choose an AI-driven agent, compared to nearly half of men.
These figures underscore an important point: real estate is not simply a transactional market. It is an area where faith, judgment and personal experience matter and where decisions often have long-term consequences.
Unlike many digital services, home buying can’t be easily reduced to a set of data points. A property is more than its square footage, price or location on a map. It is a living environment, shaped by factors such as safety, community, commuting, schools and future resale value.
Bob Lovell, founder of Home Marketing Servicescaptures this complexity succinctly. Buying a home, he suggests, involves navigating a web of considerations – financial, emotional and practical. It is not simply a search and compare exercise, but a process of balancing risk and uncertainty.
The survey results suggest that women may be more attuned to this broader context. Rather than focusing solely on the attributes of the property, many consider the “whole living situation”—including family dynamics, potential risks, and what could go wrong after the purchase.
From a scientific and behavioral perspective, this is consistent with research on decision making under uncertainty. Individuals who weigh multiple contextual factors often exhibit a more cautious approach, especially when outcomes are difficult to reverse. A home purchase, once completed, is rarely easily undone.
Canadian Perspective: Trust and Regulation
In Canada, these dynamics are reinforced by a regulatory environment that places great emphasis on consumer protection and professional accountability. Estate agents are regulated by provincial bodies such as Real Estate Council of Ontario (RECO) which impose obligations regarding disclosure, fiduciary duty and ethical conduct.
These frameworks are built on the expectation that agents act as advocates for their clients, guiding them through inspections, negotiations and contractual obligations. Translating this into an AI-only model is far from straightforward.
Canadian buyers also have to deal with a complex market. Issues such as housing affordability, regional price disparities and changing financing conditions add layers of uncertainty. In this context, the value of local knowledge becomes particularly evident.
While AI tools can provide data, they can struggle to interpret these details. A model may identify a property as “good value” based on historical price, but doesn’t take into account evolving local risks or qualitative factors that an experienced agent might recognize.
Despite these reservations, AI clearly has a role to play in modern real estate. Its ability to quickly process large data sets offers tangible advantages. Prospective buyers can compare properties, analyze price trends and access relevant information without having to consult multiple sources.
AI can also improve accessibility. For first-time buyers, especially those unfamiliar with real estate jargon, conversational AI tools can help explain terminology and describe the steps involved in a transaction. In Canada, where mortgage rules and eligibility criteria can be complex, this type of support can be valuable.
Additionally, AI can help improve the early stages of the buying process. By organizing search criteria, shortlisting properties and creating questions for agents, it enables buyers to access more prepared viewings.
Risks: Loss of advocacy and situational awareness
However, the survey findings suggest that for many, the perceived risks of removing the human element outweigh these benefits. One concern is the loss of advocacy. A human agent acts as an intermediary, representing the buyer’s interests and negotiating with sellers. This role becomes particularly important when deals become complex or contentious. IA, while able to recommend strategies, cannot take responsibility or accountability in the same way.
Another limitation is situational awareness. Real estate decisions often rely on subtle signs—how a property “feels,” if something looks out of place, or if there are signs of underlying issues. These are judgments that currently remain beyond the capabilities of automated systems.
In addition, there is the issue of liability. In Canada, agents are subject to professional standards and may be held liable for errors or omissions. With AI systems, responsibility becomes less clear. If an algorithm misinterprets data or provides inadequate guidance, determining responsibility can be more challenging.
Gender differences and risk perception
The gender divide noted in the survey may reflect broader differences in risk perception. Studies have consistently shown that women, on average, tend to be more risk averse in financial decision-making contexts. This is not a weakness, but often a rational response to uncertainty, especially in high-risk scenarios.
In real estate, where transactions involve significant financial commitments and long-term consequences, this cautious approach may lead to a stronger preference for human support. The presence of an agent provides not only expertise, but also security – a factor that should not be underestimated.
For the real estate industry, the adoption of artificial intelligence is likely to succeed where it complements human expertise rather than trying to replace it. The most effective model can be the hybrid one. AI can handle data analysis, property comparisons, and administrative tasks, while human agents focus on interpretation, negotiation, and relationship building. This approach leverages the strengths of both.
Ultimately, the survey underscores a fundamental point: technology alone does not generate trust. In areas where decisions are deeply personal and financially important, people continue to value human interaction. For many women, this belief seems particularly important. The preference for human agents does not reflect resistance to the technology per se, but rather a recognition of the limitations of current AI systems in addressing the full complexity of real estate decisions.
