Contract drafting time slashed.
In one case study at a commercial brokerage, an AI-based system reduced contract preparation time from 15 hours a week to just 2 hours, resulting in an 87% time reduction. This freed brokers to spend more time on clients and deals, rather than on paperwork.
Rapid AI document review.
Artificial intelligence can review legal documents in seconds, rather than hours. In a benchmark test, AI contract review software achieved 94% accuracy and scanned five contracts in 26 seconds, whereas human lawyers averaged 85% accuracy and 92 minutes to review the same documents. Even the fastest lawyer took 51 minutes, far slower than the machine's half-minute performance.
Fifty percent faster information retrieval.
Contract analysis software (e.g., Thomson Reuters’ Document Intelligence or Caseway) can instantly pull out key details. Users have reported speeding up contract data retrieval and review by over 50% using such software. This means less time hunting through clauses and more time closing deals.
These time savings in document preparation and review translate to faster transaction cycles. Deals that might be delayed by lengthy paperwork can move ahead more quickly. Importantly, while artificial intelligence accelerates the routine parts of contract management (filling in standard clauses, flagging issues, etc.), real estate agents still oversee the process. The best approach is to combine the efficiency of artificial intelligence with human judgment for optimal results.
AI workflows boost lead conversion and closings.
Adopting AI in day-to-day workflows helps real estate agents convert more leads into closed transactions. From chatbots that respond to inquiries 24/7 to predictive lead scoring, the data shows that assisted agents are seeing higher success rates. For example:
A brokerage that deployed an AI voice assistant to engage and qualify leads saw a 30% increase in lead conversion within three months. The artificial intelligence immediately responded to after-hours inquiries and nurtured prospects until a real estate agent could follow up, resulting in more leads turning into clients instead of slipping away.
Improving the transaction process can boost the bottom line. In the earlier case study, after automating contract workflows, the firm experienced a 35% increase in closed deals (faster paperwork resulted in fewer lost opportunities and quicker closings).
AI software is driving better outcomes, even at the front end of the pipeline. In one study, agents using marketing software and follow-up reported a 25% uptick in lead conversion rates compared to their previous manual methods. By automating personalized emails, ads and responses, these agents engaged leads more effectively and ultimately won more clients.
Why the boost in conversion? AI ensures that no lead falls through the cracks. Every inquiry gets an immediate, tailored response, and every prospect is consistently nurtured. Speed to lead is critical in sales. AI’s ability to respond in seconds, providing relevant information or scheduling appointments, gives real estate agents a competitive edge in converting inquiries into meetings and closings. The data so far indicates that when properly integrated, artificial intelligence can function as a tireless assistant, enhancing conversion metrics across the board.
Growing adoption of AI software among agents.
The adoption of artificial intelligence has surged in the real estate industry, with many real estate agents and brokers embracing software such as chat assistants, automated listing description generators, and predictive analytics. Recent surveys demonstrate the increasing familiarity of artificial intelligence in real estate practice.
Mainstream at big brokerages.
Among leading real estate brokerages, 75% already use AI technology, and nearly 80% of their agents have adopted AI software. This was reported in 2024 and shows that AI is pervasive at top real estate firms, from crafting marketing content to analyzing market data.
Agents overall.
A US nationwide REALTOR® survey found that about 28% of agents reported using artificial intelligence or machine learning in their business. Additionally, over half (55%) are at least somewhat familiar with artificial intelligence and nearly one-third use some AI every month. This indicates that many real estate agents have begun integrating artificial intelligence into their routines even beyond the big brokerages.
Canada and the global context.
Canada’s real estate professionals are not far behind. Approximately 58% of leading real estate firms in Canada have adopted AI in their operations. (By comparison, the same 2023 global survey showed the US at 75% and China at 60% adoption.) Across the world, artificial intelligence in real estate is on the rise. One industry analysis estimates that nearly 85% of real estate companies have begun using machine learning systems to enhance operations and decision-making.
The rapid adoption of artificial intelligence software suggests that agents recognize the value of these technologies. They save time, win clients or gain competitive information via data. While adoption rates vary by region and company size, the overall trend is clear: algorithmic decision-making is becoming a standard part of the real estate toolkit.
Importantly, organizations like NAR and CREA encourage training in these software platforms so that less tech-savvy real estate agents don’t get left behind. AI in real estate has moved from a buzz-worthy concept to everyday reality for many agents.
AI-powered home pricing models vs. traditional comparative market analysis (CMA).
Property valuation is one area where humans and machines excel in different ways. Home pricing models, such as Zillow’s Zestimate or Redfin’s Estimate, can instantly analyze millions of comparables and data points to estimate a home’s value. Traditional comparative market analyses conducted by real estate agents rely on local expertise and nuanced judgment. How do they stack up?
According to Zillow, the median error rate of the Zestimate is only ~1.9% for on-market homes (homes listed for sale). The Zestimate’s median error is approximately 7.1% for off-market homes with limited data available. Similarly, Redfin’s automated estimates report a median error of ~1.98% for active listings and about 7.7% for off-market homes.
In other words, when sufficient market data is available, these machine learning systems often predict sale prices within a couple of percentage points half the time, an impressive feat using purely algorithms.
Agents’ CMAs account for nuance.
Real estate professionals point out that a well-prepared CMA can be even more precise for a specific property because it factors in on-the-ground details that an algorithm might miss. Unlike an algorithm, a real estate agent will consider a home’s unique condition, recent renovations, quirky layout or neighbourhood buzz that the data might not capture.
CMAs involve “personalized precision.” One Realtor-backed source notes that a CMA, enriched by an agent’s local knowledge, is generally “more accurate and reliable” than a Zestimate for pricing a particular home. Property agents can adjust for intangible factors (curb appeal, odour, neighbour influences) that a machine learning system cannot measure from data alone.
Real-world pricing results.
The value of human expertise shows up in outcome data. In 2024, US homes sold on average for 100% of their listing price. Essentially, homes sold at the price that agents (via their CMA and pricing strategy) had determined was fair market value. Hitting the exact listing price suggests that, in aggregate, agents are pricing homes accurately in line with what buyers are willing to pay.
In contrast, an automated model working off older or generic data might occasionally misprice outliers. Notably, when Zillow ventured into home buying, its algorithm sometimes overpaid for homes in a changing market. This is a reminder that AI isn’t infallible without human oversight.
Digital intelligence valuations are a powerful starting point. They’re quick, data-driven and usually in the right ballpark. In fact, for standard homes in data-rich areas, an online estimate might be as good as an agent’s gut feeling. However, the agent's CMA still tends to win for maximum accuracy on an individual property, especially one with unique features.
Many real estate professionals treat automated values as a “second opinion” but rely on their analysis for the final pricing decision. The combination of both can be ideal: agents often use tools like Zestimate alongside their Comparative Market Analysis (CMA) to educate sellers, then apply their expertise to fine-tune the number.
Consumers still prefer working with agents (despite digital options).
Even as technology empowers consumers with more information (such as listings, valuations, online tours, and guidance on dealing with construction disputes), most buyers and sellers continue to use real estate agents to navigate their transactions. The data underscores that the agent’s role remains fundamental in the digital age:
According to the National Association of REALTORS®, 88% of recent homebuyers purchased through a real estate agent or broker, rather than going alone. On the selling side, it’s even higher: 90% of home sellers used an agent to sell their property. In other words, roughly nine in ten consumers on both ends of the deal choose to be represented by a professional, despite the plethora of DIY websites and apps available.
FSBO remains rare.
About 6% of home sales are done FSBO (for sale by owner) without the assistance of a real estate agent. This tiny fraction has decreased over the decades, indicating that the convenience of online listing hasn’t significantly grown the FSBO share. Most sellers still hire an agent for marketing, negotiating and transaction management.
Consumers primarily value the expertise agents provide. Surveys show 88% of buyers would use their agent again or recommend their agent to others. This is a strong testament to the perceived benefit of having an agent guide them. Similarly, 90% of buyers reported that their real estate agent was a very or somewhat useful information source during their home search, ranking agents as the most helpful resource (above websites, mobile apps, or yard signs).
Buying or selling a home is a complex, high-stakes process. Digital tools can deliver data (listings, home value estimates, neighbourhood stats), but clients often prefer an expert to interpret that data and handle the intricacies of the deal. For instance, one of the most complex parts of selling FSBO is “getting the price right,” which 17% of owner-sellers cited as a significant challenge.
Negotiating offers, handling legal paperwork, and managing timelines are other pain points. Unsurprisingly, most people still choose to have an agent shoulder these burdens, even if they begin their research online.
Consumers are utilizing online portals and digital intelligence software to access information with great success. Today's buyers typically find homes online and check algorithmic valuations. But when executing the transaction, they overwhelmingly entrust that job to real estate agents.
The data suggests that while digital intelligence and platforms augment the real estate experience, they have not replaced the personal guidance, negotiation skills, or local market savvy of human agents. Agents who embrace technology often deliver the best service, combining high-tech efficiency with high-touch expertise, which resonates with clients and keeps agents at the center of real estate transactions.
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