In the 2024 New Delta Media Survey, three-out-of-four of the top U.S. brokerages reported already using artificial intelligence in their operations. Here’s a look at where it’s making the biggest impact — and where the road ahead still holds questions.
The AI Wave in Real Estate
The real estate industry is in the midst of a transformation. AI is no longer just a buzzword — it’s increasingly embedded in how the business works.
- The global AI real-estate market was valued at $222.65 billion in 2024 and is projected to reach $301.58 billion in 2025 — a compound annual growth rate (CAGR) of about 35.5%.
- In the U.S., roughly 75% of leading brokerages now report deploying AI tools, and a similar proportion of their agents say they use those tools to improve efficiency.
- Generative AI in the real-estate sector (still a much smaller slice today) is forecast to grow from about $437.65 million in 2024 to roughly $1.3 billion by 2034 (CAGR ≈ 11.5%).
These numbers reflect more than hype — they point to a real shift in how properties are bought, sold, valued and marketed. Let’s dig into the key arenas where AI is already making a difference.
Key Areas of Impact
To understand how artificial intelligence is reshaping the real estate market, we decided to look at where it’s already making a measurable difference. AI’s influence is not limited to a single tool or task — it cuts across the entire process, from how clients are found to how investments are evaluated and priced. Each stage reveals a different way in which algorithms are taking over the most time-consuming parts of the business and augmenting human decision-making with speed and precision. By examining a few core areas, we can see how these systems are starting to redefine professional roles, streamline operations, and ultimately change what it means to make a smart move in real estate today.
Acquisition
Modern AI platforms comb through vast datasets — browsing behaviour, income levels, past purchases, location trends — to identify people who are likely to buy or sell. The idea: detect subtle signals that reliably forecast movement or investment intent. This allows agents to target leads more precisely and to engage at the right moment.
Risk Assessment
For investors looking to buy an apartment with an eye to resale: AI is not just scanning today’s prices. It’s estimating future value growth. By analysing historical price trends, buyer activity, listing volumes and search-query patterns, predictive systems point to the neighbourhoods where value is more likely to rise. It’s less about where things stand now, and more about where they’re going.
Property Valuation
Valuation has always been part science, part art. With AI, science is gaining ground. By combining property features, market trends and economic indicators, AI-powered tools yield sharper, more reliable assessments. According to JLL Research, AI and specifically generative-AI solutions are among the top three innovations set to reshape real estate. For example, one firm — CAPE Analytics — reported enhancements in valuation accuracy of around 7.7% and cut manual inspections by up to half.
Hurdles on the Road to Scale
The potential is vast — smarter pricing, faster deals, richer client service — but success depends on more than just the technology. It demands thoughtful deployment, human governance and institutional readiness.
- Privacy and Data Protection: Real-estate AI systems often handle highly sensitive data: financials, property histories, personal-profile information. Any breach, mishandling or opaque practice can do serious damage. Firms must ensure compliance with laws such as GDPR or CCPA, enforce strong encryption and access controls, and maintain transparent audit trails.
- Costs and Implementation: The upfront investment isn’t trivial—software licensing, systems integration, employee training. Without a clear roadmap, companies may under-deliver on promise.
- Bias and Fairness: Predictive models inherit the biases of their data. If historical patterns reflect inequities, then so will the output. Firms must regularly audit for fairness, monitor outcomes and maintain human oversight to validate the logic.
- Adoption and Culture: Introducing AI means changing workflows. Agents may fear displacement or distrust the outputs. If technology is merely grafted onto old practices without change management and training, the investment may not pay off.
These challenges show that the industry’s AI revolution is as much about people and policy as it is about technology
What It All Means
AI is fast becoming a strategic pillar in real estate, not just a nice-to-have. But that doesn’t mean a takeover of “agents replaced by algorithms”. The human connection, negotiation savvy and contextual judgment still matter — perhaps more than ever.
For real-estate professionals who learn to combine the speed and scale of AI with deep domain expertise and ethical practice, the payoff could be significant. For those who treat it as a simple automation, risks remain.