What is Zillow's Zestimate and how does it work?

Zillow's Zestimate is an AI-driven tool that provides instant property valuations. It functions by analyzing a vast amount of data, including property characteristics, recent sales in the area, and market trends, to estimate a home's value. This estimation is then displayed publicly, influencing both buyers and sellers.

How does Zestimate contribute to real estate inflation according to the study?

The study suggests that Zestimate can create a feedback loop contributing to inflation. This happens through a few mechanisms. Overestimation by Zestimate leads sellers to list at higher prices, and buyers accept them. Underestimation leads to quick sales at higher prices than the Zestimate. In both scenarios, the Mass Real Estate Estimators (MREEs) adjust their algorithms based on new sales data, continuing a cycle of increasing price estimations that drive up housing costs. This is called the ratchet effect.

What is the "ratchet effect" in the context of Zestimate and the housing market?

The "ratchet effect" refers to the continuous upward trend in housing costs facilitated by the AI-driven Zestimate. When Zestimate overestimates or underestimates a property's value, the market reacts. Overestimations lead to higher listing prices, and underestimations lead to higher sale prices. The MREE then adjusts its algorithms upward based on these sales data, thus contributing to the increasing price estimations in the market.

What solutions are proposed to mitigate the impact of AI price estimations on the housing market?

The study suggests making participation in Mass Real Estate Estimators (MREE) databases opt-in. This would allow homeowners to choose whether their property is included. By making Zestimate's data less comprehensive, this method aims to disrupt the feedback loop that fuels inflation. The idea is that properties not included in the MREE system would rely less on price corrections, and would be priced more on utility and MREE location estimations.

In what type of market conditions is the impact of Zestimate's estimations most pronounced?

The impact of Zestimate's estimations is most pronounced in a seller's market, where demand outstrips supply. In such conditions, buyers are more likely to accept inflated prices, which reinforces the AI's upward price adjustments, thus exacerbating inflationary pressures.

AI brain in the background controlling real estate tides, symbolising the influence of AI on real estate prices.

Zillow's Zestimate: How AI House Price Predictions Could Be Distorting the Housing Market

Samir D’Costa in Business & Economy December 2025 • 4 min read.

"Is artificial intelligence inadvertently fueling real estate inflation? A new study explores the feedback loop between AI price estimations and actual market values."

The rise of Artificial Intelligence (AI) has touched nearly every aspect of modern life, including how we buy and sell homes. Publicly available AI-driven tools like Zillow's Zestimate provide instant property valuations, influencing buyer and seller expectations. However, a new study suggests that these tools may inadvertently contribute to the persistent inflation seen in the real estate market over the past decade.

The study, conducted by researchers at the Florida Institute of Technology, models the interaction between AI-powered Mass Real Estate Estimators (MREEs) and homeowners, highlighting how estimation errors can create a self-fulfilling prophecy of rising prices. This challenges traditional economic models and raises questions about the long-term impact of AI on housing affordability.

The research delves into the theoretical game between MREEs and homeowners, where each holds private information. Through simulations, the authors explore how limiting the public availability of MREE price estimations—specifically, making them opt-in—could help mitigate the feedback loop driving inflation. The core idea is to examine if the MREE's pressure on real estate inflation correlates with its estimation errors, which simulation then validates.

The Zestimate Effect: How AI Could Be Inflating Home Prices

AI brain in the background controlling real estate tides, symbolising the influence of AI on real estate prices.

Imagine a Native American tribe seeking guidance on the severity of the upcoming winter. Instead of relying on traditional knowledge, the chief consults a meteorologist, who predicts a harsh winter. The tribe, trusting the forecast, gathers excessive firewood, reinforcing the meteorologist's initial prediction.

This anecdote, cited in the study, illustrates a key concept: AI-driven tools like Zillow's Zestimate can inadvertently influence the very market they are trying to predict. Here's how:

Overestimation: If the Zestimate overvalues a home, sellers might list at that inflated price, and buyers, trusting the AI's assessment, may be willing to pay it. This immediately increases the perceived value of comparable homes in the area.
Underestimation: Conversely, if the Zestimate undervalues a property, savvy buyers will recognize the bargain and bid accordingly. The final sale price, exceeding the Zestimate, signals to the AI that the location is more desirable than initially assessed, leading to upward adjustments for nearby properties.
The Ratchet Effect: In both scenarios, the MREE adjusts its algorithms based on recent sales data, perpetuating a cycle of increasing price estimations and contributing to a continuous upward trend in housing costs.

The study models these dynamics, suggesting that even small errors in AI estimations, when amplified by market behavior, can lead to significant inflationary pressures. This is especially true in a seller's market where demand outstrips supply, and buyers are more willing to accept inflated prices.

Opt-In or Opt-Out: A Potential Solution

Recognizing that completely eliminating MREEs is unrealistic, the study proposes an alternative: making participation opt-in. By allowing homeowners to choose whether or not their property is included in MREE databases, the feedback loop can be partially disrupted. This approach assumes that properties not listed in the MREE system will not generate the same neighbor resentment and price correction dynamics, relying more on user utility and MREE location estimations.