Property tax appeals are a routine part of owning commercial real estate. And there are lots of people who will help you with an appeal. One common way that these consultants charge for their services is as a percentage of achieved savings. This creates a low-commitment scenario for landlords and a strong incentive for the consultant to perform and get paid. The same is true for individual households, who also engage in property tax appeals. However, research shows that some groups are far less likely to appeal:
Lower-income homeowners are substantially less likely to file an appeal. Even holding home values constant, Hispanic and Black homeowners appeal at lower rates than White homeowners, while less-educated homeowners appeal at lower rates than more-educated homeowners. These disparities are often attributed, at least in part, to differences in knowledge of the tax system, confidence in navigating the appeals process, and the ability to afford a human agent (Doerner and Ihlanfeldt, 2015).
But what if more tools and support were provided?
Here’s an interesting study. To test this, the researchers recruited a sample of 645 households in Dallas County, Texas and gave each of them a website providing personalized property tax information and instructions for how to file an appeal. However, half of the households were assigned to a “treatment” version of the website that included a Claude-powered AI chatbot, which was there ready to answer tax-related questions and provide personalized guidance.
What they generally found was that homeowners liked the chatbot. 78% of those who had access to it initiated a conversation. The researchers also found that using the chatbot meaningfully increased the probability of filing a property tax appeal. The baseline increased from 41.4% to 50.5% (a 22% increase!). Importantly though, the increase in appeal filing was smaller among less-educated homeowners, those with lower-valued properties, and those from racial or ethnic minority groups. Overall chatbot take-up wasn’t all that different, but the translation into action was.
This is interesting because it provides “suggestive evidence” that simply providing access to AI isn’t enough. In fact, it had the opposite effect in this study. Rather than reduce inequity, it exacerbated it by increasing filing rates among the already more advantaged.