There is a lot of interest in AI across real estate right now, and for good reason. The use cases range from custom chat assistants on a company's own website, to analytics, to a new generation of platforms with much faster capabilities for querying the business and surfacing issues quickly. Used well, AI can shorten the time between a question and a useful answer, and help teams oversee operations that are otherwise spread across several systems.
The honest part is what sits underneath it. Data is the key to good working systems, and a lot of organisations are still fighting the basics of data management. That gap has to be filled first. AI applied to messy or siloed data produces confident but unreliable answers, which is worse than no answer at all. Good systems and good AI rest on the same foundation: clean, well-structured, well-governed data, plus the right training and setup.
Digevo's take
We are practical about AI. Before anything else, we work to understand a business's data and its structural issues, because the real key is resolving those problems before reaching for fancier tools. As experienced analysts, spotting those issues early is a large part of what we do, and it is what makes any AI layer on top actually trustworthy.