Artificial intelligence is drawing major investment across real estate, with proptech funding reaching $16.7 billion in 2025. Yet few firms piloting AI are seeing the results they expected. A recent Real Estate Today article suggests the missing piece is property data quality.
e2Value co-founder and CEO Todd Rissel puts it simply: “AI is dependent on the quality and structure of the data it receives. If you want meaningful insight, you need meaningful data architecture supporting it.” Decades of paper records and inconsistent terminology across data sources make that a real challenge.
As an example, Rissel points to square footage: “Two homes can both say 3,000 square feet on paper and feel totally different in real life.” One might feature high-ceiling rooms, while the other counts attic space or a half-finished basement. As Rissel notes, “Because measurement standards vary so much across different public records, comparing homes isn’t always apples-to-apples.” That creates confusion for buyers, lenders and insurers alike. Read the full article here Real Estate AI Investment: Property Data Accuracy
Rissel believes progress is underway but requires cooperation among public agencies, industry groups and technology providers. As AI expands, reliable property data will become essential infrastructure for valuation, lending and risk assessment.