The five critical problems with using generic AI for property analysis
1. Generic AI often gets it wrong (and you'd never know)
General AI models like ChatGPT are trained to sound confident and authoritative, even when they're completely wrong. This phenomenon, known as "hallucination," is a well-documented issue where large language models generate plausible yet entirely fabricated information. Research from OpenAI itself acknowledges that language models hallucinate because their training procedures reward guessing over acknowledging uncertainty.
Here's what makes this particularly dangerous: Generic AI like ChatGPT or Claude will often do an excellent job analyzing your documents, but other times it will miss critical details, get facts wrong, or fabricate information entirely. The answers that are wrong will sound just as confident and authoritative as the ones that are correct.
Imagine uploading your strata report and asking about special levies. ChatGPT might confidently tell you there's a $50,000 special levy coming up next year—completely fabricated. Or it might miss a real $30,000 levy that's actually documented in the AGM minutes. Both responses would be delivered with the same authoritative tone.
Unless you read, understand, and remember every detail of your 500-page strata report, you have no way of knowing which response is accurate. ChatGPT might analyze nine things perfectly and fabricate the tenth—but all ten answers will sound equally credible. For people dealing in property the consequences of mistakes can damage lives and ruin businesses, so this really is a risk that shouldn’t be taken.
How PropWiz addresses this: We've implemented extensive proprietary techniques that address the risks of hallucinations. While no AI system can eliminate this risk entirely, our specialized approach is specifically designed to extract facts from property documents accurately, not to generate plausible-sounding answers. This targeted focus makes our system far more reliable than both general-purpose models for property analysis and human experts.
2. Document processing: the hidden challenge
Before an AI can answer your questions, it first needs to accurately extract information from your document. This sounds simple, but it's where things often go wrong. Property documents are uniquely challenging. Strata reports combine inspection summaries with dozens of attached documents. Building and pest reports mix images, tables, and technical descriptions. Contracts of sale contain dense legal language in specific formats. General AI models treat these as generic PDFs, which means they'll successfully extract some information while quietly missing or misinterpreting other potentially critical details—with no indication of which is which.
How PropWiz addresses this: We've developed an intensive document processing system tailored specifically to property documents. This allows us to extract information far more consistently and accurately than general-purpose tools.
3. Context rot: your document gets "forgotten"
When you upload a PDF to generic AI models, the model only has temporary memory of that document during your session. As your conversation grows longer, important details get pushed out or distorted.
This creates an unpredictable reliability problem: your first questions might receive perfectly accurate answers while later ones become increasingly unreliable—yet every response maintains the same confident tone. For a property report, you might get good answers to your first few questions, but by question ten, the AI is working with a degraded understanding of the document. You're getting misleading insights about a property worth hundreds of thousands of dollars, with no way to distinguish the reliable answers from the unreliable ones.
How PropWiz addresses this: We process your documents thoroughly upfront and store the extracted information in a structured way that doesn't degrade over time. Every insight we provide is based on a complete, accurate understanding of your documents, significantly reducing the risk of context-related errors.
4. You don’t know what to ask or how to ask it
Perhaps the biggest problem with using generic AI is that it requires you to ask the right questions in the right way. If you're not an expert, how would you know what to ask? And if you are an expert and can rely on yourself to ask every important question, do you know how to ask it? Questions you pose to models can feel self explanatory but actually aren’t to an AI with limited context. For instance, you might ask what; “What’s the balance of the admin fund”.. But what you really mean to ask is “what’s the current balance of the admin fund”. Sometimes the model will answer your question correctly but other times it will find the first reference to the admin fund in the document and cite that as the answer, even if it’s not current leading to a misunderstanding.
How PropWiz addresses this: We've essentially pre-asked all the important questions for you in the ideal way. Our analysis automatically covers the critical areas that matter for your property decision, presented in an easy-to-understand format. You don't need to be an expert; we've built that expertise into the platform. While you should always review key findings yourself, our system ensures comprehensive coverage that would be difficult to achieve even with expert knowledge.
5. Edge cases that trip up general models
Property documents are full of quirks and edge cases that general AI models aren't equipped to handle. Here are just a few of many examples:
Financial data interpretation: Tables in financial statements can be formatted in dozens of different ways. ChatGPT might correctly read most financial data but confuse income with expenses in one crucial table, or misread a fund balance from a poorly scanned document. The correctly interpreted figures and the errors will be presented with equal confidence, making it impossible to know which numbers to trust without checking everything yourself.
Local date formats: This one might seem trivial, but it's not. For instance dates in Australian documents follow day/month/year format, but AI models trained primarily on American data assume month/day/year. When ChatGPT sees "5/3/2025," it thinks May 3rd, not March 5th. For time-sensitive levy information or building defects, getting dates wrong matters.
Address typos: Strata reports surprisingly often contain typos in addresses or unit numbers. Without access to a property database, ChatGPT might start pulling information from the internet about the wrong property entirely, mixing up your building with a different one across town.
How PropWiz addresses this: Every one of these edge cases requires a tailored solution—and that's exactly what we've developed. While general-purpose models will continue to improve, many of these challenges are specific to Australian property documents and require specialized handling that generic AI tools will never prioritize. Our targeted approach has dramatically improved accuracy and consistency for the specific documents and scenarios property buyers actually encounter.
