Choosing the right AI tools for your real estate scenarios

It’s time to take the next step in your AI journey: choosing which AI technologies are the best fit for your unique scenarios.  

In our previous blogs, we discussed ways to prepare your data for AI and how to define the real estate scenarios where AI can help. The time has come to talk about how to choose the right AI tools. 

Before we dive in, it’s important to be aware that different scenarios may call for different AI technology. This can feel overwhelming — AI is flying at us fast and furious, and there’s a long list of new terms to learn, but this blog will aim to simplify that. 

You likely use AI every day, whether you realize it or not. For instance, when you ask Siri or Alexa a question, when Netflix recommends shows you may like, or when Google Maps guides you through the best way to get somewhere, you guessed it – it’s all AI.  

Those are excellent examples from our personal lives, but what about real estate scenarios? Let’s take a deeper look at AI to see how it applies to your business.   

What are the different types of AI technologies?

Artificial Intelligence (AI) is a broad term that covers several types of AI technologies. Understanding the different types of AI and how they can benefit real estate helps determine which tools you need to get the job done: 

• Machine Learning (ML) – This refers to how computers learn from data and get better at tasks over time, without being told exactly what to do. It excels at anomaly detection, data clustering and classification, and predictive analytics — making it ideal for spotting trends in lease data, identifying expense recovery patterns, and forecasting. 

• Natural Language Processing (NLP) – This type of AI is used to understand and generate human language. NPL is typically used in chatbots and search engines, enabling computers to interact with written or spoken prompts and provide the requested information from contracts and forms. This can include text summaries and/or translations, lease clauses and terms, or key audit findings.  

• Generative AI – The most popular example of generative AI is ChatGPT, which can produce new content such as text, images, and code. This is useful for drafting reports, letters, or lease summaries. 

• Computer Vision – This type of AI technology is used for object detection and facial recognition. It interprets visual inputs and extracts information, such as image tagging or text in photos. PropTech solutions that use computer vision can read scanned leases and invoices, help analyze footfall traffic, and understand pedestrian patterns. 

Here are a couple more advanced AI terms that you may have heard of: 

• Large Language Models (LLMs) – Smart computer programs that are trained on large amounts of data, enabling them to understand and create human-like language. An example of an LLM is ChatGPT. 

• Agentic AI – Autonomous AI that can make its own decisions and take action to reach a goal, without requiring step by step instructions. An example of agentic AI is telling an AI assistant to “Plan a trip to Paris”. The AI assistant books flights and hotels and creates the itinerary for you.  

Common misconceptions of AI: What AI is, and what it isn’t

Now that we’ve discussed different kinds of AI technologies and their use cases, let’s look at a few misconceptions around AI and understand the truth. 

• If it’s automated, it’s AI – Automation doesn’t require intelligence. Rules-based systems follow instructions; AI adapts and learns. 

• Excel macros and formulas are AI – They’re powerful, but they’re manual scripts, not machine learning. 

• Optical Character Recognition (OCR) is AI – OCR is used to read text. AI interprets, classifies, and extracts meaning from it. 

• AI is perfect and objective – AI reflects the data it’s trained on — biases included. This is why human review of AI-generated content is essential.  

• Using AI means giving up control – You’re still in charge. AI supports decisions; it does not make them for you. 

What should you consider when evaluating AI tools for real estate?

After you’ve determined the type of AI technology that best matches the needs of your real estate scenarios, there are a few more things to consider before making a decision. 

• Ease of use – Will the tool require a developer or is it a no-code solution? 

• Integration – Are APIs available or is the tool compatible with the platform you use to store data? 

• Scalability – can the AI tool evolve as your real estate business grows? Can it handle the continually increasing volume of data? 

• Cost – Is the AI product free or does it have freemium or enterprise pricing? Note that free AI tools typically offer less security than paid solutions.  

• Security & Compliance – Is the AI product secure, especially for sensitive data? Does the vendor develop their products using a responsible AI framework that you can trust? 

You’ve picked your AI tool, now what?

It’s time to start with a prototype. Try out your new AI tool on a small dataset and evaluate the results. This will help determine whether you need to expand it to additional datasets, tweak the model, or maybe you’ll decide that it’s simply not the right AI tool for you.  

Be sure to evaluate performance. When you’re using a small subset of data, think about how performance will be impacted when you increase your data volume. And the most important thing to keep in mind – be ready to iterate based on feedback. It’s ok if you don’t get it right the first time, so be sure to allow room to iterate. 

Now, you have your data ready, you know your scenarios and you know how to pick the right AI tool for your needs. Remember to stay flexible, leave room for iteration and most of all, keep learning!  

To learn more about preparing your business for AI, get the report: Guide to AI Adoption for Real Estate Firms.