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From Rule-Based Bots to LLMs: A 15yr Timeline of Real Estate AI Evolution

AI is not as new as you may think.

Home / AI Fundamentals / From Rule-Based Bots to LLMs: A 15yr Timeline of Real Estate AI Evolution

Author – Ken Hobson.

2010 – Early Rule-Based Chat Widgets

  • Simple “if-this-then-that” pop-ups start answering set questions like inspection times on agency sites.

  • Web plug-ins let offices drop property-data widgets into pages without any coding, hinting at the self-serve tools to come. 

2011 – Automated Valuation Models (AVMs) Appear

  • Major portals publish computer-generated price guides built from past sales and suburb stats.

  • Clients arrive quoting “the number on the website”, so agents must explain market method, not just gut feel. 

2012 – Smart Email Alerts Launch

  • Early machine-learning rules email buyers the minute a matching home lists.

  • Personalised timing lifts open-rate compared with the old weekly bulk send.

2013 – Keyword SMS Bots

  • Text “1” and get a floor-plan link; text “2” and book an inspection.

  • Staff save hours while weekend leads stay warm.

2014 – First Virtual-Reality Tours

  • Portals trial headset walk-throughs for off-the-plan apartments, letting buyers “teleport” around new builds.

  • Visuals now need to be richer than photos—3-D spins soon become standard.

2015 – Image Tagging Learns to “See”

  • Computer vision starts auto-labelling photos (kitchen, pool, view) so the best shots surface first online.

  • Teams spend less time renaming files and more time choosing hero images.

2016 – Messenger Bots Work 24/7

  • Facebook integrations chat about suburbs, collect details, and book inspections after hours.

  • Early adopters capture late-night enquiries before rivals even open their inbox.

2017 – Voice Search Experiments

  • Portals build skills for Siri and Alexa: “Find three-bed houses in Burleigh.”

  • Hands-free search habits begin to form.

2018 – AI Photo Ranking & Drone Metrics

  • Algorithms predict which hero image will win the most clicks.

  • Drone mapping tools measure land size and sun angles, helping justify price guides on acreage.

2019 – Predictive Lead Scoring Goes Mainstream

  • CRMs flag contacts most likely to list or buy in the next quarter, based on call logs, clicks, and past appraisals.

  • Prospecting time shifts to “hot” scores, trimming cold calls. 

2020 – COVID Drives Virtual Inspections

  • Lockdowns ban in-person opens, so portals fast-track 3-D walkthrough features.

  • Agents who mastered digital tours keep deals moving while competitors pause.

2021 – CoreLogic Buys RiTA (AiRE)

  • The data giant acquires Brisbane start-up AiRE, baking the RiTA AI assistant into its ecosystem.

  • Database nurture by machine learning shifts from “nice extra” to baked-in subscription.

2022 – Generative Copy for Listings

  • Early language models draft property descriptions, emails, and suburb snapshots in seconds.

  • Teams jump from blank page to final polish, cutting write-up time.

2023 – ChatGPT Makes Headlines

  • News stories show agents using ChatGPT for copy, scripts, and even buyer questions. 

  • Vendors start asking, “Do you use AI?”—tech literacy becomes a listing-pitch edge.

2024 – CRMs Plug In Large-Language Models

  • New plug-ins write one-to-one emails, suggest next-step tasks, and summarise voice notes automatically. 

  • From one prompt, agents can spin up matching video, text, and images—shrinking marketing budgets for boutique offices.


What This Means for Today’s Agents

  • Speed wins: Every leap cuts response times. Being first to answer is still the easiest advantage.

  • Clean data counts: A tidy CRM makes each new tool smarter—from lead scores to letter-box-drop lists.

  • Blend tech with touch: Let AI handle the grunt work, then add your local knowledge and rapport.

  • Stay curious: Set aside one hour a month to test new features so you ride the next wave, not chase it later.

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