Connor with Honor | Real Estate | Fasting | A.I. Integration/Agentic/Bots | Ticket Whisperer | Santa Clarita Open Houses

The rise of AI in Real Estate is going to cause more distrust than ever due to the creators


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Introduction: The Rise of AI in Real Estate—And Why You Should Be Cautious

As we step into February 2025, the Santa Clarita real estate market is buzzing with speculation. From chatbots forecasting price surges to algorithms predicting inventory crashes, AI-driven content dominates online discussions. But here’s the truth: not all that glitters is gold.

In my recent open houses—like the one I hosted just yesterday—buyers and sellers alike expressed confusion. “Should we hurry to buy before prices skyrocket?” they asked. “Is now the time to sell?” The answer isn’t in a chatbot’s script. It’s in the nuanced, lived experience of local experts who’ve navigated Santa Clarita’s market through booms, crashes, and everything in between.

In this 2025 market update, I’ll break down:

  • Why AI predictions often miss the mark (and how they might be steering you wrong).
  • The real factors shaping Santa Clarita’s inventory, buyer demand, and pricing.
  • Actionable advice for buyers and sellers in today’s climate.
  • How to leverage our Santa Clarita Open Houses tools to make informed decisions.

Let’s dive in.

Part 1: The Problem With AI-Driven Real Estate Predictions

1.1 The Self-Serving Nature of Algorithmic “Advice”

AI tools are only as unbiased as their programming—and many are designed to keep you engaged, not informed. For instance:

  • Confirmation Bias Amplification: If you’ve searched “Is 2025 a bad time to buy a home?”, AI may feed you content reinforcing that fear, ignoring data suggesting otherwise.
  • Hidden Agendas: Some platforms prioritize listings from paid partners or promote urgency (e.g., “Prices will jump 20% next month!”) to drive clicks.

Example: A buyer told me last week that a chatbot advised them to “wait for rates to drop below 5%” before purchasing. But with current mortgage rates at 6.2% and inventory climbing, waiting could mean losing out on their dream home.

1.2 Case Study: When AI Gets It Wrong

In 2024, an AI model predicted a 15% price drop in Valencia due to “overbuilding.” Instead, prices rose 8% as demand surged for new energy-efficient homes. Why? The algorithm ignored local infrastructure upgrades, like the expansion of the Metrolink station, which boosted buyer interest.

Takeaway: AI lacks contextual awareness. For neighborhood-specific insights, explo

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Connor with Honor | Real Estate | Fasting | A.I. Integration/Agentic/Bots | Ticket Whisperer | Santa Clarita Open HousesBy Connor MacIvor


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