The AI Adoption Tipping Point
At this point, a lot of people have tried AI and walked away unimpressed or at minimum, unsure how it’s supposed to fit into their day. New habits are hard, y’all. The problem likely wasn’t the idea of AI. I’d be willing to bet the problem was actually how they used it. Prompting matters. Knowing what it can (and can’t) do matters.
We’re now at a turning point. Not in hype, but in actual capability. OpenAI released GPT-4.1, designed to enhance performance in coding, instruction following, and long-context comprehension. Google is embedding Gemini into Gmail and Docs. At the Google I/O 2025 event, CEO Sundar Pichai, announced the upcoming launch of "Agent Mode" in the Gemini app. This feature will allow users to delegate complex tasks and planning to Gemini, moving beyond traditional reactive AI functionalities. The initiative is part of Google's broader effort to integrate agentic AI capabilities across its platforms, including Chrome and Search. Microsoft has tucked Copilot into Teams, Word, and Excel like it’s always belonged there.
These aren’t shiny side features anymore. They’re becoming part of the operating system of work. McKinsey’s latest State of AI report confirms what many of us already feel: 65% of companies now use AI in at least one business function. Customer support is leading, followed by marketing and operations.
This is no longer about early adopters. It’s about whether your organization is adapting with intention or just drifting along in the current. While it’s tempting to think you’re behind, the real divide isn’t between those who use AI and those who don’t. It’s between those who trained it with the right knowledge and the ones who haven’t taken the time to learn how to actually use it.
Most generative AI tools are trained on public internet data. That’s fine if you need a cookie recipe or a basic definition of escrow. Real estate doesn’t run on general advice. It runs on precision. And a lot of laws… so it better be correct. CE requirements. Lockbox rules. MLS policies. Membership dues. These things vary not just by region, but by organization, and they change more often than most websites get updated.
So when someone asks ChatGPT a local question, it doesn’t know. It will still answer, though. Confidently. Incorrectly. That’s where things go sideways. It’s exactly why companies like OpenAI, Amazon, and Meta are scrambling to license structured, reliable content from medical institutions, legal databases, and publishers. They’ve realized that without high-integrity data, AI is just a well-spoken guesser.
All real estate organizations should be thinking this way.
AI becomes powerful when it’s trained on your knowledge. That’s where the real transformation happens. Imagine a member texting their MLS with a question about license renewal. Instead of waiting on hold or submitting a ticket, they get an accurate response in seconds because the assistant knows your policies, your procedures, your forms.
That’s not science fiction. That’s real. This is exactly what agentic AI looks like: AI that doesn’t just answer, but takes meaningful, informed action in context. It’s not just conversational. It’s capable.
Voiceflip’s MLS and Association AI assistant, Ardi, is a prime example. Trained on internal MLS documentation, Ardi helps MLSs and Associations respond instantly to member questions that would otherwise clog up support channels. From CE rules to Supra access, Ardi knows the difference between "general" and "local" because it’s been fed the facts.
When AI handles the repetitive questions, your team finally has the headspace to do the kind of work that actually moves the needle. Higher-value work looks like this:
Building a referral pipeline between top agents and new members
Developing retention strategies based on onboarding trends
Creating educational content based on actual member questions
Supporting brokers with tailored recruiting tools
Using support data to guide service improvements
AI isn’t here to replace your people. It’s here to clear the clutter so they can finally focus on what they’re best at. If AI still feels a little fuzzy, you're not late. You’re right on time. However, each week you delay is another week someone else’s system is learning, adapting, and freeing up performance capacity.
As Steve Brown put it at the T3 Sixty Leadership Summit last week: “This is the worst AI will ever be.”
The tipping point isn’t about whether you’re using AI. It’s about how well you’re using it. The ones who win will be the ones training it on the truth that actually runs their business.
Want to Learn the Tools? Start Here.
Here are four free, hands-on courses to help you build confidence with AI in 2025:
Google’s Generative AI Series
Covers everything from fundamentals to practical use cases
🦾 Start here
Microsoft’s AI Fundamentals
Foundations of neural networks and machine learning
🦾 Start here
Prompt Engineering for ChatGPT (Vanderbilt)
Learn how to write better prompts and get more helpful responses
🦾 Start here
ChatGPT Prompt Engineering for Devs (OpenAI + DeepLearning.ai)
Taught by Isa Fulford and Andrew Ng
🦾 Start here
Pro tip: Use “Audit the course” on Coursera to take them for free. No subscription needed.