AI will not replace humans, writes Kate Hulbert. It’s about reducing friction, increasing consistency, and freeing up your team to spend time on high-value work.
There are many ways to use and abuse AI in the real estate industry. Over the past year, we’ve been exploring simple and practical ways to bring AI into our brokerage operations to protect our brand, clarify company policies, and support onboarding and training, while reducing staff time without replacing brokerage talent.
3 ways to use AI to improve your brokerage operations
Here are some wins worth sharing (and replicating).
1. Custom GPT for brand and social media compliance
Like many brokerages, we have a comprehensive brand book outlining our approved fonts, colors, photography styles and design standards. And like many brokerages, we still struggle to maintain brand consistency across dozens of agencies, platforms, and marketing materials.
The challenge is not a lack of guidelines. It’s the scale. Agents create social posts, graphics, emails, letters, and marketing materials every day, often acting quickly and making small design decisions that slowly take a brand off track.
Solution: We built a custom GPT agent that allows agents to upload graphics, marketing materials, emails, and more. The agent checks each item against your brand guidelines and returns a clear list of what needs to be adjusted to bring it back into compliance.
Why we like it: Rather than policing agent content after the fact, AI acts as a built-in brand check before anything is published. Agents receive instant feedback, brand consistency is maintained, and marketing teams are freed from endless revisions and reminders.
2. Custom GPT for company policies and internal knowledge
Your brokerage firm’s administrative staff probably spends a significant amount of time answering the same questions over and over again.
Can I post a list of upcoming releases? What is our policy regarding personal branding? How do I handle team splits? What are my floor shifts?
Not only is this time-consuming, but it also poses major challenges when employees change hands. Institutional knowledge resides in people’s heads, inboxes, and scattered documents, and when someone leaves a company, much of that clarity is lost as well.
Solution: We built a custom GPT that references internal policies, internal documents, and MLS guidelines. Agents can use it to get clear, consistent answers to their questions in real time without having to chase down office managers or dig through PDFs.
Why we like it: Creates a single source of truth. Agents get answers faster, staff time is spent on higher-value work, and everyone is working from the same information. It also serves as an invaluable onboarding tool, helping new agents get up to speed quickly while reducing confusion across the company.
3. AI for agent onboarding and training
Onboarding new agents is not for the faint of heart. With all the processes, marketing standards, MLS rules, and tacit knowledge of “this is how we do things here,” the onboarding process takes a lot of time and effort for both agents and brokers.
Solution: We built a custom GPT trained on onboarding documents, educational materials, MLS rules, best practices, policy documents, and marketing standards. New agents can ask GPT anything at any time without fear of “annoying” anyone or feeling like they already know the answer.
Why we love it: When you join a real estate team as a new agent, you can quickly become overwhelmed with information. By giving your agents the space to ask as many questions as they arise, you’ll feel less overwhelmed and build confidence faster. At the same time, standardize the training process so everyone is learning from the same source no matter when they join.
Introducing AI to your brokerage firm doesn’t require a major overhaul to be effective. In our experience, the best use case is not to replace people or automate everything. It is about strengthening the systems already in place.
By using AI to protect our brand, centralize internal knowledge, and improve onboarding, we reduced friction, improved consistency, and gave agents and staff more space to focus on higher-value work.
