Imagine a world where a property manager could respond instantly to every request and manage hundreds of properties simultaneously.
But in and around the hype (and hope!), here’s one thing that should be given some thought: How does the actual customer – the tenant, landlord, buyers or sellers feel about interacting with your business using the tools?
I read an article in the New York Times on the weekend titled “When Your Building Super Is an A.I. Bot,” which highlighted some innovative property management businesses in the US.
When Your Building Super Is an A.I. Bot
From handling maintenance requests to optimising energy use, here are some of the other tasks taken over by chatbots mentioned in the article:
- Scheduling repair requests
- Managing maintenance appointments
- Answering questions from prospective tenants
- Reminding tenants to pay rent
- Tracking the use of common areas
- Monitoring energy use
- Aiding in construction management
- Conducting leasing agent duties (interacting with potential renters)
- Assisting with self-guided apartment tours
- General communications with tenants via chat, text, email, and voice
- Asking follow-up questions for maintenance requests (e.g., verifying which sink needs fixing)
- Helping renters troubleshoot maintenance issues (e.g., providing instructional videos)
- Answering questions about rent payment procedures
- Providing details about available apartments
… and the list goes on.
But are consumers ready to trust AI with one of our most significant life decisions – buying a home?
Out of the corner of my eye, I noticed 35 plus comments on the article, so I couldn’t help but wonder: How do consumers really feel about interacting with a chatbot?
AI Examines AI
If you’ve had experience with any of the AI language models, you’ll know that they have three definite superpowers:
- Making it easier for you to consume more content
- Enabling you to create more content
- Finding patterns in content that are out there.
So, to understand what humans were thinking about these chatbots in real estate, I copied and pasted the 35 comments from the NYT article and fed them into Claude, an AI language model, asking it to analyse the sentiments and identify patterns.
Claude identified several pros and cons of using AI in real estate:
Pros:
- Efficiency in handling routine tasks
- 24/7 availability
- Consistency in service delivery
- Cost-effectiveness
- Streamlined scheduling
Cons:
- Lack of human touch and empathy
- Limited problem-solving capabilities for complex issues
- Transparency concerns
- Potential job displacement
- Privacy and data security concerns
I think Claude has done pretty well at summarising both the promises and the pitfalls!
But perhaps more intriguing were the patterns Claude recognised in the comments through a follow-up prompt:
- There’s a generational divide in AI acceptance. Before implementing an AI solution like a chatbot into your service design, you really need to know who your customer is and what their preference in service will be.
- Scepticism towards “AI hype”, comparing AI to previous technological trends that didn’t live up to the hype, eg Blockchain (I disagree with this, and I don’t think Blockchain is over either!)
- Strong desire for human interaction, especially for complex issues
- Concerns about transparency in AI deployments – consumers want to know explicitly when they are talking to an AI
- Varying levels of understanding: The comments show a range of understanding about AI, from those well-informed about its current capabilities to those with misconceptions or limited information.
This public sentiment analysis reveals both the potential and just a few challenges in change management and implementation, which we as an industry will need to navigate over the coming months/years.
Implications for Real Estate Professionals
So, what does this mean for you, the real estate professional? Nothing new for my long-time followers!
1. Balance AI with human touch: Use AI to boost your admin and marketing abilities, but ensure there is always a human in the loop. Don’t email when you could call. Don’t SMS when you could send a video update.
2. Prioritise transparency: Be upfront about AI use. Communicate when clients interact with AI versus humans to build trust and prevent misunderstandings. I think it’s fine to give AIs human names but be upfront they are not human.
3. Continuous refinement: Review AI interactions regularly, gather feedback, and be prepared to make adjustments. Remember, AI is a tool to enhance your service, not replace your expertise.
I have something cool in the works to help you embed this within your teams, but more on that soon…
One more thing: Did you see what I did there?
I’ve just demonstrated a pretty cool use (and methodology) for summarising data, which you can deploy on other types of data to gain all sorts of intel for your customers and your business.
Consider some other use cases for this technique:
- Analysing open home data for buyer preferences
- Summarising Google reviews to pinpoint your business’s strengths and weaknesses
- Summarising Google reviews to pinpoint your competitor’s strengths and weaknesses 😉
Can you think of any others?
Happy hunting! 🤖
*This story was originally published by AI Powered Agents.
