Are You Treating AI Like People?

The Real Estate Espresso Podcast

Are You Treating AI Like People?

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Are You Treating AI Like People?

Welcome to the Real Estate Espresso Podcast, your morning shot of what’s new in the world of real estate investing. I’m your host, Victor Menasce.

On today’s show we’re talking about the adoption of artificial intelligence in the workplace. We’re going to look at three studies that were done last year by Harvard, Boston Consulting Group, and the third one was from Microsoft, who looked at about 370,000 employees using Copilot. The studies looked at AI usage and productivity gains for certain types of tasks. The results were quite striking. A study found that even with widespread initial usage in the first three weeks, many employees stopped using AI in their daily work.

In fact, true adoption of AI in the daily workplace seems to be following an 80-20 rule, with nearly 80% dropping the use of AI almost altogether. For those, on mobile devices usage continued, but the usage shifted to be more like a search tool than a full-on AI assistant.

The issue doesn’t appear to be related to basic training. People are averaging six hours of training and they learn how to generate prompts. The issue is that they hit a wall. The study found 20% monthly active usage. The rest are dormant after the initial period.

There is a big difference in usage between the mobile device and a desktop. In a lot of cases, people who gave up tried to get the tool to write a report. The first attempt gave them something generic. The second attempt gave them something confident but wrong. And the third attempt, they decided it was faster to do the work themselves, and they stopped using AI altogether.

If we distinguish between people who are true AI experts and beginners, there are some stark differences between the experts and beginners in how they approach the problem. Experts are using AI to write new software applications for them. They’re automating many aspects of their daily workflow. They’re managing teams of these autonomous agents who are working for them.

In contrast, beginners are using AI like a turbocharged search engine. It’s a question-and-answer type interaction. Beginners are using AI like a tool. Experts are treating AI like an entire team of employees. These are completely different mindsets. Completely different usage patterns. And completely different skill sets.

People who are using AI as a team of employees are behaving like managers. They’re directing their team. People who are using AI like a tool are behaving as technicians and trying to use the tool without the full breadth of skills to truly use the tools as experts.

The gap appears to be between, let’s call it, 100-level training and the 400-level training that experts use. There’s lots of examples of tools that are available to these 400-level users. There’s complete libraries of skills that are at that 400 level, and they’re able to incorporate them into their daily workflow.

But those who are looking to graduate from the 100 level to the 200 level are asking the basic questions. They don’t even know what the heck a skill is, or how to find one, or how to use it. The training market has bifurcated, and it’s addressing the 100 level and the 400 level. And there’s a massive gap in the middle. That missing middle is where the majority of global productivity gains are going to come from.

It’s about knowing which part of the workflow are candidates to outsource to AI, which parts to keep in-house, and knowing how to evaluate the results you get and is it good or not? The strategic insight is that the problem is not a technology adoption problem, even though it does look like one. It’s an organizational capability problem.

We’ve been categorizing AI tools, I think, incorrectly from the start. People who view it as a tool are getting poor results. If they viewed their employees as tools, they’d also be getting poor results. The best leaders get the most out of their people because they provide the best training. Knowing when to trust is a management skill. These same people have always got the most out of their people. They have great domain knowledge and they have great people development skills.

Would you give a hundred-page RFP to a brand-new intern and tell him to come back when it’s done? Of course not. You would break it into pieces and explain what’s expected for each section, and you would explain what good looks like and what the expectations are. You would provide structure in how to break down the work and how to tackle it. You would review the work and provide constructive feedback.

AI needs the same guidance as an intern. The people who are at the 200 level, who treat AI as a capable but inexperienced employee, are the ones who are getting the most out of AI, and they are also the ones getting the most out of their people.

So why am I telling you this? This is, after all, a real estate podcast, not an AI podcast. Well, real estate investing is a business like any other business and has all the same basic functions. It’s got a finance function, operations, customer service, quality assurance, project management. All these functions can have their productivity improved to some degree with the adoption of AI somewhere in the workflow.

I personally see the use of AI as an important step for quality assurance, and that’s where we’re starting to use it a lot. It is possible to increase the quality of any document that’s produced by asking an AI tool to perform specific checks on a document. We’re also using it to automate certain portions of our workflow that would have otherwise just taken a lot of manual steps. And of course, the capability is not uniform and it’s changing rapidly.

And you might be thinking, I don’t have the time to keep investing in maintaining current on what’s the latest AI, and I understand and respect that. I can also tell you, if you’re not doing that, your competition is.

As you think about that, have an awesome rest of your day! Go make some great things happen, and we’ll talk again tomorrow.

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