My previous articles in this series discuss why and how to build property data sets to gain a competitive advantage. AI is on an upward trajectory, with an estimated CAGR of 36.6% through 2030. Meanwhile, Nvidia, whose hardware powers AI, has become the world’s largest company by market cap at $3.326 trillion. There’s a major transformation taking place, and your firm can’t afford to sit on the sidelines.

Applying AI/ML techniques to gain insights

A major advantage of AI is analyzing data and finding investments in ways traditional manual methods can’t. Instead of spreadsheets, these models allow us to quickly explore and query our proprietary datasets.

Our experience shows:

  • Rather than manually finding or calculating information, I can instantly retrieve details by asking the AI in plain language. It pulls from our knowledge base to quickly provide the query on-demand.
  • Our team brainstorms “what-if” scenarios, and the AI immediately provides relevant data insights aligned to each question. We no longer have to spend time chasing down disparate data points.
  • We leverage our information assets to ask questions from every angle like “What about adjusting for this factor?” or “How would changing these parameters impact the projections?” The AI supplies these responses and helps us to quickly spot opportunities.

These insights uncover previously hidden deals. We gain an evidence-based perspective for our strategies based on facts, not assumptions.

Building AI-powered workflows and automation

AI allows us to streamline operations by automating key workflows and processes – saving time and costs.

For example, we built a mobile app that our team uses to collect property details during on-site evaluations. Using a checklist, they enter data points like parking lot condition, needed facade repairs, and required facility upgrades.

We’d have to collect this information through site visits regardless. But leveraging AI means we can produce multiple detailed 20+ page property reports from that data in just two days for virtually no cost. If we’d hired consultants, those reports would have easily cost $100,000 to $200,000.

Automation doesn’t stop at reporting, either. We also use AI to handle initial property scoring and valuations. What once required hours of analysis now gets instant answers to questions like, is this opportunity aligned with our criteria? Or, what’s the projected return profile?

Outcomes with AI investment decision-making

Real estate investors face intense pressure to land deals, which can lead to emotional attachments overriding red flags. Even after closing half a billion in transactions, I can still feel that pull toward a promising opportunity. AI modeling reveals major drawbacks that I might initially try justifying, but the data provides an objective reality check.

The AI contains our full investment criteria because we built the model ourselves. That unbiased view stops me from talking myself into a bad investment based on excitement when it shows a deal wouldn’t make financial sense.

For commercial investors, chasing potential acquisitions that are a poor fit leads to costly errors. We could easily waste $500,000 on upfront contracts and inspections for properties that we never close on. The AI helps avoid wasting unnecessary time and money by quickly identifying bad deals to walk away from.

The data is the data-the AI understands everything because it’s built from my own analysis processes and benchmarks. This objectivity enables cost avoidance and competitive advantage by quickly separating true opportunities from poor fits. Facts drive decision-making, not emotions or hype.

Wrapping up

The competitive advantages of integrating AI and machine learning models are clear. Your firm gains the ability to rapidly analyze data and uncover investments that would go unseen through manual methods alone.

Tedious workflows become streamlined through automation, saving time and costs. Most importantly, AI provides an objective lens for decision-making – separating promising investments from potential pitfalls.

The future is already here. Early adopters are actively leveraging these capabilities to drive consistently better returns. Commercial real estate firms that take a wait-and-see approach risk watching the industry pass them by. The time to start building proprietary datasets and customized AI models aligned to your strategies is now.