Global payments networks use AI to catch fraud across billions of transactions; commercial real estate uses AI to write emails.

This disparity alone reveals how dramatically this industry lags behind where it should be technologically, currently operating decades behind other sectors in leveraging computational intelligence. This fundamental disconnect and need for advanced technology is one of the main reasons why RETS AI was built.

Commercial real estate firms are approaching an organizational inflection point where traditional business operations will be fundamentally restructured around integrated artificial intelligence operating systems rather than human-dependent workflows, yet most remain trapped in superficial AI platforms that barely scratch the surface of what's operationally possible.

One firm in particular we have worked with has used their AI-powered operating system we built for them to have a part in every single workflow at their firm. From automating their underwriting, to completing their due diligence, to generating the legal documents that they bring to closing. This isn't about replacing human judgment, but about amplifying execution speed.

There will come a time in the industry where we will see the Red Queen effect-with each company adopting this technology as a means to increase their force in the marketplace, it will in turn escalate the need for the next company to adopt, and so on and so forth to remain competitive. What begins as competitive advantage inevitably becomes operational necessity.

The critical distinction lies in understanding AI and large language models as a raw material that must be fashioned into purpose-built solutions. Just as lumber requires refinement, shaping, and assembly before becoming structural architecture, AI requires extensive customization, workflow integration, orchestration, unification of a firm's proprietary data, and operational fine-tuning before delivering systematic value that matches and exceeds what other industries have already achieved and for what real estate is unacceptably behind in.

Most firms approach AI implementation backwards-they use generic tools and attempt to force them into their operations. This approach fails because it treats broader AI applications as interchangeable commodities rather than recognizing that effective implementation requires transforming raw computational intelligence into an operating system that understand your firm-specific ontology.

As time goes on, the commercial real estate industry will either modernize its operational infrastructure, or it will be modernized by competitors who understand that computational intelligence is the foundation of a true competitive advantage.