Mortgage lending’s relationship with artificial intelligence has changed quickly, moving from early experimentation to broader operational use, according to Addy AI founder and CEO Michael Vandi. In his view, the industry has become one of the clearest examples of how AI can move from a novelty to a tool embedded in day-to-day business processes.
Vandi said mortgage lending was a natural starting point for AI because the work is highly standardized across companies. While other industries can involve very different use cases from one business to the next, lenders generally operate with similar loan products and comparable workflows. That consistency, he said, makes it easier to spot repeatable problems that technology can solve at scale. It also made mortgage an attractive enterprise market for Addy AI, helping the company build a team with both AI expertise and deep mortgage knowledge.
From interest in AI to workflow implementation
He also noted a major shift in the way lenders talk about AI. Two years ago, many conversations were driven by general interest and a sense that firms needed an AI strategy because the topic was gaining attention across the industry. Today, those discussions are far more specific. Lenders are coming in with defined workflows, staffing levels and loan volumes, and they are looking for ways to automate parts of those processes. The challenge, Vandi said, is no longer recognizing the potential of AI but putting it into practice within existing operations.
That is why he describes AI adoption in mortgage as a trust curve rather than a learning curve. In his experience, people can learn to use AI tools quickly, often faster than traditional mortgage software. The real change happens as teams begin to rely on the technology more fully. At first, users may allow AI to handle an initial pass while reviewing every result themselves. Over time, as the system performs reliably on live files, confidence grows and organizations are willing to assign it more responsibility.
Vandi said the firms making the most progress are the ones treating AI as part of operational workflow rather than a separate technology project. In those organizations, AI is being used to support specific tasks and then expanded when it proves useful in adjacent steps. A lender may start by using it to validate closing documents, only to discover it can also review files, check pre-underwritten loans and automate additional parts of the process. That, he said, is where mortgage AI adoption begins to become transformational rather than experimental.
Source: housingwire.com
