We’re entering an inflection point in AI’s evolution: One where the hype begins to give way to real business transformation. Among the many headline-grabbing developments in AI, there’s a quieter, more targeted revolution happening in industries like ours. In mortgage, the real impact of AI isn’t about sentient machines or Hollywood sci-fi. It’s about background AI. These are intelligent systems that quietly but powerfully automate end-to-end tasks, all without requiring users to learn a new system or step in mid-process.
Historically, the mortgage industry has seen wave after wave of technology adoption, often accompanied by more overhead than savings. The promise of efficiency was undermined by user training demands, ongoing oversight, and the creation of internal teams to support each new “innovation.” In too many cases, technology was another task, not a solution.
With AI, we have a rare chance to change that narrative. But only if we deploy it differently. Rather than trying to make AI handle the entire mortgage lifecycle (a “boil the ocean” approach), we need to break the process into stages that can be fully owned by AI. This is how modern manufacturing works. Tasks are divided based on whether they can be automated. Once a robot can fully handle a task, it gets that task, and no human needs to touch it. That’s exactly the model we should be following in mortgage manufacturing.
Take document indexing, for example. Every lender has to identify, classify, and process hundreds of document types across products and states. It’s traditionally a manual burden. At True, we’ve trained our AI to handle over 1,000 document classes and fully automate this stage. That’s background AI at work. It performs the task entirely, passes it along to the next phase, and never needs to be rechecked or coached. The result? A true lift in efficiency, and zero drag on human teams.
This evolution toward full-stage automation is now enabling real-time borrower experiences that were previously unthinkable. Imagine this: a borrower uploads five or six documents, and within minutes, they’re pre-approved, with income and assets verified. That’s already possible today with machine-only pipelines. It’s not possible if documents are shipped overseas for manual review, which is still the norm for many companies claiming to use AI. Not only does that introduce delays, but it creates data privacy concerns and undermines scalability. A machine-only solution eliminates those constraints and paves the way for better borrower experiences and real operational efficiency.
Of course, we need to be realistic. AI isn’t magic. It can’t solve every problem. And it’s not a set-it-and-forget-it solution. Many lenders still hold misconceptions, either assuming AI can’t do enough to be worth the cost, or believing it can do everything and should be deployed everywhere. The truth is somewhere in between. Like with ChatGPT or any large language model, AI can get you 80 percent of the way, but the remaining 20 percent still matters, especially in high-stakes environments like lending.
The key is smart deployment. AI should be used where it can fully own a stage, just as robots do in physical manufacturing. At True, we’ve combined the power of large language models with over a decade of mortgage-specific machine learning to build specialized models for each step: indexing, extraction, income analysis, and more. That’s how we deliver full-stage automation at scale, without human fallback. And that’s why we’re seeing some of the largest originators in the country lean into this model.
Looking ahead, I’m particularly excited about what’s coming over the next six to 12 months. We’re working with a range of lenders and partners to build the next generation of real-time mortgage manufacturing. That means fully validated document quality within minutes of upload, instant decisioning, and borrower experiences as seamless and interactive as hailing an Uber. These aren’t just ideas, they’re actively in development now, and we’ll be sharing more publicly soon.
Ultimately, the future of mortgage isn’t just faster closings or cheaper operations. It’s about building a smarter, more transparent process that truly puts the borrower first. And background AI is how we get there, not as a shiny object, but as a real, embedded solution that lifts the entire industry forward.