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I bought one of those silicone microwave popcorn bowls recently and gave it a spin the other night. It took forever for the first kernel to pop. Then came a flurry. Then it slowed down. And just when I was convinced it was finished, another kernel popped. Then another. I think I declared it “done” three separate times before it actually finished. Which, of course, is pretty much how microwave popcorn has always worked.
But standing there waiting, I had another thought: This is starting to feel a lot like the conversation around AI. Just when you think we’ve exhausted every possible angle, another one pops up. So, forgive me in advance for writing yet another article about AI, but I do think there’s an angle we haven’t spent nearly enough time talking about.
Most of the mortgage conversation around AI has focused on what it will do for lenders — greater efficiency, faster processes, lower costs, better lead management, more automation. But what will AI do to the borrower experience? And more specifically, what happens to the loan officer relationship when borrowers no longer need their LO to answer many of the questions they’ve traditionally relied on them for? That’s where I think things get interesting.
Our question this month: If AI becomes the borrower’s source of information, how does the loan officer remain their source of trust?
For most of mortgage history, loan officers have possessed something borrowers have desperately needed: knowledge. Mortgages are complicated. Borrowers have questions about rates, products, underwriting, documentation, conditions, closing costs, and a hundred other things they encounter along the way. When they didn’t understand something, there were only so many places to turn.
So, they called their loan officer. That created a natural opportunity for the LO to demonstrate expertise. The borrower asked a question, the LO explained it, and every one of those interactions had the potential to deepen the relationship.
AI changes that dynamic.
Imagine a borrower receives an underwriting condition they don’t understand. Historically, they might call their LO and ask, “Why do they need this?” Increasingly, they can simply consult AI. They can ask what a condition means, why an underwriter might request it, how an ARM works, what happens during appraisal, what cash-to-close means, whether a particular fee is normal, or what they should expect next in the process.
And they can get an answer instantly. That doesn’t eliminate the need for a loan officer. But it does eliminate some of the moments that historically allowed the loan officer to prove why the borrower needed them. That distinction could become very important.
There’s an interesting disconnect in our MortgageCX data right now. AI is everywhere in the mortgage industry conversation, but it barely registers when we ask borrowers how they found or chose their lender. Year-to-date, fewer than 1% cite an AI conversation ask how they found their lender. And fewer than 1% cite AI as a primary reason they chose their lender.
So, I don’t think the first major borrower-facing disruption from AI is necessarily going to happen at the top of the funnel. I think it may happen inside the relationship.
The traditional LO relationship has been somewhat reactive. The borrower has a question. The LO answers it. The borrower gets nervous. The LO reassures them. Something confusing happens. The LO explains it. Those interactions build trust, but only if they actually happen.
If borrowers increasingly get their basic questions answered somewhere else, the LO can’t sit back and wait for opportunities to demonstrate value. The relationship will have to become much more intentional. And that means the definition of a great loan officer may begin to change.
The mistake would be to conclude that AI makes the relationship less important. I think it makes the relationship more important, and harder to earn. Information and advice aren’t the same thing. AI can explain what an underwriting condition generally means. Your LO knows why your underwriter is asking for it.
AI can explain different mortgage products. Your LO should understand which one makes sense given your finances, goals, and plans. AI can explain the mortgage process. Your LO knows your loan, your timeline, and the people responsible for getting it closed. That’s where the opportunity lies.
But LOs will have to stop relying on borrower questions to create those conversations. Instead of waiting for the borrower to ask what happens next, tell them. Instead of waiting for them to question a condition, explain why it’s being requested before they have to ask. Instead of waiting for anxiety to produce a phone call, recognize where anxiety typically occurs and reach out first.
In other words, the LO of the future may create value less by having the answers and more by knowing what the borrower needs before they ask the question. That’s a very different skill.
If borrowers are going to rely less on their LOs for information, lenders need to become much more intentional about how LOs create value beyond simply answering questions. I’d start with three things:
1. Coach LOs to anticipate instead of react. Look at the questions borrowers ask most often and the moments in the process that consistently create confusion or anxiety. Then coach LOs to get there first. Explain the condition before the borrower asks why it’s needed. Tell them what underwriting will be looking for before the file gets there. Prepare them for the next milestone before they start wondering what’s happening. If AI can answer a borrower’s question in seconds, the LO’s advantage is anticipating the question before it needs to be asked.
2. Start measuring the depth of the relationship. Add questions to your post-close survey that go beyond satisfaction and execution. Ask something like, “How would you characterize your relationship with your loan officer now that your loan has closed?” Then probe the behaviors underneath it: Did the LO understand your goals? Did they proactively guide you? Did you feel comfortable reaching out to them? Would they be the first person you’d contact about a future mortgage need? Track those results by LO and over time. MortgageCX can help with that.
3. Connect relationship depth to revenue. This is where it gets interesting. Compare those relationship measures against actual borrower behavior: referrals, repeat business, retention and pull-through. You may discover that some of your highest-producing LOs aren’t necessarily the ones creating the deepest relationships; or that certain relationship-building behaviors are strongly associated with future business.
Once you know which behaviors matter, you can coach them intentionally across the organization.
Final Thought: AI probably won’t eliminate the loan officer anytime soon. But it may eliminate one of the biggest advantages loan officers have historically enjoyed: being the borrower’s easiest source of mortgage knowledge. And I think that has major implications for LO revenue.
The LOs who thrive won’t be the ones sitting around waiting for borrowers to call so they can demonstrate how much they know. They’ll anticipate questions, provide context before it’s requested, understand the borrower beyond the transaction, and deliberately build a relationship worth coming back to.
In a world where everyone has access to answers, the competitive advantage may no longer be what you know, but how well you know your borrower.
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MortgageCX is now integrated with Encompass®! Mike Seminari
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