Two highly competitive LOs sit at their respective desks, each facing a new customer file. One is juggling a stack of paper documents — bank statements, income verifications, credit reports — while manually keying data into outdated software systems. The other, eyes on her screen, clicks once to let AI instantly parse every required document, generate underwriting suggestions, and highlight relevant mortgage programs. In minutes, she has a near-completed profile ready for review and is already beginning the process for another client. Her opposition? Still plowing through endless streams of data with hours of work ahead.

This dramatic difference in workflow is no longer an implausible sci-fi scenario; it’s the reality of artificial intelligence (AI) in mortgage lending. On one hand, AI brings extraordinary efficiency, slashing the time and cost of producing a single mortgage loan. On the other, it’s poised to shake the industry to its core. In an environment where the total number of loans remains essentially finite, those who leverage AI stand to capture even more volume — while everyone else fights for scraps.

Welcome to the Age of pAIn. It’s a world in which AI is both an indispensable ally and an existential threat — unleashing profound gains in speed and accuracy but also consolidating power in the hands of top-producing loan officers. Over the past several weeks, I spoke with four leading voices at the bleeding edge of AI in mortgage:

● Rick Roque (VP, Growth at NFM Lending), whose sobering analysis suggests a coming wave of industry consolidation.

● Mincheng “James” Jin (Chairman and President of General Mortgage Capital Corporation), who views AI as a supportive tool rather than a replacement for human expertise.

● Lukas Rosenblum (Chief Client Officer at AngelAI), who, with CEO Pavan Agarwal, seeks to democratize finance for underserved communities worldwide.

● Bochen Wang (CEO of Zeitro) who is building an AI-based “infrastructure” to replace the mortgage industry’s clunky, fragmented tech.

They all see a future driven by AI, but the concerning question hovering over the acceleration of automation: Will it be an age of prosperity for the few — and pain for the many?

The Coming Upheaval

In the realm of mortgage lending, few have more unflinching clarity than Rick Roque, and he has the numbers to back up his blunt assessment of where we’re headed. “We’ll be able to do twice the amount of loans in this business with 40% of the people,” he told me. “It’s a genuine threat to a bulk of the workforce in U.S. mortgage origination.”

Level Up Or Drop Out

Roque points to data from 2024 that underscores how top-heavy the mortgage industry already is. “Last year, only about 20,000 licensed loan officers did most of the volume,” he says. Many others closed only one or two loans per month, some even just a single loan for the entire year. This means a relatively small group of professionals commands the lion’s share of origination.

AI will, in Roque’s view, make that concentration even more extreme. “If you’re not in the top group doing 120+ loans a year, you’ll either have to level up or drop out,” he warns. One or two high-performing LOs, armed with advanced AI systems, can expand into markets far beyond their local territory. In an industry once tethered to in-person relationships, AI helps scale a personalized touch across multiple states — or even nationally. “All of a sudden,” Roque says, “a top-producing loan officer in any MSA will be able to amplify their influence.”

A Radical Acceleration Of Decision-Making

Roque calls AI “a radical disruption of the velocity of decision-making.” From simpler tasks like scanning borrower profiles to more complex underwriting guidance, AI compresses steps that used to take days into hours, even minutes. “It’s beyond Zoom calls and websites,” he explains. “It’s the ability to identify opportunities, build relationships, and close deals at lightning speed.” In Roque’s scenario, a shrinking cadre of super-LOs will seize deals from the conventional, mid-tier segment — those who’ve traditionally done a few dozen loans a year.

The Impact On Employment

Roque predicts a final headcount shakeout that will affect underwriters, processors, closers, and junior attorneys — every link in the mortgage chain. He likens it to the travel-agency meltdown in the 1980s: “All of a sudden, the ratio between bookings and agents got lopsided.” Similarly, in mortgage, Roque can envision a world in which productivity increases by a factor of 5, leading to a rapid escalation in consolidation.

For Roque, the writing on the wall is clear: “Last year, only about 20,000 licensed individuals did most of the volume. That number is going to shrink.” And who is going to be stuck on the outside looking in? Roque responds with this warning: “If you’re not in that top group doing 120+ loans a year, you’ll be replaced by someone who knows how to use AI.”

A Tool, Not A Tyrant

For every dire prediction about AI, there are also those who see it as a way to re-empower mortgage professionals. Mincheng “James” Jin, whose company is both mortgage broker and correspondent lender, believes AI should serve as an “assistant,” not a replacement for human expertise. “AI cannot replace the human touch in the last step — there’s psychology involved,” he says.

The RemAIning 20%

Jin describes his day-to-day challenge in bridging the industry’s fragmentation. Lenders, brokers, and underwriters contend with ever-changing program guidelines — there might be 100 different sets of underwriting ratios just for one region. AI, in Jin’s view, is uniquely qualified to handle “the first 80%,” the repetitive or data-intensive tasks: “AI can help with knowledge bases, chatbots, and pricing engines that reduce the deluge of routine inquiries.”

But that remaining 20% — the complex, nuanced scenarios requiring “psychology,” as Jin puts it — still demands a human being. “Consumers don’t always disclose everything at the start,” he explains. “They might hide additional assets or unusual income streams. AI can’t always coax that out.”

Expertise & Accuracy

Jin cites the example of matching listings with potential loan programs. “Making mortgages affordable is crucial for the American dream — AI helps match the right programs to the right buyers.” Yet he adds a cautionary note: “AI is not magical — it still requires training and human expertise to ensure accuracy.” Mortgage products constantly evolve; a new grant program might appear next week and require manual updates to the AI’s knowledge base. 

Replacing The Routine

One telling anecdote from Jin’s team involves a top producer who used to spend hours manually double-checking program eligibility. “He could remember five or six programs off the top of his head,” James says, “but if you had 15 possible ones, it would take an hour or more to research.” Now, with AI performing immediate lookups, “He can close a dozen loans a month instead of two or three.” That efficiency frees underwriters and processors from nights hunched over reams of paper. “We’re not replacing humans,” Jin insists, “we’re just replacing unnecessary work.”

The Big Altruistic Play

If Rick Roque sees AI leading to dramatic consolidation, and James Jin sees it helping existing professionals do more, Lukas Rosenblum suggests an even bolder future: a global network of AI-driven tools that anyone — particularly underserved communities — can use. To Rosenblum, this is about equity: “We’re talking about giving everyone the same playing field.”

Scaling Knowledge

At the heart of AngelAi is a belief that finance can be democratized, not dominated, by AI. “We don’t just want to serve the top 30% — we want to help billions of people,” Rosenblum says. The company started in mortgages, building a system that automates underwriting and slashes costs — allowing even smaller brokers and loan officers to remain profitable in the face of margin compression.

AngelAi has no plans to stop at mortgages, however. “We’re launching micro-lending at single-digit rates worldwide,” Rosenblum explains. “We have 2 billion people globally who are unbanked or trapped by predatory interest rates.” AngelAi’s system, he says, can process those micro-loans quickly and affordably, whether you’re a real estate agent in California or a small-scale entrepreneur in Kenya.

AI Avatars For Personalized Outreach

One of AngelAi’s standout features is a concept Rosenblum calls the “Angel Twin.” By downloading someone’s entire body of knowledge — personality, professional expertise, even published writings — an AI avatar can replicate that person’s conversational style around the clock. “You can be in 1,000 places at once, helping people while still running your business,” says Rosenblum. It’s not hard to envision a future where brokers and LOs extend their outreach with personalized avatars — a future that’s a lot closer than you might suspect, because a lot of companies are racing to be the one to pull tomorrow into today.

Human Oversight Is Key

Rosenblum is quick to stress ethics and oversight, however. “We must ensure AI benefits humankind — not just the wealthiest corporations,” he says. In practical terms, that means building decentralization into the system so that individuals own their data. “We put it on a blockchain, so you know it’s truly yours,” he explains. “We don’t want to own your data — we want you to own it.”

AngelAi also advocates for an AI Bill of Rights, safeguarding personal control over data and guaranteeing that AI-based decisions still involve human supervision. “People want the convenience of a one-click mortgage, but if you tell them it’s all AI, they worry,” Rosenblum says. “We want to show that there’s a person on the other side who cares. Because, yeah, you won’t lose your job to AI — but you might lose it to someone who knows how to use AI better than you.”

The New RAIlroad

Where AngelAi is designed as a global platform for democratizing access, Bochen Wang’s Zeitro is more akin to “rebuilding the mortgage tracks” from the ground up. “AI itself has no value — it’s like electricity. You need applications that transform industries,” Wang says.

From Fragmentation To Integration

Wang, a software engineer with roots in private equity, saw the mortgage industry’s fragmentation firsthand. “We have these legacy systems full of disconnected tools — PDFs, scanned images, separate pricing engines, separate compliance checkers,” he explains. “Before, a computer could only store PDFs and scanned images. Now, AI can extract meaningful data and structure it into a database.” Zeitro’s mission is to unify and standardize everything into a single “railway line,” spanning origination, underwriting, and secondary markets.

Reducing The ‘Human StrAIn’

In building Zeitro, Wang worked with seasoned processors and underwriters to see exactly where AI could relieve the burdens. One story struck him: “A 30-year underwriter had three eye surgeries from reading paper files every day. It’s not that we replace her job; we replace the unnecessary drudgery.” For Wang, AI is a gateway to pushing the industry forward, opening capacity for deeper client relationships or broader outreach.

That productivity bump, he concedes, may reduce raw headcount. “There are over 50,000 mortgage businesses today. We won’t need that many in the future,” he says matter-of-factly. “But the ones that remain will be more stable, more profitable. You can process 10 loans in the time it used to take for one, and spend the rest of your day helping people get approved, rather than chasing documents.”

A Future Of Fewer, Bigger Players

He echoes Rick Roque’s long-term vision of consolidation. “Mortgage is 70% of total consumer debt in the U.S. If Fannie or Freddie stumbles, the whole thing collapses. So it’s not necessarily bad to have fewer, bigger players — if those players are more efficient and better at risk management.” The real question, Wang suggests, is whether that new efficiency lifts the overall economy or creates a bottleneck for would-be loan officers. “The market’s going to shift, whether we like it or not. Our job is to build the infrastructure.”

A Booming Frontier Or The Eye Of The Storm?

So is this an “Age of pAIn” — or an era of unprecedented opportunity? The truth is, both.

Rick Roque’s data shows the stark future: fewer total employees handling a greater volume of loans. For many, that’s a grim prospect. But James Jin believes AI is making day-to-day life easier for countless practitioners: “It’s about freeing them to focus on the 20% that truly requires human empathy,” he says. Lukas Rosenblum aims to ensure that AI’s benefits spread globally, providing financial access to the unbanked. And Bochen Wang is busy laying down the digital rails to integrate every step of the mortgage process.

What unites these perspectives is the conviction that doing nothing is not an option. They speak of an industry poised to transform faster than at any point since the introduction of the 30-year mortgage — faster, even, than the “refi booms” that have sporadically swept the market in the last decade.

Embrace Or Be Eclipsed

Whatever the future may end up looking like, it’s going to get here a lot faster than we know. We’re on an exponential curve, Rick Roque explains, and focusing on job loss is to miss the forest for the trees. “For every new piece of tech, we’ve seen realtors, LOs, and underwriters worry they’ll be replaced. But that’s not the core concern,” he says. Instead, he points to the pace at which AI is already infiltrating everyday tasks — customer engagement, marketing intelligence, underwriting guidelines, compliance checks, property valuations. “People only see incremental gains at first, but it’s more exponential than they realize.”

That acceleration, he warns, will compress margins and concentrate volume. “If I’m a top producer using AI, I can handle loans in new markets. Meanwhile, the local LO who relied solely on personal relationships might lose three or four deals a month to me. It might not sound like a lot at first — but multiply that across thousands of markets. Within a few years, you might see a handful of LOs dominating entire regions.”

It’s a potential race to the top for those who adopt AI quickly — and a race to the exits for everyone else. “We already have 20,000 LOs doing the majority of production,” Rick reminds us. “That number could drop to 15,000 or even 10,000 in a decade. So yes, for the bulk of the workforce, it’s going to be painful. That’s just the reality.”

Charting A Path Through The pAIn

Change is coming to mortgage lending whether we want it or not. The “pain” half of this equation is impossible to ignore — jobs will vanish, small brokerages will fold, and a once-fragmented landscape may consolidate under the biggest players. AI algorithms will process more data in less time, and if Rick Roque is right, we’ll watch tens of thousands of LOs and processors exit the industry over the coming years. While the industry has experienced an exodus after the arrival of “higher for longer,” this potential shift would be qualitatively different: the day will come when interest rates go lower, but jobs lost to AI aren’t coming back. Ever.

Yet, for those who see the silver lining, there’s an unprecedented upside: LOs and lenders who harness AI can close more loans, serve new markets, and forge a more streamlined experience for borrowers. James Jin’s pragmatic advice stands as a reminder that humans still hold the final piece of the puzzle, and Lukas Rosenblum’s mission to democratize AI points to a future where the current mortgage model has evolved into a broad global fintech ecosystem. And from behind the scenes, Bochen Wang’s Zeitro is quietly rebuilding the entire “rail system,” ensuring the under-the-hood data pipelines run smoothly.

Whether this transformation feels exhilarating or exhausting depends largely on where you stand in the industry. If you embrace AI, you might land among the top performers consolidating the market. If you resist it, Rick Roque’s grim assessment may come true: “You’ll be replaced by someone who knows how to use AI.”

It’s a future full of hope and foreboding all at once — an Age of pAIn where heightened efficiency, globalization of lending, and potential job displacement collide. Ultimately, the question is less about whether AI will transform the mortgage sector and more about which lenders, loan officers, and tech pioneers will steer that transformation — and who, in the end, might be left behind.