Total Expert Founder & CEO Joe Welu recently joined Robbie Chrisman for an episode of the Daily Mortgage News podcast where they discussed the current (and future) state of the mortgage industry, challenges facing lenders and loan officers, and the solutions that AI-enabled tools can provide in difficult markets.

Agentic AI is reshaping loan officer productivity and customer engagement. With Total Expert’s new AI Sales Assistant, lenders can automate lead incubation and qualification—achieving human-like conversion rates in weeks, not months. Joe also highlights the power of voice AI to revive aged leads, trigger refinance opportunities, and prevent deals from falling through the cracks, all without the need for massive call centers and without removing loan officers’ ability to build authentic human connections with borrowers and homeowners.

That’s because AI-enabled tools are designed to reduce the administrative and repetitive tasks that take you away from what you do best: advising customers and guiding them toward the best possible financial outcomes. Joe also shares insights on selecting AI partners wisely, managing data responsibly, and capitalizing on both front- and back-office efficiencies. As the AI arms race heats up, Total Expert aims to empower originators—not replace them.

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Joe and Robbie's discussion begins at the 4:55 mark.

*This article was reposted from HousingWire.com*

In this exclusive interview, Joe Welu, Founder & CEO of Total Expert, shares the company’s latest advances in AI. He focuses on lessons learned from their pilot program and explores how AI is delivering a measurable lift in operational efficiency and lead conversions across lending teams.

Beyond internal improvements, Joe reveals Total Experts’ focus on the borrower experience and how their technology is designed to supercharge loan officers, not replace them. Joe shares with Allison LaForgia his forward-looking perspective on the innovations expected in the near future that will continue to drive Total Expert’s leadership in mortgage technology.

“We anticipated… it would probably take maybe nine months to a year to be able to get to parity with a human… and we’re blown away. It happened within two weeks,” Welu said. The voice AI agent, designed to qualify leads through inbound and outbound calls, is now handling more than 2 million calls a month, with multiple lenders, in various stages of scaling.

Welu attributes the rapid progress to the unprecedented pace of innovation in AI. “It’s like nothing anyone’s ever seen before… there’s hundreds of billions, if not soon trillions, being invested in infrastructure and large language models… we get the opportunity to build on top of those capabilities and reimagine what we can do in our industry.”

The pilot program, he said, was rooted in an iterative approach with tight feedback loops. “As we learn… it gives us information, and we make adjustments… A key thing we’ve learned with AI projects… get really super clear about what it is in the business that you are improving. Give them that target… so it’s not this ambiguous sort of black box.”

The results have been measurable: “We are seeing, in some cases, 10 to 20% better conversions,” Welu said. AI’s consistency is a major factor. “It always remembers to call people back… never calls in sick… works weekends… It allows you to take your great people and… have them doing the most highly productive work possible.”

Borrower experience is also improving. “One of the pleasant surprises… is the quality of the experience to the end consumer,” he said. Whether or not lenders disclose that a caller is AI, “the quality of the interaction is so high, they continue down the path.” The AI agent maintains “the right tone… the ability to match… the tempo of the conversation” while instantly tapping into contextual customer data.

Welu emphasized that Total Expert’s AI is designed to “supercharge,” not replace, loan officers. “There are still moments where consumers want high quality advice… Our goal is to take a loan officer and put them in a position where they are spending… the majority of their time having the highest quality conversations… and abstracting away things that don’t add value.”

Looking ahead, Total Expert’s roadmap focuses on intentional, scalable AI. “We think about getting super clear on… use cases, and partnering with people that are going to be as obsessive as you are, about making it great,” Welu said. Over the next year, customers can expect new capabilities in customer intelligence, lead management, and additional AI-driven use cases. “Seeing it all come together is what gets me up and excited every day.”

By: Joe Welu, Total Expert Founder & CEO

Best Practices for Executive Teams Deploying AI in Financial Services

The AI revolution feels like humanity just discovered fire—and everyone is racing to see what they can ignite.

That means a rush of AI pilots and proofs-of-concept across all industries, many of which launched without evaluating each use case against actual business value.

As I meet with CEOs and executive teams from leading mortgage lenders and financial institutions, the conversation has shifted from “What can AI do?” to “How do we deploy AI responsibly, at speed, and with measurable impact?”

The market leaders I work with are outpacing competitors by following a remarkably consistent playbook. They’re not just testing AI, they’re embedding it across their organizations with purpose, speed, and discipline.

Below, I’ve distilled the best practices I’ve observed from the institutions getting the most from AI today.

Anchor AI strategy to business outcomes

Tie every AI initiative to a clear business priority—whether it’s loan growth, customer retention, or operational efficiency.

Define KPIs, ROI targets, and adoption metrics before a project begins. No project should exist without a measurable path to value.

Start with high-impact, low-friction wins

Focus first on areas where a proof of concept or pilot is feasible within 30-60 days. Conversational and Voice AI solutions provide many options for pilot use cases. Other common use cases involve document classification, predictive churn modeling, or intelligent lead scoring. These early wins build momentum, prove ROI, and prepare teams for more complex deployments.

Invest in data quality and governance early

AI is only as good as the data feeding it.

Start by creating a single source of truth for customer and loan data. Then, anticipate obstacles to deploying AI with your data, such as consumer consent and preference management, and start addressing these things ASAP. Investing in tools like Customer Intelligence will help enrich your data and increase its value.  

Embed compliance and risk management from day one

Regulations such the Gramm-Leach-Bliley Act (GLBA), TCPA (Telephone Consumer Protection Act), and UDAP (Unfair, Deceptive, or Abusive Acts or Practices) will be a few key areas where regulators dig in and look for companies cutting corners.

Create a cross-functional AI task force

Bring together leaders from product, compliance, data science, operations, and customer experience. Avoid siloed pilots—alignment ensures every initiative supports the broader business strategy. Include change management expertise to drive adoption, not just deployment.

Prioritize customer experience and trust

Every organization has gaps in their customer journey and can benefit from leveraging AI to provide human-like touch points throughout the experience. Use AI to remove friction, improve transparency, and deliver personalization at scale. Keep humans informed about high-stakes decisions and be transparent with customers about how AI is used and how their data is protected.

Build for integration, not isolation

Select AI solutions that integrate seamlessly with your CRM, LOS, core banking systems, and data lakes. Use APIs and modular architectures to avoid “AI silos” that slow scale and ROI.

Focus on talent and change management

Embracing AI with a growth mindset should be table stakes. Incentivize adoption so teams see AI as an enabler—not a threat to their roles. Upskill executives and frontline teams in AI literacy. When needed, recruit or partner for deep ML and data science expertise.

Measure, monitor, and iterate

AI is not a one-and-done project—it’s a living product. Track performance, user adoption, and ROI continuously, and refine models quarterly to maintain accuracy and relevance.

Choose the right tech partners: favor vertical specialists

Partner with vendors who understand financial services—especially your unique customer journeys or workflows. Deep domain understanding on core systems, database schemas, compliance, and other nuances will be a key factor in the results you achieve.

Benefits of vertical-focused partners:

• Deep understand of unique data sets and customer profiles

• Faster implementation with industry-specific models

• Built-in regulatory and risk controls

• Product roadmaps aligned to lending and banking trends

Horizontal AI tools have their place, but without deep domain expertise, they often require heavy internal customization and a slower time to value.

The future is here

AI today is not the same as the project in 2018 that failed to deliver those operational efficiencies in the back office everyone was promised. Its potential to transform nearly every part of our businesses is becoming increasingly clear. Every day you delay, competitors are building up their capabilities and you will struggle to catch up. As one of my investors put it bluntly, “Every day you fail to execute a comprehensive AI strategy, the value of your business goes down.”  

To learn more about how Total Expert is working with our customers on high-impact AI initiatives, please reach out to our team.