From LOS to Agentic AI: How Mortgage Tech is Being Rewritten

In the January 20, 2026 episode of the Weekly Mortgage Update, David and Allen Pollack explored the rapidly evolving intersection of AI and mortgage technology. The conversation covered everything from generational perceptions of AI to how agentic AI platforms are transforming the loan process end-to-end.

Generational AI Awareness and Early Adoption

Allen Pollack opened with an observation about Gen Z: their familiarity with AI and digital tools shapes how they interact with technology. Even young children perceive AI as ubiquitous, blurring lines between concepts and human names. For mortgage professionals, this generational shift underscores the need to anticipate how future homebuyers will interact with digital-first processes.

AI Driving the Mortgage Process

AI is no longer a peripheral assistant in mortgage operations—it’s central to production. Platforms like Tinman AI unify key systems including LOS, CRM, underwriting, compliance, POS, and pricing into a single AI-driven workflow. According to company reports:

→ 70% of loans are processed as “one-day mortgages.”

→ Almost half of closings occur from lock to commitment in under a minute.

→ Future projections suggest over 90% of loans could be fully AI-driven, reducing cost per funded loan to below $1,000.

These advances illustrate how agentic AI is shifting the mortgage workflow from siloed tools to fully integrated, automated experiences.

The Shift from LOS Replacement to Agentic Experiences

Traditional LOS systems have become hubs rather than platforms to replace. Agentic AI experiences layer over these systems, automating interactions across departments while reducing manual intervention. Success depends on:

→ The right personnel with a technology-first mindset.

→ Proper engineering and data governance to prevent AI failures or “hallucinations.”

→ Scalable design that avoids bottlenecks and preserves operational efficiency.

Even companies investing millions can falter without expertise in AI architecture, highlighting the need for skilled teams to implement and scale technology effectively.

Operational Efficiency and Cost Implications

David highlighted operational cost structures: while average mortgage operations may cost $11,000–$13,000 per loan, AI-driven systems have demonstrated the potential to reduce costs to under $1,000 per funded loan. This consolidation and automation are expected to accelerate in 2026, emphasizing both efficiency gains and the importance of accurate vendor and resource management.

Vendor Management and Ownership

Pollack emphasized that success with AI and mortgage tech is not only about the platform but also about ownership and authority over the tech stack. Teams must:

→ Identify true vendor contributions and avoid redundancies.

→ Allocate responsibility for procurement, renewals, and implementation.

→ Evaluate systems for risk, compliance, and scalability.

Understanding the vendor landscape and operational responsibilities ensures AI deployments deliver both cost savings and functional reliability.

AI in Fraud Detection

AI is also becoming integral to risk and fraud management. Fannie Mae, for example, is collaborating with public AI companies to enhance fraud detection across mortgage operations, highlighting AI’s role in compliance as well as production.

Key Takeaways

→ AI has moved from a supporting role to a core driver in mortgage processing.

→ Agentic AI platforms can unify LOS, CRM, underwriting, compliance, and more, enabling near real-time loan processing.

→ Success depends on skilled teams, proper governance, and scalable engineering.

→ Operational costs per loan can be dramatically reduced through AI adoption.

→ Effective vendor management and ownership of the tech stack are essential.

→ AI increasingly supports fraud detection and risk management, making it a strategic priority.

As mortgage technology evolves, the combination of agentic AI and strategic operational oversight promises to redefine both efficiency and customer experience. Professionals who align their teams, vendors, and systems to these changes are positioned to lead the next generation of mortgage innovation.