AI transforms mortgage lending as nCino’s bet pays off

AI and automation adoption in mortgage lending has surged dramatically from a modest 15% in 2023 to an estimated 64% by 2025, with early 2026 projections suggesting even steeper growth. This rapid uptake reflects a broader industry shift where lenders are moving away from traditional ROI metrics focused on cost savings, instead prioritizing tangible outcomes and outputs to better capture the dynamic value of AI integration. As one analyst observed, 'We're not good at measuring ROI... It seems like outcomes and output are the better way to start thinking about this rather than what it cost me to get there.'

Distinct lender segments exhibit markedly different AI adoption behaviors: Independent Mortgage Banks (IMBs) lead the charge with a 75% adoption rate by mid-2026, outpacing banks and credit unions which lag at around 46%. IMBs embrace experimentation and rapid iteration, unafraid to 'fail fast' and learn, whereas banks adopt a more cautious stance, emphasizing governance and regulatory compliance. This divergence is underscored by the fact that banks often require concrete, practical AI use cases—such as automated income verification features—to fully appreciate the technology's value, highlighting a pragmatic approach to AI adoption.

Credit unions and private lenders distinguish themselves by their willingness to undertake significant process redesigns to fully leverage AI technologies, contrasting with IMBs’ preference for out-of-the-box AI products. This strategic openness to reengineering workflows, though a 'heavy lift,' positions these lenders to potentially unlock deeper efficiencies and innovation. Meanwhile, the burgeoning mortgage AI vendor landscape—with many new entrants hastily branding products as AI-enabled—adds complexity for lenders trying to discern credible solutions amid a flood of offerings.

The momentum behind AI adoption is not only robust but accelerating, with surveys indicating that over 80% of lenders currently using AI plan to expand their usage, and none intending to scale back. This strong forward-looking commitment reflects an industry-wide recognition that AI is becoming indispensable in mortgage operations, driving a sustained transformation in how lenders compete and serve borrowers.

Since 2023, mortgage lending has witnessed an explosive surge in AI capabilities, with large language models like ChatGPT, Gemini, and Claude rapidly evolving and prompting lenders to adopt a strategic yet cautious stance. Despite this acceleration, some foundational technologies such as eNotes remain surprisingly underutilized, highlighting that while AI integration is advancing, the full operational embedding of both new and legacy digital tools is still a work in progress within the industry.

Between 2024 and mid-2026, AI adoption in mortgage lending quadrupled, signaling a decisive shift from experimental pilots to widespread deployment focused on tangible value creation and scalability. The industry conversation matured from debating AI’s use to pinpointing where it drives operational impact, emphasizing early governance and workflow redesign as critical success factors. As one analyst observed, "those that apply it, build the governance early, and use it not just to automate tasks, but to redesign the work" will lead the transformation.

By mid-2026, AI had become integral to loan processing workflows, with platforms like Adai processing approximately 19,000 loans monthly and delivering underwriting calculations within a tenth of a percent accuracy compared to human underwriters. Organizations leveraging existing systems of record integrated AI tools to boost both customer engagement and operational productivity, marking a shift from isolated AI tasks to embedded workflow responsibilities that enhance end-to-end loan processing efficiency.

Industry leaders such as Mike Yu of Vesta underscore how AI’s role has expanded beyond back-office document processing to encompass advanced applications like voice agents and conversational AI, which have recently demonstrated impressive capabilities. This evolution enables automation across the entire loan lifecycle—from application through funding—resulting in lower operating costs, reduced processing times, and a flexible workforce model that adjusts to demand. While regulatory complexities temper rapid adoption, lenders are increasingly embracing AI in customer-facing and relationship-building functions as they internalize its broad potential.

By mid-2026, AI had become a pervasive force reshaping mortgage capital markets, influencing everything from lead generation to underwriting and funding processes, which in turn stirred mixed investor sentiment regarding mortgage-backed securities. While AI's integration promised efficiency and innovation, as evidenced by widespread industry discussions, some investors remained cautious, weighing potential risks against the technology's transformative potential.

nCino’s August 2026 launch of Mortgage MCP marked a pivotal AI-driven innovation that significantly enhanced operational efficiency for over 2,700 lenders by reducing administrative workflows from hours to mere minutes, all while maintaining rigorous compliance controls. This breakthrough, highlighted by General Manager Casey Williams’ remark that tasks 'that used to consume hours become a five-minute conversation,' directly contributed to a 12% increase in fiscal first quarter subscription revenue and lifted full-year guidance, signaling strong market validation of AI-enabled mortgage technology.

Despite the optimistic revenue trajectory—nCino projects $776 million in revenue and $117.4 million in earnings by 2029, implying a 20% upside to its current stock price—the company faces significant competitive and adoption risks. Larger cloud and fintech rivals could introduce competing AI layers that erode nCino’s pricing power and market share, while customer resistance to higher AI-linked subscription pricing remains a meaningful overhang, underscoring the delicate balance between innovation-driven growth and market realities.