65% of underwriters are missing out on the AI revolution

In this post, we examine why submission intake remains a bottleneck, how AI can help, and how top performers are seeing returns.

The submission intake challenge is real

Underwriters face intensifying pressure from rising submission volumes, fragmented systems, and inefficient manual triage practices. Submission intake remains one of the most manual, judgment-dependent stages in underwriting, with many underwriters stuck reviewing every submission that arrives to try to determine priority. The result is time and resources spent on low-probability submissions that rarely bind.

How AI improves submission intake for underwriters

By ingesting an organization’s goals, guidelines, appetite, and historical quote-bind data, AI can form an initial assessment of each submission and provide the underwriter with recommendations on which submissions merit the most attention. The underwriter then applies their judgment on which deals to pursue.

While AI in insurance underwriting will never be perfect, a really good AI can also learn as it goes along. The AI can collect feedback on how the underwriter’s judgment differs from its recommendation, and update its suggestions accordingly.  The more an organization (or even a specific underwriter) uses it, the more effective it becomes at surfacing deals the underwriter will most want to see, and at making helpful suggestions. 

This helps both individual underwriters and the larger organization: experienced underwriters can work more efficiently, while junior underwriters can benefit from the institutional knowledge baked into how the AI has learned to respond. This is especially vital as more senior underwriters approach retirement.

AI exceeds expectations for early adopters

Among insurers that have implemented AI solutions into underwriting operations, 62% say it’s already exceeding expectations. These teams are using AI to prioritize deals based on real appetite, historical binding patterns, and even broker behavior.

Velocity Risk increased volume and reduced time-to-quote with AI underwriting

Velocity Risk, a commercial E&S property hybrid MGA/Carrier, has seen significant improvements to its ability to manage growing volume and complexity through the use of AI-powered submission triage. When asked about the impact AI-powered submission intake had on their process, Velocity Risk VP of Business Development, Nina Chiapetta said,

‍“We set a goal that by noon each day, each underwriter should have quoted the best three or four deals on their desk. To do that, they have to focus on what’s in-appetite and winnable, rather than which brokers are most vocally calling for a quote. That puts the power in their hands to be more selective and write the best business quickly, and to spend more time on the deals and relationships where their particular skills can come into play.”

With AI integrated into the underwriting workflow, teams start each day with clarity. They know which deals are most likely to bind, which align with portfolio goals, and which can be deprioritized or declined altogether.

What’s holding insurers back from AI underwriting?

Insurers have long faced challenges in modernizing their underwriting infrastructure. Legacy systems often take years to implement, cost millions to maintain, and require extensive support just to adapt to evolving market conditions. Against that backdrop, the idea of introducing AI, particularly into critical workflows like underwriting, can raise concerns about complexity, disruption, and delayed value.

But when embedded directly into the underwriting process, AI becomes a tool for control, visibility, and precision. Instead of relying on outdated guidance or retrospective reporting, underwriters gain access to real-time insights about risk appetite, deal winnability, and portfolio alignment. Rules and guidelines become dynamic, and decision-making becomes proactive.

By reducing time spent on manual tasks and low-impact decisions, AI frees underwriters to focus on what matters most: building strategic broker relationships, targeting profitable growth opportunities, and shaping a resilient, high-performing portfolio.

AI delivers value when it's operationalized

To fully benefit from AI underwriting, insurers must rethink how portfolio insights are delivered and utilized. Leading teams ensure that insights are available to underwriters at the point of decision, in real time, and embedded within the workflows teams rely on every day.

AI for insurance is already helping underwriting teams work more efficiently and effectively. Those who adapt are seeing clearer priorities, stronger performance, and more consistent results. Organizations that rely on the status quo risk falling behind as the market evolves beyond what traditional underwriting frameworks and technology can support.

To explore how organizations are applying AI at submission and what is driving early success, download the full 2025 Federato State of Underwriting Report.