Across the insurance industry, a transformation is underway: underwriters are shifting from simply processing submissions to becoming strategic advisors. Fueled by AI and intelligent automation, this new model empowers underwriters to move from reactive data gathering to proactive decision making.
Ultimately, technology shouldn’t replace underwriters; it should empower them. That’s the future of underwriting: a professional equipped with smart tools that eliminate friction and uncover insights while maintaining the necessary human element of underwriting.
Enabling smarter underwriting
For too long, underwriters have spent their days buried in spreadsheets and emails, gathering information from disjointed systems and scanning documents for missing data. According to Accenture’s research, 40% of the average underwriter’s time is spent on administrative and non-core tasks.
It’s not efficient and, more importantly, it’s not sustainable in a competitive, customer-driven market.
Today’s carriers and MGAs have an opportunity to take document and workflow management a step further with AI. Modern insurance document management solutions can already centralize underwriting content, make documents easier to find, connect information, and automate the workflows that keep submissions moving. AI-powered knowledge, document intelligence, and analytics tools can build on that foundation by helping underwriters more quickly find, extract, and understand the information contained within those documents.
From transactional to tactical: AI’s role in risk strategy
AI is a game changer —not because it automates every step, but because it supports smarter, faster decision making. A recent agent experience report conducted by Vertafore found that 76% of independent agency producers and account managers noted that fast underwriting decisions are highly important to them when placing business with a given carrier.
Here are some of the cutting-edge use cases carriers and MGAs are exploring for AI in underwriting:
- Speed up submission processing: Shorten the time from quote-to-bind by using AI to compare submission information against underwriting guidelines, loss history, and real-time market conditions. This empowers underwriters with the information they need faster and and improves the likelihood of closing quality business.
- Identify information that needs attention: Document intelligence can help surface missing, inconsistent, or relevant information within submission materials for further review. That gives underwriters a more efficient starting point for determining what requires their expertise or additional follow-up.
- Data enrichment tools can automatically extract structured insights from unstructured submissions. By integrating data across internal systems and external sources, they can respond to brokers with speed and precision.
- Portfolio analysis and development: AI tools can aggregate data across books of business to help underwriters spot trends, identify concentration risks, and evaluate segment-level profitability. These insights enable underwriters to play a more strategic role in shaping a balanced, high-performing portfolio, informing product design, pricing strategy, and long-term growth planning.
- Predictive models analyze historical performance and current trends to surface early risk signals. AI is showing promise in surfacing opportunities across the business — from identifying high-performing segments to flagging underperforming risks. AI can analyze vast amounts of diverse data (e.g. weather patterns, financial behavior, driving records, etc.) and identify complex patterns and correlations that a human underwriter might miss. Having more precise risk assessments leads to more accurate and personalized pricing, improved profitability, and better risk mitigation strategies.
In fact, a recent BizTech Magazine report showed that AI has reduced the average underwriting decision time for standard policies from 3-5 days down to 12.4 minutes, while maintaining an impressive 99.3% accuracy rate in risk assessment. For more complex policies, AI has cut processing times by 31% and boosted risk-assessment accuracy by 43%, demonstrating genuine operational transformation.
Today’s leading underwriting platforms achieve this by combining rules-based engines with AI models to support straight-through processing. Submission data is automatically extracted, validated, and scored against underwriting guidelines, ensuring eligibility and pricing alignment before an underwriter ever reviews the file. For MGAs and carriers, this means faster quote turnaround, higher submission throughput, and greater consistency while still enabling human oversight for complex or referral-based links.
Empowering people, not replacing them
Across all facets of business, employees are asking the same question: Will AI replace me? For the underwriter, the answer is clear: absolutely not.
AI is a tool, not a substitute for underwriting expertise. Evaluating nuanced risks, applying judgment, and building long-term broker relationships still require human experience. The opportunity is to remove the obstacles that slow underwriters down and give them better information to make confident decisions.
Consider the work that goes into determining whether a risk should be insured. An underwriter may need to research underwriting guidelines, policy language, risk characteristics, and other insurance-specific information before reaching a decision. AI-powered knowledge tools can help bring that information together quickly, allowing underwriters to ask questions in natural language, identify important underwriting considerations, and trace answers back to trusted source material.
That support can benefit underwriters at every experience level. Newer underwriters can use AI as an on-demand knowledge resource as they build expertise, while experienced underwriters can more quickly research complex risks, evaluate submissions, and determine what additional information they may need from an agent. The result is AI helping the underwriter make a faster, more informed, and defensible decision.
A study conducted by Wipro found that 81% of U.S. insurers plan to increase AI budgets, with AI projected to make up 20% of IT spend within 3–5 years. Critically, these investments are focused on redefining human roles around judgment, empathy, and innovation—not replacing them.
By giving underwriters faster access to trusted information and decision support, AI can help them spend less time searching for answers and more time applying their expertise. It’s not about doing more with less—it’s about helping people do their best work.
Looking ahead: A strategic shift for insurance
The future of underwriting is collaborative, connected, and data driven. As risk becomes more complex and customer expectations rise, carriers and MGAs must empower their teams with technology that helps them move from reactive to strategic.
Whether it’s optimizing submission processing, enhancing pricing accuracy, or driving portfolio strategy, the augmented underwriter has strong potential to become a critical part of the modern insurance organization. For carriers and MGAs, the goal is not to automate judgment, but to reduce the manual work required so that the underwriter's judgment matters most.
Vertafore is a leader in AI integration across the insurance industry, taking a three-pronged approach to AI: improving productivity, fueling customer growth, and reinventing insurance options with AI already embedded in our products.
Read more about Vertafore’s AI initiatives.