Across the insurance industry, a familiar transformation is underway: underwriters are no longer simply processing submissions — they’re becoming strategic advisors. Fueled by AI and intelligent automation, this new model empowers underwriters to shift from reactive data gathering to proactive decision making.
Technology shouldn’t replace underwriters; it should empower them. That’s the promise of the augmented underwriter: a professional equipped with smart tools that eliminate friction, uncover insights, and keep human expertise at the center 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.
Every minute an underwriter spends searching through submissions, loss runs, policy documents, correspondence, and other records is time not spent evaluating risk or working with brokers. AI-powered document intelligence can help turn that unstructured information into trusted context, bringing forward the information underwriters need to make decisions faster.
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. Underwriting is a natural place to see that value in action. AI can help teams review information more efficiently, surface relevant details across multiple documents, and reduce the time spent gathering and synthesizing information so underwriters can focus more of their expertise on evaluating risk and making decisions.
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:
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.
Submission triage: Streamline quote-to-bind by using AI to compare submissions against underwriting guidelines, loss history, and real-time market conditions helps get work to the right underwriters — reducing wasted cycles and improving the likelihood of closing quality business.
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.
If the goal of introducing AI is to reduce friction across underwriting workflows, how and where that AI is introduced matters.
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 great 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 just a tool. Underwriting still requires expertise in navigating nuanced risks or building long-term broker relationships. The goal isn’t to remove underwriters from the equation, but to remove obstacles that can slow them down. 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. But critically, these investments are focused on redefining human roles from process execution to judgement, empathy, and innovation — not replacing them.
Carriers and MGAs that centralize documents, organize them effectively, and reduce manual document handling create an environment where people can find what they need faster and with confidence. Modern document intelligence can bring information and AI directly into underwriting workflows, helping teams spend less time searching and more time evaluating risk without sacrificing control.
Looking ahead: A strategic shift for insurance
AI creates the most value when it is built for the realities of insurance and put to work inside the workflows people rely on every day.
That is the approach behind the Vertafore Velocity™ AI Platform. Purpose-built for insurance, Velocity AI is the foundation for bringing intelligent automation and AI agents into Vertafore solutions to reduce manual work, bring the right information forward, and help insurance professionals make better decisions while keeping human expertise at the center.
For carriers and MGAs, document intelligence is one example of what that can look like: transforming complex, unstructured information into trusted context so underwriting teams can spend less time searching and more time evaluating risks, making decisions, and working with brokers.
Read more about Vertafore’s AI initiatives.