Success in insurance today means mastering both challenging market conditions and battle-hardened competition. Artificial Intelligence (AI) can improve insurance underwriting, claims management, policy servicing, and other areas by accelerating critical workflows to deliver benefits across processes, from risk assessment to more cost-efficient claims handling to improved operational efficiency.
By embracing AI, insurers will deliver greater profitability by enhancing human excellence and delighting brokers, agents, and policyholders with a high-grade customer experience. Embracing AI will be the key to building a competitive advantage and ensuring success—now and in the long run. Additionally, the use of AI in these strategically important areas of the insurance value chain will make a company more resilient during times of economic uncertainty and allow a company to adjust or adapt to changing market conditions very quickly.
AI-Powered Underwriting Creates Efficiencies That Reduce Operational Expenses
Using traditional methods for reviewing documents within submission packages—which can include emails with attachments, ACORD forms, loss runs, schedules, and applications—has created serious backlogs and other complications. Teams can be overwhelmed by submission package volume, which increases the risk of errors and inconsistencies and then slows down the customer response time.
Deploying AI can dramatically increase team productivity, expanding their capacity to review and process complex data from multiple sources. Automating data extraction and classification can identify key data points and streamline their integration into a carrier’s underwriting systems. Human-in-the-Loop (HITL) systems continually improve the performance of these AI systems, validating data and offering feedback to boost data accuracy significantly.
This can lead to remarkable results, such as 80% straight-through processing of underwriting submissions, which in turn, maximize the value of human expertise by giving underwriters the bandwidth to do what they do best—complex risk analysis, informed decision-making, and building broker relationships.
How AI improves insurance underwriting:
- Automating data collection, risk assessment, document processing, and other manual tasks can streamline the quoting process to deliver quotes faster. AI applies machine learning algorithms and natural language processing (NLP) to analyze applicant data, giving underwriters key insights needed to generate quotes efficiently. Accelerating the underwriting process significantly enhances operational efficiency and improves customer experience with timely quotes.
- Underwriters frequently encounter risks that don’t align with their company’s appetites or underwriting guidelines. Using AI to process unstructured data in submissions surfaces greater quantities of information from policy applications, financial statements, medical records, and other documents, enabling underwriters to find and prioritize submissions that align with business objectives quickly. This targeted approach saves time and resources spent on less promising submissions, leading to significant cost savings, improved underwriting efficiency, and higher revenues.
Using advanced models early in the underwriting process to predict potential risks drives more effective risk management. This information enables insurers to lower their loss ratio by refining pricing strategies and offering more tailored coverage options.
AI-driven automation can potentially increase productivity by 100% (measured in terms of premium per underwriter) without increasing the risk of premium leakage.
How AI Integration Reduces Claims Costs
AI is revolutionizing claims management. It has transformed the traditionally labor-intensive claims intake, processing, and settlement processes.
AI can turn days of indexing claims submissions into minutes while also cutting manual review. For example, mailroom turnaround times can go from 3-5 days to under 1 hour and cut manual review by 60%, greatly enhancing productivity, boosting capacity for peak demand times, and increasing job satisfaction.
How AI-accelerated claims management helps insurance businesses create a strategic advantage:
- Driving operational efficiency by removing repetitive and error-prone manual effort from document processing. For example, using AI-powered tools to extract and analyze data from demand packets, subrogation demands, and other complex documents can yield greater quantities of critical data insights for accurately settling claims and reducing overpayments.
- Cutting claims cycle times by accelerating data analysis. AI drives quicker claims resolution by processing vast amounts of data faster. AI also enables more effective decision-making by automating key processes such as claims triage, document verification, and fraud detection.
- Streamlining claims management by automating data intake and document verification. With manual effort removed from these tasks. Claims managers and adjusters have the bandwidth for delivering personalized support activities such as handling complex claims and delivering personalized support to claimants.
Integrating AI into claims management allows insurers to reduce overall claims expenditures and indemnity costs. Faster, more efficient claims management also boosts customer loyalty by creating effortless claims settlements.
AI Adoption Is No Longer an Option
Making the leap to AI is a strategic imperative for insurers looking to enhance financial and operational performance. Successful AI implementation starts with clear strategies and resources to minimize business disruption and ensure return on investment (ROI).
Essential elements for effective AI implementation include:
- Quality of Data: Models need to be trained on clean, structured, and well-integrated data.
- Working with Strategic Partners: Consider strategic partnerships to overcome talent and technical barriers within your business. Working with a vertical insurance AI vendor can create a much shorter path to AI implementation success.
- Human-in-the-Loop (HITL) for Human/AI Collaboration: AI is most effective when augmenting human experience, rather than replacing it. HITL in insurance workflows empowers your experts by giving them oversight and control for reviewing and refining AI outputs
- Use Case Selection for Rapid ROI: Deploying AI across critical areas, including claims underwriting automation, triage, and fraud detection, offers quick wins for building consensus around broader AI implementation.
The future of insurance is intelligent, efficient, and customer-focused—and this future is powered by AI. By reducing operational costs, improving pricing accuracy, and minimizing claims expenses, AI directly contributes to insurance companies' profitability. Insurers that adopt AI strategically and leverage data effectively will stand out as the market evolves.
Download the annual 2025 State of AI Adoption in Insurance Report for valuable insights from insurance underwriting, claims management, and operations leaders.