AI in Insurance: 5 Ways to Automate What’s Slowing You Down

“Is AI going to replace me?” You’ve probably asked yourself or heard someone on your team ask this in the last few weeks.

Here’s the reality: AI isn’t taking jobs, it’s making them easier. MGAs and program managers who use AI tools in their day-to-day are outpacing competitors, cutting costs, and getting more efficient in ways that weren’t possible before–McKinsey reported that AI can increase productivity by 10-20% in the insurance industry.

AI-powered claims processing reduces settlement times from weeks to a couple days. AI-driven underwriting engines improve risk assessments with proactive insights. This is the new standard.

The best part? You can start using AI to unlock these benefits today and start automating the most time-consuming, manual, and costly parts of your operation.

AI-powered submission parsing: increase efficiency without sacrificing accuracy

Despite being the first step in underwriting, the submission process is one of the most time-consuming and error-prone aspects of insurance. MGAs and program managers can receive submissions from all different sources–email, fax, PDFs, spreadsheets–requiring hours of manual data entry, review, and verification. Not to mention all of the back and forth with brokers that can slow down the quoting process and delay binding policies.

AI-powered submission parsing can automate this entire intake process. AI-enabled systems today can receive an email submission from a broker and extract data directly from applications, statements of values, and supporting documents. Data is then automatically processed and quotes are populated with information organized for underwriters.

This eliminates data silos, reduces errors and allows MGAs and program managers to process more applications in less time. Instead of waiting days for manual reviews, quotes are automatically generated, unlocking faster policy issuance and a better experience for brokers and insureds.

Longer term, expect these AI models to actually communicate with the broker also, following up and requesting information like financials and retro dates that may not have been included in the initial submission email.

AI-powered underwriting: faster & more accurate risk assessment

Underwriting is the backbone of insurance, yet traditional models rely on fixed one-size-fits-all style rules, which don’t consider newer and evolving risk factors. As customer risks become more complex, manual underwriting struggles to keep up, leading to mispriced policies or delays in approvals.

AI-powered underwriting changes the game by automating risk analysis, pricing, and approvals, allowing insurers to assess risk faster, improve pricing accuracy and increase operational efficiency.

Unlike traditional underwriting, which relies heavily on historical data, AI underwriting uses real-time data-driven decision-making to evaluate emerging risks and customer-specific factors. By leveraging machine learning and predictive learning, AI can process risk factors and customer data instantly, forecast potential losses, and approve low-risk applications in seconds. Pricing is also more accurate, as risk models are continuously updated based on new claims data, customer behaviour and macroeconomic trends.

AI underwriting models are also more focused on the risks being insured–whether it’s a company, individual, or asset (like a vehicle or property). By automating underwriting with customizable risk assessments, insurers can improve accuracy, reduce manual workload, and offer fairer pricing to their insureds. For example, in many commercial trucking programs, there is often as much as a 20% difference between the trucks in use and the VINs listed on the policy. This risk exposure has been unavoidable for years, but with newer systems, the policy and the real-world situation can stay in closer parity, pricing the policy better.

For MGAs and program managers, this means faster decisions, lower operational costs, and more precise underwriting at scale. No more manual data entry, reviews or approvals needed.

AI-powered invoice auditing & indemnity prediction: greater financial strength

Detecting errors and financial discrepancies is a costly challenge for the insurance industry with $308 billion lost to fraudulent claims each year.

Traditionally, insurers rely on manual bill reviews, cross-checking line items against service agreements and reconciling payments by hand–a lengthy process that usually requires significant time from multiple departments (including finance). And identifying fraud involves auditing boxes of documents, verifying policy details and comparing past claims history–all of which are prone to human error and inconsistency.

AI changes this by automating financial oversight. Insurance companies can leverage automated bill review, which scans invoices in real-time, extracts line items, and flags discrepancies, such as duplicate charges or fees that violate service agreements–preventing overpayments before they happen.

Additionally, indemnity prediction can also boost a program’s financial strength by analyzing claims and policy documents to identify non-covered claims proactively, reducing unnecessary payouts and mitigating financial risk.

With AI, MGAs and program managers can boost compliance and gain confidence in their financial integrity. Instead of relying on manual reviews or reactive corrections, insurers can proactively catch errors, prevent fraud and ensure that only valid claims and bills are approved–saving time and money at scale.

AI-powered compliance monitoring: proactive & automated compliance checks

Insurance is one of the most heavily regulated industries, and staying compliant is only getting more complex. Shifting climate risks, cybersecurity threats, and unpredictable macroeconomic conditions are increasing regulations, making manual checks, paper records, and reactive audits difficult to manage and less effective. This can be costly–leading to missed red flags, audit failures and costly regulatory fines.

By leveraging AI, insurance professionals can automate compliance oversight. AI-powered compliance monitoring validates claims, invoices, and policy agreements against industry regulations in real-time–reducing the risk of penalties and ensuring regulatory compliance. AI can also generate automated audit logs and real-time risk alerts, giving insurers visibility into potential violations before they become an expensive issue.

AI shifts compliance and risk mitigation from a reactive process to a proactive one. Insurers stay ahead of regulatory changes, minimize risk exposure, avoid costly fines, and maintain full transparency.

AI-powered claims processing: reduce settlement time from weeks to days

Every year, insurers lose $34 billion due to customers switching providers, with 60% of switchers leaving due to slow claims settlements. Claims processing can be a slow grind–adjusters have to sift through paperwork, verify policyholder details and assess fraud risks. This not only lengthens settlement times but also increases the chance of error and fraudulent payouts.

AI-powered claims processing automates every step of the workflow: from instant data extraction to real-time fraud detection–reducing settlement times from weeks to days. AI models today can automatically extract key claim details from submitted documents, eliminating manual entry. Additionally, predictive analytics help insurers detect fraud patterns early, preventing unnecessary payouts and disputes.

As customer expectations increase, MGAs and program managers can better meet demand with AI-driven claims processing, ensuring faster claims resolution, improved customer satisfaction and reduced churn.

What was once an emerging trend and the elephant in the room, is quickly becoming table stakes. AI enables a better experience for both insurers and insureds–unlocking faster resolution times, eliminating tedious data entry, finding cost & time savings, improving compliance, and enhancing customer satisfaction.

With benefits like these, AI isn’t going to replace anyone in the industry–it’ll make their jobs easier. And it’s enabling the insurance industry as a whole to get smarter, faster, and more resilient. The time to start using AI isn’t tomorrow or next week. It’s now.

Meet the Author

Cameron MacArthur, CEO of AI Insurance

Cameron is the CEO of AI Insurance, which makes an AI-powered software platform for running insurance programs, MGAs and MGUs. Cameron is a Northwestern graduate, and has been awarded for his research in human-computer interaction.  With a background as a cognitive software engineer at IBM, Cameron is focused on bringing AI to the insurance space so folks can spend less time doing data entry and manual processing.