8 Manual Processes You Should Not Still Be Doing

For decades, insurance underwriters, claims adjusters, and other skilled experts have lost countless hours of productivity by manually working and reviewing data locked in an endless stream of documents – ACORDs, submissions, legal demands, and policy-servicing forms, like COIs and endorsements. Even now, as some insurers are just dipping a toe into AI, others are already scaling capacity by deploying AI to take on the heavy lifting across many high-volume, document-driven workflows.  

Let’s look at eight common manual processes where AI cuts through routine tasks to help your teams unlock capacity, win more business, improve the customer experience, and accelerate your organization’s overall AI transformation. 
 

How Insurance AI Eliminates the [Not-so-Hidden] Costs of Manual Work

The insurance industry is increasingly unlocking performance by reducing time spent by human experts on administrative work and shifting that expertise toward higher value activities. By automating document intake, data capture, correspondence tracking, and other tasks, seasoned insurance professionals regain valuable capacity to redouble their focus on risk analysis, complex claims, client advisory, and decision making.  

This shift improves agility, enabling faster quotes, claims settlements, renewals, and endorsements, while delivering more consistent outcomes and streamlining compliance.

With repetitive tasks moved into the background, error rates decline, rework is reduced, and service becomes more reliable. The insurance work experience improves as well, with roles that better align to their skills and experience while presenting them new opportunities to build AI fluency, deepen domain expertise, and take on more meaningful, judgment-driven work.

Many carriers and brokers have historically relied on BPO arrangements to manage volume when automation is limited. While these models can provide short-term relief, they often invite complexity and other challenges demanding attention from internal teams.  

By deploying AI to handle routine manual processes, insurers across underwriting, policy servicing, and claims are reporting measurable gains, including: 

8 Manual Workflows That Are Ready for Automation

These workflows remain manual across much of the insurance industry, yet they are among the most ready for automation today. In each case, AI is already delivering measurable gains in efficiency, accuracy, and capacity – freeing teams from repetitive work while accelerating outcomes across underwriting, policy servicing, and claims.

1. Clearing and preparing submissions by hand

AI-powered submission intake accelerates time to quote cycles by reducing submission clearance times and preparing structured, decision-ready data for underwriting teams. This lowers operational costs, increases underwriting capacity, and helps identify coverage underrepresentation earlier in the process, reducing premium leakage.

2. Reviewing and re-keying loss runs

AI-enhanced loss run processing accelerates underwriting and renewal decisions by transforming unstructured loss histories from PDFs and spreadsheets into structured, usable data. Automation improves accuracy, shortens review cycles, provides summaries by claim type, and enables teams to handle higher volumes without additional manual effort.

3. Extracting data from schedules and statements of values

AI-powered processing of schedules and statements of values (SOVs) reduces manual document handling and standardizes complex, multi-location and multi-asset exposure data. This improves underwriting efficiency, supports more consistent risk evaluation, and enables scale as submission complexity increases.

4. Processing endorsements and policy changes

AI-driven processing of endorsements submitted via email automates policy updates, increases underwriter efficiency, and improves customer satisfaction through faster turnaround times. During periods of elevated volume, automation helps absorb demand spikes and prevents endorsement backlogs, maintaining service consistency.

5. Creating and issuing certificates of insurance

Automated COI generation increases operational efficiency by streamlining request intake, validation, and issuance, while improving customer satisfaction through faster, more consistent turnaround. Teams are able to respond to COI requests at scale without compromising accuracy, especially during peak request periods or high transaction volume.

6. Reviewing and reconciling premium audits

AI-driven premium audit processing accelerates audit completion while improving accuracy and reducing operational costs. Automation helps minimize leakage and increase premium revenue by reducing missed adjustments and delayed audit completion, even as audit volumes fluctuate.

7. Indexing and classifying claim documents

AI-driven claims indexing reduces handling costs by automatically classifying incoming claim documents and preparing structured data for downstream workflows such as coverage review, reserving, and triage. Improved accuracy and more consistent application of categories supports higher straight-through processing rates and enables better prioritization.

8. Managing legal demands and tracking deadlines

AI-driven legal demand identification accelerates demand handling by organizing incoming documents, prioritizing deadlines, and triggering automated alerts for adjusters and legal teams. This reduces missed demand dates, improves SLA performance, and helps prevent claims leakage.

As insurance organizations move from manual processing to AI-driven workflows, the impact extends beyond internal efficiency to the customer's experience itself. Automation enables faster, more predictable service with real-time customer response, aligning what insurance delivers with what customers already expect (and receive) from more digitally mature industries such as retail and financial services.  

At a high level, insurance customers want fast responses, accurate quotes and claims settlements, and transparent, trustworthy service. Insurers should be assessing whether their operations consistently deliver on those expectations – and, if not, where manual work is introducing friction, delay, or unnecessary costs. 

By automating routine, document-driven workflows, insurers create space for their experts to focus on judgment, problem solving, and relationship building – the work that truly drives differentiation and long-term growth. At the same time, customers benefit from faster, more predictable service that aligns insurance with the digital experiences they already expect from more mature industries. 

The result is more than operational efficiency. It is a more resilient organization, a better experience for both customers and employees, and a stronger foundation for scaling AI responsibly across the business. For insurers still weighed down by manual processes, the question is no longer whether AI belongs in core workflows – but how quickly it can be applied where it matters most.