Operations in insurance don’t break down in dramatic ways; they just quietly drag you down one small task at a time. COI requests. Policy checks. Endless forms. It’s not that these things are hard. It’s that they never stop coming. And while most agency owners know this grind isn’t sustainable, many still treat it like a rite of passage, instead of what it actually is: solvable.

The smartest agencies are using Generative AI in insurance the way they’d use a solid assistant, not to replace people, but to remove the constant low-value busywork. And even better? They're outsourcing the execution layer to trained support teams who actually know how to work with AI instead of wrestling it.

In this blog, we’ll break down what that looks like. Just a real look at where AI fits, what tasks it's already owning, and how it's shifting the way insurance operations run, for the better.

Challenges insurance companies face (Still)

Even the best insurance agencies are stuck in a weird loop. The systems are clunky. The workload is uneven. And half the time, people are chasing down paperwork instead of clients.

A few things that keep coming up:

• Too much manual work - Everything from endorsements to follow-ups feels heavier than it should.
• Data entry hell - Every new policy feels like a copy-paste marathon.
• Response delays - No one likes being the agency that ghosts a client for 3 days because things got buried.
• Burnout - Your team didn’t sign up to babysit a queue all day.

And no, hiring ‘just one more person’ isn’t going to fix it. You don’t need more hands. You need fewer things to handle.

5 insurance tasks AI can handle with precision

These aren’t hypotheticals. These are tasks that AI is handling right now, in actual insurance environments, not just in demo videos or LinkedIn case studies. We're talking about tasks that used to drain your team’s time and energy, and are now being quietly and efficiently offloaded.

1. COI requests

What used to take 10 minutes per request now happens almost instantly.

This is one of the most common and annoying recurring asks agencies deal with, and clients always want it done ASAP.

Here’s how AI handles it:

• Scans the incoming request email - Identifies client name, insured party, job site, limits required, and cert holder.
• Auto-pulls policy details from the AMS or CRM - commercial liability, workers’ comp, auto, whatever’s needed.
• Auto-fills the COI template - Complete with coverages, correct policy numbers, expiration dates, and carrier info.
• Triggers a human check only if something’s off - Like a missing endorsement or mismatched data.
• Emails the COI directly to the cert holder or client, and logs the activity for compliance.

2. Policy endorsements

High volume, low complexity, exactly the kind of thing AI thrives on.

Policy changes come in all the time: name changes, address updates, adding/removing vehicles, adjusting coverage limits. And each request means:

• Reading the client’s email or phone note
• Logging into the system
• Pulling up the right policy
• Double-checking current coverage
• Making the change
• Confirming with the carrier
• Sending a confirmation back

That’s a ton of tiny steps, which, when you’re doing 20–30 of these a day, becomes a serious drag.

Here’s what AI does instead:

• Reads and interprets the endorsement request using NLP (natural language processing).
• Cross-references policy data - confirms the change is valid and within bounds.
• Populates the change in the AMS, queues it for approval if required.
• Alerts your team only if something needs manual intervention - like if the change affects pricing or breaks a rule.
• Drafts the confirmation email back to the client, complete with updated documents attached.

No more bottlenecks. No more ‘Sorry for the delay’ follow-ups. Just clean execution.

3. Renewal data checks

The kind of mind-numbing work that AI eats for breakfast. 

Renewals are deceptively heavy. It’s not just reissuing a policy. It’s validating a dozen little things, addresses, exposures, coverage types, endorsements, premium changes, and claims history. 

AI makes this process smoother by:

• Pulling last year’s policy side-by-side with the renewal version.
• Running field-level comparisons - Flags changes in limits, classifications, insured names, etc.
• Identifying missing or outdated info - Like lapsed licenses or expired driver info.
• Highlighting upsell opportunities - For example, if a client added a new location but didn’t increase property limits.
• Prepping the renewal summary - Structured, easy to review, and ready for the client.

The end result? Your team gets to spend more time reviewing strategy and less time sifting through policy PDFs.

4. First-touch client replies

The inbox assistant you always needed but never had.

Most client interactions start simple:

• Can I get a copy of my policy?
• Did you get my COI request?
• When does my coverage renew?
• How do I file a claim?
• Can I add my new car today?

These aren’t tasks that need your top account manager. They’re just requests that need fast, accurate, polite responses. That’s AI’s sweet spot.

Here’s how it works:

• AI sits on your support inbox or chat system
• Recognizes common requests and identifies the client
• Pulls account details from your system
• Drafts a response that’s on-brand, clear, and helpful, no weird robotic tone
• Logs the interaction in your CRM, flags anything unusual for a follow-up

Instead of your team chasing emails all morning, AI clears the first wave. Think of it like an inbox bouncer, filtering out what doesn't need human touch.

5. Claims intake categorization

Before your adjuster even opens the file, it’s already sorted, scored, and tagged.

Claims aren’t just operationally heavy, they’re sensitive. Clients are stressed. Details are fuzzy. Time matters. But most of the initial work is organizational:

• Reading long narrative emails
• Parsing attachments (photos, police reports, etc.)
• Identifying policy numbers, coverage lines, dates
• Categorizing the claim: property damage, liability, auto, etc.
• Routing it to the right adjuster

AI handles all that upfront load:

• Ingests and parses documents & emails
• Extracts critical data points - names, dates, policy #, loss type, and incident notes
• Assigns a claim category and severity level
• Flags potential red flags - duplicate claims, mismatched info, etc.
• Routes it to the right internal queue - based on policy type, region, or volume

Your adjusters don’t waste an hour just figuring out what’s going on. They open the file and get straight to work.

Use & applications of AI in insurance

Let’s keep it simple. Here’s where AI already fits:

• Document sorting & analysis
• Email intake → task creation
• Client account data pulls
• Claims data extraction
• Renewal packet prep
• Compliance rule-checks

These are not ‘ideas for the future’. These are daily use & applications in insurance today, quietly improving ops in the agencies that have stopped waiting and started experimenting.

This isn’t a tech trend, it’s a workload reset

Always remember that there’s no reward for doing things the hard way. Your team’s too sharp to spend another quarter buried in low-leverage work. And your clients? They’ll notice when things move faster and smoother without you having to work twice as hard.

Generative AI in insurance isn’t a magic wand. But it is a very good assistant. Pair that with a support team that knows what they’re doing, and you’ve got a real operating model, not just another tool collecting dust.

At FBSPL, we help insurance teams offload the grunt work, integrate AI the right way, and get back to doing work that matters.

Need help figuring out where to start? Let’s talk.