AI in Insurance Customer Service: A Complete Guide for 2025

Amir Prodensky
CEO
Nov 7, 2025
11 min read
How to deploy AI tools that solve customer issues faster and more accurately.
Not long ago, getting help from your insurance company meant waiting on hold, explaining your issue three times, and hoping someone could find your policy.
Today, that’s changing fast. AI is quietly reshaping customer service, turning long calls and confusing emails into instant, personalized conversations.
This shift isn’t a fad anymore; it’s becoming the norm.
Insurance teams need to move faster, reduce costs, and still deliver great experiences. AI makes that possible by speeding up responses, learning from every interaction, and helping smaller teams do more with less.
In this guide, you’ll see how companies like Strada, Lemonade, Ema, Kustomer, Beam.ai, and Cognizant are transforming support with real examples. You’ll also learn how Strada’s AI phone agent platform helps carriers, MGAs, and brokers handle more calls and boost revenue, all while keeping the human touch that customers trust.
Let’s explore how AI is making insurance simpler, friendlier, and a lot less stressful.
How is AI changing customer service in insurance?
AI is making insurance customer service faster, easier, and more accurate.
Instead of waiting on hold for a human agent, customers can now get instant help from AI-powered chatbots, virtual assistants, and automated systems that work 24/7. These tools quickly answer questions, handle claims, and direct requests without delays.
Before diving in, let’s see the big picture of how AI changes the entire customer journey, from the first question to claim settlement.

For example, platforms like Strada, EMA, Kustomer, and Beam.ai provide continuous support across websites, apps, and messaging, delivering consistent, mistake-free service anytime.
AI also helps reduce errors. It checks claim details immediately and spots mistakes that humans might miss. This boosts accuracy and speeds up processing.
Voice AI is another big change. Strada offers AI phone agents that handle calls instantly, with no waiting. They can help with renewals, claims, and policy questions around the clock.
This means customers never get stuck on hold, and insurers get more calls answered, even outside normal hours.
Here’s a quick look at the top AI tools in insurance customer service:
Strada → voice and SMS with zero-hold live call support
Lemonade → chatbot that processes claims in 2 seconds
EMA → chat plus automation for nonstop workflow handling
Kustomer → chat with AI help for human agents
Beam.ai → smart chat that routes claims efficiently
Together, these tools show how AI insurance customer service makes support faster, more accurate, and easier to access 24/7.
Now that you know how AI is reshaping insurance service, let’s look at the tools making it happen in more detail. You’ll see what insurers are actually using on the ground.
What AI tools and tech are insurers using today?
Let’s break down the main AI tools that insurance companies use to improve customer service.
Most solutions combine several smart technologies into one system to make things run smoothly. These are the key building blocks of AI customer service for insurance, helping companies automate support while keeping a human touch.
Here are the key tools:
AI tool / Tech | What it does | How it helps | Best used for | Tools |
Chatbots & Virtual assistants | Answer questions instantly, 24/7 | Reduce wait times, boost satisfaction | Common customer queries | Intercom, Drift, Ada, Boost.ai |
Voice AI (e.g., Strada) | Handles live calls automatically | Cuts hold times, improves access | Renewals, claims, policy updates | Strada |
Predictive analytics | Uses data to predict next steps | Personalizes offers, reduces churn | Customer retention, upselling | DataRobot, H2O.ai, SAS Predictive Analytics, Google Cloud Vertex AI |
OCR (Optical Character Recognition) | Reads forms and documents | Speeds up claims, reduces manual work | Claims handling | ABBYY FlexiCapture, Amazon Textract, Google Document AI, Kofax |
Sentiment analysis | Detects tone and emotions in messages | Helps respond with empathy | Complaint resolution | MonkeyLearn, AWS Comprehend, Google Cloud Natural Language, IBM Watson Tone Analyzer |
Machine learning | Learns from data patterns | Detects fraud, improves accuracy | Risk management | TensorFlow, PyTorch, Scikit-learn, Azure Machine Learning |
Some companies go even further. For example, Strada’s AI voice agents answer calls, verify who the customer is, start important workflows like opening claim files or scheduling renewals, and update all records instantly, all without needing IT support.
Once you know the tech, it’s easier to see how it transforms big pain points like claims and risk. Let’s explore how AI makes these processes faster and fairer.
How can AI improve claims and risk management?
AI can do a lot more than just answer customer questions in insurance. It helps make the whole claims process faster and easier while managing risks better.
Let’s visualize what a real AI-driven claims process looks like from start to finish.

And let’s see the details.
One big help is with paperwork. AI uses technologies like OCR and AI to quickly read and understand documents such as forms and IDs. This means less manual typing, fewer mistakes, and faster claims processing.
In AI customer service for insurance, claims management becomes proactive – AI predicts issues before customers even reach out. It looks at patterns from many claims to spot anything unusual or suspicious that people might miss. This helps approve real claims quickly and prevent fraud.
AI in insurance customer service doesn’t just handle chats. It transforms entire workflows, from claims to compliance. Risk assessment gets smarter, too. By using data from things like driving habits, wearable devices, and weather, insurers can tailor coverage to each person and predict possible claims.
For example, usage-based insurance changes premiums based on actual behavior, making pricing fairer and more accurate.
Here are a few simple, practical ways AI is already reshaping insurance operations:
Instant claim triage → automatically categorize and route claims based on severity or type.
Smart document handling → extract key details from PDFs, photos, and forms without manual entry.
24/7 virtual assistance → provide customers with accurate answers anytime, across chat, email, or phone.
Proactive policy updates → detect life events or data changes that trigger coverage adjustments.
Fraud detection → flag unusual patterns in claims or customer behavior before payouts.
Personalized risk scoring → combine data from wearables, IoT devices, and driving apps for precise pricing.
Regulatory compliance checks → verify documentation and process steps automatically to meet audit standards.
Dynamic pricing is another way AI helps. It uses data to set insurance rates that match how risky things really are. This helps insurers stay competitive and profitable.
AI also keeps insurers compliant with laws and rules. It monitors interactions and makes sure everything follows regulations like the EU’s AI Act. This lowers legal risks and builds customer trust.
A great example of AI improving customer success is Strada, which now automates the entire claims process from the very first customer interaction. Instead of hours of manual coordination, everything happens in minutes:
Captures First Notice of Loss (FNOL) details automatically over phone or SMS, 24/7, no hold times.
Creates a new claim file instantly in the carrier’s AMS or claims system.
Assigns the right adjuster automatically based on claim type, policy, or location.
Sends required documents to the insured by SMS or email, with full tracking.
Updates CRM and AMS records in real time, syncing every action across systems.
Notifies internal teams (claims, underwriting, service) the moment the file is created.
Launches follow-up workflows like payment reminders or inspection scheduling automatically.
With Strada, what used to take hours of back-and-forth now happens instantly, making claims faster, more accurate, and far less stressful for both customers and teams.
This cuts down manual work from hours to minutes, improving speed and customer happiness.
But AI doesn’t just work behind the scenes. It changes how customers feel. Next, you’ll see how AI creates personal, one-to-one experiences at scale.
How does AI personalize the customer experience?
AI makes insurance customer service smarter and more personal. Instead of just answering questions, AI learns what each customer prefers and responds based on their behavior.
For example, AI uses data from things like driving habits or health trackers to offer personalized policies and prices. This means customers pay fairly and are encouraged to stay safe and healthy.
Chatbots and virtual assistants go further by acting like personal advisors. They help customers find the best policies, compare options, and get answers quickly. Studies show this makes insurance easier to understand and more engaging.
AI also reads how customers feel during chats or calls. If a customer seems frustrated or happy, AI changes its tone to sound more caring or upbeat. This makes the conversation feel more human and builds trust.
Insurers can also use AI to reach out at the right time. If someone might cancel their policy, AI spots this early and sends special offers to keep them. Customers get reminders about their coverage or updates that matter to them.
Strada’s AI takes things even further during renewal calls. It focuses on important customers and offers deals based on what it learns while talking to them. This makes customers feel valued and helps insurers keep their business.
Here’s how AI boosts renewal success:
Prioritizes high-value or at-risk customers automatically.
Suggests personalized offers or discounts in real time.
Detects churn signals and flags accounts for follow-up.
Updates CRM and policy systems instantly after each call.
Tracks renewal outcomes to improve future recommendations.
Overall, AI helps insurers guess what customers need before they ask. From fair pricing to friendly, personalized messages, AI creates faster, smarter, and more caring service.
Personalization is just one piece of the puzzle. AI doesn’t stop at understanding customers. It also takes action behind the scenes, simplifying the everyday tasks that keep policies running smoothly.
How can AI simplify policy servicing and renewals?
Most insurance service calls are about small but important things: updating an address, adding a driver, or checking renewal dates. These tasks take time, but they don’t always need a person to handle them.
AI can now take care of many of these steps automatically, making service faster and easier for everyone.
When a customer calls or texts, AI can verify their policy, make simple changes in the management system, and send confirmation by SMS or email — all in one smooth conversation.
During renewals, AI can remind customers about upcoming dates, answer questions about premium changes, and even alert a human agent if someone seems unsure about renewing.
With platforms like Strada Workflows, every call or message can trigger updates across CRM, billing, and renewal systems automatically. The result: quicker service, fewer missed renewals, and happier customers who feel taken care of.
But great service isn’t only about speed. It’s about staying connected. Once those routine processes are automated, AI helps every conversation stay consistent, no matter where it happens.
How does AI keep communication consistent across channels?
Customers want the same experience no matter how they reach you: phone, chat, text, or email. AI makes that possible by connecting all those channels so the conversation feels continuous and personal.
For example, if someone texts about their policy and later calls, AI remembers the details and continues the conversation where it left off.
No repeating information or waiting for a transfer.
Here’s what that looks like in practice:
Unified history → every interaction is stored and shared across systems.
Accurate answers → AI pulls real data from CRM and policy systems before replying.
Automatic follow-ups → after each call or message, the right next step happens instantly, like sending reminders or creating tasks.
24/7 service → customers can get help anytime, without losing the personal touch.
With platforms like Strada, every interaction stays consistent and on-brand, no matter who reaches out or how they do it.
And here’s how you can start using AI right away.
How to get started with Strada for AI customer service in insurance?
You’ve seen what’s possible with AI. Now let’s make it real. If you’re ready to bring AI insurance customer service to life, here’s a simple step-by-step guide to start using Strada – the voice AI platform built for insurers, MGAs, and brokers.
Strada helps you handle calls, renewals, and claims automatically while keeping every conversation personal and compliant. You don’t need a tech team or months of setup.
You just need a clear plan and a few smart steps.
Step 1 → define your first use case
Start small. Choose one process that slows your team down but repeats every day, like:
Handling renewal calls
Collecting First Notice of Loss (FNOL) details
Answering policy-servicing requests
These are perfect starting points for AI customer service for insurance, because they’re high-volume and rule-based.
Ask yourself: “Where do we waste time repeating the same questions?” That’s your first automation target.
Step 2 → map the conversation
Next, write out how those calls usually go. What do customers ask first? What info do you collect? What happens at the end?
For example: “Hi, I need to update my policy.”
Verify the customer
Check policy details in AMS
Make update or transfer to agent
Strada’s Workflows feature can turn that simple outline into a live, automated conversation. You’ll use a drag-and-drop builder. No coding required.
Tip: Keep the conversation natural. Use short sentences and warm tone, just like a real agent would.
Step 3 → connect your systems
This is where Strada really shines. You can link it directly to your:
CRM (like Salesforce or HubSpot)
AMS or policy systems
Claims or billing platforms
These integrations make Strada more than a chatbot – it becomes a real agentic AI customer service insurance platform that actually completes actions, not just chats.
For example: after a claim call, Strada can:
Create the claim file automatically
Assign the right adjuster
Send follow-up documents
Notify your team, all within minutes
No manual data entry. No missed steps.
Step 4 → automate the follow-ups
Every call ends with tasks.

Strada’s Workflows turn those into instant actions:
A prospect didn’t finish a quote? → Strada schedules a follow-up.
A customer promised to pay later? → It checks the billing system and sends a reminder.
A renewal is at risk? → It alerts your retention team instantly.
This is where you see real value: AI in insurance customer service working in the background so your team can focus on people, not paperwork.
Step 5 → test, train, and go live
Before you launch, test the experience. Strada lets you:
Review call transcripts
Adjust tone and phrasing
Set escalation rules for sensitive topics
Once everything feels right, turn it on. You’ll start getting insights right away: what customers ask, where they hesitate, how long calls take, and which requests need human touch.
Within days, you’ll see faster response times, happier customers, and fewer missed calls.
Step 6 → scale and evolve
After your first success, expand to new workflows: claims follow-up, quote intake, or even certificate issuance.
Because Strada is infinitely scalable and requires no engineering lift, adding new automations is as simple as cloning a workflow and tweaking a few details.
You can keep growing at your own pace, from simple renewals to fully agentic AI customer service insurance operations.
Step 7 → track and improve
Strada comes with built-in analytics that show:
How many calls were handled by AI
Customer satisfaction trends
Cost and time savings
These insights help you refine scripts, retrain AI responses, and keep improving results.

You’ll see measurable ROI from day one: faster calls, higher retention, and happier teams.
And starting with Strada isn’t about replacing people. It’s about helping them do more of what matters.
When your AI handles the busywork, your agents can focus on empathy, relationships, and growth.
You don’t need to plan for months. Pick one use case. Build it. Watch it work.
That’s how AI customer service insurance industry leaders are scaling smarter, one workflow at a time.
Of course, using AI sounds great until you try to make it real. Let’s talk about what stands in the way and how smart insurers overcome those hurdles.
What are the challenges and best practices for AI adoption in insurance customer service?
AI can greatly improve insurance customer service, but companies face some key challenges when adopting it. Modern AI tools can speed up support and claims, but insurers need to handle these issues carefully to succeed.
Here’s a quick cheat sheet to guide you.
Challenge | What happens | Smart fix | Why it works |
Low customer trust | People don’t feel comfortable with AI decisions | Be transparent: explain how AI helps and when humans step in | Builds confidence and loyalty |
Poor data quality | AI gives wrong or incomplete results | Clean and unify data before using it | Improves accuracy and reliability |
Regulatory pressure | Rules like the EU AI Act add complexity | Use explainable, auditable AI systems | Keeps you compliant and protected |
Employee resistance | Staff fear AI might replace them | Train teams to use AI as a tool, not a threat | Boosts teamwork and adoption |
Integration issues | Systems don’t “talk” to each other | Pick AI that connects with CRMs and claims systems | Saves setup time and avoids errors |
After tackling the challenges, the next question is simple: is it worth it? Here’s how insurers track the real value and impact of their AI efforts.
How do insurers measure the ROI and effectiveness of AI customer service solutions?
Insurers want to know if AI really helps their customer service. And measuring AI customer service insurance performance means tracking what customers actually feel, not just what the system reports.
Here’s how insurers track what matters and spot real improvements.
Metric | What it means | Why it matters | Good benchmark |
Average Handling Time (AHT) | Time to resolve a customer issue | Shows efficiency | Under 3 minutes |
First Contact Resolution (FCR) | Issues solved on first interaction | Reflects AI accuracy and ease | 80%+ |
Customer Satisfaction (CSAT) | How happy customers feel | Indicates overall experience | 90%+ |
Net Promoter Score (NPS) | Likelihood customers recommend you | Measures loyalty | 50+ |
Chatbot containment rate | % of queries solved by AI alone | Measures automation success | 60–70% |
Cost per interaction | Average cost per customer touchpoint | Shows ROI impact | 30–50% lower than human-only service |
Special AI tools like Cognizant Insights or EMA dashboards help insurers watch these numbers live. They also track AI-specific stats like how often chatbots handle questions without needing a human (called chatbot containment rate) and how much work AI does on its own, reducing the need for human help.
Here are a few more metrics that are important:
Chatbot containment rate → how many queries are solved without escalation.
Average handling time → how quickly AI resolves customer requests.
AI accuracy rate → how often answers are correct and relevant.
Deflection rate → how much workload AI removes from human agents.
Resolution quality → how often AI fully completes a task versus partial help.
Adoption rate → how frequently staff and customers use AI tools.
Based on them insurers test different AI setups with A/B testing to find what works best, using customer feedback to keep improving answers and insurance workflows. This means AI keeps getting smarter and more helpful over time.
Another big factor is cost savings. Automating simple tasks like claims processing and fraud checks cuts down on labor costs and mistakes.
Tools like Strada dashboards show important data like call answering rates over 85%, savings from shorter wait times, around-the-clock service, and how automating work lowers expenses.
But numbers alone aren’t enough. Let’s make sure those results come responsibly, with trust, transparency, and strong data protection.
How to ensure ethical AI use and data privacy in insurance customer service?
Using AI in insurance customer service can improve efficiency, but it’s important to do it the right way. AI platforms must be transparent, fair, and avoid bias, following rules like the EU’s AI Act and the US’s CCPA.
To protect customer data, follow these simple steps:
Remove personal details from data so customers stay anonymous.
Always get clear permission before using anyone’s data.
Store data securely using strong encryption and limited access.
Use tools that show how AI makes decisions, like IBM AI Explainability 360, so you can track and understand AI actions. Always have humans check AI decisions and fix mistakes quickly, especially when decisions affect customers deeply.
Work closely with legal, compliance, and data teams to keep all AI use trustworthy and within laws.
Strada supports ethical AI with strong security measures such as: SOC 2 Type 2 certification, keeping each customer’s data separate, never reusing training data, and regular security tests by outside experts.
These steps help make sure AI-driven customer service is safe, fair, and reliable while still working efficiently.
Once you’ve built ethical foundations, you can start tailoring AI to fit your business. Here’s how insurers customize solutions for their unique needs.
What customization options exist for AI solutions in insurance customer service?
Insurers today can customize AI tools to fit their specific needs, making customer service smarter and more efficient. Modern AI platforms are flexible, letting companies adjust workflows, conversations, and system connections to match their business goals and brand style.
There are two main types of AI platforms: white-label and off-the-shelf.
White-label solutions, like custom EMA integrations, let insurers build AI tailored to their unique processes.
Off-the-shelf tools, like Lemonade’s chatbot, offer ready-to-use features but are less flexible.
Between these two extremes, low-code or no-code workflow builders, such as Beam.ai’s Generative Workflow Engine (GWE), allow insurers to create and change AI workflows without heavy technical work. This makes it easier to update AI for new tasks or rules quickly.
As insurers expand globally, multilingual and regional language support is important. AI can speak customers’ languages naturally, improving communication in different markets. Also, AI’s tone and personality can be customized to match the insurer’s brand, creating a consistent and friendly experience.
Finally, none of this works in isolation. Integration with other systems is key. Top AI platforms connect smoothly with CRMs like HubSpot and Salesforce, as well as claims and policy systems. This helps share data and automate tasks across channels seamlessly.
Platforms like Strada are paving the way for agentic AI customer service insurance, where systems can act intelligently and independently within safe limits.
What agentic AI can do now:
Trigger smart workflows instantly → turn every call outcome (like a quote, claim, or payment promise) into real business actions across CRM, AMS, or policy systems.
Connect seamlessly across platforms → use deep integrations with tools like Salesforce, Duck Creek, or custom APIs to keep data synced without manual effort.
Follow intelligent rules → automate responses and next steps based on customer intent, policy details, or risk level; no coding required.
Act in real time → update records, send reminders, issue certificates, or schedule follow-ups the moment a conversation ends.
Ensure compliance and trust → operate within defined guardrails: secure data isolation, SOC 2 controls, and no model cross-training.
Scale automatically → handle thousands of calls and follow-ups with zero engineering lift, growing capacity as your business grows.
Learn from interactions → capture insights from every call to improve workflows, detect churn risks, and optimize future automations.
Its AI voice agents understand insurance terms and can handle tasks like taking calls, scheduling policy renewals, routing claims, and triggering downstream actions. Insurers can easily set rules and automate complex processes using Strada Workflows.
Customization is just the beginning. After seeing how AI is changing insurance service today, the next step is for insurers to start using these ideas in real life.
How will you lead the future of AI in insurance?
AI is changing insurance customer service in big ways.
It helps automate claims, personalize how customers are treated, support agents, and create smarter workflows. Using AI in insurance customer service is no longer just a nice-to-have; it’s a must for insurers who want to stay competitive, keep customers happy, and work more efficiently.
To succeed, insurers should build strong data systems, combine human skills with AI, and pick reliable AI tools that meet both performance and safety standards. Platforms like Strada offer easy-to-use solutions that handle insurance calls, automate tasks quickly, and deliver real business results with top-level security.
And these platforms make it super-easy to take your first step into AI-powered customer service.
You don’t need to rebuild your systems or hire a tech team – Strada connects with what you already use and helps you handle calls, renewals, and claims automatically, while keeping a real human tone.
Think of it as your always-on teammate: one that learns from every interaction, gets smarter over time, and gives your team more space to focus on what really matters – helping people.
If you’re ready to see how AI insurance customer service can feel effortless, Strada’s platform is a great place to start learning, testing, and growing.
Book a quick demo to see how it works in action and discover how it fits your business.
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AI in Insurance Customer Service: A Complete Guide for 2025

Amir Prodensky
CEO
Nov 7, 2025
11 min read
How to deploy AI tools that solve customer issues faster and more accurately.
Not long ago, getting help from your insurance company meant waiting on hold, explaining your issue three times, and hoping someone could find your policy.
Today, that’s changing fast. AI is quietly reshaping customer service, turning long calls and confusing emails into instant, personalized conversations.
This shift isn’t a fad anymore; it’s becoming the norm.
Insurance teams need to move faster, reduce costs, and still deliver great experiences. AI makes that possible by speeding up responses, learning from every interaction, and helping smaller teams do more with less.
In this guide, you’ll see how companies like Strada, Lemonade, Ema, Kustomer, Beam.ai, and Cognizant are transforming support with real examples. You’ll also learn how Strada’s AI phone agent platform helps carriers, MGAs, and brokers handle more calls and boost revenue, all while keeping the human touch that customers trust.
Let’s explore how AI is making insurance simpler, friendlier, and a lot less stressful.
How is AI changing customer service in insurance?
AI is making insurance customer service faster, easier, and more accurate.
Instead of waiting on hold for a human agent, customers can now get instant help from AI-powered chatbots, virtual assistants, and automated systems that work 24/7. These tools quickly answer questions, handle claims, and direct requests without delays.
Before diving in, let’s see the big picture of how AI changes the entire customer journey, from the first question to claim settlement.

For example, platforms like Strada, EMA, Kustomer, and Beam.ai provide continuous support across websites, apps, and messaging, delivering consistent, mistake-free service anytime.
AI also helps reduce errors. It checks claim details immediately and spots mistakes that humans might miss. This boosts accuracy and speeds up processing.
Voice AI is another big change. Strada offers AI phone agents that handle calls instantly, with no waiting. They can help with renewals, claims, and policy questions around the clock.
This means customers never get stuck on hold, and insurers get more calls answered, even outside normal hours.
Here’s a quick look at the top AI tools in insurance customer service:
Strada → voice and SMS with zero-hold live call support
Lemonade → chatbot that processes claims in 2 seconds
EMA → chat plus automation for nonstop workflow handling
Kustomer → chat with AI help for human agents
Beam.ai → smart chat that routes claims efficiently
Together, these tools show how AI insurance customer service makes support faster, more accurate, and easier to access 24/7.
Now that you know how AI is reshaping insurance service, let’s look at the tools making it happen in more detail. You’ll see what insurers are actually using on the ground.
What AI tools and tech are insurers using today?
Let’s break down the main AI tools that insurance companies use to improve customer service.
Most solutions combine several smart technologies into one system to make things run smoothly. These are the key building blocks of AI customer service for insurance, helping companies automate support while keeping a human touch.
Here are the key tools:
AI tool / Tech | What it does | How it helps | Best used for | Tools |
Chatbots & Virtual assistants | Answer questions instantly, 24/7 | Reduce wait times, boost satisfaction | Common customer queries | Intercom, Drift, Ada, Boost.ai |
Voice AI (e.g., Strada) | Handles live calls automatically | Cuts hold times, improves access | Renewals, claims, policy updates | Strada |
Predictive analytics | Uses data to predict next steps | Personalizes offers, reduces churn | Customer retention, upselling | DataRobot, H2O.ai, SAS Predictive Analytics, Google Cloud Vertex AI |
OCR (Optical Character Recognition) | Reads forms and documents | Speeds up claims, reduces manual work | Claims handling | ABBYY FlexiCapture, Amazon Textract, Google Document AI, Kofax |
Sentiment analysis | Detects tone and emotions in messages | Helps respond with empathy | Complaint resolution | MonkeyLearn, AWS Comprehend, Google Cloud Natural Language, IBM Watson Tone Analyzer |
Machine learning | Learns from data patterns | Detects fraud, improves accuracy | Risk management | TensorFlow, PyTorch, Scikit-learn, Azure Machine Learning |
Some companies go even further. For example, Strada’s AI voice agents answer calls, verify who the customer is, start important workflows like opening claim files or scheduling renewals, and update all records instantly, all without needing IT support.
Once you know the tech, it’s easier to see how it transforms big pain points like claims and risk. Let’s explore how AI makes these processes faster and fairer.
How can AI improve claims and risk management?
AI can do a lot more than just answer customer questions in insurance. It helps make the whole claims process faster and easier while managing risks better.
Let’s visualize what a real AI-driven claims process looks like from start to finish.

And let’s see the details.
One big help is with paperwork. AI uses technologies like OCR and AI to quickly read and understand documents such as forms and IDs. This means less manual typing, fewer mistakes, and faster claims processing.
In AI customer service for insurance, claims management becomes proactive – AI predicts issues before customers even reach out. It looks at patterns from many claims to spot anything unusual or suspicious that people might miss. This helps approve real claims quickly and prevent fraud.
AI in insurance customer service doesn’t just handle chats. It transforms entire workflows, from claims to compliance. Risk assessment gets smarter, too. By using data from things like driving habits, wearable devices, and weather, insurers can tailor coverage to each person and predict possible claims.
For example, usage-based insurance changes premiums based on actual behavior, making pricing fairer and more accurate.
Here are a few simple, practical ways AI is already reshaping insurance operations:
Instant claim triage → automatically categorize and route claims based on severity or type.
Smart document handling → extract key details from PDFs, photos, and forms without manual entry.
24/7 virtual assistance → provide customers with accurate answers anytime, across chat, email, or phone.
Proactive policy updates → detect life events or data changes that trigger coverage adjustments.
Fraud detection → flag unusual patterns in claims or customer behavior before payouts.
Personalized risk scoring → combine data from wearables, IoT devices, and driving apps for precise pricing.
Regulatory compliance checks → verify documentation and process steps automatically to meet audit standards.
Dynamic pricing is another way AI helps. It uses data to set insurance rates that match how risky things really are. This helps insurers stay competitive and profitable.
AI also keeps insurers compliant with laws and rules. It monitors interactions and makes sure everything follows regulations like the EU’s AI Act. This lowers legal risks and builds customer trust.
A great example of AI improving customer success is Strada, which now automates the entire claims process from the very first customer interaction. Instead of hours of manual coordination, everything happens in minutes:
Captures First Notice of Loss (FNOL) details automatically over phone or SMS, 24/7, no hold times.
Creates a new claim file instantly in the carrier’s AMS or claims system.
Assigns the right adjuster automatically based on claim type, policy, or location.
Sends required documents to the insured by SMS or email, with full tracking.
Updates CRM and AMS records in real time, syncing every action across systems.
Notifies internal teams (claims, underwriting, service) the moment the file is created.
Launches follow-up workflows like payment reminders or inspection scheduling automatically.
With Strada, what used to take hours of back-and-forth now happens instantly, making claims faster, more accurate, and far less stressful for both customers and teams.
This cuts down manual work from hours to minutes, improving speed and customer happiness.
But AI doesn’t just work behind the scenes. It changes how customers feel. Next, you’ll see how AI creates personal, one-to-one experiences at scale.
How does AI personalize the customer experience?
AI makes insurance customer service smarter and more personal. Instead of just answering questions, AI learns what each customer prefers and responds based on their behavior.
For example, AI uses data from things like driving habits or health trackers to offer personalized policies and prices. This means customers pay fairly and are encouraged to stay safe and healthy.
Chatbots and virtual assistants go further by acting like personal advisors. They help customers find the best policies, compare options, and get answers quickly. Studies show this makes insurance easier to understand and more engaging.
AI also reads how customers feel during chats or calls. If a customer seems frustrated or happy, AI changes its tone to sound more caring or upbeat. This makes the conversation feel more human and builds trust.
Insurers can also use AI to reach out at the right time. If someone might cancel their policy, AI spots this early and sends special offers to keep them. Customers get reminders about their coverage or updates that matter to them.
Strada’s AI takes things even further during renewal calls. It focuses on important customers and offers deals based on what it learns while talking to them. This makes customers feel valued and helps insurers keep their business.
Here’s how AI boosts renewal success:
Prioritizes high-value or at-risk customers automatically.
Suggests personalized offers or discounts in real time.
Detects churn signals and flags accounts for follow-up.
Updates CRM and policy systems instantly after each call.
Tracks renewal outcomes to improve future recommendations.
Overall, AI helps insurers guess what customers need before they ask. From fair pricing to friendly, personalized messages, AI creates faster, smarter, and more caring service.
Personalization is just one piece of the puzzle. AI doesn’t stop at understanding customers. It also takes action behind the scenes, simplifying the everyday tasks that keep policies running smoothly.
How can AI simplify policy servicing and renewals?
Most insurance service calls are about small but important things: updating an address, adding a driver, or checking renewal dates. These tasks take time, but they don’t always need a person to handle them.
AI can now take care of many of these steps automatically, making service faster and easier for everyone.
When a customer calls or texts, AI can verify their policy, make simple changes in the management system, and send confirmation by SMS or email — all in one smooth conversation.
During renewals, AI can remind customers about upcoming dates, answer questions about premium changes, and even alert a human agent if someone seems unsure about renewing.
With platforms like Strada Workflows, every call or message can trigger updates across CRM, billing, and renewal systems automatically. The result: quicker service, fewer missed renewals, and happier customers who feel taken care of.
But great service isn’t only about speed. It’s about staying connected. Once those routine processes are automated, AI helps every conversation stay consistent, no matter where it happens.
How does AI keep communication consistent across channels?
Customers want the same experience no matter how they reach you: phone, chat, text, or email. AI makes that possible by connecting all those channels so the conversation feels continuous and personal.
For example, if someone texts about their policy and later calls, AI remembers the details and continues the conversation where it left off.
No repeating information or waiting for a transfer.
Here’s what that looks like in practice:
Unified history → every interaction is stored and shared across systems.
Accurate answers → AI pulls real data from CRM and policy systems before replying.
Automatic follow-ups → after each call or message, the right next step happens instantly, like sending reminders or creating tasks.
24/7 service → customers can get help anytime, without losing the personal touch.
With platforms like Strada, every interaction stays consistent and on-brand, no matter who reaches out or how they do it.
And here’s how you can start using AI right away.
How to get started with Strada for AI customer service in insurance?
You’ve seen what’s possible with AI. Now let’s make it real. If you’re ready to bring AI insurance customer service to life, here’s a simple step-by-step guide to start using Strada – the voice AI platform built for insurers, MGAs, and brokers.
Strada helps you handle calls, renewals, and claims automatically while keeping every conversation personal and compliant. You don’t need a tech team or months of setup.
You just need a clear plan and a few smart steps.
Step 1 → define your first use case
Start small. Choose one process that slows your team down but repeats every day, like:
Handling renewal calls
Collecting First Notice of Loss (FNOL) details
Answering policy-servicing requests
These are perfect starting points for AI customer service for insurance, because they’re high-volume and rule-based.
Ask yourself: “Where do we waste time repeating the same questions?” That’s your first automation target.
Step 2 → map the conversation
Next, write out how those calls usually go. What do customers ask first? What info do you collect? What happens at the end?
For example: “Hi, I need to update my policy.”
Verify the customer
Check policy details in AMS
Make update or transfer to agent
Strada’s Workflows feature can turn that simple outline into a live, automated conversation. You’ll use a drag-and-drop builder. No coding required.
Tip: Keep the conversation natural. Use short sentences and warm tone, just like a real agent would.
Step 3 → connect your systems
This is where Strada really shines. You can link it directly to your:
CRM (like Salesforce or HubSpot)
AMS or policy systems
Claims or billing platforms
These integrations make Strada more than a chatbot – it becomes a real agentic AI customer service insurance platform that actually completes actions, not just chats.
For example: after a claim call, Strada can:
Create the claim file automatically
Assign the right adjuster
Send follow-up documents
Notify your team, all within minutes
No manual data entry. No missed steps.
Step 4 → automate the follow-ups
Every call ends with tasks.

Strada’s Workflows turn those into instant actions:
A prospect didn’t finish a quote? → Strada schedules a follow-up.
A customer promised to pay later? → It checks the billing system and sends a reminder.
A renewal is at risk? → It alerts your retention team instantly.
This is where you see real value: AI in insurance customer service working in the background so your team can focus on people, not paperwork.
Step 5 → test, train, and go live
Before you launch, test the experience. Strada lets you:
Review call transcripts
Adjust tone and phrasing
Set escalation rules for sensitive topics
Once everything feels right, turn it on. You’ll start getting insights right away: what customers ask, where they hesitate, how long calls take, and which requests need human touch.
Within days, you’ll see faster response times, happier customers, and fewer missed calls.
Step 6 → scale and evolve
After your first success, expand to new workflows: claims follow-up, quote intake, or even certificate issuance.
Because Strada is infinitely scalable and requires no engineering lift, adding new automations is as simple as cloning a workflow and tweaking a few details.
You can keep growing at your own pace, from simple renewals to fully agentic AI customer service insurance operations.
Step 7 → track and improve
Strada comes with built-in analytics that show:
How many calls were handled by AI
Customer satisfaction trends
Cost and time savings
These insights help you refine scripts, retrain AI responses, and keep improving results.

You’ll see measurable ROI from day one: faster calls, higher retention, and happier teams.
And starting with Strada isn’t about replacing people. It’s about helping them do more of what matters.
When your AI handles the busywork, your agents can focus on empathy, relationships, and growth.
You don’t need to plan for months. Pick one use case. Build it. Watch it work.
That’s how AI customer service insurance industry leaders are scaling smarter, one workflow at a time.
Of course, using AI sounds great until you try to make it real. Let’s talk about what stands in the way and how smart insurers overcome those hurdles.
What are the challenges and best practices for AI adoption in insurance customer service?
AI can greatly improve insurance customer service, but companies face some key challenges when adopting it. Modern AI tools can speed up support and claims, but insurers need to handle these issues carefully to succeed.
Here’s a quick cheat sheet to guide you.
Challenge | What happens | Smart fix | Why it works |
Low customer trust | People don’t feel comfortable with AI decisions | Be transparent: explain how AI helps and when humans step in | Builds confidence and loyalty |
Poor data quality | AI gives wrong or incomplete results | Clean and unify data before using it | Improves accuracy and reliability |
Regulatory pressure | Rules like the EU AI Act add complexity | Use explainable, auditable AI systems | Keeps you compliant and protected |
Employee resistance | Staff fear AI might replace them | Train teams to use AI as a tool, not a threat | Boosts teamwork and adoption |
Integration issues | Systems don’t “talk” to each other | Pick AI that connects with CRMs and claims systems | Saves setup time and avoids errors |
After tackling the challenges, the next question is simple: is it worth it? Here’s how insurers track the real value and impact of their AI efforts.
How do insurers measure the ROI and effectiveness of AI customer service solutions?
Insurers want to know if AI really helps their customer service. And measuring AI customer service insurance performance means tracking what customers actually feel, not just what the system reports.
Here’s how insurers track what matters and spot real improvements.
Metric | What it means | Why it matters | Good benchmark |
Average Handling Time (AHT) | Time to resolve a customer issue | Shows efficiency | Under 3 minutes |
First Contact Resolution (FCR) | Issues solved on first interaction | Reflects AI accuracy and ease | 80%+ |
Customer Satisfaction (CSAT) | How happy customers feel | Indicates overall experience | 90%+ |
Net Promoter Score (NPS) | Likelihood customers recommend you | Measures loyalty | 50+ |
Chatbot containment rate | % of queries solved by AI alone | Measures automation success | 60–70% |
Cost per interaction | Average cost per customer touchpoint | Shows ROI impact | 30–50% lower than human-only service |
Special AI tools like Cognizant Insights or EMA dashboards help insurers watch these numbers live. They also track AI-specific stats like how often chatbots handle questions without needing a human (called chatbot containment rate) and how much work AI does on its own, reducing the need for human help.
Here are a few more metrics that are important:
Chatbot containment rate → how many queries are solved without escalation.
Average handling time → how quickly AI resolves customer requests.
AI accuracy rate → how often answers are correct and relevant.
Deflection rate → how much workload AI removes from human agents.
Resolution quality → how often AI fully completes a task versus partial help.
Adoption rate → how frequently staff and customers use AI tools.
Based on them insurers test different AI setups with A/B testing to find what works best, using customer feedback to keep improving answers and insurance workflows. This means AI keeps getting smarter and more helpful over time.
Another big factor is cost savings. Automating simple tasks like claims processing and fraud checks cuts down on labor costs and mistakes.
Tools like Strada dashboards show important data like call answering rates over 85%, savings from shorter wait times, around-the-clock service, and how automating work lowers expenses.
But numbers alone aren’t enough. Let’s make sure those results come responsibly, with trust, transparency, and strong data protection.
How to ensure ethical AI use and data privacy in insurance customer service?
Using AI in insurance customer service can improve efficiency, but it’s important to do it the right way. AI platforms must be transparent, fair, and avoid bias, following rules like the EU’s AI Act and the US’s CCPA.
To protect customer data, follow these simple steps:
Remove personal details from data so customers stay anonymous.
Always get clear permission before using anyone’s data.
Store data securely using strong encryption and limited access.
Use tools that show how AI makes decisions, like IBM AI Explainability 360, so you can track and understand AI actions. Always have humans check AI decisions and fix mistakes quickly, especially when decisions affect customers deeply.
Work closely with legal, compliance, and data teams to keep all AI use trustworthy and within laws.
Strada supports ethical AI with strong security measures such as: SOC 2 Type 2 certification, keeping each customer’s data separate, never reusing training data, and regular security tests by outside experts.
These steps help make sure AI-driven customer service is safe, fair, and reliable while still working efficiently.
Once you’ve built ethical foundations, you can start tailoring AI to fit your business. Here’s how insurers customize solutions for their unique needs.
What customization options exist for AI solutions in insurance customer service?
Insurers today can customize AI tools to fit their specific needs, making customer service smarter and more efficient. Modern AI platforms are flexible, letting companies adjust workflows, conversations, and system connections to match their business goals and brand style.
There are two main types of AI platforms: white-label and off-the-shelf.
White-label solutions, like custom EMA integrations, let insurers build AI tailored to their unique processes.
Off-the-shelf tools, like Lemonade’s chatbot, offer ready-to-use features but are less flexible.
Between these two extremes, low-code or no-code workflow builders, such as Beam.ai’s Generative Workflow Engine (GWE), allow insurers to create and change AI workflows without heavy technical work. This makes it easier to update AI for new tasks or rules quickly.
As insurers expand globally, multilingual and regional language support is important. AI can speak customers’ languages naturally, improving communication in different markets. Also, AI’s tone and personality can be customized to match the insurer’s brand, creating a consistent and friendly experience.
Finally, none of this works in isolation. Integration with other systems is key. Top AI platforms connect smoothly with CRMs like HubSpot and Salesforce, as well as claims and policy systems. This helps share data and automate tasks across channels seamlessly.
Platforms like Strada are paving the way for agentic AI customer service insurance, where systems can act intelligently and independently within safe limits.
What agentic AI can do now:
Trigger smart workflows instantly → turn every call outcome (like a quote, claim, or payment promise) into real business actions across CRM, AMS, or policy systems.
Connect seamlessly across platforms → use deep integrations with tools like Salesforce, Duck Creek, or custom APIs to keep data synced without manual effort.
Follow intelligent rules → automate responses and next steps based on customer intent, policy details, or risk level; no coding required.
Act in real time → update records, send reminders, issue certificates, or schedule follow-ups the moment a conversation ends.
Ensure compliance and trust → operate within defined guardrails: secure data isolation, SOC 2 controls, and no model cross-training.
Scale automatically → handle thousands of calls and follow-ups with zero engineering lift, growing capacity as your business grows.
Learn from interactions → capture insights from every call to improve workflows, detect churn risks, and optimize future automations.
Its AI voice agents understand insurance terms and can handle tasks like taking calls, scheduling policy renewals, routing claims, and triggering downstream actions. Insurers can easily set rules and automate complex processes using Strada Workflows.
Customization is just the beginning. After seeing how AI is changing insurance service today, the next step is for insurers to start using these ideas in real life.
How will you lead the future of AI in insurance?
AI is changing insurance customer service in big ways.
It helps automate claims, personalize how customers are treated, support agents, and create smarter workflows. Using AI in insurance customer service is no longer just a nice-to-have; it’s a must for insurers who want to stay competitive, keep customers happy, and work more efficiently.
To succeed, insurers should build strong data systems, combine human skills with AI, and pick reliable AI tools that meet both performance and safety standards. Platforms like Strada offer easy-to-use solutions that handle insurance calls, automate tasks quickly, and deliver real business results with top-level security.
And these platforms make it super-easy to take your first step into AI-powered customer service.
You don’t need to rebuild your systems or hire a tech team – Strada connects with what you already use and helps you handle calls, renewals, and claims automatically, while keeping a real human tone.
Think of it as your always-on teammate: one that learns from every interaction, gets smarter over time, and gives your team more space to focus on what really matters – helping people.
If you’re ready to see how AI insurance customer service can feel effortless, Strada’s platform is a great place to start learning, testing, and growing.
Book a quick demo to see how it works in action and discover how it fits your business.
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AI in Insurance Customer Service: A Complete Guide for 2025

Amir Prodensky
CEO
Nov 7, 2025
11 min read
How to deploy AI tools that solve customer issues faster and more accurately.
Not long ago, getting help from your insurance company meant waiting on hold, explaining your issue three times, and hoping someone could find your policy.
Today, that’s changing fast. AI is quietly reshaping customer service, turning long calls and confusing emails into instant, personalized conversations.
This shift isn’t a fad anymore; it’s becoming the norm.
Insurance teams need to move faster, reduce costs, and still deliver great experiences. AI makes that possible by speeding up responses, learning from every interaction, and helping smaller teams do more with less.
In this guide, you’ll see how companies like Strada, Lemonade, Ema, Kustomer, Beam.ai, and Cognizant are transforming support with real examples. You’ll also learn how Strada’s AI phone agent platform helps carriers, MGAs, and brokers handle more calls and boost revenue, all while keeping the human touch that customers trust.
Let’s explore how AI is making insurance simpler, friendlier, and a lot less stressful.
How is AI changing customer service in insurance?
AI is making insurance customer service faster, easier, and more accurate.
Instead of waiting on hold for a human agent, customers can now get instant help from AI-powered chatbots, virtual assistants, and automated systems that work 24/7. These tools quickly answer questions, handle claims, and direct requests without delays.
Before diving in, let’s see the big picture of how AI changes the entire customer journey, from the first question to claim settlement.

For example, platforms like Strada, EMA, Kustomer, and Beam.ai provide continuous support across websites, apps, and messaging, delivering consistent, mistake-free service anytime.
AI also helps reduce errors. It checks claim details immediately and spots mistakes that humans might miss. This boosts accuracy and speeds up processing.
Voice AI is another big change. Strada offers AI phone agents that handle calls instantly, with no waiting. They can help with renewals, claims, and policy questions around the clock.
This means customers never get stuck on hold, and insurers get more calls answered, even outside normal hours.
Here’s a quick look at the top AI tools in insurance customer service:
Strada → voice and SMS with zero-hold live call support
Lemonade → chatbot that processes claims in 2 seconds
EMA → chat plus automation for nonstop workflow handling
Kustomer → chat with AI help for human agents
Beam.ai → smart chat that routes claims efficiently
Together, these tools show how AI insurance customer service makes support faster, more accurate, and easier to access 24/7.
Now that you know how AI is reshaping insurance service, let’s look at the tools making it happen in more detail. You’ll see what insurers are actually using on the ground.
What AI tools and tech are insurers using today?
Let’s break down the main AI tools that insurance companies use to improve customer service.
Most solutions combine several smart technologies into one system to make things run smoothly. These are the key building blocks of AI customer service for insurance, helping companies automate support while keeping a human touch.
Here are the key tools:
AI tool / Tech | What it does | How it helps | Best used for | Tools |
Chatbots & Virtual assistants | Answer questions instantly, 24/7 | Reduce wait times, boost satisfaction | Common customer queries | Intercom, Drift, Ada, Boost.ai |
Voice AI (e.g., Strada) | Handles live calls automatically | Cuts hold times, improves access | Renewals, claims, policy updates | Strada |
Predictive analytics | Uses data to predict next steps | Personalizes offers, reduces churn | Customer retention, upselling | DataRobot, H2O.ai, SAS Predictive Analytics, Google Cloud Vertex AI |
OCR (Optical Character Recognition) | Reads forms and documents | Speeds up claims, reduces manual work | Claims handling | ABBYY FlexiCapture, Amazon Textract, Google Document AI, Kofax |
Sentiment analysis | Detects tone and emotions in messages | Helps respond with empathy | Complaint resolution | MonkeyLearn, AWS Comprehend, Google Cloud Natural Language, IBM Watson Tone Analyzer |
Machine learning | Learns from data patterns | Detects fraud, improves accuracy | Risk management | TensorFlow, PyTorch, Scikit-learn, Azure Machine Learning |
Some companies go even further. For example, Strada’s AI voice agents answer calls, verify who the customer is, start important workflows like opening claim files or scheduling renewals, and update all records instantly, all without needing IT support.
Once you know the tech, it’s easier to see how it transforms big pain points like claims and risk. Let’s explore how AI makes these processes faster and fairer.
How can AI improve claims and risk management?
AI can do a lot more than just answer customer questions in insurance. It helps make the whole claims process faster and easier while managing risks better.
Let’s visualize what a real AI-driven claims process looks like from start to finish.

And let’s see the details.
One big help is with paperwork. AI uses technologies like OCR and AI to quickly read and understand documents such as forms and IDs. This means less manual typing, fewer mistakes, and faster claims processing.
In AI customer service for insurance, claims management becomes proactive – AI predicts issues before customers even reach out. It looks at patterns from many claims to spot anything unusual or suspicious that people might miss. This helps approve real claims quickly and prevent fraud.
AI in insurance customer service doesn’t just handle chats. It transforms entire workflows, from claims to compliance. Risk assessment gets smarter, too. By using data from things like driving habits, wearable devices, and weather, insurers can tailor coverage to each person and predict possible claims.
For example, usage-based insurance changes premiums based on actual behavior, making pricing fairer and more accurate.
Here are a few simple, practical ways AI is already reshaping insurance operations:
Instant claim triage → automatically categorize and route claims based on severity or type.
Smart document handling → extract key details from PDFs, photos, and forms without manual entry.
24/7 virtual assistance → provide customers with accurate answers anytime, across chat, email, or phone.
Proactive policy updates → detect life events or data changes that trigger coverage adjustments.
Fraud detection → flag unusual patterns in claims or customer behavior before payouts.
Personalized risk scoring → combine data from wearables, IoT devices, and driving apps for precise pricing.
Regulatory compliance checks → verify documentation and process steps automatically to meet audit standards.
Dynamic pricing is another way AI helps. It uses data to set insurance rates that match how risky things really are. This helps insurers stay competitive and profitable.
AI also keeps insurers compliant with laws and rules. It monitors interactions and makes sure everything follows regulations like the EU’s AI Act. This lowers legal risks and builds customer trust.
A great example of AI improving customer success is Strada, which now automates the entire claims process from the very first customer interaction. Instead of hours of manual coordination, everything happens in minutes:
Captures First Notice of Loss (FNOL) details automatically over phone or SMS, 24/7, no hold times.
Creates a new claim file instantly in the carrier’s AMS or claims system.
Assigns the right adjuster automatically based on claim type, policy, or location.
Sends required documents to the insured by SMS or email, with full tracking.
Updates CRM and AMS records in real time, syncing every action across systems.
Notifies internal teams (claims, underwriting, service) the moment the file is created.
Launches follow-up workflows like payment reminders or inspection scheduling automatically.
With Strada, what used to take hours of back-and-forth now happens instantly, making claims faster, more accurate, and far less stressful for both customers and teams.
This cuts down manual work from hours to minutes, improving speed and customer happiness.
But AI doesn’t just work behind the scenes. It changes how customers feel. Next, you’ll see how AI creates personal, one-to-one experiences at scale.
How does AI personalize the customer experience?
AI makes insurance customer service smarter and more personal. Instead of just answering questions, AI learns what each customer prefers and responds based on their behavior.
For example, AI uses data from things like driving habits or health trackers to offer personalized policies and prices. This means customers pay fairly and are encouraged to stay safe and healthy.
Chatbots and virtual assistants go further by acting like personal advisors. They help customers find the best policies, compare options, and get answers quickly. Studies show this makes insurance easier to understand and more engaging.
AI also reads how customers feel during chats or calls. If a customer seems frustrated or happy, AI changes its tone to sound more caring or upbeat. This makes the conversation feel more human and builds trust.
Insurers can also use AI to reach out at the right time. If someone might cancel their policy, AI spots this early and sends special offers to keep them. Customers get reminders about their coverage or updates that matter to them.
Strada’s AI takes things even further during renewal calls. It focuses on important customers and offers deals based on what it learns while talking to them. This makes customers feel valued and helps insurers keep their business.
Here’s how AI boosts renewal success:
Prioritizes high-value or at-risk customers automatically.
Suggests personalized offers or discounts in real time.
Detects churn signals and flags accounts for follow-up.
Updates CRM and policy systems instantly after each call.
Tracks renewal outcomes to improve future recommendations.
Overall, AI helps insurers guess what customers need before they ask. From fair pricing to friendly, personalized messages, AI creates faster, smarter, and more caring service.
Personalization is just one piece of the puzzle. AI doesn’t stop at understanding customers. It also takes action behind the scenes, simplifying the everyday tasks that keep policies running smoothly.
How can AI simplify policy servicing and renewals?
Most insurance service calls are about small but important things: updating an address, adding a driver, or checking renewal dates. These tasks take time, but they don’t always need a person to handle them.
AI can now take care of many of these steps automatically, making service faster and easier for everyone.
When a customer calls or texts, AI can verify their policy, make simple changes in the management system, and send confirmation by SMS or email — all in one smooth conversation.
During renewals, AI can remind customers about upcoming dates, answer questions about premium changes, and even alert a human agent if someone seems unsure about renewing.
With platforms like Strada Workflows, every call or message can trigger updates across CRM, billing, and renewal systems automatically. The result: quicker service, fewer missed renewals, and happier customers who feel taken care of.
But great service isn’t only about speed. It’s about staying connected. Once those routine processes are automated, AI helps every conversation stay consistent, no matter where it happens.
How does AI keep communication consistent across channels?
Customers want the same experience no matter how they reach you: phone, chat, text, or email. AI makes that possible by connecting all those channels so the conversation feels continuous and personal.
For example, if someone texts about their policy and later calls, AI remembers the details and continues the conversation where it left off.
No repeating information or waiting for a transfer.
Here’s what that looks like in practice:
Unified history → every interaction is stored and shared across systems.
Accurate answers → AI pulls real data from CRM and policy systems before replying.
Automatic follow-ups → after each call or message, the right next step happens instantly, like sending reminders or creating tasks.
24/7 service → customers can get help anytime, without losing the personal touch.
With platforms like Strada, every interaction stays consistent and on-brand, no matter who reaches out or how they do it.
And here’s how you can start using AI right away.
How to get started with Strada for AI customer service in insurance?
You’ve seen what’s possible with AI. Now let’s make it real. If you’re ready to bring AI insurance customer service to life, here’s a simple step-by-step guide to start using Strada – the voice AI platform built for insurers, MGAs, and brokers.
Strada helps you handle calls, renewals, and claims automatically while keeping every conversation personal and compliant. You don’t need a tech team or months of setup.
You just need a clear plan and a few smart steps.
Step 1 → define your first use case
Start small. Choose one process that slows your team down but repeats every day, like:
Handling renewal calls
Collecting First Notice of Loss (FNOL) details
Answering policy-servicing requests
These are perfect starting points for AI customer service for insurance, because they’re high-volume and rule-based.
Ask yourself: “Where do we waste time repeating the same questions?” That’s your first automation target.
Step 2 → map the conversation
Next, write out how those calls usually go. What do customers ask first? What info do you collect? What happens at the end?
For example: “Hi, I need to update my policy.”
Verify the customer
Check policy details in AMS
Make update or transfer to agent
Strada’s Workflows feature can turn that simple outline into a live, automated conversation. You’ll use a drag-and-drop builder. No coding required.
Tip: Keep the conversation natural. Use short sentences and warm tone, just like a real agent would.
Step 3 → connect your systems
This is where Strada really shines. You can link it directly to your:
CRM (like Salesforce or HubSpot)
AMS or policy systems
Claims or billing platforms
These integrations make Strada more than a chatbot – it becomes a real agentic AI customer service insurance platform that actually completes actions, not just chats.
For example: after a claim call, Strada can:
Create the claim file automatically
Assign the right adjuster
Send follow-up documents
Notify your team, all within minutes
No manual data entry. No missed steps.
Step 4 → automate the follow-ups
Every call ends with tasks.

Strada’s Workflows turn those into instant actions:
A prospect didn’t finish a quote? → Strada schedules a follow-up.
A customer promised to pay later? → It checks the billing system and sends a reminder.
A renewal is at risk? → It alerts your retention team instantly.
This is where you see real value: AI in insurance customer service working in the background so your team can focus on people, not paperwork.
Step 5 → test, train, and go live
Before you launch, test the experience. Strada lets you:
Review call transcripts
Adjust tone and phrasing
Set escalation rules for sensitive topics
Once everything feels right, turn it on. You’ll start getting insights right away: what customers ask, where they hesitate, how long calls take, and which requests need human touch.
Within days, you’ll see faster response times, happier customers, and fewer missed calls.
Step 6 → scale and evolve
After your first success, expand to new workflows: claims follow-up, quote intake, or even certificate issuance.
Because Strada is infinitely scalable and requires no engineering lift, adding new automations is as simple as cloning a workflow and tweaking a few details.
You can keep growing at your own pace, from simple renewals to fully agentic AI customer service insurance operations.
Step 7 → track and improve
Strada comes with built-in analytics that show:
How many calls were handled by AI
Customer satisfaction trends
Cost and time savings
These insights help you refine scripts, retrain AI responses, and keep improving results.

You’ll see measurable ROI from day one: faster calls, higher retention, and happier teams.
And starting with Strada isn’t about replacing people. It’s about helping them do more of what matters.
When your AI handles the busywork, your agents can focus on empathy, relationships, and growth.
You don’t need to plan for months. Pick one use case. Build it. Watch it work.
That’s how AI customer service insurance industry leaders are scaling smarter, one workflow at a time.
Of course, using AI sounds great until you try to make it real. Let’s talk about what stands in the way and how smart insurers overcome those hurdles.
What are the challenges and best practices for AI adoption in insurance customer service?
AI can greatly improve insurance customer service, but companies face some key challenges when adopting it. Modern AI tools can speed up support and claims, but insurers need to handle these issues carefully to succeed.
Here’s a quick cheat sheet to guide you.
Challenge | What happens | Smart fix | Why it works |
Low customer trust | People don’t feel comfortable with AI decisions | Be transparent: explain how AI helps and when humans step in | Builds confidence and loyalty |
Poor data quality | AI gives wrong or incomplete results | Clean and unify data before using it | Improves accuracy and reliability |
Regulatory pressure | Rules like the EU AI Act add complexity | Use explainable, auditable AI systems | Keeps you compliant and protected |
Employee resistance | Staff fear AI might replace them | Train teams to use AI as a tool, not a threat | Boosts teamwork and adoption |
Integration issues | Systems don’t “talk” to each other | Pick AI that connects with CRMs and claims systems | Saves setup time and avoids errors |
After tackling the challenges, the next question is simple: is it worth it? Here’s how insurers track the real value and impact of their AI efforts.
How do insurers measure the ROI and effectiveness of AI customer service solutions?
Insurers want to know if AI really helps their customer service. And measuring AI customer service insurance performance means tracking what customers actually feel, not just what the system reports.
Here’s how insurers track what matters and spot real improvements.
Metric | What it means | Why it matters | Good benchmark |
Average Handling Time (AHT) | Time to resolve a customer issue | Shows efficiency | Under 3 minutes |
First Contact Resolution (FCR) | Issues solved on first interaction | Reflects AI accuracy and ease | 80%+ |
Customer Satisfaction (CSAT) | How happy customers feel | Indicates overall experience | 90%+ |
Net Promoter Score (NPS) | Likelihood customers recommend you | Measures loyalty | 50+ |
Chatbot containment rate | % of queries solved by AI alone | Measures automation success | 60–70% |
Cost per interaction | Average cost per customer touchpoint | Shows ROI impact | 30–50% lower than human-only service |
Special AI tools like Cognizant Insights or EMA dashboards help insurers watch these numbers live. They also track AI-specific stats like how often chatbots handle questions without needing a human (called chatbot containment rate) and how much work AI does on its own, reducing the need for human help.
Here are a few more metrics that are important:
Chatbot containment rate → how many queries are solved without escalation.
Average handling time → how quickly AI resolves customer requests.
AI accuracy rate → how often answers are correct and relevant.
Deflection rate → how much workload AI removes from human agents.
Resolution quality → how often AI fully completes a task versus partial help.
Adoption rate → how frequently staff and customers use AI tools.
Based on them insurers test different AI setups with A/B testing to find what works best, using customer feedback to keep improving answers and insurance workflows. This means AI keeps getting smarter and more helpful over time.
Another big factor is cost savings. Automating simple tasks like claims processing and fraud checks cuts down on labor costs and mistakes.
Tools like Strada dashboards show important data like call answering rates over 85%, savings from shorter wait times, around-the-clock service, and how automating work lowers expenses.
But numbers alone aren’t enough. Let’s make sure those results come responsibly, with trust, transparency, and strong data protection.
How to ensure ethical AI use and data privacy in insurance customer service?
Using AI in insurance customer service can improve efficiency, but it’s important to do it the right way. AI platforms must be transparent, fair, and avoid bias, following rules like the EU’s AI Act and the US’s CCPA.
To protect customer data, follow these simple steps:
Remove personal details from data so customers stay anonymous.
Always get clear permission before using anyone’s data.
Store data securely using strong encryption and limited access.
Use tools that show how AI makes decisions, like IBM AI Explainability 360, so you can track and understand AI actions. Always have humans check AI decisions and fix mistakes quickly, especially when decisions affect customers deeply.
Work closely with legal, compliance, and data teams to keep all AI use trustworthy and within laws.
Strada supports ethical AI with strong security measures such as: SOC 2 Type 2 certification, keeping each customer’s data separate, never reusing training data, and regular security tests by outside experts.
These steps help make sure AI-driven customer service is safe, fair, and reliable while still working efficiently.
Once you’ve built ethical foundations, you can start tailoring AI to fit your business. Here’s how insurers customize solutions for their unique needs.
What customization options exist for AI solutions in insurance customer service?
Insurers today can customize AI tools to fit their specific needs, making customer service smarter and more efficient. Modern AI platforms are flexible, letting companies adjust workflows, conversations, and system connections to match their business goals and brand style.
There are two main types of AI platforms: white-label and off-the-shelf.
White-label solutions, like custom EMA integrations, let insurers build AI tailored to their unique processes.
Off-the-shelf tools, like Lemonade’s chatbot, offer ready-to-use features but are less flexible.
Between these two extremes, low-code or no-code workflow builders, such as Beam.ai’s Generative Workflow Engine (GWE), allow insurers to create and change AI workflows without heavy technical work. This makes it easier to update AI for new tasks or rules quickly.
As insurers expand globally, multilingual and regional language support is important. AI can speak customers’ languages naturally, improving communication in different markets. Also, AI’s tone and personality can be customized to match the insurer’s brand, creating a consistent and friendly experience.
Finally, none of this works in isolation. Integration with other systems is key. Top AI platforms connect smoothly with CRMs like HubSpot and Salesforce, as well as claims and policy systems. This helps share data and automate tasks across channels seamlessly.
Platforms like Strada are paving the way for agentic AI customer service insurance, where systems can act intelligently and independently within safe limits.
What agentic AI can do now:
Trigger smart workflows instantly → turn every call outcome (like a quote, claim, or payment promise) into real business actions across CRM, AMS, or policy systems.
Connect seamlessly across platforms → use deep integrations with tools like Salesforce, Duck Creek, or custom APIs to keep data synced without manual effort.
Follow intelligent rules → automate responses and next steps based on customer intent, policy details, or risk level; no coding required.
Act in real time → update records, send reminders, issue certificates, or schedule follow-ups the moment a conversation ends.
Ensure compliance and trust → operate within defined guardrails: secure data isolation, SOC 2 controls, and no model cross-training.
Scale automatically → handle thousands of calls and follow-ups with zero engineering lift, growing capacity as your business grows.
Learn from interactions → capture insights from every call to improve workflows, detect churn risks, and optimize future automations.
Its AI voice agents understand insurance terms and can handle tasks like taking calls, scheduling policy renewals, routing claims, and triggering downstream actions. Insurers can easily set rules and automate complex processes using Strada Workflows.
Customization is just the beginning. After seeing how AI is changing insurance service today, the next step is for insurers to start using these ideas in real life.
How will you lead the future of AI in insurance?
AI is changing insurance customer service in big ways.
It helps automate claims, personalize how customers are treated, support agents, and create smarter workflows. Using AI in insurance customer service is no longer just a nice-to-have; it’s a must for insurers who want to stay competitive, keep customers happy, and work more efficiently.
To succeed, insurers should build strong data systems, combine human skills with AI, and pick reliable AI tools that meet both performance and safety standards. Platforms like Strada offer easy-to-use solutions that handle insurance calls, automate tasks quickly, and deliver real business results with top-level security.
And these platforms make it super-easy to take your first step into AI-powered customer service.
You don’t need to rebuild your systems or hire a tech team – Strada connects with what you already use and helps you handle calls, renewals, and claims automatically, while keeping a real human tone.
Think of it as your always-on teammate: one that learns from every interaction, gets smarter over time, and gives your team more space to focus on what really matters – helping people.
If you’re ready to see how AI insurance customer service can feel effortless, Strada’s platform is a great place to start learning, testing, and growing.
Book a quick demo to see how it works in action and discover how it fits your business.
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© 2025 Strada API, Inc.
© 2025 Strada API, Inc.
© 2025 Strada API, Inc.
