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The 2025 Guide to RPA in Insurance Workflows (Updated)
Amir Prodensky
CEO
Sep 22, 2025
14 min read
See how RPA speeds up claims, policies, and back-office tasks.
Insurance runs on processes. Every claim, every policy renewal, every customer call – it’s all a workflow.
For years, RPA in insurance has helped insurers cut costs by handling repetitive back-office tasks. But in 2025, the story has shifted. RPA isn’t just a support tool anymore; it's a core strategy for staying competitive.
What’s new, you might ask?
It’s matured → no longer pilots or experiments, but scaled, proven systems.
It’s expanded → automation now powers customer-facing conversations, not just data entry.
That means RPA in insurance looks very different today.
Take Strada, for instance. It isn’t traditional RPA. it’s a conversational AI purpose-built for insurance. By managing renewals, claims intake, and service requests over phone and SMS, it pushes automation beyond the back office and directly into customer interactions.
And that’s why this guide exists. It will walk you through the latest use cases of robotic process automation in insurance, what’s changing, and how you can put it to work.
And we’ll start with the foundations.
What is RPA in insurance, and why does it matter?
Robotic process automation in insurance may sound complex, but it’s really simple.
Think of it as software “bots” that handle repetitive digital tasks so people don’t have to. For example, a bot can copy customer details from one system into another, process a claim form, or generate a report, all without a human clicking through screens.
In everyday terms, it’s like having a super-fast assistant who never gets tired, makes fewer mistakes, and works 24/7. That’s why insurance is such a natural fit.
Few industries rely more on processes:
Claims must be logged, checked, and approved.
Policies need renewals and updates.
Customer records have to be accurate across multiple systems.
When you look at it this way, you see why the RPA in the insurance sector is growing so quickly. Automating these steps saves time, reduces errors, and frees teams to focus on what matters most – serving customers.
Independent research confirms this momentum.
Deloitte’s global RPA survey found that 53% of businesses have already implemented automation, with adoption expected to become nearly universal within the next two years.
And according to McKinsey, as much as 45% of business tasks can be automated, underscoring just how many opportunities insurers can tap into.
So, foundations? Done.
Next, let’s explore the specific workflows where RPA delivers real value, both behind the scenes and in customer interactions.
What kinds of tasks can RPA in the insurance sector handle?
When you break it down, insurance is a series of repeatable, rule-based tasks. So, let’s look at where RPA creates the most value:
Area | Example tasks | How RPA helps | How Strada extends it |
Claims | FNOL, document validation, routing | Speeds processing, reduces errors | Handles FNOL 24/7 through conversational logging, eliminating hold times. |
Policy servicing | Renewals, endorsements, certificates | Automates updates, ensures accuracy | Proactively calls customers for renewals and answers routine questions instantly. |
Underwriting | Data intake, quote generation | Produces faster, more accurate quotes | Captures quotes over the phone or SMS without waiting for an agent. |
Customer onboarding | Identity checks, compliance steps | Saves time, meets regulatory standards | Provides conversational onboarding that meets compliance while simplifying the experience. |
Finance | Billing, collections, reconciliation | Reduces manual work, improves accuracy | Extends to customer-facing interactions (e.g., payment reminders) for better collections. |
While RPA automates back-office workflows, Strada is not RPA but rather an insurance-specific conversational AI that extends automation into customer-facing phone and SMS interactions.
As a result, instead of replacing RPA, it augments it. Traditional bots handle the data behind the scenes, while Strada manages the phone-based workflows with natural, human-like conversations.
The result is a full stack of automation: back-office accuracy plus front-office engagement. That’s why the use cases of RPA in insurance now span from claims processing to customer experience.
So how do these pieces fit together? Think of it like stacking blocks.
For leaders, this shift matters. It shows automation isn’t limited to cutting costs. It can improve service, retain more customers, and even grow revenue. That’s the real power of combining RPA with AI in today’s insurance workflows.
Now that you know what can be automated, let’s explore why it matters.
What are the main benefits of RPA in insurance?
The real value of RPA in insurance isn’t just speed; it’s how it makes the customer experience better. People want fast answers, no errors, and zero hold times.
When bots handle repetitive steps, customers get smoother service without the usual frustration.
The efficiency gains are huge too. RPA creates compliance-ready audit trails automatically. It reduces costs by eliminating manual effort. And it frees employees to focus on higher-value tasks like solving complex cases or building relationships.
But the biggest story in 2025 is how automation drives outcomes, not just efficiency. Strada is a great example here. Its AI phone agents deliver results you can measure:
85% of calls answered, compared to many missed calls with human-only teams.
24/7/365 availability, no business hours, no downtime.
Infinite scalability without adding headcount.
That changes the game. Instead of simply “doing more with less,” Strada helps insurers grow. More answered calls mean more quotes captured, more renewals completed, and more claims logged on time.
Customers stick around because the experience feels responsive and easy.
Still, even with clear benefits, automation comes with hurdles. Let’s talk about the challenges insurers face and how purpose-built solutions can help overcome them.
What are the biggest challenges in RPA in insurance?
Even with proven benefits, RPA in insurance faces real-world hurdles that slow progress:
Scaling beyond pilots → bots work in tests but stall when rolled out broadly.
Legacy IT integration → connecting modern automation to old systems is harder than expected.
Regulatory compliance → every workflow must meet strict standards, adding overhead.
Employee resistance → staff may fear being replaced instead of supported.
Customer-facing risk → even small errors can break trust and damage brand credibility.
Slow ROI realization → early wins don’t always translate into enterprise-wide impact.
These challenges highlight why many insurers stall in their automation journey. But they also set the stage for the next step: a solution designed specifically to overcome them.
This is where Strada shines. It’s purpose-built for insurance. Its AI understands the nuances of renewals, claims, and servicing. Even better, it has built-in accuracy checks that constantly monitor performance. That means fewer errors, lower E&O risk, and peace of mind.
The result? Automation you can trust.
Strada proves that customer-facing AI can be both efficient and compliant. It helps insurers overcome common roadblocks, legacy systems, scaling hurdles, and regulatory pressure without stress.
Understanding the obstacles is just the start. Next, you’ll learn how to pick the processes that deliver the fastest, most impactful wins, so you can see results quickly and confidently.
How do you choose the right processes for RPA in insurance to automate?
One of the biggest questions leaders face is: where do we start with automation? Not every task is a good fit. The right processes make all the difference.
The sweet spot is clear. Look for tasks that are:
Rule-based → steps follow a clear “if this, then that” pattern.
Repetitive → the same work happens again and again.
High-volume → tasks that eat up hours every week.
These are perfect for RPA because they don’t require judgment or creativity. Think data entry, reconciliations, or document validation.
To find them, many insurers use process mining. It analyzes system logs to reveal which workflows take the most time and where the bottlenecks are. It’s a smart way to prioritize.
To move from theory to action, insurers need a clear, repeatable way to zero in on the right candidates for automation. Here’s a simple, practical process you can follow:
List candidate processes → sit with operations, claims, underwriting, and finance teams. Ask: “Which tasks feel like busywork or bottlenecks?” Capture everything without filtering.
Measure the workload → for each task, note average handling time, frequency, and staff hours per week. Even a rough estimate is enough to see which ones consume the most effort.
Check the rules → document whether the task follows clear decision rules. If humans often need judgment, put it aside; if it’s “if X then Y,” keep it on the list.
Test with a sample → take a day or week’s worth of cases for one process and map the exact steps. This shows whether it’s consistent enough for automation.
Rank by ROI → score tasks on effort saved, error risk reduced, and impact on customer experience. Start with the ones that score highest across these three.
Pilot before scaling → automate one narrow use case (e.g., policy certificate requests) to validate the benefits before rolling out broadly.
If you’re wondering “how do I know which process to start with?” – use this simple decision path:
But here’s a tip: don’t just chase back-office savings. Start with tasks that impact both efficiency and customer experience. When you reduce errors and speed up turnaround, customers notice. That’s where the business impact grows.
Front-office calls are one of the biggest untapped opportunities. Missed calls mean lost revenue. Long hold times hurt retention. Yet most teams still rely on human-only coverage.
That’s changing fast.
Strada makes it simple. Its pre-built, insurance-specific voice workflows cover renewals, claims intake, quotes, and servicing. You don’t need engineers or months of setup. You can identify, launch, and scale conversational automation in days.
This is why RPA in insurance is evolving. It’s not just about automating what happens in the back office. It’s about tackling customer-facing workflows that drive growth.
The practical takeaway:
Use clear criteria (rule-based, repetitive, high-volume).
Apply tools like process mining to prioritize.
Don’t ignore front-office calls, start there for maximum impact.
Use platforms like Strada to accelerate deployment without technical heavy lifting.
Get those steps right, and you’ll build a roadmap that delivers both quick wins and long-term value.
Once you know which tasks to automate, the next step is execution. Here’s a practical, step-by-step approach to rolling out RPA successfully.
So, you’ve got a roadmap in hand, you need the right tools. Let’s explore the platforms leading the charge, from general RPA to insurance-specific AI solutions like Strada.
What RPA tools and platforms stand out in 2025?
When it comes to RPA tools in 2025, you’ve got plenty of options. Some are broad, enterprise-grade platforms. Others are purpose-built for insurance.
Let’s break down the key RPA use cases in insurance from claims to customer onboarding and finance.
UiPath
UiPath is one of the most established RPA platforms and works well for big insurers with complex operations. It handles large volumes of claims, processes documents quickly, and connects with older policy systems.
Key features:
Rich robotics & agentic automation (attended & unattended bots)
Strong document understanding / data extraction
Orchestrator / robot management, governance, process-mining tools
Wide integrations (legacy systems, UI, API)
Pricing: Starts at about US$420/month for a small bundle (attended + unattended bots, Action Center, Studio) for SMEs; enterprise licensing is quoted per deal.
Automation Anywhere
Automation Anywhere is cloud-native and built for scale. Insurers use it to speed up renewals, endorsements, and customer updates, especially when automation needs to run across regions or business lines.
Key features:
Cloud-native Agentic Process Automation system
Strong document automation & AI-powered data extraction
Control Room / Bot Creator tools, collaboration, role-based security
Pre-built bots, large bot marketplace
Pricing: Starting price around US$9,000/year for basic usage-based package (one unattended bot, bot creator, control room); extra bots (attended / unattended) add cost.
Blue Prism
Blue Prism is known for strong security and governance. It’s often chosen for underwriting, compliance reporting, and other processes where accuracy and audit trails are essential.
Key features:
Strong governance, security, audit trails
Capable of enterprise-grade unattended automation
Good support for compliance & regulated workflows
Offers both cloud (SaaS) and on-prem/hybrid deployment options
Document automation, process intelligence, decision automation addons
Pricing: Quote-based; one digital worker (concurrent bot) starts at about US$13,000/year for on-premises deployments; cloud/digital worker bundles may run higher.
Microsoft Power Automate
Power Automate is the easiest option for insurers already using Microsoft tools. It helps automate billing, reconciliations, and the flow of data between Outlook, Excel, Teams, and CRM without heavy setup.
Key features:
Tight integration with Microsoft ecosystem (Office, Teams, Outlook, Excel, Azure)
Both attended and unattended robotic flows
Licensing with “user / bot / process” options, capacity add-ons
Process & task mining available, AI Builder for intelligence in flows
Pricing: Premium plan is ~US$15/user/month for attended / basic cloud flows; “Process” / unattended automation bots ~US$150-US$215/bot/month in many markets.
Here’s a side-by-side comparison to help readers see what trade-offs to expect:
Dimension | UiPath | Automation Anywhere | Blue Prism | Power Automate |
Ease of onboarding | Very good; strong documentation, large user community, many pre-built components. | Also good; cloud-native, many bots/templates; but some steep learning for advanced features. | Moderate; often more complex setup, especially for large/secure/hybrid deployments. | Very easy for Microsoft shops; many users already familiar with the tools. |
Governance & Compliance | Strong; good audit trail, governance controls, role-based access. | Robust; Control Room, security layers. | Very strong; built for regulated environments. | Decent; might need add-ons or extra care for sensitive data or regulatory reporting. |
Scalability for unattended bots | High; can scale to many bots, cloud or on-prem. | High; cloud version supports large bot counts. | High; particularly with enterprise or cloud offerings. | Good; but cost per bot / flow can add up; licensing model matters. |
Cost-efficiency for small deployments | Moderate; small bundles are affordable but enterprise scale gets expensive. | Slightly more expensive initially; but good value where many automations are used. | Less cost-efficient in small deployments due to license floor, worker minimums. | Very good; low entry cost especially if already using Microsoft 365 / Azure. |
Best fit by use case | Legacy systems + high volume document workflows; or mix of attended & unattended bots. | Customer-updates, renewals, cross-region automation; distributed operations. | Regulation, audit, compliance, underwriting; where security and governance are first order. | Internal process automation in MS environment; handling data transfer, simple underwriting tasks or customer service integrations. |
Drawbacks / Considerations | Pricing complexity; managing many licenses / bots can get costly. | Some advanced AI features or integrations may require professional services. | Steeper implementation time; sometimes less flexibility for citizen developers. | Less suited for non-Microsoft ecosystems; some limitations on connectors, unattended scale unless paying higher bot licensing. |
These platforms give insurers the core building blocks for robotic process automation. They’re widely used for back-office processes, integrations, and RPA in insurance claims processing.
But the trend in 2025 isn’t just RPA. It’s RPA combined with AI, which many call “intelligent automation.” That’s where the biggest value is created. Bots take care of repetitive steps, while AI handles conversations, decisions, and customer interactions.
So, while the big platforms are flexible, they’re not specialized.
That’s where Strada stands out. It focuses on insurance front-office calls that directly affect revenue and customer retention. Strada combines RPA and AI in insurance to automate back-office and front-office workflows seamlessly.
Here are a few Strada’s strengths:
Feature | What it does | Benefit |
Pre-built insurance workflows | Renewals, FNOL processes, servicing, and quote intake | Launch automation quickly with tasks ready to go |
Seamless integrations | Connects with policy & claims systems, AMS, and APIs | Keeps data flowing without manual effort |
Quick deployment | No engineering lift required | Voice AI agents can be up and running in days, not months |
Real-world adoption is already strong. Carriers, MGAs, and brokers are using Strada to scale conversations without adding headcount. Instead of missed calls, they now capture more quotes, process more claims, and retain more customers.
Take the example of the Aimee AI agent. Embedded insurance provider, Tint, deployed Aimee to handle after-hours calls for policy servicing and claims intake.
Within the first month, Aimee answered hundreds of calls that would have otherwise gone to voicemail. Customers got help instantly, and Tint saw customer satisfaction improve.
That’s the kind of practical, measurable impact automation should deliver.
And here's why it matters: the RPA landscape is maturing. General platforms are excellent for back-office efficiency. But insurers also need tools that move the needle on customer experience and revenue. Strada proves that automation can be both specialized and powerful.
Here are a few use cases of RPA in insurance:
Use broad RPA platforms like UiPath or Automation Anywhere for process-heavy back-office automation.
Combine them with AI-driven tools to deliver intelligent automation.
Deploy specialized platforms like Strada to capture the front-office opportunity.
In other words, don’t just think about automation as “cost-cutting.” Think about it as growth. RPA in insurance is no longer limited to forms and compliance, it’s now about conversations, retention, and customer trust.
Tools are only part of the story. To see if automation really works, you need clear metrics and ongoing measurement.
How do you measure success with robotic process automation in insurance?
Measuring success with automation isn’t just about saying, “We deployed bots.” You need clear KPIs to prove value and keep improving.
To evaluate the impact of robotic process automation in insurance, track both operational and customer-facing metrics.
Start with the basics
Core operational metrics show how well your automation works:
Cost savings → fewer manual hours, lower overhead.
Error reduction → fewer mistakes in claims, billing, and compliance.
Turnaround times → faster processing for claims, renewals, and onboarding.
Compliance adherence → consistent audit trails and reduced risk.
These metrics make a strong business case. But they only tell half the story. Customers care about speed, accuracy, and ease. That’s why you should track at the high level:
KPI type | Example metrics | Why it matters | Typical benchmarks |
Operational | Cost savings, fewer errors, faster turnaround, compliance rates | Shows how much time and money automation saves while reducing risk. | 40–60% cost reduction, 60–80% fewer errors, 30–50% faster cycle times |
Customer | CSAT, NPS, policy retention | Reflects how automation improves service quality, satisfaction, and loyalty. | CSAT >85%, NPS +30 or higher, policy retention +5–10% |
Business impact | Number of calls answered, renewals completed, FNOLs logged | Proves automation drives growth by capturing more revenue and reducing lost business. | 50–70% of routine calls answered by automation, 10–20% increase in renewals processed, 24/7 FNOL capture with 60% touchless rate |
Together, these numbers show whether automation improves the customer experience, not just internal efficiency.
Continuous monitoring matters
Automation isn’t static. Processes evolve, customer expectations rise, and regulations change. That’s why you should monitor KPIs regularly and refine workflows over time. Small tweaks often unlock big gains.
Here’s how to build a continuous monitoring culture:
Pick 3–4 core KPIs (e.g., error rate, turnaround time, CSAT, renewals completed).
Set a baseline before automation goes live so improvements are clear.
Review monthly, not just once a year. Use dashboards or simple reports.
Act on signals. If a KPI dips, adjust workflows instead of waiting.
Rinse and repeat by building monitoring into daily operations so automation keeps pace with business needs.
Tracking the impact of automation shouldn’t be complicated. Insurers need to see clear, measurable results that tie directly to business goals.
Strada makes success easy to track. It delivers outcomes you can see right away:
Higher connection rates with customers.
No missed calls ever.
Gains in satisfaction because service is instant and accurate.
Pre-built insurance workflows, seamless integrations, and quick deployment make it easy to start with RPA and AI in insurance. On top of that, Strada affects revenue.
You can measure policy retention and renewal lift directly, since customers who get quick service are far less likely to churn.
Tracking results today sets you up for tomorrow. No doubt that the future is exciting, but the key is to start now.
Here’s how insurers can take the first step, safely and effectively, toward automation that drives real business impact.
How can insurers get started today?
A few months ago, an operations leader at a mid-sized insurer told me: “We know automation will help, but we don’t know where to start.” That hesitation is common – the potential feels huge, yet the first step can seem unclear.
The good news? Getting started doesn’t require a massive overhaul. With the right approach, insurers can move from idea to impact in weeks, not years. Here’s how:
Pick one process that’s high-impact but manageable: renewals, FNOL, or certificate issuance.
Set clear KPIs upfront, like turnaround time, error rate, or customer satisfaction scores.
Align key teams: loop in IT, compliance, and operations from the start.
Launch a quick pilot with a narrow scope (one line of business, one region, or one workflow).
Measure results fast and compare against the baseline.
Refine the workflow based on what you learn. Small tweaks unlock major gains.
Scale step-by-step into adjacent processes once the first pilot proves value.
At this point, many insurers also look for ways to extend automation beyond internal workflows into direct customer interactions. That’s where Strada comes in.
It makes it even easier.
You can get a demo to explore insurance-specific AI phone agents handling renewals, claims intake, and servicing. It’s quick to deploy, purpose-built, and designed for real insurance workflows. Security is built in, with SOC 2 Type 2 certification, data isolation, and privacy-first LLM policies.
The result is simple: automation that boosts efficiency, improves customer experience, and drives revenue. Start today, measure results quickly, and begin scaling revenue-driving calls with AI.
Pair with Strada, robotic process automation in insurance is finally ready to move from pilot to profit.
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The 2025 Guide to RPA in Insurance Workflows (Updated)
Amir Prodensky
CEO
Sep 22, 2025
14 min read
See how RPA speeds up claims, policies, and back-office tasks.
Insurance runs on processes. Every claim, every policy renewal, every customer call – it’s all a workflow.
For years, RPA in insurance has helped insurers cut costs by handling repetitive back-office tasks. But in 2025, the story has shifted. RPA isn’t just a support tool anymore; it's a core strategy for staying competitive.
What’s new, you might ask?
It’s matured → no longer pilots or experiments, but scaled, proven systems.
It’s expanded → automation now powers customer-facing conversations, not just data entry.
That means RPA in insurance looks very different today.
Take Strada, for instance. It isn’t traditional RPA. it’s a conversational AI purpose-built for insurance. By managing renewals, claims intake, and service requests over phone and SMS, it pushes automation beyond the back office and directly into customer interactions.
And that’s why this guide exists. It will walk you through the latest use cases of robotic process automation in insurance, what’s changing, and how you can put it to work.
And we’ll start with the foundations.
What is RPA in insurance, and why does it matter?
Robotic process automation in insurance may sound complex, but it’s really simple.
Think of it as software “bots” that handle repetitive digital tasks so people don’t have to. For example, a bot can copy customer details from one system into another, process a claim form, or generate a report, all without a human clicking through screens.
In everyday terms, it’s like having a super-fast assistant who never gets tired, makes fewer mistakes, and works 24/7. That’s why insurance is such a natural fit.
Few industries rely more on processes:
Claims must be logged, checked, and approved.
Policies need renewals and updates.
Customer records have to be accurate across multiple systems.
When you look at it this way, you see why the RPA in the insurance sector is growing so quickly. Automating these steps saves time, reduces errors, and frees teams to focus on what matters most – serving customers.
Independent research confirms this momentum.
Deloitte’s global RPA survey found that 53% of businesses have already implemented automation, with adoption expected to become nearly universal within the next two years.
And according to McKinsey, as much as 45% of business tasks can be automated, underscoring just how many opportunities insurers can tap into.
So, foundations? Done.
Next, let’s explore the specific workflows where RPA delivers real value, both behind the scenes and in customer interactions.
What kinds of tasks can RPA in the insurance sector handle?
When you break it down, insurance is a series of repeatable, rule-based tasks. So, let’s look at where RPA creates the most value:
Area | Example tasks | How RPA helps | How Strada extends it |
Claims | FNOL, document validation, routing | Speeds processing, reduces errors | Handles FNOL 24/7 through conversational logging, eliminating hold times. |
Policy servicing | Renewals, endorsements, certificates | Automates updates, ensures accuracy | Proactively calls customers for renewals and answers routine questions instantly. |
Underwriting | Data intake, quote generation | Produces faster, more accurate quotes | Captures quotes over the phone or SMS without waiting for an agent. |
Customer onboarding | Identity checks, compliance steps | Saves time, meets regulatory standards | Provides conversational onboarding that meets compliance while simplifying the experience. |
Finance | Billing, collections, reconciliation | Reduces manual work, improves accuracy | Extends to customer-facing interactions (e.g., payment reminders) for better collections. |
While RPA automates back-office workflows, Strada is not RPA but rather an insurance-specific conversational AI that extends automation into customer-facing phone and SMS interactions.
As a result, instead of replacing RPA, it augments it. Traditional bots handle the data behind the scenes, while Strada manages the phone-based workflows with natural, human-like conversations.
The result is a full stack of automation: back-office accuracy plus front-office engagement. That’s why the use cases of RPA in insurance now span from claims processing to customer experience.
So how do these pieces fit together? Think of it like stacking blocks.
For leaders, this shift matters. It shows automation isn’t limited to cutting costs. It can improve service, retain more customers, and even grow revenue. That’s the real power of combining RPA with AI in today’s insurance workflows.
Now that you know what can be automated, let’s explore why it matters.
What are the main benefits of RPA in insurance?
The real value of RPA in insurance isn’t just speed; it’s how it makes the customer experience better. People want fast answers, no errors, and zero hold times.
When bots handle repetitive steps, customers get smoother service without the usual frustration.
The efficiency gains are huge too. RPA creates compliance-ready audit trails automatically. It reduces costs by eliminating manual effort. And it frees employees to focus on higher-value tasks like solving complex cases or building relationships.
But the biggest story in 2025 is how automation drives outcomes, not just efficiency. Strada is a great example here. Its AI phone agents deliver results you can measure:
85% of calls answered, compared to many missed calls with human-only teams.
24/7/365 availability, no business hours, no downtime.
Infinite scalability without adding headcount.
That changes the game. Instead of simply “doing more with less,” Strada helps insurers grow. More answered calls mean more quotes captured, more renewals completed, and more claims logged on time.
Customers stick around because the experience feels responsive and easy.
Still, even with clear benefits, automation comes with hurdles. Let’s talk about the challenges insurers face and how purpose-built solutions can help overcome them.
What are the biggest challenges in RPA in insurance?
Even with proven benefits, RPA in insurance faces real-world hurdles that slow progress:
Scaling beyond pilots → bots work in tests but stall when rolled out broadly.
Legacy IT integration → connecting modern automation to old systems is harder than expected.
Regulatory compliance → every workflow must meet strict standards, adding overhead.
Employee resistance → staff may fear being replaced instead of supported.
Customer-facing risk → even small errors can break trust and damage brand credibility.
Slow ROI realization → early wins don’t always translate into enterprise-wide impact.
These challenges highlight why many insurers stall in their automation journey. But they also set the stage for the next step: a solution designed specifically to overcome them.
This is where Strada shines. It’s purpose-built for insurance. Its AI understands the nuances of renewals, claims, and servicing. Even better, it has built-in accuracy checks that constantly monitor performance. That means fewer errors, lower E&O risk, and peace of mind.
The result? Automation you can trust.
Strada proves that customer-facing AI can be both efficient and compliant. It helps insurers overcome common roadblocks, legacy systems, scaling hurdles, and regulatory pressure without stress.
Understanding the obstacles is just the start. Next, you’ll learn how to pick the processes that deliver the fastest, most impactful wins, so you can see results quickly and confidently.
How do you choose the right processes for RPA in insurance to automate?
One of the biggest questions leaders face is: where do we start with automation? Not every task is a good fit. The right processes make all the difference.
The sweet spot is clear. Look for tasks that are:
Rule-based → steps follow a clear “if this, then that” pattern.
Repetitive → the same work happens again and again.
High-volume → tasks that eat up hours every week.
These are perfect for RPA because they don’t require judgment or creativity. Think data entry, reconciliations, or document validation.
To find them, many insurers use process mining. It analyzes system logs to reveal which workflows take the most time and where the bottlenecks are. It’s a smart way to prioritize.
To move from theory to action, insurers need a clear, repeatable way to zero in on the right candidates for automation. Here’s a simple, practical process you can follow:
List candidate processes → sit with operations, claims, underwriting, and finance teams. Ask: “Which tasks feel like busywork or bottlenecks?” Capture everything without filtering.
Measure the workload → for each task, note average handling time, frequency, and staff hours per week. Even a rough estimate is enough to see which ones consume the most effort.
Check the rules → document whether the task follows clear decision rules. If humans often need judgment, put it aside; if it’s “if X then Y,” keep it on the list.
Test with a sample → take a day or week’s worth of cases for one process and map the exact steps. This shows whether it’s consistent enough for automation.
Rank by ROI → score tasks on effort saved, error risk reduced, and impact on customer experience. Start with the ones that score highest across these three.
Pilot before scaling → automate one narrow use case (e.g., policy certificate requests) to validate the benefits before rolling out broadly.
If you’re wondering “how do I know which process to start with?” – use this simple decision path:
But here’s a tip: don’t just chase back-office savings. Start with tasks that impact both efficiency and customer experience. When you reduce errors and speed up turnaround, customers notice. That’s where the business impact grows.
Front-office calls are one of the biggest untapped opportunities. Missed calls mean lost revenue. Long hold times hurt retention. Yet most teams still rely on human-only coverage.
That’s changing fast.
Strada makes it simple. Its pre-built, insurance-specific voice workflows cover renewals, claims intake, quotes, and servicing. You don’t need engineers or months of setup. You can identify, launch, and scale conversational automation in days.
This is why RPA in insurance is evolving. It’s not just about automating what happens in the back office. It’s about tackling customer-facing workflows that drive growth.
The practical takeaway:
Use clear criteria (rule-based, repetitive, high-volume).
Apply tools like process mining to prioritize.
Don’t ignore front-office calls, start there for maximum impact.
Use platforms like Strada to accelerate deployment without technical heavy lifting.
Get those steps right, and you’ll build a roadmap that delivers both quick wins and long-term value.
Once you know which tasks to automate, the next step is execution. Here’s a practical, step-by-step approach to rolling out RPA successfully.
So, you’ve got a roadmap in hand, you need the right tools. Let’s explore the platforms leading the charge, from general RPA to insurance-specific AI solutions like Strada.
What RPA tools and platforms stand out in 2025?
When it comes to RPA tools in 2025, you’ve got plenty of options. Some are broad, enterprise-grade platforms. Others are purpose-built for insurance.
Let’s break down the key RPA use cases in insurance from claims to customer onboarding and finance.
UiPath
UiPath is one of the most established RPA platforms and works well for big insurers with complex operations. It handles large volumes of claims, processes documents quickly, and connects with older policy systems.
Key features:
Rich robotics & agentic automation (attended & unattended bots)
Strong document understanding / data extraction
Orchestrator / robot management, governance, process-mining tools
Wide integrations (legacy systems, UI, API)
Pricing: Starts at about US$420/month for a small bundle (attended + unattended bots, Action Center, Studio) for SMEs; enterprise licensing is quoted per deal.
Automation Anywhere
Automation Anywhere is cloud-native and built for scale. Insurers use it to speed up renewals, endorsements, and customer updates, especially when automation needs to run across regions or business lines.
Key features:
Cloud-native Agentic Process Automation system
Strong document automation & AI-powered data extraction
Control Room / Bot Creator tools, collaboration, role-based security
Pre-built bots, large bot marketplace
Pricing: Starting price around US$9,000/year for basic usage-based package (one unattended bot, bot creator, control room); extra bots (attended / unattended) add cost.
Blue Prism
Blue Prism is known for strong security and governance. It’s often chosen for underwriting, compliance reporting, and other processes where accuracy and audit trails are essential.
Key features:
Strong governance, security, audit trails
Capable of enterprise-grade unattended automation
Good support for compliance & regulated workflows
Offers both cloud (SaaS) and on-prem/hybrid deployment options
Document automation, process intelligence, decision automation addons
Pricing: Quote-based; one digital worker (concurrent bot) starts at about US$13,000/year for on-premises deployments; cloud/digital worker bundles may run higher.
Microsoft Power Automate
Power Automate is the easiest option for insurers already using Microsoft tools. It helps automate billing, reconciliations, and the flow of data between Outlook, Excel, Teams, and CRM without heavy setup.
Key features:
Tight integration with Microsoft ecosystem (Office, Teams, Outlook, Excel, Azure)
Both attended and unattended robotic flows
Licensing with “user / bot / process” options, capacity add-ons
Process & task mining available, AI Builder for intelligence in flows
Pricing: Premium plan is ~US$15/user/month for attended / basic cloud flows; “Process” / unattended automation bots ~US$150-US$215/bot/month in many markets.
Here’s a side-by-side comparison to help readers see what trade-offs to expect:
Dimension | UiPath | Automation Anywhere | Blue Prism | Power Automate |
Ease of onboarding | Very good; strong documentation, large user community, many pre-built components. | Also good; cloud-native, many bots/templates; but some steep learning for advanced features. | Moderate; often more complex setup, especially for large/secure/hybrid deployments. | Very easy for Microsoft shops; many users already familiar with the tools. |
Governance & Compliance | Strong; good audit trail, governance controls, role-based access. | Robust; Control Room, security layers. | Very strong; built for regulated environments. | Decent; might need add-ons or extra care for sensitive data or regulatory reporting. |
Scalability for unattended bots | High; can scale to many bots, cloud or on-prem. | High; cloud version supports large bot counts. | High; particularly with enterprise or cloud offerings. | Good; but cost per bot / flow can add up; licensing model matters. |
Cost-efficiency for small deployments | Moderate; small bundles are affordable but enterprise scale gets expensive. | Slightly more expensive initially; but good value where many automations are used. | Less cost-efficient in small deployments due to license floor, worker minimums. | Very good; low entry cost especially if already using Microsoft 365 / Azure. |
Best fit by use case | Legacy systems + high volume document workflows; or mix of attended & unattended bots. | Customer-updates, renewals, cross-region automation; distributed operations. | Regulation, audit, compliance, underwriting; where security and governance are first order. | Internal process automation in MS environment; handling data transfer, simple underwriting tasks or customer service integrations. |
Drawbacks / Considerations | Pricing complexity; managing many licenses / bots can get costly. | Some advanced AI features or integrations may require professional services. | Steeper implementation time; sometimes less flexibility for citizen developers. | Less suited for non-Microsoft ecosystems; some limitations on connectors, unattended scale unless paying higher bot licensing. |
These platforms give insurers the core building blocks for robotic process automation. They’re widely used for back-office processes, integrations, and RPA in insurance claims processing.
But the trend in 2025 isn’t just RPA. It’s RPA combined with AI, which many call “intelligent automation.” That’s where the biggest value is created. Bots take care of repetitive steps, while AI handles conversations, decisions, and customer interactions.
So, while the big platforms are flexible, they’re not specialized.
That’s where Strada stands out. It focuses on insurance front-office calls that directly affect revenue and customer retention. Strada combines RPA and AI in insurance to automate back-office and front-office workflows seamlessly.
Here are a few Strada’s strengths:
Feature | What it does | Benefit |
Pre-built insurance workflows | Renewals, FNOL processes, servicing, and quote intake | Launch automation quickly with tasks ready to go |
Seamless integrations | Connects with policy & claims systems, AMS, and APIs | Keeps data flowing without manual effort |
Quick deployment | No engineering lift required | Voice AI agents can be up and running in days, not months |
Real-world adoption is already strong. Carriers, MGAs, and brokers are using Strada to scale conversations without adding headcount. Instead of missed calls, they now capture more quotes, process more claims, and retain more customers.
Take the example of the Aimee AI agent. Embedded insurance provider, Tint, deployed Aimee to handle after-hours calls for policy servicing and claims intake.
Within the first month, Aimee answered hundreds of calls that would have otherwise gone to voicemail. Customers got help instantly, and Tint saw customer satisfaction improve.
That’s the kind of practical, measurable impact automation should deliver.
And here's why it matters: the RPA landscape is maturing. General platforms are excellent for back-office efficiency. But insurers also need tools that move the needle on customer experience and revenue. Strada proves that automation can be both specialized and powerful.
Here are a few use cases of RPA in insurance:
Use broad RPA platforms like UiPath or Automation Anywhere for process-heavy back-office automation.
Combine them with AI-driven tools to deliver intelligent automation.
Deploy specialized platforms like Strada to capture the front-office opportunity.
In other words, don’t just think about automation as “cost-cutting.” Think about it as growth. RPA in insurance is no longer limited to forms and compliance, it’s now about conversations, retention, and customer trust.
Tools are only part of the story. To see if automation really works, you need clear metrics and ongoing measurement.
How do you measure success with robotic process automation in insurance?
Measuring success with automation isn’t just about saying, “We deployed bots.” You need clear KPIs to prove value and keep improving.
To evaluate the impact of robotic process automation in insurance, track both operational and customer-facing metrics.
Start with the basics
Core operational metrics show how well your automation works:
Cost savings → fewer manual hours, lower overhead.
Error reduction → fewer mistakes in claims, billing, and compliance.
Turnaround times → faster processing for claims, renewals, and onboarding.
Compliance adherence → consistent audit trails and reduced risk.
These metrics make a strong business case. But they only tell half the story. Customers care about speed, accuracy, and ease. That’s why you should track at the high level:
KPI type | Example metrics | Why it matters | Typical benchmarks |
Operational | Cost savings, fewer errors, faster turnaround, compliance rates | Shows how much time and money automation saves while reducing risk. | 40–60% cost reduction, 60–80% fewer errors, 30–50% faster cycle times |
Customer | CSAT, NPS, policy retention | Reflects how automation improves service quality, satisfaction, and loyalty. | CSAT >85%, NPS +30 or higher, policy retention +5–10% |
Business impact | Number of calls answered, renewals completed, FNOLs logged | Proves automation drives growth by capturing more revenue and reducing lost business. | 50–70% of routine calls answered by automation, 10–20% increase in renewals processed, 24/7 FNOL capture with 60% touchless rate |
Together, these numbers show whether automation improves the customer experience, not just internal efficiency.
Continuous monitoring matters
Automation isn’t static. Processes evolve, customer expectations rise, and regulations change. That’s why you should monitor KPIs regularly and refine workflows over time. Small tweaks often unlock big gains.
Here’s how to build a continuous monitoring culture:
Pick 3–4 core KPIs (e.g., error rate, turnaround time, CSAT, renewals completed).
Set a baseline before automation goes live so improvements are clear.
Review monthly, not just once a year. Use dashboards or simple reports.
Act on signals. If a KPI dips, adjust workflows instead of waiting.
Rinse and repeat by building monitoring into daily operations so automation keeps pace with business needs.
Tracking the impact of automation shouldn’t be complicated. Insurers need to see clear, measurable results that tie directly to business goals.
Strada makes success easy to track. It delivers outcomes you can see right away:
Higher connection rates with customers.
No missed calls ever.
Gains in satisfaction because service is instant and accurate.
Pre-built insurance workflows, seamless integrations, and quick deployment make it easy to start with RPA and AI in insurance. On top of that, Strada affects revenue.
You can measure policy retention and renewal lift directly, since customers who get quick service are far less likely to churn.
Tracking results today sets you up for tomorrow. No doubt that the future is exciting, but the key is to start now.
Here’s how insurers can take the first step, safely and effectively, toward automation that drives real business impact.
How can insurers get started today?
A few months ago, an operations leader at a mid-sized insurer told me: “We know automation will help, but we don’t know where to start.” That hesitation is common – the potential feels huge, yet the first step can seem unclear.
The good news? Getting started doesn’t require a massive overhaul. With the right approach, insurers can move from idea to impact in weeks, not years. Here’s how:
Pick one process that’s high-impact but manageable: renewals, FNOL, or certificate issuance.
Set clear KPIs upfront, like turnaround time, error rate, or customer satisfaction scores.
Align key teams: loop in IT, compliance, and operations from the start.
Launch a quick pilot with a narrow scope (one line of business, one region, or one workflow).
Measure results fast and compare against the baseline.
Refine the workflow based on what you learn. Small tweaks unlock major gains.
Scale step-by-step into adjacent processes once the first pilot proves value.
At this point, many insurers also look for ways to extend automation beyond internal workflows into direct customer interactions. That’s where Strada comes in.
It makes it even easier.
You can get a demo to explore insurance-specific AI phone agents handling renewals, claims intake, and servicing. It’s quick to deploy, purpose-built, and designed for real insurance workflows. Security is built in, with SOC 2 Type 2 certification, data isolation, and privacy-first LLM policies.
The result is simple: automation that boosts efficiency, improves customer experience, and drives revenue. Start today, measure results quickly, and begin scaling revenue-driving calls with AI.
Pair with Strada, robotic process automation in insurance is finally ready to move from pilot to profit.
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The 2025 Guide to RPA in Insurance Workflows (Updated)
Amir Prodensky
CEO
Sep 22, 2025
14 min read
See how RPA speeds up claims, policies, and back-office tasks.
Insurance runs on processes. Every claim, every policy renewal, every customer call – it’s all a workflow.
For years, RPA in insurance has helped insurers cut costs by handling repetitive back-office tasks. But in 2025, the story has shifted. RPA isn’t just a support tool anymore; it's a core strategy for staying competitive.
What’s new, you might ask?
It’s matured → no longer pilots or experiments, but scaled, proven systems.
It’s expanded → automation now powers customer-facing conversations, not just data entry.
That means RPA in insurance looks very different today.
Take Strada, for instance. It isn’t traditional RPA. it’s a conversational AI purpose-built for insurance. By managing renewals, claims intake, and service requests over phone and SMS, it pushes automation beyond the back office and directly into customer interactions.
And that’s why this guide exists. It will walk you through the latest use cases of robotic process automation in insurance, what’s changing, and how you can put it to work.
And we’ll start with the foundations.
What is RPA in insurance, and why does it matter?
Robotic process automation in insurance may sound complex, but it’s really simple.
Think of it as software “bots” that handle repetitive digital tasks so people don’t have to. For example, a bot can copy customer details from one system into another, process a claim form, or generate a report, all without a human clicking through screens.
In everyday terms, it’s like having a super-fast assistant who never gets tired, makes fewer mistakes, and works 24/7. That’s why insurance is such a natural fit.
Few industries rely more on processes:
Claims must be logged, checked, and approved.
Policies need renewals and updates.
Customer records have to be accurate across multiple systems.
When you look at it this way, you see why the RPA in the insurance sector is growing so quickly. Automating these steps saves time, reduces errors, and frees teams to focus on what matters most – serving customers.
Independent research confirms this momentum.
Deloitte’s global RPA survey found that 53% of businesses have already implemented automation, with adoption expected to become nearly universal within the next two years.
And according to McKinsey, as much as 45% of business tasks can be automated, underscoring just how many opportunities insurers can tap into.
So, foundations? Done.
Next, let’s explore the specific workflows where RPA delivers real value, both behind the scenes and in customer interactions.
What kinds of tasks can RPA in the insurance sector handle?
When you break it down, insurance is a series of repeatable, rule-based tasks. So, let’s look at where RPA creates the most value:
Area | Example tasks | How RPA helps | How Strada extends it |
Claims | FNOL, document validation, routing | Speeds processing, reduces errors | Handles FNOL 24/7 through conversational logging, eliminating hold times. |
Policy servicing | Renewals, endorsements, certificates | Automates updates, ensures accuracy | Proactively calls customers for renewals and answers routine questions instantly. |
Underwriting | Data intake, quote generation | Produces faster, more accurate quotes | Captures quotes over the phone or SMS without waiting for an agent. |
Customer onboarding | Identity checks, compliance steps | Saves time, meets regulatory standards | Provides conversational onboarding that meets compliance while simplifying the experience. |
Finance | Billing, collections, reconciliation | Reduces manual work, improves accuracy | Extends to customer-facing interactions (e.g., payment reminders) for better collections. |
While RPA automates back-office workflows, Strada is not RPA but rather an insurance-specific conversational AI that extends automation into customer-facing phone and SMS interactions.
As a result, instead of replacing RPA, it augments it. Traditional bots handle the data behind the scenes, while Strada manages the phone-based workflows with natural, human-like conversations.
The result is a full stack of automation: back-office accuracy plus front-office engagement. That’s why the use cases of RPA in insurance now span from claims processing to customer experience.
So how do these pieces fit together? Think of it like stacking blocks.
For leaders, this shift matters. It shows automation isn’t limited to cutting costs. It can improve service, retain more customers, and even grow revenue. That’s the real power of combining RPA with AI in today’s insurance workflows.
Now that you know what can be automated, let’s explore why it matters.
What are the main benefits of RPA in insurance?
The real value of RPA in insurance isn’t just speed; it’s how it makes the customer experience better. People want fast answers, no errors, and zero hold times.
When bots handle repetitive steps, customers get smoother service without the usual frustration.
The efficiency gains are huge too. RPA creates compliance-ready audit trails automatically. It reduces costs by eliminating manual effort. And it frees employees to focus on higher-value tasks like solving complex cases or building relationships.
But the biggest story in 2025 is how automation drives outcomes, not just efficiency. Strada is a great example here. Its AI phone agents deliver results you can measure:
85% of calls answered, compared to many missed calls with human-only teams.
24/7/365 availability, no business hours, no downtime.
Infinite scalability without adding headcount.
That changes the game. Instead of simply “doing more with less,” Strada helps insurers grow. More answered calls mean more quotes captured, more renewals completed, and more claims logged on time.
Customers stick around because the experience feels responsive and easy.
Still, even with clear benefits, automation comes with hurdles. Let’s talk about the challenges insurers face and how purpose-built solutions can help overcome them.
What are the biggest challenges in RPA in insurance?
Even with proven benefits, RPA in insurance faces real-world hurdles that slow progress:
Scaling beyond pilots → bots work in tests but stall when rolled out broadly.
Legacy IT integration → connecting modern automation to old systems is harder than expected.
Regulatory compliance → every workflow must meet strict standards, adding overhead.
Employee resistance → staff may fear being replaced instead of supported.
Customer-facing risk → even small errors can break trust and damage brand credibility.
Slow ROI realization → early wins don’t always translate into enterprise-wide impact.
These challenges highlight why many insurers stall in their automation journey. But they also set the stage for the next step: a solution designed specifically to overcome them.
This is where Strada shines. It’s purpose-built for insurance. Its AI understands the nuances of renewals, claims, and servicing. Even better, it has built-in accuracy checks that constantly monitor performance. That means fewer errors, lower E&O risk, and peace of mind.
The result? Automation you can trust.
Strada proves that customer-facing AI can be both efficient and compliant. It helps insurers overcome common roadblocks, legacy systems, scaling hurdles, and regulatory pressure without stress.
Understanding the obstacles is just the start. Next, you’ll learn how to pick the processes that deliver the fastest, most impactful wins, so you can see results quickly and confidently.
How do you choose the right processes for RPA in insurance to automate?
One of the biggest questions leaders face is: where do we start with automation? Not every task is a good fit. The right processes make all the difference.
The sweet spot is clear. Look for tasks that are:
Rule-based → steps follow a clear “if this, then that” pattern.
Repetitive → the same work happens again and again.
High-volume → tasks that eat up hours every week.
These are perfect for RPA because they don’t require judgment or creativity. Think data entry, reconciliations, or document validation.
To find them, many insurers use process mining. It analyzes system logs to reveal which workflows take the most time and where the bottlenecks are. It’s a smart way to prioritize.
To move from theory to action, insurers need a clear, repeatable way to zero in on the right candidates for automation. Here’s a simple, practical process you can follow:
List candidate processes → sit with operations, claims, underwriting, and finance teams. Ask: “Which tasks feel like busywork or bottlenecks?” Capture everything without filtering.
Measure the workload → for each task, note average handling time, frequency, and staff hours per week. Even a rough estimate is enough to see which ones consume the most effort.
Check the rules → document whether the task follows clear decision rules. If humans often need judgment, put it aside; if it’s “if X then Y,” keep it on the list.
Test with a sample → take a day or week’s worth of cases for one process and map the exact steps. This shows whether it’s consistent enough for automation.
Rank by ROI → score tasks on effort saved, error risk reduced, and impact on customer experience. Start with the ones that score highest across these three.
Pilot before scaling → automate one narrow use case (e.g., policy certificate requests) to validate the benefits before rolling out broadly.
If you’re wondering “how do I know which process to start with?” – use this simple decision path:
But here’s a tip: don’t just chase back-office savings. Start with tasks that impact both efficiency and customer experience. When you reduce errors and speed up turnaround, customers notice. That’s where the business impact grows.
Front-office calls are one of the biggest untapped opportunities. Missed calls mean lost revenue. Long hold times hurt retention. Yet most teams still rely on human-only coverage.
That’s changing fast.
Strada makes it simple. Its pre-built, insurance-specific voice workflows cover renewals, claims intake, quotes, and servicing. You don’t need engineers or months of setup. You can identify, launch, and scale conversational automation in days.
This is why RPA in insurance is evolving. It’s not just about automating what happens in the back office. It’s about tackling customer-facing workflows that drive growth.
The practical takeaway:
Use clear criteria (rule-based, repetitive, high-volume).
Apply tools like process mining to prioritize.
Don’t ignore front-office calls, start there for maximum impact.
Use platforms like Strada to accelerate deployment without technical heavy lifting.
Get those steps right, and you’ll build a roadmap that delivers both quick wins and long-term value.
Once you know which tasks to automate, the next step is execution. Here’s a practical, step-by-step approach to rolling out RPA successfully.
So, you’ve got a roadmap in hand, you need the right tools. Let’s explore the platforms leading the charge, from general RPA to insurance-specific AI solutions like Strada.
What RPA tools and platforms stand out in 2025?
When it comes to RPA tools in 2025, you’ve got plenty of options. Some are broad, enterprise-grade platforms. Others are purpose-built for insurance.
Let’s break down the key RPA use cases in insurance from claims to customer onboarding and finance.
UiPath
UiPath is one of the most established RPA platforms and works well for big insurers with complex operations. It handles large volumes of claims, processes documents quickly, and connects with older policy systems.
Key features:
Rich robotics & agentic automation (attended & unattended bots)
Strong document understanding / data extraction
Orchestrator / robot management, governance, process-mining tools
Wide integrations (legacy systems, UI, API)
Pricing: Starts at about US$420/month for a small bundle (attended + unattended bots, Action Center, Studio) for SMEs; enterprise licensing is quoted per deal.
Automation Anywhere
Automation Anywhere is cloud-native and built for scale. Insurers use it to speed up renewals, endorsements, and customer updates, especially when automation needs to run across regions or business lines.
Key features:
Cloud-native Agentic Process Automation system
Strong document automation & AI-powered data extraction
Control Room / Bot Creator tools, collaboration, role-based security
Pre-built bots, large bot marketplace
Pricing: Starting price around US$9,000/year for basic usage-based package (one unattended bot, bot creator, control room); extra bots (attended / unattended) add cost.
Blue Prism
Blue Prism is known for strong security and governance. It’s often chosen for underwriting, compliance reporting, and other processes where accuracy and audit trails are essential.
Key features:
Strong governance, security, audit trails
Capable of enterprise-grade unattended automation
Good support for compliance & regulated workflows
Offers both cloud (SaaS) and on-prem/hybrid deployment options
Document automation, process intelligence, decision automation addons
Pricing: Quote-based; one digital worker (concurrent bot) starts at about US$13,000/year for on-premises deployments; cloud/digital worker bundles may run higher.
Microsoft Power Automate
Power Automate is the easiest option for insurers already using Microsoft tools. It helps automate billing, reconciliations, and the flow of data between Outlook, Excel, Teams, and CRM without heavy setup.
Key features:
Tight integration with Microsoft ecosystem (Office, Teams, Outlook, Excel, Azure)
Both attended and unattended robotic flows
Licensing with “user / bot / process” options, capacity add-ons
Process & task mining available, AI Builder for intelligence in flows
Pricing: Premium plan is ~US$15/user/month for attended / basic cloud flows; “Process” / unattended automation bots ~US$150-US$215/bot/month in many markets.
Here’s a side-by-side comparison to help readers see what trade-offs to expect:
Dimension | UiPath | Automation Anywhere | Blue Prism | Power Automate |
Ease of onboarding | Very good; strong documentation, large user community, many pre-built components. | Also good; cloud-native, many bots/templates; but some steep learning for advanced features. | Moderate; often more complex setup, especially for large/secure/hybrid deployments. | Very easy for Microsoft shops; many users already familiar with the tools. |
Governance & Compliance | Strong; good audit trail, governance controls, role-based access. | Robust; Control Room, security layers. | Very strong; built for regulated environments. | Decent; might need add-ons or extra care for sensitive data or regulatory reporting. |
Scalability for unattended bots | High; can scale to many bots, cloud or on-prem. | High; cloud version supports large bot counts. | High; particularly with enterprise or cloud offerings. | Good; but cost per bot / flow can add up; licensing model matters. |
Cost-efficiency for small deployments | Moderate; small bundles are affordable but enterprise scale gets expensive. | Slightly more expensive initially; but good value where many automations are used. | Less cost-efficient in small deployments due to license floor, worker minimums. | Very good; low entry cost especially if already using Microsoft 365 / Azure. |
Best fit by use case | Legacy systems + high volume document workflows; or mix of attended & unattended bots. | Customer-updates, renewals, cross-region automation; distributed operations. | Regulation, audit, compliance, underwriting; where security and governance are first order. | Internal process automation in MS environment; handling data transfer, simple underwriting tasks or customer service integrations. |
Drawbacks / Considerations | Pricing complexity; managing many licenses / bots can get costly. | Some advanced AI features or integrations may require professional services. | Steeper implementation time; sometimes less flexibility for citizen developers. | Less suited for non-Microsoft ecosystems; some limitations on connectors, unattended scale unless paying higher bot licensing. |
These platforms give insurers the core building blocks for robotic process automation. They’re widely used for back-office processes, integrations, and RPA in insurance claims processing.
But the trend in 2025 isn’t just RPA. It’s RPA combined with AI, which many call “intelligent automation.” That’s where the biggest value is created. Bots take care of repetitive steps, while AI handles conversations, decisions, and customer interactions.
So, while the big platforms are flexible, they’re not specialized.
That’s where Strada stands out. It focuses on insurance front-office calls that directly affect revenue and customer retention. Strada combines RPA and AI in insurance to automate back-office and front-office workflows seamlessly.
Here are a few Strada’s strengths:
Feature | What it does | Benefit |
Pre-built insurance workflows | Renewals, FNOL processes, servicing, and quote intake | Launch automation quickly with tasks ready to go |
Seamless integrations | Connects with policy & claims systems, AMS, and APIs | Keeps data flowing without manual effort |
Quick deployment | No engineering lift required | Voice AI agents can be up and running in days, not months |
Real-world adoption is already strong. Carriers, MGAs, and brokers are using Strada to scale conversations without adding headcount. Instead of missed calls, they now capture more quotes, process more claims, and retain more customers.
Take the example of the Aimee AI agent. Embedded insurance provider, Tint, deployed Aimee to handle after-hours calls for policy servicing and claims intake.
Within the first month, Aimee answered hundreds of calls that would have otherwise gone to voicemail. Customers got help instantly, and Tint saw customer satisfaction improve.
That’s the kind of practical, measurable impact automation should deliver.
And here's why it matters: the RPA landscape is maturing. General platforms are excellent for back-office efficiency. But insurers also need tools that move the needle on customer experience and revenue. Strada proves that automation can be both specialized and powerful.
Here are a few use cases of RPA in insurance:
Use broad RPA platforms like UiPath or Automation Anywhere for process-heavy back-office automation.
Combine them with AI-driven tools to deliver intelligent automation.
Deploy specialized platforms like Strada to capture the front-office opportunity.
In other words, don’t just think about automation as “cost-cutting.” Think about it as growth. RPA in insurance is no longer limited to forms and compliance, it’s now about conversations, retention, and customer trust.
Tools are only part of the story. To see if automation really works, you need clear metrics and ongoing measurement.
How do you measure success with robotic process automation in insurance?
Measuring success with automation isn’t just about saying, “We deployed bots.” You need clear KPIs to prove value and keep improving.
To evaluate the impact of robotic process automation in insurance, track both operational and customer-facing metrics.
Start with the basics
Core operational metrics show how well your automation works:
Cost savings → fewer manual hours, lower overhead.
Error reduction → fewer mistakes in claims, billing, and compliance.
Turnaround times → faster processing for claims, renewals, and onboarding.
Compliance adherence → consistent audit trails and reduced risk.
These metrics make a strong business case. But they only tell half the story. Customers care about speed, accuracy, and ease. That’s why you should track at the high level:
KPI type | Example metrics | Why it matters | Typical benchmarks |
Operational | Cost savings, fewer errors, faster turnaround, compliance rates | Shows how much time and money automation saves while reducing risk. | 40–60% cost reduction, 60–80% fewer errors, 30–50% faster cycle times |
Customer | CSAT, NPS, policy retention | Reflects how automation improves service quality, satisfaction, and loyalty. | CSAT >85%, NPS +30 or higher, policy retention +5–10% |
Business impact | Number of calls answered, renewals completed, FNOLs logged | Proves automation drives growth by capturing more revenue and reducing lost business. | 50–70% of routine calls answered by automation, 10–20% increase in renewals processed, 24/7 FNOL capture with 60% touchless rate |
Together, these numbers show whether automation improves the customer experience, not just internal efficiency.
Continuous monitoring matters
Automation isn’t static. Processes evolve, customer expectations rise, and regulations change. That’s why you should monitor KPIs regularly and refine workflows over time. Small tweaks often unlock big gains.
Here’s how to build a continuous monitoring culture:
Pick 3–4 core KPIs (e.g., error rate, turnaround time, CSAT, renewals completed).
Set a baseline before automation goes live so improvements are clear.
Review monthly, not just once a year. Use dashboards or simple reports.
Act on signals. If a KPI dips, adjust workflows instead of waiting.
Rinse and repeat by building monitoring into daily operations so automation keeps pace with business needs.
Tracking the impact of automation shouldn’t be complicated. Insurers need to see clear, measurable results that tie directly to business goals.
Strada makes success easy to track. It delivers outcomes you can see right away:
Higher connection rates with customers.
No missed calls ever.
Gains in satisfaction because service is instant and accurate.
Pre-built insurance workflows, seamless integrations, and quick deployment make it easy to start with RPA and AI in insurance. On top of that, Strada affects revenue.
You can measure policy retention and renewal lift directly, since customers who get quick service are far less likely to churn.
Tracking results today sets you up for tomorrow. No doubt that the future is exciting, but the key is to start now.
Here’s how insurers can take the first step, safely and effectively, toward automation that drives real business impact.
How can insurers get started today?
A few months ago, an operations leader at a mid-sized insurer told me: “We know automation will help, but we don’t know where to start.” That hesitation is common – the potential feels huge, yet the first step can seem unclear.
The good news? Getting started doesn’t require a massive overhaul. With the right approach, insurers can move from idea to impact in weeks, not years. Here’s how:
Pick one process that’s high-impact but manageable: renewals, FNOL, or certificate issuance.
Set clear KPIs upfront, like turnaround time, error rate, or customer satisfaction scores.
Align key teams: loop in IT, compliance, and operations from the start.
Launch a quick pilot with a narrow scope (one line of business, one region, or one workflow).
Measure results fast and compare against the baseline.
Refine the workflow based on what you learn. Small tweaks unlock major gains.
Scale step-by-step into adjacent processes once the first pilot proves value.
At this point, many insurers also look for ways to extend automation beyond internal workflows into direct customer interactions. That’s where Strada comes in.
It makes it even easier.
You can get a demo to explore insurance-specific AI phone agents handling renewals, claims intake, and servicing. It’s quick to deploy, purpose-built, and designed for real insurance workflows. Security is built in, with SOC 2 Type 2 certification, data isolation, and privacy-first LLM policies.
The result is simple: automation that boosts efficiency, improves customer experience, and drives revenue. Start today, measure results quickly, and begin scaling revenue-driving calls with AI.
Pair with Strada, robotic process automation in insurance is finally ready to move from pilot to profit.
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Phone AI agents for insurance distribution
© 2025 Strada API, Inc.
Phone AI agents for insurance distribution
© 2025 Strada API, Inc.
Phone AI agents for insurance distribution
© 2025 Strada API, Inc.