Conversational AI in Insurance: 2025 Guide to Automation, CX, and Claims Efficiency

Why Conversational AI Matters in 2025

The insurance industry is facing compounding pressures in 2025, including customer expectations for instant digital service, labor shortages in key roles, and increasing demands for operational efficiency. At the same time, generative AI is moving from hype to enterprise-grade adoption. 

Conversational AI, which combines natural language processing (NLP), large language models (LLMs), and real-time orchestration, is now a strategic capability for insurance providers.

According to Deloitte, 75% of insurers are either piloting or scaling conversational AI solutions, targeting use cases like automating claims processing, policyholder self-service, and multilingual support. This technology is no longer a chatbot experiment.

When properly deployed, it can resolve 60-80% of customer inquiries without human agents, significantly reducing average handling time and boosting customer satisfaction.

What Is Conversational AI?

Conversational AI refers to systems that can understand, interpret, and respond to human language with accuracy and context-awareness.

Unlike traditional insurance chatbots, which rely on scripted rules, modern conversational AI platforms use a combination of natural language processing, large language models, and real-time retrieval mechanisms to produce accurate, human-like responses.

What sets enterprise-grade platforms apart is the ability to deploy these conversational AI technologies with explainability, governance, and secure integration into insurance operations.

AgentFlow, for example, supports digital transformation in the insurance sector with confidence scoring, execution trace logs, and model configurability to align with compliance mandates.

Artificial Intelligence in Insurance Impressive Stats

• The market signals are clear: conversational AI in insurance is moving from innovation to core infrastructure.
• The global market is forecast to reach $61.69 billion by 2032, driven by increasing demand for real-time assistance and intelligent automation in customer interactions.
• Within the insurance sector, adoption continues to grow. 79% of insurers use some form of conversational AI technology, and 95% of all customer interactions are expected to involve virtual assistants by year-end.
• More than half of policyholders prefer AI chatbots or virtual agents over phone calls when seeking fast, accurate answers to their insurance needs.

How Conversational AI Works in Insurance

In the insurance industry, conversational AI enables virtual agents to interpret customer needs, access relevant customer data, and deliver real-time, accurate responses through both voice and digital channels.

Whether integrated into messaging platforms, agent portals, or IVRs, these systems operate through three main stages:

• Intent Detection identifies what the customer wants. For example, when a user asks, “Can I process claims through the app?” the AI classifies the task and maps it to the correct workflow.
• Data Retrieval uses semantic search and RAG to access insurance policy documents, underwriting notes, and prior customer interactions. This ensures that the AI response is grounded in source-approved materials.
• Response Generation then constructs a clear, contextual response. If needed, the AI can escalate to a human insurance agent with the full conversation log, ensuring seamless integration and handoff.

These conversational AI solutions support customer engagement across self-service portals, call centers, and digital touchpoints, while maintaining auditability and reducing agent workload.

Use Cases Across the Insurance Value Chain

Conversational AI isn’t limited to one department or use case. It now serves as a foundational layer across the insurance process. Here are the key opportunities insurance companies are targeting.

Use Case #1: Claims Intake & FNOL Automation

Filing a First Notice of Loss (FNOL) is one of the most stressful moments for a policyholder. Conversational AI transforms this process by guiding customers step-by-step, reducing confusion and ensuring a complete, accurate submission. Instead of navigating a long static form, users can simply describe what happened, and the AI extracts structured details automatically.

Conversational AI supports FNOL by:

• Asking clarifying questions to ensure all required information is captured
• Validating policyholder identity and coverage before initiating a claim
• Collecting photos, documents, and incident descriptions directly through chat or voice
• Routing complete submissions to the correct adjuster or claims desk

This reduces back-and-forth communication, decreases cycle time, and improves claim accuracy. In real deployments, conversational AI has brought FNOL completion times down from 18 minutes to under 6, and shortened overall claim cycle time by 22%, allowing adjusters to focus on complex reviews.

Use Case #2: Customer Support Automation

Conversational AI serves as a frontline assistant that handles a wide range of customer service interactions instantly and accurately. Instead of waiting in call queues or navigating complex portals, customers can simply ask questions in natural language and get clear answers. This frees up human agents from repetitive tasks and allows them to focus on high-value or emotionally sensitive cases.

Conversational AI assists customers by:

• Providing real-time information on billing, coverage, due dates, and document access
• Guiding users through simple actions such as password resets or address changes
• Authenticating identity securely before providing personal policy details
• Logging requests directly into CRM or ticketing systems for continuity

For insurers, this translates to shorter wait times, lower support costs, and higher customer satisfaction. One carrier using this approach reduced live-agent handoffs by 63%, saving more than 1,200 monthly hours on routine support interactions.

Use Case #3: Underwriting Support

Underwriting is document-heavy, detail-intensive, and often slowed by missing or incomplete information. Conversational AI acts as a digital intake assistant that interacts with brokers, agents, or applicants to gather the information underwriters need, before it ever reaches their desk.

Conversational AI assists underwriting teams by:

• Collecting applicant or risk details through guided conversations
• Checking submissions for missing documents or inconsistencies
• Pulling historical data, previous claims, or policy information from backend systems
• Summarizing key risk elements with confidence scores to help underwriters make decisions faster

Read this customer story to learn how our AI Agents improved insurance underwriting with over 95% accuracy and streamlined operations.

With this augmented intake workflow, insurers reduce backlogs and accelerate case processing. In one example, conversational + document AI reduced underwriting back-and-forth by 38%, enabling 30% faster approvals for standard cases.

Use Case #4: Multilingual Service

Insurance interactions often break down when customers are not fluent in the primary language used by support teams. Conversational AI eliminates this barrier by delivering consistent, accurate communication across multiple languages, whether spoken or written. This supports inclusive customer experiences across global and multicultural markets.

Conversational AI enhances multilingual service by:

• Handling customer conversations across dozens of languages with contextual understanding
• Translating both user messages and system responses in real time without losing nuance
• Supporting voice-based interactions for customers who prefer speaking rather than typing
• Maintaining consistency in terminology, policy interpretation, and compliance messaging

With multilingual AI, insurers reduce miscommunication, shorten resolution times, and improve NPS among bilingual or non-English-speaking policyholders. Some carriers report up to a 71% reduction in resolution time for non-English queries after adopting AI-driven multilingual workflows.

Use Case #5: Renewals & Cross-Sell

Retaining policyholders and identifying opportunities for additional coverage are core revenue drivers for insurers, yet these processes often rely heavily on manual outreach and time-consuming back-and-forth interactions. Conversational AI automates proactive communication, simplifies renewal decisions, and personalizes upsell recommendations, all while maintaining continuity across channels.

Conversational AI supports renewals and cross-selling by:

• Sending timely, personalized renewal reminders via chat, email, SMS, or app notifications
• Answering coverage, pricing, or eligibility questions instantly and in context
• Identifying upsell or cross-sell opportunities based on customer profiles and protection gaps
• Guiding customers through quote comparisons or upgrade options in natural language

This results in smoother renewal cycles, reduced customer drop-off, and improved conversion rates. Many insurers see measurable lifts in engagement, such as a 44% increase in renewal interactions and a 12% improvement in upsells when AI-driven, multilingual outreach is deployed.

Use Case #6: Voice Integration & IVR Modernization

Traditional IVR systems frustrate customers with rigid menus, long navigation paths, and limited self-service options. Conversational AI transforms voice channels into natural, intuitive experiences where customers can simply “say what they need” and receive immediate help. This improves both call-center efficiency and customer satisfaction.

Conversational AI modernizes voice workflows by:

• Replacing legacy touch-tone menus with natural language understanding
• Authenticating callers securely and retrieving real-time policy or claims information
• Handling routine queries, like claim status or payment confirmation, without agent intervention
• Seamlessly handing off calls to human agents with full context preserved

The result is a major improvement in call outcomes. Insurers integrating conversational AI into IVR systems have seen reductions of 35% in average call duration and 28% increases in first-call resolution rates, while lowering live-agent workload.

Real-World Benefits for Insurers

Conversational AI is delivering results that improve customer service, reduce costs, and boost operational efficiency across insurance firms.

Cost Reduction

AI agents automate routine tasks, freeing the customer service team to handle complex issues. Insurance companies report measurable cost savings and fewer escalations to human agents.

Faster Resolution

With intelligent routing and machine learning-backed reasoning, customer queries are handled in seconds, not minutes. This speeds up every step in the insurance process.

Improved Customer Experience

Conversational AI enables always-on, multilingual coverage with natural language fluency, meeting evolving customer expectations for efficient services.

Operational Agility

With AI handling documentation, self-service, and claims triage, insurers can scale their insurance product lines without expanding headcount.

Implementing Conversational AI in Insurance Companies

Here are some steps we recommend for successful implementation:

• Assess organizational needs and use cases: Identify the areas where conversational AI can deliver the most value, such as customer support or claims management.
• Choose the right AI solutions and vendors: Select tools like Conversational AI and Database AI that align with your goals, and choose your vendor wisely.
• Check for compatibility with legacy systems: Confirm compatibility with your existing insurance systems and digital channels.
• Ensure accuracy with model fine-tuning and training: Train AI models on relevant data. Tailor them to your company’s specific needs to ensure accurate and context-aware performance.
• Train your employees: Conversational AI should be a partner for insurance agents. Train staff to collaborate effectively with AI Agents, ensuring a seamless transition.
• Monitor performance: Continuously leverage customer feedback and analytics to refine and enhance AI system functionality.
• Ensure data security, privacy, and compliance: Implement strong protocols to safeguard sensitive information and adhere to regulatory requirements.
• Manage bias risks: Conduct regular evaluations to identify and address biases in AI systems, ensuring equitable and accurate outcomes.
• Pilot project or POC: A pilot or proof of concept (POC) are great ways to evaluate the AI solution's effectiveness before scaling it organization-wide.

Security, Compliance & Legal Considerations

Conversational AI must operate within insurance's strict regulatory environment. Below are the safeguards built into AgentFlow:

• Data residency: All customer data is deployed within the customer’s VPC or on-prem environment.
• Encryption: AES-256 encryption at rest and TLS 1.3 in transit protect sensitive customer information.
• Access controls: Role-based access management integrates with AD, LDAP, and MFA.
• Audit logging: Every AI decision is logged with a timestamp, input/output hash, and confidence score.
• Regulatory alignment: Frameworks like IFRS 9, CECL, and GDPR are supported via embedded protocols.
• Model governance: Retraining cycles, drift monitoring, and validation ensure ongoing compliance.
• Liability guardrails: Human-in-the-loop oversight limits regulatory exposure and reputational risk.
• Confidentiality zones: Customer data and models are isolated, ensuring no cross-tenant leakage.
• Incident response: Automated patching and 24/7 support deliver enterprise-grade uptime and recovery.

Our AI Agent Recommendations

Multimodal has developed AgentFlow, an all-in-one agentic AI platform designed specifically for the insurance industry. It orchestrates dozens of purpose-built AI agents to automate complex processes, reduce friction between existing systems, and ensure traceability in every AI decision. AgentFlow helps insurance companies scale process automation while improving accuracy, compliance posture, and customer relationships.

To deliver this next-generation capability, we recommend starting with two core AI agents:

Conversational AI

Why? Conversational AI enhances customer and employee interactions by delivering instant, contextually relevant responses across digital channels.

Features:

• Personalized responses: Utilizes NLP to understand and reply to inquiries in a human-like manner. This ensures each interaction feels tailored to the individual, even for non-technical users.
• Domain knowledge fine-tuning: Incorporates domain-specific knowledge through fine-tuning, ensuring responses are highly relevant to insurance workflows.
• Multilingual support: Communicates effectively in multiple languages, broadening your reach and improving accessibility for a diverse customer base.
• Seamless integration: Integrates with your existing systems, including core insurance platforms, to provide accurate and timely information.
• Explainability and confidence scoring: Provides insights into "how," “what, “and "why" for every action with a generated answer. It also offers confidence scores that enhance trust in its outputs.
• Decision support and feedback loop: Incorporates user feedback (e.g., upvotes or downvotes) and employee-in-the-loop actions to continuously improve its accuracy and performance over time.
• Audit trails for compliance: Maintains detailed records of interactions to support compliance and regulatory needs. These are essential in the highly regulated insurance sector.

Applications:

• Customer onboarding: Guides new customers through the onboarding process, simplifying policy setup and enhancing the initial user experience.
• Routine task automation: Handles common customer inquiries and internal requests, freeing up staff to focus on more complex tasks.
• Claims process automation: Simplifies claims filing and tracking.
• Customer inquiries: Resolves routine queries efficiently.
• Personalized insurance advice: Offers tailored insurance recommendations based on individual customer data, helping clients make informed decisions.
• Complex workflow assistance: Aids in multi-step, high-stakes tasks by surfacing contextual information from multiple sources, ensuring reliability, and reducing errors and hallucinations.

Database AI

This agent connects to structured data systems to resolve knowledge queries and support underwriting processes. It’s ideal for analyzing customer data, querying policy records, and delivering accurate insights from enterprise databases. Includes schema awareness, audit trails, and seamless integration into existing policy platforms.

Insurance Companies' Future Is Conversational AI Solutions

Conversational AI is evolving quickly, and insurers will soon benefit from more intelligent, proactive, and multimodal capabilities. These advancements will transform AI from a support tool into a core operational layer.

Proactive Engagement

AI agents will shift from reactive responses to proactive outreach, sending renewal reminders, prompting missing documents, and surfacing fraud signals before issues arise.

Multi-Agent Collaboration

Insurers will increasingly adopt multiple specialized AI agents like Conversational AI, Database AI, and Document AI that work together to automate end-to-end workflows across claims, underwriting, and service.

Multimodal Understanding

Next-generation AI will combine text, voice, images, and documents, enabling faster claims triage, more accurate damage assessment, and smarter underwriting decisions.

Institutional Knowledge Capture

AI will help preserve the expertise of senior adjusters and underwriters by learning from their decisions, ensuring consistent reasoning as the workforce evolves.

Enhanced Governance & Compliance

Expect stronger guardrails: better auditability, bias detection, and explainability to meet regulatory requirements and maintain trust.

These trends point to an industry where AI becomes an integrated partner, augmenting human teams, improving decision quality, and accelerating every stage of the insurance journey.

Interested in Conversational AI for Insurance?

Are you ready to leverage Conversational AI and Database AI for insurance to enhance customer experience, streamline processes, and reduce costs? Schedule a free 30-minute call with our experts today!