Rearchitecting insurance customer experience for the MCP generation
AI is transforming how insurers serve policyholders, detect risk, and operate across increasingly complex technology environments. But one question stands above the rest: Who controls the future of your policyholder and employee experiences, you or your technology vendors?
At Avaya, we believe the answer should be you. That is why we are embracing the open future of AI, building the Avaya Infinity® platform to support Model Context Protocol (MCP).
It is the right move for insurers that need to innovate without abandoning trusted systems, sensitive data, established workflows, or the governance requirements that protect their customers and their business.
What is MCP?
MCP stands for Model Context Protocol, an emerging open standard that enables AI models such as GPT, Claude, or Gemini to securely and reliably interact with external tools, data sources, APIs, and user context in a structured way.
For insurers, this can give AI access to the context needed to understand a policyholder, claim, policy, interaction history, or servicing request across multiple systems. Instead of operating in isolation, AI can work with relevant enterprise context, established workflows, permissions, and operational intent.
The result is AI that can become significantly more useful in high-stakes insurance environments where accuracy, security, continuity, and trust matter.
"This is not a 'wait-and-see' moment. Avaya believes the time to be intentional about building the definitive open orchestration engine for the modern enterprise is now."
David Funck, Chief Technology Officer, Avaya
How does MCP work?
MCP is built on a client → model → server architecture:
- The Client gathers context such as policyholder information, employee role, current task, permissions, interaction history, or servicing environment.
- The Model such as Claude or GPT receives the context and a list of available tools or actions.
- The Server hosts approved tools, APIs, databases, and enterprise systems and executes authorized actions requested by the model.
All communication follows structured schemas so interactions can be interpretable, traceable, and governed, an essential requirement when AI is interacting with sensitive insurance information and business processes.
Avaya Infinity with MCP: Achieving AI-powered insurance communications intelligence
Insurers can move beyond static dashboards to analyze CX data, uncover trends, and generate real-time views. Supervisors, claims leaders, and servicing teams can explore vital insights while maintaining full system security and data governance.
Removing friction from insurance AI with MCP
For too long, bringing AI into insurance customer experience has meant choosing between two difficult options:
- Lock in to a single provider's closed ecosystem, limiting flexibility as AI models, regulations, customer expectations, and business requirements evolve.
- Create costly, one-off integrations across policy administration, claims, CRM, billing, knowledge, fraud, workforce, communications, and other systems.
This false choice slows innovation and places additional pressure on already complex insurance technology environments. It can also fragment the experience for policyholders and employees, especially when information is distributed across legacy and modern platforms.
Enter MCP, an open, vendor-agnostic standard designed to help AI models interact with tools, data, and operational logic securely and at scale.
Think of MCP as a universal connection layer for AI. Instead of building a different connection between every model and every insurance system, organizations can create a standardized way for approved AI capabilities to access the enterprise context and tools they need.
As the AI ecosystem evolves, this approach can give insurers greater freedom to innovate while maintaining control over the systems, data, workflows, and customer relationships that make their business unique.
MCP enables AI systems to operate with dynamic awareness of customer, employee, session, and business context.
For Avaya Infinity, this means AI models can deliver experiences informed by relevant information across complex insurance environments. A servicing interaction could draw upon approved policy, claim, billing, CRM, knowledge, and interaction data while respecting the permissions governing each source.
That level of contextual intelligence can be especially valuable for insurers managing thousands of employees, workflows, integrations, products, policies, and customer journeys across multiple lines of business.
Shaping the future of open AI for insurance customer experience
Avaya is not just talking about open AI. We are actively helping shape open standards while bringing native MCP support to Avaya Infinity for secure, model-agnostic, enterprise-ready orchestration.
For insurance organizations, that creates three important advantages:
- Control: Gain more control over AI models and tools so you can select capabilities based on the requirements of each insurance use case instead of the limitations of a single vendor.
- Governance: Strengthen interoperability and oversight across customer experience systems, data, workflows, and AI so capabilities can be introduced responsibly.
- Future-readiness: Build an AI architecture designed for complex, regulated environments where security, resilience, auditability, and long-term trust are essential.
Collaboration with Databricks
As part of our commitment to secure, scalable, and open AI, Avaya is collaborating with Databricks to bring enterprise-grade governance and data privacy capabilities to the MCP implementation within the Avaya Infinity platform.
For insurers, this approach can help establish controlled access between AI and the structured and unstructured data distributed across the enterprise.
With fine-grained access controls, audit logging, and governed integration with enterprise data sources, insurers can explore AI-powered customer and employee experiences while maintaining greater visibility into how information is accessed and used.
"Generative AI offers tremendous potential to transform customer experiences, and we are thrilled to collaborate with Avaya to help organizations quickly unify their data, simplify data and AI governance and security, and ultimately deliver AI that understands their business."
Heather Akuiyibo, VP of GTM Integration, Databricks
From fragmented insurance systems to freedom with MCP
A typical insurer may have dozens or hundreds of tools and data sources, including policy administration systems, claims platforms, CRM, billing, knowledge bases, fraud systems, document repositories, data platforms, and workforce applications. At the same time, multiple AI models, copilots, applications, and agents may need controlled access to those systems.
Before MCP, connecting each system to each AI model could require its own point-to-point integration. As the number of systems and AI capabilities grows, so does the development effort, maintenance burden, complexity, and technical debt. MCP changes that paradigm by introducing a standardized intermediary layer. Instead of solving an increasingly complex N x M integration problem, organizations can move toward a more scalable N + M model.
Each enterprise tool can expose approved capabilities through an MCP server, while AI models and applications connect through MCP clients. Once components can communicate through MCP, insurers gain a more flexible foundation for connecting AI with existing and future systems. That can dramatically reduce redundant integration work while protecting investments already made in the technologies and workflows that support policyholders today. This matters because insurance customer journeys rarely live in one application. A single interaction may touch communications, CRM, policy administration, claims, billing, knowledge, authentication, document management, fraud detection, and analytics.
Avaya Infinity with MCP can help connect those technologies, insights, channels, and workflows so insurers can modernize the experience without requiring the entire enterprise architecture to be replaced first.
The potential ROI of MCP for insurers
With MCP, Avaya Infinity users can unlock deeper business value by giving AI access to more relevant context and approved enterprise capabilities.
For insurers, that can mean faster service, more informed claims interactions, more natural conversations, stronger brand consistency, greater employee productivity, and better continuity throughout the policyholder journey.
MCP creates the foundation for generative and agentic AI that is not simply intelligent, but situationally aware of the customer, employee, policy, claim, business process, and permissions surrounding an interaction.
| Before MCP | After MCP | |
| Integration | Custom connectors between individual AI models and insurance systems | A standardized MCP interface can work across models and approved enterprise tools |
| Deployment time | Long, expensive due to bespoke engineering | 50–70% faster, lower costs via reuse (quiq.com, Palma AI, Humanloop, aibase.com) |
| Data access | AI operates with limited visibility into customer and operational context | AI can access approved real-time context across CRM, policy, claims, billing, knowledge, and other systems |
| Risk management | Employees manually search multiple systems to validate information and identify potential issues | AI can assist with cross-system checks and surface relevant information earlier in the workflow |
The future of insurance AI is open
Insurance organizations have spent decades building the systems, processes, data, expertise, and customer relationships that make their businesses unique. They should not have to surrender control of those investments to participate in the AI era. The world's leading AI technology providers are increasingly embracing open, contextual approaches to AI. Avaya shares that vision.
By bringing MCP to enterprise customer experience, Avaya can help insurers connect AI with the systems they already trust, adopt the models that best serve each use case, preserve greater control over their architecture, and continuously innovate as the AI ecosystem evolves.
The future of insurance customer experience should not be defined by a closed technology stack. It should be defined by what your organization can make possible.
Learn how Model Context Protocol reinforces Avaya’s open AI strategy
Glossary
Full glossary of terms below.
| Term | Definition | Why It Matters for Insurance |
| MCP (Model Context Protocol) | An open protocol that standardizes how AI models interact with tools, APIs, and memory via structured context objects. | Creates a scalable way to connect AI with policy, claims, CRM, billing, knowledge, and other insurance systems. |
| Context | A bundle of structured information passed to a model—such as user ID, session history, roles, time, or tool availability. | Helps AI understand the policyholder, employee, claim, policy, and situation surrounding an interaction. |
| Model | The generative AI (e.g., Claude, GPT-4, Gemini) that receives the MCP context and generates responses. | Gives insurers flexibility to select different AI models based on the requirements of individual use cases. |
| Client | The application or interface (e.g., chat window, agent framework, customer portal) that gathers and sends context to the model. | Can include customer portals, employee desktops, virtual assistants, agent applications, and other insurance experiences. |
| Server | The logic layer that hosts tools, APIs, functions, and data sources the model can use via MCP. | Creates a governed way for AI to interact with insurance systems without giving models unrestricted access to enterprise resources. |
| Tools | Discrete functions or APIs (e.g., “search knowledge base,” “check ticket status,” “update CRM”) exposed to the model via MCP. | Allows AI to move beyond conversation and assist employees or customers with real insurance tasks. |
| Schemas | The structured definitions (in JSON or YAML) for how tools and context should be represented and passed to models. | Creates consistency between AI models and insurance systems, making integrations easier to understand, govern, and troubleshoot. |
| Memory | Persistent context retained across sessions (user history, preferences, past actions) provided to the model. | Can enable more continuous policyholder experiences so customers do not have to repeatedly explain the same situation. |
| Ephemeral Context | Short-lived, session-specific information (e.g., current task, temporary variables). | Helps AI remain focused on the immediate servicing, claims, or employee workflow without unnecessarily retaining temporary information. |
| Agent | An AI system that can take actions, invoke tools, and make decisions based on MCP context — often used in autonomous or semi-autonomous workflows. | Provides the foundation for controlled agentic AI that can assist with multi-step insurance processes and workflows. |
| Orchestration | Coordinating multiple steps, tools, and model outputs to achieve a higher-order business goal. | Helps insurers connect customer interactions with the many systems and processes required to complete servicing and claims journeys. |
| Observability | The ability to inspect what context was passed, what decisions the model made, and how tools were used. | Supports the transparency, governance, troubleshooting, and oversight required in highly regulated insurance environments. |
| Interoperability | The ability for different AI models and platforms to work with a shared structure of tools and context. | Gives insurers greater flexibility to evolve their AI strategies without replacing established systems or becoming dependent on a single AI provider. |