Rearchitecting media and entertainment customer experience for the MCP generation
AI is transforming how media and entertainment companies engage audiences, support subscribers, empower employees, and operate across increasingly complex content and technology environments. But one question stands above the rest: Who controls the future of your audience and employee experiences, your organization 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 media and entertainment organizations that need to innovate without abandoning trusted systems, audience data, content workflows, established operations, or the security and governance requirements that protect customers, creators, intellectual property, and the brand.
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 media and entertainment, this can give AI access to the context needed to understand a viewer, subscriber, fan, account, content preference, service issue, advertising relationship, or interaction across multiple systems. Instead of operating in isolation, AI can work with relevant audience and business context, established workflows, permissions, and operational intent.
The result is AI that can become significantly more useful across subscriber care, streaming support, content discovery, fan engagement, advertising services, account management, technical support, and other media environments where speed, personalization, 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 viewer, subscriber, employee, or advertiser information, role, current task, permissions, interaction history, content preferences, or service 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 media systems and executes authorized actions requested by the model.
All communication follows structured schemas so interactions can be interpretable, traceable, and governed, an important requirement when AI is interacting with audience data, subscription information, content rights, advertising workflows, and valuable intellectual property.
Avaya Infinity with MCP: Achieving AI-powered media and entertainment communications intelligence
Media and entertainment companies can analyze audience data for real-time insights. Authorized teams, including CX, subscriber care, operations, advertising, and digital, securely access context under enterprise controls.
Removing friction from media and entertainment AI with MCP
For too long, bringing AI into media and entertainment customer experience has meant choosing between two difficult options:
- Lock in to a single provider's closed ecosystem, limiting flexibility as AI models, audience expectations, business models, content strategies, and digital platforms evolve.
- Create costly, one-off integrations across subscriber management, CRM, streaming platforms, content management, advertising systems, billing, identity, knowledge bases, analytics, and other applications.
This false choice slows innovation and places additional pressure on already complex media technology environments. It can also fragment the audience experience when information is distributed across streaming services, apps, websites, contact centers, advertising platforms, live experiences, and legacy and modern systems.
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 media system, organizations can create a standardized way for approved AI capabilities to access the context and tools they need.
As the AI ecosystem evolves, this approach can give media and entertainment companies greater freedom to innovate while maintaining control over the systems, data, workflows, content, and audience relationships that differentiate their brands.
MCP enables AI systems to operate with dynamic awareness of audience, subscriber, employee, session, content, account, and service context.
For Avaya Infinity, this means AI models can deliver experiences informed by relevant information across complex media and entertainment environments. A subscriber interaction could draw upon approved account, billing, viewing, CRM, entitlement, knowledge, and interaction data while respecting the permissions governing each source.
That level of contextual intelligence can be especially valuable for media companies managing millions of viewers, subscribers, fans, creators, advertisers, content assets, digital interactions, and service relationships across multiple brands and channels.
Shaping the future of open AI for media and entertainment 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 media and entertainment 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 audience, content, advertising, or operational use case instead of the limitations of a single vendor.
- Governance: Strengthen interoperability and oversight across customer experience systems, audience data, content workflows, applications, and AI so capabilities can be introduced responsibly.
- Future-readiness: Build an AI architecture designed for fast-changing media environments where personalization, security, scalability, interoperability, and long-term flexibility 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 media and entertainment organizations, this approach can help establish controlled access between AI and the structured and unstructured data distributed across audience, content, subscriber, advertising, operational, and enterprise systems.
With fine-grained access controls, audit logging, and governed integration with enterprise data sources, media companies can explore AI-powered audience 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 media systems to freedom with MCP
A typical media or entertainment organization may have dozens or hundreds of tools and data sources, including subscriber management platforms, CRM, streaming systems, content management, digital asset management, advertising technology, billing, identity services, knowledge bases, analytics environments, 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, media and entertainment companies can move toward a more scalable N + M model.
Each approved enterprise tool can expose capabilities through an MCP server, while AI models and applications connect through MCP clients. Once components can communicate through MCP, media and entertainment organizations 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, platforms, content operations, and workflows that support audiences today. This matters because media customer journeys rarely live in one application. A single interaction may touch communications, streaming, CRM, subscriptions, billing, identity, entitlements, content systems, advertising, knowledge, and analytics.
Avaya Infinity with MCP can help connect those technologies, insights, channels, and workflows so media companies can modernize the experience without requiring the entire technology environment to be replaced first.
The potential ROI of MCP for media and entertainment
With MCP, Avaya Infinity users can unlock deeper business value by giving AI access to more relevant context and approved enterprise capabilities.
For media and entertainment organizations, that can mean faster subscriber support, more personalized audience engagement, more efficient account and billing assistance, stronger fan experiences, greater employee productivity, and better continuity across digital and service journeys.
MCP creates the foundation for generative and agentic AI that is not simply intelligent, but situationally aware of the viewer, subscriber, account, content preferences, entitlement, service history, and permissions surrounding an interaction.
| Before MCP | After MCP | |
| Integration | Custom connectors between individual AI models and media 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 audience, content, subscription, and service context | AI can access approved real-time context across CRM, subscriptions, streaming, billing, entitlements, knowledge, and other systems |
| Risk management | Employees manually search multiple systems to understand accounts, access issues, content entitlements, billing, or previous interactions | AI can help surface relevant subscriber, content, account, and service information earlier in the interaction or workflow |
The future of media and entertainment AI is open
Media and entertainment organizations have spent years building the content, brands, platforms, systems, audience insights, creative expertise, intellectual property, and fan relationships that differentiate their businesses. 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 media and entertainment companies 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 audience expectations and AI evolve.
The future of media and entertainment customer experience should not be defined by a closed technology stack. It should be defined by how intelligently you can connect every audience, every channel, and every moment.
Learn how Model Context Protocol reinforces Avaya’s open AI strategy
Glossary
Full glossary of terms below.
| Term | Definition | Why It Matters for Media and Entertainment |
| 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 CRM, subscriptions, streaming platforms, content systems, billing, advertising technology, and other media platforms. |
| 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 viewer, subscriber, employee, account, content preference, entitlement, and situation surrounding an interaction. |
| Model | The generative AI (e.g., Claude, GPT-4, Gemini) that receives the MCP context and generates responses. | Gives media organizations flexibility to select different AI models based on personalization, performance, security, cost, creative, or use-case requirements. |
| Client | The application or interface (e.g., chat window, agent framework, customer portal) that gathers and sends context to the model. | Can include streaming apps, subscriber portals, employee desktops, virtual assistants, fan applications, and contact center interfaces. |
| 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 media systems without giving models unrestricted access to audience data, content, or 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 audiences and employees with real media and entertainment service 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 media systems, making integrations easier to understand, govern, scale, and troubleshoot. |
| Memory | Persistent context retained across sessions (user history, preferences, past actions) provided to the model. | Can enable more continuous and personalized audience experiences across channels and over time. |
| Ephemeral Context | Short-lived, session-specific information (e.g., current task, temporary variables). | Helps AI remain focused on the immediate audience or service need 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 subscriber care, account, content, advertising, and service workflows. |
| Orchestration | Coordinating multiple steps, tools, and model outputs to achieve a higher-order business goal. | Helps media organizations connect audience interactions with the many platforms, applications, teams, and workflows required to deliver seamless experiences. |
| Observability | The ability to inspect what context was passed, what decisions the model made, and how tools were used. | Supports transparency, governance, troubleshooting, security, and oversight when AI interacts with audience, content, account, and enterprise information. |
| Interoperability | The ability for different AI models and platforms to work with a shared structure of tools and context. | Gives media and entertainment organizations greater flexibility to evolve their AI strategies without replacing established systems or becoming dependent on a single AI provider. |