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.

Read the press release

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.

MCP Illustration on how it works

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.

Innovate on your terms with an open, model-agnostic platform
  • Choose the right LLM or AI capability for each audience, subscriber, advertising, content, or operational use case without being locked into a single model provider.
  • Let AI securely access approved information from CRM, subscriber management, streaming platforms, content systems, advertising technology, billing, knowledge bases, and other sources where your audience and business truth lives.
  • Future-proof your ecosystem so new models and tools can be introduced without repeatedly rebuilding the integrations that connect AI to your media environment.
Deliver contextual experiences that turn audiences into loyal fans
  • Create flexible CX environments informed by viewing history, subscriptions, preferences, previous interactions, content interests, account status, intent, and journey context.
  • Give subscriber care representatives, fan support teams, advertising specialists, digital service teams, and other employees a more complete view across touchpoints, systems, and time.
  • Help employees access the knowledge and context they need to provide faster, more personalized, and more consistent experiences across voice and digital channels.
Build with enterprise-grade trust, security, and governance at scale
  • Apply zero-trust principles so AI interactions can pass through governed gateways with defined identities, permissions, and access controls.
  • Use auditability and tool-level controls to help support privacy, security, intellectual property protection, content rights, compliance, and enterprise governance.
  • Keep human judgment in the process for sensitive or high-impact actions, helping media organizations accelerate work with AI while maintaining appropriate oversight.

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.
Agentic AI Foundation and Linux Silver Member Logo

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

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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 MCPAfter MCP
IntegrationCustom connectors between individual AI models and media systemsA standardized MCP interface can work across models and approved enterprise tools
Deployment timeLong, expensive due to bespoke engineering 50–70% faster, lower costs via reuse (quiq.com, Palma AI, Humanloop, aibase.com
Data accessAI operates with limited visibility into audience, content, subscription, and service contextAI can access approved real-time context across CRM, subscriptions, streaming, billing, entitlements, knowledge, and other systems
Risk managementEmployees manually search multiple systems to understand accounts, access issues, content entitlements, billing, or previous interactionsAI 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.

Glossary

Full glossary of terms below.

TermDefinitionWhy 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.
ContextA 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.
ModelThe 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.
ClientThe 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.
ServerThe 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.
ToolsDiscrete 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.
SchemasThe 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.
MemoryPersistent 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 ContextShort-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.
AgentAn 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.
OrchestrationCoordinating 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.
ObservabilityThe 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.
InteroperabilityThe 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.