Zendesk launches public directory to help AI agents find A2A service options for customers

Zendesk has unveiled a public directory designed to help AI agents find and connect with verified brand support channels and AI agents. 

It's the first time a CX solution provider has launched a product or service to support agent-to-agent (A2A) AKA machine-to-machine (M2M) customer service.

The Zendesk Open Service Directory (OSD) is an open specification and public directory to help personal AI assistants find and connect with verified brand support channels and AI agents. 

According to Zendesk, businesses register their channels, retaining control of the information they share and when human review is required. 

Announcing the launch as part of the Outcome AI platform during its AI Summit this week, Zendesk said OSD does not access private customer data or take service actions and complements protocols that govern communication after an assistant connects. 

CX platforms, AI agent builders and brands are invited to help shape the directory, alongside existing partners Betterment, ElevenLabs, Flex, TeamSystem, TBA Auctions, Telekom Payment S.A. and Wireless Logic.

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What else is offered as part of the Outcome AI platform? 

This is one of four platform features confirmed for Outcome AI. The other developments include: 

Zendesk Bridge

This is an enterprise-grade "trusted and governed" platform for AI agents, which enables businesses to bring an AI interface of their choice and securely connect to Zendesk's AI, service context, workflows and actions, without rebuilding service workflows or switching to a Zendesk-native interface. 

Zendesk says administrators control and govern which AI tools and agents can connect, what information they can access, and which actions they can take. 
It's a plug and play solution that tackles security, policy and permissions.

Every action passes through Zendesk Bridge which applies identity, permissions, policy, human approvals, observability, and audit consistently, so businesses can build differentiated AI-first service experiences without rebuilding ticketing, workflow, compliance, or audit infrastructure.

Self-Improving Zendesk

This connects insights and actions across AI agents, human workflows, knowledge and quality to help teams improve over time.

Specialized Agents

Including both industry and custom agents, this brings domain expertise and business logic directly into service workflows, driving automated resolutions that feed continuous learning across the platform. 

It comprises: 

• Agentic Analytics: To help teams understand performance and identify where to improve. 
• Admin Copilot: Which recommends actions.
• AI Agent Launchpad: Which helps teams find automation opportunities and build, test and scale AI agents. On testing, teams can use Agentic Analytics and Quality Score to see whether changes reduce repeat contacts or improve service quality.

Developing outcome-based pricing models for CX

The final reveal was that all new capabilities will be billed based on "successful outcomes", which Zendesk defines as "the next evolution of the resolution-based pricing model it pioneered".

This element is called Zendesk Unlimited and marks a move away from traditional seat-based software consumption models. 

Outcome AI Platform plans give users access to Zendesk AI, with features varying by tier. Clients set an "outcome budget" and pay for eligible issues resolved and business work completed. 

Spend is tied to two kinds of outcomes: 

1. Conversational outcomes: When an issue is successfully addressed within a customer interaction.
2. Operational AI outcomes: When an automated workflow is completed across business systems.

Lucy Field, VP of product, said: "We're giving customers more freedom to automate with AI and bringing more people in to help resolve customer issues. Unlimited seats and a flexible Outcome Budget help teams resolve issues their way, with the visibility and safeguards they need to stay in control."

Zendesk says platform users can automate up to 84 percent of service requests, cut resolution times "from hours to minutes", and improve customer satisfaction (CSAT). 

Zendesk evaluates each outcome for quality and completeness, so users can see what counts toward their budget. They can start with a low upfront investment and expand as AI delivers more work and outcomes for their business.

The pricing model is a clear step away from the resolution-based models many vendors have built their business on. 

Zendesk explained: "Resolution is a milestone, but the outcome is what matters, and it now has to happen in more places than ever. A customer may ask a personal AI assistant, like Muse, for help. An employee may start in Slack. Increasingly, the first 'person' a company hears from will be someone's AI agent." Its Outcome Platform can "deliver better outcomes wherever service begins"    

In June, Salesforce announced a pay-per-resolution agent for Agentforce, but did not define what "resolution" means. 

Zendesk aims to solve some of the greatest challenges CX faces

The product suite tackles some of the biggest and most persistent challenges CX faces head on, such as a lack of preparedness for machine customers, an inability to measure the benefits of AI in customer service, and AI use that is difficult to scale because of budget constraints. 

Zendesk's own research has found: 

• Among CX leaders, 79 percent say traditional metrics alone can't capture the full impact of AI-driven service. 
• Among customers, 83 percent believe customer experience should be far better than it is today, and 88 percent say the quality of service they receive strongly influences what they buy.
• Nearly two-thirds of consumers already use AI more than they did a year ago, driving expectations that use cases will soon extend into service. 

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