What if your personal AI assistant could call customer service for you—and actually get things done?

Personal AI agents like Muse are changing how we interact with technology, helping us manage information, make decisions, and take action on our behalf. Meanwhile, businesses are deploying AI agents to handle customer questions, troubleshoot problems, and manage service requests. But what happens when these two worlds meet? What if your agent could communicate directly with a company's customer service agent, without you having to navigate a phone tree, repeat your account details, or explain your problem for the third time?

In this talk, we'll explore the emerging possibilities of agent-to-agent communication between personal assistants and enterprise customer service systems. We'll examine how these agents might exchange context, establish intent, authenticate users, negotiate available options, and coordinate actions to resolve customer needs. We'll also look at the technical and design challenges behind making this interaction work, from interoperability and identity verification to permissions, privacy, trust, and knowing when a human needs to step in.

Drawing on my experience as a Forward Deployed Engineer at NiCE Cognigy, we'll connect the possibilities of personal AI to the realities of enterprise conversational AI. Through practical examples and demonstrations, we'll explore what it takes to move from agents that simply answer questions to agents that collaborate across organizational boundaries.

The future of customer service may not be a conversation between a person and a bot. It may be a conversation between two agents, working together on behalf of the people they serve.
Intended audience
Software developers, AI engineers, conversational AI practitioners, and anyone interested in agentic AI, AI interoperability, and the future of customer experience.

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