Sydney, Australia – Businesses are increasingly using teams of artificial intelligence (AI) agents to manage interactions with customers’ personal AI assistants, as agent-to-agent communication becomes more common in customer service operations.
Research involving 118 customer service practitioners across more than 70 organisations using NiCE products found that approximately six in ten respondents were already employing multi-agent ecosystems. The findings also indicate that businesses are developing orchestration, identity verification and governance controls to manage interactions between personal and enterprise AI agents.
Within organisations, multiple AI agents are being used to handle different stages of customer service processes. One agent may identify a customer’s intent, another retrieve account information, while a third routes the case or initiates follow-up actions. Respondents associated these arrangements with faster issue resolution, reduced manual work and more consistent customer experiences.
Businesses are also encountering personal AI agents acting on behalf of customers and partners. Examples include personal agents scheduling appointments and customer service agents coordinating with logistics partners’ agents.
More than half of respondents identified oversight, auditability, human-in-the-loop controls or unified interaction logs as important measures for expanding automation while maintaining visibility and control.
Some organisations have reported operational improvements from these interactions. A propane distributor uses a customer-facing agent to handle delivery and billing enquiries through direct communication with telemetry and routing systems. A healthcare technology provider reported that agent-to-agent hand-offs had reduced most after-call work while improving documentation quality and case-closure times.
“We are increasingly seeing customer-side personal AI agents interacting directly with our front-line virtual agents to negotiate appointments, clarify account details or initiate service requests without a human present on either side. This has dramatically reduced call hold times and human agent handling time for routine queries,” said an engineer at a global transportation company.
“NiCE helps us manage this transition by maintaining strict intent-verification workflows, ensuring API security at the routing layer, and providing unified interaction logs so our human supervisors can monitor agent-to-agent dialogue in real time,” the engineer continued.
A UK energy utility has also reported an increase in automated customer interactions. “We went from 0% of interactions being handled via end-to-end automation to almost 35% of all interactions being effectively contained within an AI agent,” said its head of customer experience.
“What we’re seeing is a shift from AI assistants supporting people to AI agents collaborating with other AI agents to complete end-to-end tasks. That creates significant opportunities around speed, scale and automation,” said a non-clinical performance manager at a UK urgent and integrated care provider.
“NiCE provides visibility and control over these interactions. It centralises customer engagement data, tracks automated actions and ensures AI-driven processes remain auditable and aligned to business rules,” said a customer service planner at a global building technologies company.
“This gives me confidence that automation is improving efficiency without losing oversight or customer experience,” the planner continued.
“Our customers are telling us something important: agent-to-agent AI is not a future state. It is how work already gets done,” said Sascha Poggemann, COO of NiCE Cognigy.
“The organisations scaling fastest are the ones that can see and govern every agent interaction. That is exactly what NiCE is built for: the intelligence, orchestration and oversight that let AI agents work with each other, and with customers’ own agents, at enterprise scale,” Poggemann continued.
NiCE Cognigy supports interactions with customers’ personal AI agents across voice and digital channels, as well as protocols including Agent2Agent (A2A), Model Context Protocol (MCP) and ChatGPT Apps. Its capabilities include identity verification, governance and human oversight.
NiCE CXone brings AI agents, workflows and interaction analytics together in a managed environment. The company is also working with Meta and other partners on the Personal Agent Protocol (PAP), a proposed standard for secure communication between personal and enterprise AI agents.
In Australia, a major insurer has reported an increase in personal AI agent traffic on its quotation and purchase pages, creating challenges in distinguishing potential customers from activity initiated by personal agents. NiCE is working with the insurer to explore ways to accommodate these interactions rather than simply blocking or restricting them.
In New Zealand, a telecommunications and utilities provider has developed a voice-based AI concierge with NiCE’s engineering team. The system allows customers to describe their needs in natural language, verify their identities and troubleshoot internet issues. It can also transfer conversations to human agents with relevant context when further assistance is required. The project is estimated to save between 90 and 120 seconds in average handling time per call.
Another New Zealand healthcare organisation is preparing to deploy Cognigy.AI for voice-based X-ray concierge services, call routing and appointment booking. The implementation is expected to make it one of the first organisations in the country to introduce live voice AI at scale, according to NiCE.
“Across Australia and New Zealand, we’re seeing how AI is creating new opportunities for businesses to transform customer experiences and improve operational efficiency. In Australia, a major insurer is experiencing a significant increase in personal AI agent traffic on its quote and purchase pages, creating new challenges for its digital team in distinguishing genuine customer prospects from activity initiated by personal AI agents,” said Ben Hancock, APAC Lead, Forward Deployed Engineering at NiCE.
“Rather than simply blocking or restricting these interactions, NiCE is working with the customer to explore how our platform can support and accommodate personal AI agents, helping businesses adapt to this emerging trend.
In New Zealand, a leading telecommunications and utilities provider has developed a Voice AI Concierge in collaboration with NiCE Labs’ Forward Deployed Engineering team. The AI agent allows customers to explain their needs in plain language, verify their identity, troubleshoot internet issues and, when necessary, transfer the conversation to a human agent with the relevant context, enabling a more seamless customer experience. With an estimated 90–120 seconds saved in average handling time per call, the project is progressing faster than more traditional AI initiatives, driven by its expected return on investment.
We’re also seeing momentum in the healthcare sector, with another New Zealand organisation preparing to go live with Cognigy.AI by Christmas. The deployment will make it one of the first organisations in the country to implement live Voice AI at scale and the first NiCE customer to use Cognigy.AI for X-ray concierge services, routing and appointment booking. These examples demonstrate how organisations across the region are moving beyond experimentation to apply AI to real-world customer needs and measurable business outcomes,” Hancock continued.
