At Zendesk Relate 2026, a new agent builder, omnichannel AI agents, copilots, and outcome-based pricing were announced to help enterprises deliver more connected customer and employee service.

Imagine this scenario: It is 2027. ABC Corp, an Asia Pacific enterprise, no longer thinks of service as a queue of tickets handed from one team to another. Instead, it runs a blended workforce of human specialists and AI teammates across customer support, IT help, HR operations, and field service.

A customer begins in chat, switches to email, and later calls support; the same AI agent follows the case across channels, carrying full context, language preferences, account history, and prior decisions.

What used to require multiple handoffs now feels like one continuous conversation, with the AI resolving straightforward issues on its own and pulling in a human expert only when judgment, negotiation, or exception handling is needed.

Behind that experience is a network of specialized AI agents, each designed for a different kind of work but coordinated through a common service platform.

One agent handles refunds and subscription changes, another manages warranty claims, and another resolves internal requests such as laptop provisioning, software access, and policy questions for employees. When a case becomes complex, Agent Copilot helps the human representative step in with a complete summary, the relevant procedure, and recommended actions already prepared.

At the same time, Admin Copilot monitors workflow health across the operation, while Knowledge Copilot and Analyst Copilot identify recurring failure points, missing content, and process changes that should be rolled into the next version of service.

Governance is no longer a layer added after automation; it is built into the way the workforce operates. Employee-service agents answer inside Slack and Microsoft Teams, but they respect source-level permissions and only retrieve what each person is authorized to see.

Context Graph preserves operational memory from prior analyses and decisions, while the Knowledge Graph connects the workforce to trusted content across SharePoint, OneDrive, and other repositories.

Quality Score continuously reviews both human and AI interactions, flagging weak resolutions, risky responses, or process drift before problems spread. In practice, this means the system gets smarter without becoming looser: every action is more connected, but also more observable, measurable, and governed.

New business model in the workforce era
The biggest change is not that humans disappear, but that their work becomes more concentrated where human judgment matters most. AI now absorbs the repetitive coordination work that once slowed teams down: collecting facts, retrieving policy, routing requests, updating systems, and closing routine cases end to end.

Human specialists spend more of their time resolving exceptions, rebuilding trust after service failures, refining workflows, and designing better experiences across the business. Because the organization pays for verified resolutions rather than simple automation volume, success is measured by whether problems are truly solved.

In this near-future model, the strongest service organizations are the ones that treat AI not as a replacement for people, but as a disciplined, accountable workforce that expands what people can do well.

Tom Eggemeier, CEO, Zendesk, said: “We believe every business will soon run on specialized AI agents that work alongside human experts as one unified team. These agents will be more than just code; they will be team members, held to the same high standards of accountability as any human.”

However, he warned, while the speed and productivity AI affords us is great, we must not be obsessed with that. Acknowledging he does not have all the answers, his opinion is that organizations still need to learn how to balance employee experience and the power of AI. “The optimized human-AI workforce is an existential question.”

Tom Eggemeier, is optimistic about AI, boldly stating that he believes the transformative force of AI is much bigger than that of the printing press or even the industrial revolution: “While we need to go figure out aspects such as creativity, and find answers to what it all means for humanity, I think what we will see is that there will be many more smaller organizations in the autonomous service workforce, each with fewer employees.”

The Autonomous Service Workforce
At its annual Relate conference in Denver, Colorado, Zendesk announced its vision for the Autonomous Service Workforce, a new approach to customer service powered by its core platform.

This move replaces standard deflection-based bots with specialized AI agents that operate across all channels and use cases, and are priced solely on the outcomes Zendesk verifiably resolves. The strategy addresses a common industry failure where organizations have layered disconnected tools onto legacy workflows, often prioritizing ticket deflection over actual problem-solving.

At the center of this vision is the Zendesk Resolution Platform, a unified system that brings together data, intelligence, knowledge, workflows, and governance. Trained on roughly 20 billion ticket interactions, the platform operates through the Resolution Learning Loop, which captures insights from every interaction to close knowledge gaps and improve automated responses in real time.

“The era of the chatbot – the era of frustration and deflection – is over. We are entering the age of the Autonomous Service Workforce,” said Eggemeier. “Our vision is to put the power to build this workforce into the hands of every enterprise, on one elegant platform. Whether those agents are crafted by Zendesk, by our partners, or by your own teams, they will all speak with one voice. We are providing a future where AI is the foundation, and human experts are the architects.”

Bikram Mazumdar, Vice President, Asia, Zendesk, added: “Across Asia, service is rarely a single-market problem. It is a multilingual, multi-modal and multi-journey challenge that looks very different in Singapore, the Philippines, Indonesia, Hong Kong, South Korea and beyond. As AI resets expectations for what good service should look like, the old model of scaling support linearly simply cannot keep up.”

An autonomous service workforce that enables Asia Pacific enterprises to move beyond the trade-off between efficiency and service quality, he said, helps “bring the precision, context continuity, and governance needed to deliver high-touch support at the pace the region now demands.”

“What’s compelling about Zendesk’s direction is that it recognizes a core truth about service: automation on its own is not enough,” said Daniel Newman, CEO, Futurum Research. “To improve the experience meaningfully, AI has to be part of a broader system that can connect context, take action, and evolve with the needs of the business. That’s the kind of approach that can help organizations build a more scalable and responsive support experience over time.”