Experience Hub: What the Future Contact Centre Looks Like

Jonathan Barouch shares how the Experience Hub bridges AI and human collaboration, shifting focus from speed and metrics to meaningful resolutions, empathy, and customer relationships that drive long-term trust and loyalty. 

Excerpts from the interview:

Do you believe the future contact centre will still need the concept of “handoff” between humans and AI? Or should we be designing journeys where the lines are completely blurred?

There will inevitably be handoffs and escalations, but as AI continues to mature, the distinction between “digital” and “human” will fade, replaced by personalised experiences where customers simply feel supported, and resolution is the ultimate goal. Whether human or digital, agents will shift from reactive responders to proactive collaborators, with human agents overseeing AI-powered digital workers and stepping in as needed to ensure quality.

Best practices and expertise of top agents are embedded into every action, scaling elite performance instantly without the lengthy process of attracting, training and retaining talent. With AI, businesses can bring the knowledge of their best agent to every customer interaction.

At Zendesk, we help make this vision a reality by equipping human agents with AI-powered tools like the Zendesk Agent Copilot. These tools provide real-time insights and tailored response suggestions, enabling agents to deliver faster, more personalised, and empathetic support. 

This seamless blend of AI and human expertise ensures customers receive consistently high-quality service while always having the option to connect with a human when needed.

Many AI-enhanced contact centre tools are still built around efficiency metrics like AHT and deflection. What’s your take on how this obsession with productivity is shaping, or warping, the customer experience?

Productivity metrics like AHT, Occupancy, and even ACW will eventually become irrelevant in a future where customer experience is frictionless, automated, and proactive. 

For example, AHT becomes meaningless when the cost to serve with AI approaches zero—making a 10-minute support call no more costly than a one-hour call. As a result, businesses must shift focus to resolution-centric metrics that prioritise effectively resolving customer issues and delivering the outcomes customers expect.

For Zendesk, a resolution means the issue is truly resolved and the case is closed. We were first to market with resolution-based pricing, and our platform is purpose-built to deliver on this outcome, irrespective of the channel. This is powered by a scalable CCaaS, deep omnichannel capabilities, a robust knowledge base, and advanced AI agents that together unify and streamline the customer journey.

We believe businesses need to rethink customer experience as an ongoing relationship where agents actively manage outcomes, owning resolutions informed by AI-driven insights and holistic context. 

The Zendesk Resolution Platform integrates AI agents, a unified knowledge system, automation, and human expertise to help businesses resolve both customer and employee requests more efficiently and accurately, moving beyond traditional productivity metrics to truly elevate CX.

In a human + machine contact centre, how can one ensure the emotional intelligence of the human agent isn’t eroded by too much reliance on automated prompts or scripts?

The technology in this space is still in its infancy. While AI can already detect customer sentiment and tone, and even adjust engagement in real time, there are clear limits to its capabilities—especially when it comes to replicating genuine human empathy and understanding.

There will always be a natural tension between deploying automation for efficiency and making sure that humans stay in the loop for more complex work or escalations. 

In situations where a customer simply needs to reset a password, for example, most are not looking for emotional intelligence—they just want the issue resolved quickly, whether the interaction is with a human or a digital agent.

To ensure emotional intelligence isn’t eroded, it’s important that automation is reserved for routine, transactional tasks, while human agents are empowered and supported to manage the complex, sensitive, and high-value interactions where their EQ is essential. 

At Zendesk, our approach is to blend smart AI automation for repetitive tasks, freeing up human agents to focus on the moments that require empathy, creativity, and strengthening customer connections.

You’ve probably seen customers who no longer want service; they want resolution, ownership, and empathy in real time. How can the Experience Hub model respond to this psychological shift?

As customer expectations evolve, the Experience Hub model will unify all interactions and data across channels, transforming the contact centre into the connectivity tissue of the customer journey. This ensures that every individual’s history and needs are recognised, while agents are equipped with a real-time, 360-degree view to support personalised experiences.

We believe businesses need to shift their mindset toward prioritising an “ongoing relationship” with customers. Within this model, agents can actively manage outcomes and own resolutions, informed by AI-driven insights and holistic context. 

The Experience Hub ultimately positions itself as the strategic heart of the brand, cultivating trust and loyalty, rather than just functioning as a traditional call centre.

What kinds of organisational changes do you believe are necessary before a contact centre can truly become an Experience Hub? Where do most companies get stuck?

Becoming a true Experience Hub requires more than new technology—it demands a fundamental rethinking of how contact centres operate, including the transformation of workflows, team structures, and organisational culture. 

AI is central to this shift, automating routine, repetitive tasks across channels and freeing agents to focus on complex, high-value interactions that require empathy and judgment. This enables agents to become proactive supervisors, managing AI-powered automation at scale while embedding their expertise at every customer touchpoint.

Many organisations get stuck due to legacy systems and siloed departments, which prevent seamless integration between support and other teams and result in fragmented customer experiences. 

Even as digital channels proliferate, voice remains the most natural and trusted way for customers to engage. In this context, AI’s role is not to replace the human voice but to enhance it.

For businesses aiming to transform their contact centres, the critical questions are: 

– How can AI be thoughtfully integrated to elevate the customer experience? 

– How should workflows and organisational structures evolve to support this new approach? 

– And how can the unique value of voice be preserved and amplified in a multichannel world? 

Addressing these considerations will define the next generation of customer experience.

Where most companies falter is in viewing technology as a silver bullet, underestimating the organisational and cultural change required. Real success depends on leadership fostering a culture of experimentation, rewarding collaboration, and shifting incentives toward delivering customer resolutions rather than focusing on isolated productivity metrics.

When everything is orchestrated, from tone of voice to resolution pathways, how do you ensure the experience still feels human to the customer? What does “authenticity” even mean in this future model?

I would actually challenge the premise of the question. The assumption seems to be that future Experience Hubs will simply involve humans interacting with other humans or automated agents dutifully fulfilling human commands. In reality, future support models are likely to be far more complex, multi-modal, and cross-channel. 

For example, a customer journey may begin with an asynchronous message to an AI voice assistant, which then relays the request to an automated service agent on a platform like Zendesk, using agent-to-agent APIs to resolve issues with the brand. 

If the request can’t be fulfilled, data is passed back to the voice assistant, which may need to gather additional context from the human customer. In this future, what does “authenticity” mean? It’s less about replicating traditional human interaction and more about delivering highly personalised, seamless service. 

While the user experience must remain tailored to individual needs, authenticity in this context is about providing genuine, effective support—regardless of whether it’s delivered by a human or an AI-powered system.

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