AI Didn’t Replace the Contact Center; It Redefined It

For the past year, one theme has been impossible to ignore: investment in AI for customer experience has surged, and expectations have surged right alongside it. 

At Liveops, we spent time with enterprise leaders across retail, financial services, insurance, consumer brands, and more who are actively building the next version of their support operations. The takeaway was consistent and refreshingly honest. 

The question is no longer whether to invest in AI. The real question is how to use it in a way that improves outcomes, without compromising trust, quality, or the human moments that make support work in the first place. 

Many of the organizations in the room had already deployed AI in some form. But a second reality surfaced quickly: adoption is high, and in many cases the early wins are starting to plateau. 

This is not because AI is disappointing. It’s because the industry is shifting from experimentation to execution, and execution is where the hard parts live. 

Orchestration. Integration. Accountability. Governance. Operational ownership. Real change management. 

And that is exactly where the contact center is being redefined. 

AI is absorbing volume, not replacing humans 

The most practical view shared by leaders was also the clearest: AI performs best when it reduces volume and handles intent, not when it tries to mimic empathy, judgment, or complex resolution. 

The use cases gaining traction are not flashy. They are effective. They remove friction and create capacity. 

Common examples discussed included: 

• Self-service containment and deflection 

• Intent classification and smarter routing 

• Case summarization embedded directly into CRM workflows 

• Automated quality analysis and customer satisfaction insight 

Several brands noted that voice bots alone are already reducing live call volume by roughly 10 to 15% in certain interaction types, especially repetitive requests. The important nuance is what comes next. 

This is not about eliminating people. It is about reshaping the work. 

As AI takes on simpler, transactional interactions, live agents become the team that handles the conversations that actually require a human. The high stakes conversations. The emotional conversations. The ones where context matters and the answer is not sitting cleanly in a single knowledge article. 

Some leaders even shared that they expect average handle time to increase for live agents, and they are fine with that. The remaining calls are more complex by design, so they should take longer. The goal is not speed for its own sake. The goal is resolution, clarity, trust, and outcomes. 

Want the customer side of this story? Explore the Liveops Holiday AI and Customer Service Report to see why shoppers still prefer human support when it matters most.

Read the report

The next frontier is agent enablement, not automation 

If there was one area of strong consensus, it was this: the biggest untapped opportunity for AI in customer experience is agent enablement. 

Not automation for automation’s sake. Enablement that makes humans better in the moment. 

Leaders are prioritizing tools that help agents do three things faster: understand, decide, and act. 

The capabilities they want most look like this: 

• Real time guidance during live interactions 

• Flags for incorrect answers, with better alternatives suggested instantly 

• Next best action recommendations based on the situation, not generic scripts 

• Context surfaced proactively, so agents do not have to hunt across tabs and systems 

When AI is used this way, it stops being a cost-cutting play and starts becoming something more valuable: a performance multiplier. 

It helps agents stay confident, consistent, and accurate. It reduces cognitive load. It supports better decision-making. And it improves the experience for the customer because the agent is not scrambling to stitch together the story while the customer waits. 

This shift matters because it changes what leaders measure. Instead of asking, “How many interactions can we deflect?” teams start asking, “How many moments can we improve?” 

Governance and integration matter more than novelty 

As AI becomes embedded in daily operations, governance has moved to the center of the conversation, and for good reason. 

Leaders repeatedly emphasized a few principles that are becoming standard practice: 

• AI must be operationally driven, not technology driven.
  Tools do not create outcomes. Teams create outcomes. AI initiatives need clear operational owners who are accountable for results. 
• Functional teams should own outcomes, with centralized oversight.
  Many organizations described cross functional oversight models that set standards for security, compliance, and consistency, while still letting frontline teams drive use cases and performance. 
• Systems have to talk to each other.
  If AI sits on top of fractured data, it amplifies the fragmentation. If AI is connected across systems, it can accelerate decisions and resolution. 
• Standalone “bolt-on” tools that are not integrated become workflow tax. 
  This came up again and again. When AI becomes “one more place to check,” it adds steps instead of removing them. Adoption suffers. Outcomes flatten. 

Several leaders said AI steering committees are now common, not as a bureaucratic hurdle, but as a way to ensure accountability and keep innovation aligned with risk management. 

The point is simple: AI maturity is not about how many tools you deploy. It is about how well those tools are orchestrated across the operation. 

Global delivery is becoming more strategic and more selective 

The conversation around nearshore and offshore delivery has also evolved. 

Organizations are no longer chasing the lowest rate and hoping quality follows. They are taking a more disciplined approach that weighs risk, resiliency, and overall fit. 

Factors leaders highlighted included: 

• Infrastructure reliability 

• Political and geopolitical stability 

• Talent availability and education 

• Cultural alignment and communication norms 

• The role of technology in enabling consistent execution 

The new mindset is about matching the right work to the right location, supported by strong workflows and agent enablement. Technology is becoming the bridge that makes global delivery viable at scale, especially when leaders are intentional about what belongs where. 

In practice, this means global delivery is less of a blanket strategy and more of a precision strategy. More selective. More thoughtful. More aligned to outcomes. 

What this signals for the future of customer experience 

Put all of these shifts together, and the direction is clear. 

The future of customer experience is not human or AI. It is human and AI, intentionally orchestrated. 

The organizations that will win in the next chapter will be the ones that: 

• Use AI to absorb volume and surface insight 

• Equip agents with real-time intelligence and guidance 

• Govern AI thoughtfully across functions 

• Integrate systems end to end so work flows cleanly 

• Deliver globally with discipline and adaptability 

Customer experience is becoming a system, not a department. And like any high-performing system, it has to learn, adapt, and scale. 

The brands that get this right will not just operate more efficiently. They will deliver better outcomes for customers, stronger performance for agents, and more measurable business results. 

Ready to move from AI ambition to operational reality? 

If your organization has already invested in AI but you are feeling the plateau, you are not alone. The next gains do not come from adding more tools. They come from turning AI into an operating model that is accountable, integrated, and built for the real world. 

That is exactly why LiveNexus by Liveops exists. 

Explore LiveNexus

LiveNexus is designed to help enterprises modernize customer care with confidence by orchestrating AI and human delivery in a way that is testable, measurable, and scalable. If you are ready to turn pilots into repeatable outcomes, let’s talk about what it would look like to operationalize AI in your environment with the rigor it deserves. 

Because the future of customer experience is not about choosing between AI and people. It is about designing the system where they work together, on purpose. AI should absorb volume, surface insight, and reduce friction. Humans should own the moments that require judgment, empathy, and trust.  

With the right governance and integration, that combination does not just improve efficiency. It improves outcomes across the board, for customers, for frontline teams, and for the business. If you are ready to move past pilots and build a model that can scale with confidence, LiveNexus is built for that next step.