AI in the Contact Center: Why Human-AI Collaboration Will Drive the Next Era of Customer Experience

Artificial intelligence has stormed the corporate agenda, but its impact remains uneven. Nowhere is this clearer than in customer experience, where enterprises have poured money into automation yet struggle to see consistent returns. The next leap forward will not come from replacing humans with machines. It will come from a more powerful shift: humans and AI learning, working, and improving together.

That was the focus of my conversation at Ai4 in Las Vegas with Sai Vivek, Chief Customer Officer and Field CTO at Cresta. His dual role places him at the intersection of customer outcomes and product innovation, offering a rare perspective on how AI is reshaping both the customer and employee experience. His message to executives: treat human-ai augmentation as a core strategy, not a temporary step.

Adoption: Ambition Outpaces Execution

Metric Sherpa’s latest research shows nearly three quarters of CX leaders deployed at least one AI initiative in the past 18 months, but fewer than half report measurable improvements in customer satisfaction or employee productivity. Vivek sees this disconnect up close.

“There isn’t a single conversation I’m having with customers where value isn’t the first question,” he said.

“Enterprises want to know not just if AI can handle a task, but how quickly it can show results across every channel.”

The conversation has shifted from whether AI can handle tasks to how broadly and effectively it can be applied.

From Automation to Augmentation

Early enterprise investment emphasized automation: deflecting calls, routing inquiries, handling routine needs. Vivek argues the real gains now come from augmentation.

“There’s a myth that human augmentation is just a step toward automation,” he explained. “The reality is that human-AI collaboration is the engine that will drive your AI.”

Augmentation means real-time coaching for frontline agents, streamlined knowledge access, and offloading repetitive tasks. Enterprises benefit twice: agents perform better, and the AI improves with every interaction.

Metric Sherpa’s data reinforces this pivot. Agent Assist ranked as the number one AI investment priority for CX leaders in 2025, ahead of self-service automation. Executives increasingly view augmentation as the foundation for long-term success.

Where Enterprises Stumble

Why aren’t results arriving faster? Vivek identifies two primary barriers: knowledge management and integration.

“Our customers called knowledge management the number one problem they’re facing,” he said. “You need your knowledge documented and structured in a way that AI can consume and make useful for customers and employees.”

Metric Sherpa’s research found that nearly 60 percent of enterprises admit their knowledge assets are incomplete or poorly structured for AI readiness. No model, however advanced, can compensate for broken inputs.

The second barrier is APIs. “To scale automation, you need cutting-edge enterprise APIs,” Vivek said. Without seamless data access and the ability to transact across systems, AI projects stall.

The Omnichannel Imperative

Executives have long promised seamless omnichannel experiences, but most have failed to deliver. Vivek argues this is because enterprises have tried to “force fit” separate ecosystems, human agent, voice and digital, into a single journey.

Cresta has taken a different route: building from one platform, starting with agent assist, then expanding into coaching and agentic automation. Vivek describes this as a “single pane of glass” capable of powering every channel without fragmentation.

Metric Sherpa’s research shows why this matters. Only 28 percent of enterprises report delivering a consistent experience across voice and digital. Customers expect continuity. Leaders must move beyond patchwork integrations and adopt unified AI architectures.

Personalization Without Fragmentation

Even with unified platforms, AI must reflect the brand. Vivek outlined a three-layered approach: domain-specific models, brand personas applied to those models, and APIs feeding the data needed for real-time relevance.

“AI gets real when you have the right level of information supplied to it,” he said. “That’s what ensures consistency across channels while still behaving appropriately for each interaction.”

Metric Sherpa research shows brand consistency ranks among the top three executive concerns for AI deployments, second only to ROI. Vivek’s layered approach offers a practical framework for addressing it.

The Human Side of AI Adoption

Technology is straightforward compared to organizational change. Vivek put it plainly: “AI buy-in is easy, but ensuring everybody adopts it is the hard part.”

Cresta invests heavily in enablement, embedding training long after initial deployment. “It’s a continuous evolution,” Vivek said. “Your frontline needs ongoing support as AI capabilities expand.”

Metric Sherpa’s analysis shows enterprises that pair AI investment with structured change management are 2.5 times more likely to achieve measurable ROI. Culture, not technology, determines outcomes.

Measuring What Matters

Executives can’t afford to rely solely on traditional KPIs like handle time and revenue. Vivek believes new measures are emerging.

“Look at coaching effectiveness,” he said. “Look at supervisor-to-agent ratios over time. That shows whether your coaching process is improving.”

He also pointed to automated quality assurance: “Today, less than five percent of calls are QA’d manually. We believe 100 percent should be analyzed and QA’d.”

Metric Sherpa concurs: AI-driven QA and coaching metrics are becoming leading indicators of both employee development and customer experience. Leaders who adopt them gain sharper visibility than their competitors.

What’s Next

Over the next 12 months, Vivek expects growth across automation, augmentation, and AI-led interactions. But his eye is on the space where humans and AI collaborate.

“The feedback loop—human agents training AI, and AI helping human agents—that’s the real engine of value,” he said.

His advice to executives: “Start small. Have a clear line of sight to what business value your AI is driving. And choose the right partner.”

The Executive Mandate

Executives evaluating AI have a choice. They can continue chasing automation at the expense of employees, or they can design for augmentation as the foundation of transformation. The latter demands discipline: structured knowledge, robust APIs, cultural alignment, and modern metrics. It also delivers the strongest return. Customer experience will not be defined by AI replacing people. It will be defined by how effectively enterprises design for humans and AI to improve each other. Leaders who focus here will unlock AI’s long-promised value.