Is Agentforce Contact Center the Fix for CX Fragmentation, or a New Risk Layer?

Cisco: The AI Chatbot Era Is Dead – Here's What Comes Next

At Cisco Live 2026, Cisco pulled back the curtain on a suite of AI-native tools designed to help organizations orchestrate, secure, and manage a blended workforce of human and AI agents. To get the inside track, CX Today’s Rhys Fisher sat down with Vinod Muthukrishnan, VP and GM of Webex CX at Cisco, for a wide-ranging conversation on what the shift to AI-native CX actually demands in practice. Muthukrishnan is clear that the industry has moved past the experimentation phase, and that the bar for what comes next is significantly higher than most vendors are letting on: > “It’s never been easier to build an AI agent. It’s, however, never been harder to make it enterprise grade. And that’s the dichotomy we’ve got to deal with.” The conversation covers a lot of ground. Muthukrishnan pushes back on the industry’s fixation with deflection and containment rates, arguing that no single metric can capture the full customer journey. He walks through Cisco’s AI Agent 360, a framework combining custom guardrailing, runtime monitoring, and Splunk-powered observability, and makes the case that security and observability are foundational requirements for any serious agentic deployment, not optional extras bolted on afterward. He also introduces the concept of “one experience”: the idea that regardless of channel, timing, or how many agents were involved, every customer interaction should feel like a continuation of the last. Looking further ahead, Muthukrishnan raises a question that will resonate with anyone thinking seriously about where this technology leads. If agentic AI can cut across every organizational silo, does the enterprise as we know it still make sense?

Two Lanes, One Outcome: Designing Dual Paths for Humans and AI - TTEC Digital

In this CX Today interview, Carrie Brough, Director of Strategy and Ops for TTEC Digital EMEA, argues that a single CX model is fast becoming a liability. Brough explains why AI-driven interactions need quick, decision-ready responses, while humans still need empathy, context, and brand nuance. Carrie breaks down the operational warning signs that your AI and human traffic are colliding, including repeat contacts, confused outcomes, and frontline teams being forced into a “clean-up” role. The conversation also covers when an interaction should move from the AI lane to a human agent, and why risk, not emotion, needs to drive escalation decisions.

Supporting Human CX Agents In An AI Era

What does great customer experience look like when artificial intelligence is handling half the calls? For Danny Wareham, Founder and Lead Psychologist at Firgun, the answer has less to do with the technology and everything to do with how leaders treat the humans left holding the line. In a wide-ranging conversation with CX Today, Wareham argues that too many organizations are approaching AI deployment from entirely the wrong direction. "Decision makers purchase AI tools because they feel that if they don't, their competitors are going to have some sort of lead on them," he says. The result is a wave of reactive, FOMO-driven implementations that fail to solve real operational problems, and leave frontline agents feeling like change is being done to them rather than with them. That psychological friction, Wareham explains, is rooted in self-determination theory. When agents feel their competence is threatened, their autonomy restricted, or their role uncertain, they revert to familiar behavior, bypassing new tools, creating workarounds, or simply disengaging. The organizations that beat this pattern, he says, are the ones that swap compulsion for curiosity. His go-to example is IKEA. When AI tools reduced the company's inbound call volume by 47 percent, the typical response would have been to cut headcount accordingly. Instead, IKEA asked why 53 percent of customers were still calling. The answer revealed an appetite for design advice. The company retrained its freed-up agents as amateur interior designers and generated an additional one billion dollars in revenue from the insight buried in their contact center data. "Your contact centers are the source for where that rubber meets the road," Wareham says. "If your CFO's mindset is around OPEX savings, you tend to miss all of the value that's potentially there." Wareham also introduces his Constellation leadership model, explored in depth in his book. Rather than confining people to rigid job descriptions, Constellation asks what individuals can contribute toward a shared goal, freeing teams to bring their full range of skills to complex, high-stakes situations. The model draws on military frameworks like mission command used by the British Army and the US Navy SEALs, where shared intent replaces hierarchy the moment situations become unpredictable. "Constellation is not leaderless," Wareham clarifies. "Culture and our behaviors become the leader." For CX leaders navigating the AI era, his message is clear: invest in understanding why your people are resisting change before trying to overcome that resistance, and start treating your contact center as a source of strategic value, not just operational cost.

Openreach's Brutal Honesty About What it Really Took to Transform CX at National Scale with NiCE

Upgrading 25 million homes to full fiber broadband is a logistical feat in itself. Doing it while delivering a consistently good customer experience – across 700 communications providers, each with their own messaging – is another challenge entirely. That was the reality facing Openreach before it deployed NiCE's proactive AI agents. Engineers were showing up to empty homes, customers were getting conflicting information depending on their provider, and the company's NPS sat below zero. In this video interview, CX Today's Rhys Fisher sits down with Chris Herbert, Director of Customer Service at Openreach, Eifion Lloyd, Senior Manager of Customer Enablement and Strategy, and Giles Bryan, General Manager of Proactive AI at NiCE. Together, they walk through how a proof of concept built on daily Excel uploads eventually scaled into a deployment spanning 15 million customer journeys – reducing missed appointments by a third, cutting inbound contact volumes by a similar margin, and pushing Openreach's Trustpilot score from 2.0 to 4.7 across 300,000 reviews. The conversation covers what it took to get internal and external buy-in, how NiCE's platform handles landline-only customers without a separate configuration, and a generative AI result that didn't make the press release: a 22% reduction in install cancellations from an ask-me-anything chatbot trialed late last year. On the lessons learned, Herbert is candid: > "We could have stopped when it was a bit hard. But we knew by listening to our customers that this was worth pushing through." Check out the full interview [https://www.youtube.com/watch?v=XGg5rf6Ixt0] to find out precisely how a CX vendor delivers an implementation of this scale.

Not Building Trust Before AI Agents Is a Mistake

Rob Wilkinson sits down with Amazon Connect Customer leaders, Tony Shen and Jeremy Puent, to unpack what slows real deployments down, where things go wrong, and why the biggest risk is not the mistake itself but failing to spot it in time. They explain why ambiguous documentation creates inconsistent outcomes, why bad experiences drive disloyalty faster than good experiences build loyalty, and what “visibility” really means when an AI agent makes decisions you need to defend. The discussion gets practical on non negotiables like guardrails, transparency, customer consent for critical actions, and clear escalation paths to humans. You will also hear why containment and deflection can undermine CX, and what metrics and operating habits matter more as AI becomes a production channel. Check out Amazon Connect Customer here [https://aws.amazon.com/products/connect/customer/].