CX Today

When AI learns from real conversations, not pre-built rules, the contact center transformation timeline collapses 

In this discussion, Rhys Fisher, Associate Editor at CX Today, sits down with Claudio Rodrigues, Chief Product Officer at Omilia, to dig into one of the most pressing questions in customer experience right now: what does truly intelligent, self-learning contact center AI actually look like in practice? 

If you're tired of AI conversations that stay at surface level, this one's for you. 

The contact center AI story is usually told the same way: clean your data, build your rules, wait months for results. Omilia is telling a very different story. 

Claudio Rodrigues breaks down how Omilia's platform skips the data preparation bottleneck entirely, connecting directly to live contact center operations and learning from the ground up: 

The data myth, debunked: Why asking customers to have "perfect data" before deploying AI is a broken approach, and how Omilia listens to 100% of contact center calls to build automation from reality, not assumptions. 

From insight to automation: How the platform identifies automation opportunities, quantifies their business impact, and deploys them to production with built-in safety rails and automatic rollback – all from a single approval click. 

The gap between AI and human agents is closing: What it looks like when AI and human agents are benchmarked in real time, and why Claudio believes the future contact center workforce will be defined by brand experience, not call handling speed. 

The 30-day/six-month/one-year curve: A frank, specific breakdown of what organizations can realistically expect as self-learning compounds over time. 

NEXT STEPS: 

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Gartner VP Analyst Kathy Ross on why AI agents belong in your tech stack, not on your org chart – and what happens when leaders get this wrong. 

In this CX Today interview, Associate Editor Rhys Fisher sits down with Kathy Ross, VP Analyst at Gartner, to unpack a provocative Gartner stance: that customer service leaders are fundamentally mismanaging AI agents by treating them like human talent. 

With 39% of CEOs already viewing AI agents as employees, the stakes for getting this right – or wrong – have never been higher. 

AI agents are powerful. But power without the right management model is a liability, and Gartner's Kathy Ross isn't pulling punches about where most organizations are going wrong. 

The scale problem is real: A human agent might affect 30-45 customers if something goes wrong. An AI agent? Hundreds of thousands, in minutes. That changes everything about how failures need to be managed. 

The org chart is the wrong place for AI: Placing AI agent oversight under people managers stretches them too thin and puts fundamentally different skill sets in conflict. Operations and technology leaders need to own this. 

Accountability has to be deliberate: Ross outlines a clear split: ops leaders own requirements, monitoring, and escalation; tech leaders own observability, integration, and compliance. People managers only get looped in when AI failure directly impacts the human workforce. 

This isn't about replacing humans, it's about redirecting them: The real opportunity is using AI to create space for human agents to do what only humans can: build relationships, drive loyalty, and uncover growth. 

Sara Richter breaks down what peak season stress tests really expose, and why most brands are failing the customer relationship before it even starts. 

Rhys Fisher, Associate Editor at CX Today, sits down with Sara Richter, CMO of SAP Engagement Cloud, to unpack the findings of SAP's 2026 Engagement Index. 

With AI agents now driving purchasing decisions for nearly half of Gen Z, the pressure on brands to deliver truly connected CX has never been higher. If you're wondering what separates brands that build loyalty from those that quietly erode it, this conversation is worth your time. 

The research shows that AI is reshaping the customer journey faster than most brands can keep up. Sara Richter doesn't sugarcoat what that means... and she's got the receipts: 

AI is accelerating the customer journey, not just assisting it. When a customer arrives guided by an AI agent, they may already be close to a decision, yet brands are still treating them like they're at the start of the funnel. That mismatch is costly. 

Peak periods expose the cracks. Disconnected channels, siloed teams, and unused "dark data" don't just create friction; they erode trust and, eventually, loyalty. Sara explains why this is the first thing that breaks under pressure. 

Data quality beats data quantity. Most organizations are drowning in data. The next chapter of customer engagement will be won by whoever can turn that data into action most effectively, not whoever has the biggest pile. 

Gibson is a masterclass in getting it right. SAP's guitar brand customer is using AI to personalize engagement across the entire musician journey, freeing up marketers for creativity while driving real business outcomes. 

📊 Explore the SAP 2026 Engagement Index to benchmark your own engagement strategy 

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Do customers really dislike AI, or are they tired of poor AI experiences?

In this CX Today interview, Francesca Roche speaks with Ali Fazal, Chief Marketing Officer at Gladly, about why many consumers are frustrated by AI in customer experience and what brands need to do differently.

Drawing on findings from WordPress VIP’s Future of the Web 2026 report, Ali explores why 60 percent of consumers are turned off by brands using AI in marketing, why 86 percent verify AI-generated information against original sources, and how this reflects a deeper trust gap.

The conversation looks at how brands often deploy AI for speed, cost reduction, or convenience, without asking whether the experience actually helps customers. Ali explains why that approach can damage trust, especially when AI produces generic content, inaccurate answers, or impersonal interactions.

He also shares where AI can create real value: helping customers find the right product faster, providing better delivery updates, answering support questions more efficiently, and enabling more personalized service at scale.

The discussion also covers where human support still matters most, particularly in emotionally sensitive, high-consideration, or complex customer moments. For CX leaders, the message is clear: successful AI strategy is not about replacing human service wherever possible. It is about knowing where automation improves the experience and where empathy, context, and human judgment are still essential.

For more Customer Experience tech news visit https://www.cxtoday.com

Is the CCaaS market moving faster than enterprise contact centers can adapt?

In this CX Today interview, Nicole Willing speaks with Martin Taylor, Co-Founder and Deputy CEO at Content Guru, about the market forces reshaping contact center as a service (CCaaS), from vendor consolidation and AI acceleration to rising customer expectations and the pressure to modernize legacy platforms.

Taylor explains why customer experience has become one of the most important battlegrounds for competitive advantage, and why enterprise buyers still running on legacy on-premises contact center infrastructure may find it harder to keep pace with AI-enabled innovation.

The conversation explores the shift from generative AI toward agentic AI, where automation can move beyond summarizing and transcribing to resolving more complex customer queries and orchestrating data across systems. Taylor also shares why many AI projects fail to prove return on investment, and why organizations need to baseline current service performance before rolling out new automation.

For enterprise buyers assessing a replacement platform, Taylor outlines the non-negotiables: vendor experience, security, data sovereignty, sector knowledge, complex migration capability, customer data readiness, and AI orchestration. Taylor also warns against being swayed by a single polished demo when the real challenge is connecting systems, processes, data, and people at scale.

What does it really take to move AI sales agents from a controlled demo into a live enterprise sales organization?

In this CX Today interview, Francesca Roche speaks with Kris Billmaier, EVP and General Manager, Agentforce Sales at Salesforce, about what Salesforce has learned from deploying Agentforce Sales across its own go-to-market teams.

Salesforce has positioned its internal sales organization as “customer zero” for Agentforce Sales, giving the company a practical view of where AI agents succeed, where they need more context, and what enterprises need to fix before trusting agents with customer-facing work.

Billmaier explains why production-ready AI depends on strong data foundations, especially conversational data from calls, emails, and sales interactions. He also explores how Salesforce trains and supervises agents, why governance needs to be built into the full agent lifecycle, and how sellers are helping shape the product through real-world feedback.

The discussion also looks at how the seller’s role is changing as agents take on top-of-funnel work, outbound prospecting, email engagement, account planning, and other time-consuming tasks. Rather than replacing sellers, Billmaier argues that agents can give sales teams more time to focus on customer meetings, preparation, and higher-value conversations.

For enterprise leaders moving from AI pilots to production, the message is clear: start with the right use case, assign a clear goal, measure impact, and build trust through data quality, governance, and continuous feedback.

For more Customer Experience tech news visit https://www.cxtoday.com

What happens when customer expectations keep rising, but the systems behind service still sit in silos? In this CX Today interview, Rob Wilkinson speaks with Mark Ashton, VP Solution Consulting CRM EMEA at ServiceNow, about why traditional CRM is no longer enough for modern customer experience.

They explore the growing gap between speed and empathy, why AI projects fail when built on weak foundations, and how disconnected front, middle, and back-office processes create friction for both customers and agents. Mark also shares practical examples of where organizations are using AI and connected workflows to reduce order exceptions, improve resolution times, and free up teams to focus on higher-value customer interactions.

If you are a CX, CRM, or service leader trying to balance automation, trust, governance, and real business impact, this conversation offers useful lessons on where to start and what to avoid.

For more Customer Experience tech news visit https://www.cxtoday.com

Are brands truly listening when customers speak on social media?

In this CX Today interview, Francesca Roche explores how AI is reshaping social media community management, and why human judgment remains central to protecting customer trust. The discussion examines the opportunity for AI to process high volumes of social interactions, identify patterns, and speed up triage, without handing over sensitive customer decisions to automation alone.

The conversation addresses a critical reality for CX leaders: social media comments can be simple service inquiries, but they can also signal frustration, risk, a wider operational problem, or a developing crisis. AI can help teams see those signals faster. Human experts provide the context, empathy, and escalation judgment required to act on them responsibly.

It also considers the growing challenge of sophisticated AI-generated spam and the importance of platform-specific moderation strategies. From the long lifecycle of YouTube conversations to the fast pace of X, brands need governance that reflects how customers actually use each channel.

Watch the full interview for practical insight into using AI to make social care teams more effective, while keeping people accountable for the moments that matter most.

For more Customer Experience tech news visit https://www.cxtoday.com

CX Today's Associate Editor Rhys Fisher sits down with Wayne Butterfield, Founder of STX, to unpack one of the most talked-about analyst reports of the year. 

Wayne sparked a firestorm on LinkedIn when Gartner's 2026 Magic Quadrant for Conversational AI dropped, and his criticisms resonated. With hundreds of comments and close to 100,000 views on his post, it was clear he wasn't alone. 

In this conversation, Wayne goes beyond the LinkedIn hot takes to explain exactly what he thinks went wrong, why the methodology deserves scrutiny, and what enterprise buyers should actually be doing when they go to market for conversational AI. 

The 2026 Gartner Magic Quadrant for Conversational AI generated more debate than most, and Wayne Butterfield was at the center of it. 

In this interview, he gets into the specifics. 

The acquisition double standard: Wayne argues that Salesforce and SoundHound were elevated in the quadrant largely on the back of acquisitions, while NiCE Cognigy was effectively demoted for the same reason. He calls the inconsistency out directly and questions whether Gartner's criteria are being applied evenly. 

Why methodology alone isn't the problem: Wayne doesn't just blame the framework. He points to a lack of transparency around the "what, why, and how" of vendor inclusion, and suggests that reports skewed toward big-budget names risk losing credibility with the practitioners who use them daily. 

What buyers should actually do: Forget one-size-fits-all rankings. Wayne makes the case for shortlisting based on people, commercial flexibility, and skin in the game from the vendor — and argues that implementation quality will always matter more than which tool you buy. 

His advice to Gartner: Test the report with the market before publishing. Not vendors with something to gain, but practitioners with nothing to lose. "You need other people tasting your vintage," he says — and it's hard to argue with that.

For more Customer Experience tech news visit https://www.cxtoday.com

Are your sales conversations creating trust, or setting customer success teams up for failure?

In this CX Today interview, Francesca Roche speaks with Seth Marrs, Chief Strategy Officer at Sandler, about how seller performance inside live buyer conversations can shape customer trust, long-term customer experience, and revenue outcomes.

Seth explains why the first sales conversation is such a critical moment in the customer relationship. When sellers overpromise, stretch expectations, or fail to align the buyer’s needs with what the solution can realistically deliver, those gaps may not appear immediately. Instead, they often surface later as churn risk, implementation issues, and a breakdown in trust.

The discussion explores Sandler’s sales performance ecosystem, which focuses on measuring how sellers actually behave in live customer conversations, not just what they know from training. Seth highlights the difference between understanding a sales methodology in theory and applying it under real pressure when buyers raise objections, ask hard questions, or expect transparency.

Seth also discusses the growing role of AI in coaching. He explains how sales leaders can use AI to support base-level coaching while focusing human coaching on higher-order skills, real call performance, and the behaviors that create unique value for customers.

Finally, the conversation looks at why sales, customer success, and CX teams need better shared visibility into buyer conversations. As more businesses move toward consumption-based models, customer experience and sales performance are becoming increasingly connected.

Watch the full interview to learn why the promises made in the first sales conversation can define the entire customer relationship.

For more Customer Experience tech news visit https://www.cxtoday.com