CX Today

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 CX Today.

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.

 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. Read the full Gartner research at gartner.com Share this with your CX or operations leadership team Drop your take in the comments: who owns AI agent oversight in your organization today?For more Customer Experience tech news visit https://www.cxtoday.com 

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.

At CCW Las Vegas, CX Today's Rob Scott sat down with Hannah Bloking (Head of Applied AI Acceleration Solutions Architecture, Amazon Connect Customer), Andrei Papancea (Head of AI Engineering, AWS), and Nate Brown (Co-Founder, CX Accelerator) right after their session on why AI pilots fail — and what the 5% who succeed do differently.Three questions. Three perspectives. Fifteen minutes of the most practical AI deployment advice from the conference floor.What CX leaders are really afraid of when it comes to AI What actually kills a pilot before it ships What the organisations that succeed do differently Key takeaways:Speed is a differentiator Iterate — don't aim for perfection Minimise confusion for customers, agents, and teams Reported live from CCW Las Vegas 2026See Amazon's playbook here

A packed Academy Ballroom at Caesars Forum. Thousands of contact center leaders on their feet. And a conversation about what AI-first service actually looks like when it is no longer a roadmap — it is running, right now, inside one of Europe's most recognised travel brands.The moment the session closed, Rob Scott pulled three of the people who built that story into a room and kept the cameras rolling.What followed was something the main stage format simply does not allow. No moderated talking points. No polished announcements. Just the airline, the transformation partner, and the Microsoft product leader behind the platform — talking honestly about what it took, what broke, what surprised them, and what they would do differently.This is not the version you heard on stage.easyJet handles millions of customer contacts at the most pressurised moments in travel — and John Leighton, Head of Customer Experience, shared how the expectations on their service team have never been higher. Aggie Pulawski, Executive Vice President at Concentrix, came in not as a vendor, but as a partner sitting inside a genuinely complex three-way relationship — customer, implementer, and ecosystem ally all at once. And Darya Mazandarany, Microsoft's Head of Product for Dynamics 365 Contact Center, was there to answer the questions that do not get asked when a moderator is managing four thousand people and a 30-minute clock.The result is one of the most candid contact center transformation conversations CX Today has produced — and one of the most relevant for any leader who is serious about what comes next.The transformation drivers. The partnership dynamics no one talks about publicly. The reality of building a modern contact center when the pressure is live and the margin for error is low. The point at which automation goes too far. The lessons that never make it into a business case. And where all three of them believe this is heading.

In this interview, recorded live at NiCE World London, CX Today's Rob Wilkinson sits down with Dorothy Copeland, Chief Partner Officer at NiCE, to unpack why businesses struggle to move from isolated AI pilots to meaningful, scalable transformation — and why the right partner ecosystem may now be the biggest factor in making AI work at scale.Dorothy shares her priorities for partner growth at NiCE, breaks down the newly announced NiCE AI Specialization Program, and explains why the shift from point solutions to connected systems spanning AI, data, workflows, and people is becoming the new standard for enterprise transformation.00:00 Introduction00:44 Dorothy's key priorities for partner growth at NiCE01:59 Building a vibrant AI partner ecosystem02:43 What is the NiCE AI Specialization Program?04:13 The shift from point solutions to integrated systems07:07 Why formalizing AI capability in the partner ecosystem matters now11:01 Closing thoughtsGuest: Dorothy Copeland, Chief Partner Officer, NiCEHost: Rob Wilkinson, CX Today#CXToday #NiCE #AIPartnerships #CustomerExperience #NiCEWorld #ArtificialIntelligence

How can CX leaders scale AI without creating more risk than value?That is the central question in this CX Today interview with Rebecca Wettemann, Principal at Valoir, as she joins Rob Wilkinson to unpack how enterprise thinking around AI in customer experience is changing. The conversation shows how many organizations have moved beyond early enthusiasm and are now under pressure to prove that AI can deliver measurable business outcomes without harming trust, increasing costs, or disrupting operations.Wettemann explains that the market has shifted from fear of missing out to what she describes as fear of messing up. In practice, that means leaders are no longer satisfied with experimentation for its own sake. They want AI initiatives that improve workflows, support customers effectively, and justify the spend. According to Wettemann, one of the biggest barriers remains trust, especially when teams still associate AI with hallucinations, weak chatbot experiences, and unpredictable costs.The interview also highlights why data integration continues to hold back progress. Wettemann argues that AI needs consistent, current, and correct data to perform well, especially in customer-facing use cases. Rather than trying to build one system that handles everything, she advises organizations to break work into smaller skills and tasks, then apply AI where the business case is clear.Workforce design is another major theme. Wettemann notes that AI is changing the role of the human agent, with more people taking on higher-value work, supervising AI-driven interactions, and helping refine AI agents. That shift, she says, requires leaders to rethink metrics, compensation, onboarding, and support structures.For CX leaders wondering where to begin, Wettemann’s advice is practical: experiment broadly, keep pilots small, learn what your data and workflows can support, and use those findings to build the right path into production.

In this CX Today discussion, host and Associate Editor Rhys Fisher sits down with Claudio Rodrigues, Chief Product Officer at Omilia, to cut through the AI hype and get real about why so many contact centers are underperforming despite significant investment.If your AI deployment isn't delivering, Claudio argues the problem started long before you went live, and he's got the framework to fix it. This is a must-watch for any CX leader tired of chasing metrics that don't tell the full story.The contact center AI gold rush has left a lot of organizations holding fool's gold. Claudio Rodrigues has seen it firsthand... and he's not mincing words.Key discussion points:The root cause of AI failure: Most deployments collapse at the problem definition stage. Organizations chase “agentic AI” as a strategy rather than a solution, with no clear metric to measure success againstContainment rate isn't enough anymore: It's still a valid metric, but Claudio makes a compelling case for shifting the language from containment to resolution – and expanding the lens to include upsell, churn reduction, and revenue growthStatic vs. dynamic AI assets: A contact center frozen at a point in time will depreciate in value. Omilia's Self-Learning Agentic CX platform is built to continuously learn from real interactions, removing the need for armies of manual annotatorsWhat CX leaders aren't getting but should be: Faster time-to-value, deployment-ready data pipelines, and a clear line of sight between their AI investment and company growth metrics.Audit your current AI deployment against a clearly defined problem statement and explore whether your metrics capture resolution, upsell, and growth – not just containment.

Public sector transformation does not move on hype alone. It moves under pressure, scrutiny, and long-term delivery demands. This conversation explores what major recent wins may signal for the wider market, what themes are rising fastest, and where the most overlooked opportunities now sit.In this interview, Rob Wilkinson sat down at NiCE World 2026 with Fiona Virture, Head of Public Sector Sales at Route 101 to discuss  the business and operational realities shaping public sector transformation, market, policy, and technology factors influencing what happens next. It is designed to bring a practical sector perspective into the campaign while keeping the discussion grounded in tangible change.

Diabolocom’s AI Product Manager Tom Azernour on why orchestration, not automation, is the real future of contact center AI Host Rhys Fisher, Associate Editor at CX Today, sits down with Tom Azernour, AI Product Manager at Diabolocom, to unpack why the virtual agent category is long overdue for a rethink. As contact centers move beyond legacy voice bots into the agentic era, Tom explains what "orchestration-first" AI actually means in practice and why the architecture decisions made today will define CX performance for years to come. If your virtual agent is still just deflecting calls, this is the conversation you need to watch. Most virtual agents deflect calls. Diabolocom's orchestrates them. Tom Azernour breaks down what separates the new generation of AI-powered virtual agents from legacy bots, and why the difference matters more than most leaders realize. From deflection to orchestration: Why the decision tree model is dead, and how Diabolocom's agentic approach gives virtual agents a goal and the autonomy to achieve it, connecting to CRMs, ERPs, and ticketing tools without overhauling your existing stack. The structured handoff: Why passing a raw transcript isn't enough, and how Diabolocom extracts intent, summaries, flags, and custom data fields to give the next agent, human or virtual, everything they need from the first second. Built for operators, not engineers: How Diabolocom designed a platform that non-technical teams can configure in minutes, without sacrificing the depth that technical users need. The CCaaS + telco advantage: 20+ years of end-to-end infrastructure ownership means Diabolocom optimizes its AI models and telephony stack in harmony, delivering latency that competitors wrapping third-party solutions simply can't match.

Jeannie Walters and Dr. Alyona Medelyan reveal what nearly 2,000 unfiltered airline reviews say about the chasm between brand promise and operational reality, and what CX leaders must do about it. In this CX Today discussion, host Rhys Fisher, Associate Editor, sits down with two leading voices in customer experience: Jeannie Walters, CX expert and author, and Dr. Alyona Medelyan, CEO of Thematic. Together, they've co-authored Experience Is The Promise, a data-driven report analyzing nearly 2,000 App Store reviews across six US airlines using Thematic's AI scoring agent. If you lead a CX, contact center, or service team, this one is unmissable. The findings cut through the brand-speak and get to what customers are actually experiencing at the moments that matter most. When things go wrong, a cancelled flight, an app that won't load, a support line nobody answers, that's the moment a brand either earns loyalty or loses it for good. This conversation, backed by real customer data, explores exactly why so many airlines are falling short at those critical touchpoints. Key discussion points: 🔴 Recovery beats reliability – Delta's Empathy score outpaced the group average not because it never fails, but because its people, processes, and tools are designed for disruption moments. Jeannie unpacks what that strategic commitment actually looks like on the ground. 🔴 The compounding failure problem – Alyona's data shows 60% of negative reviews cited inability to reach support during disruptions. When the flight fails and the service fails, the brand takes a double hit, and customers don't forget it. 🔴 Your app is your frontline – App crashes drove 9.5% of Breeze's negative Ease score. Alyona draws a direct parallel to banking data from Asia, where app instability alone triggered switching intent in 5% of users.

Are traditional survey links dead? With response rates at historic lows, the answer might be yes.In this episode, Rob Scott sits down with Sprinklr’s Sonal Singhal, Direct of Product, and Valarie Grant, Director of Solutions Consulting, to explore why relying on static, post-interaction forms leaves CX leaders with delayed insights, blind spots, and a fractured view of the customer experience.When you force a customer out of their natural channel just to leave feedback, you disrupt the journey and lose the context. The solution? Conversational listening. Sonal and Valarie break down how context-aware tools allow brands to capture sentiment natively within the channel the customer is already using - reducing friction and dramatically improving the richness of the data.If you are struggling with survey fatigue or looking for a practical way to innovate your feedback strategy this quarter, this conversation is for you. Learn how to stop asking generic questions and start listening in the moment.

Live from the floor of CCW Las Vegas, the mood has noticeably shifted. The industry is exhausted by the endless promises of AI replacing human agents and the daunting prospect of ripping out legacy systems. Leaders are facing severe system fatigue, and the mandate from the boardroom is clear: show me the ROI, and show it to me now.  To make sense of this tension, I sat down with Matt Clare, VP of Product Marketing at UJET, for a candid conversation about where contact center technology is actually heading.  In this exclusive interview, Matt reveals UJET's strategic pivot from a traditional CCaaS provider to a CX AI company. We explore the myth that AI is here to replace human connection—because at the end of the day, people still buy from people. Instead, the real opportunity lies in eliminating unnecessary, frustrating interactions and using AI to augment the high-value conversations that drive revenue and loyalty. To help leaders navigate this shift, Matt and I unpacked the specific technologies UJET is deploying to accelerate CX transformation without the traditional operational chaos. Here is a look at the core innovations we discussed: Maximizing Existing Investments with CX AI Accelerators The days of ripping out your entire legacy infrastructure are fading. Matt explains how UJET is now leading with CX AI Accelerators—intelligent layers like Virtual Agents, Agent Assist, Screenshare/Cobrowse , and Conversational Analytics that plug directly into your current setup. The goal is rapid transformation, allowing brands to maximize their existing tech investments and see time-to-value in days or weeks, not years. Zero-Friction Analytics via Spiral by UJET A massive part of this rapid ROI comes from Spiral by UJET, their conversational analytics platform that turns unstructured data into actionable intelligence. Matt breaks down how Spiral is delivering what he calls "zero-friction analytics": Interactive Dashboards: Instead of waiting weeks for data scientists to build complex reports, anyone in the business can use natural language prompts. You can literally ask your data, "Why did CSAT drop yesterday?" and Spiral instantly generates the dashboard and the answer. Automated QM Scorecarding: Quality management at scale is finally here. Leaders can now upload their ideal scorecard and ask the AI to automatically grade interactions, build reports, and generate training modules, turning raw insights into immediate action. Developer-First Flexibility and Reducing Agent Load We also discuss the growing demand for flexibility and the rejection of vendor lock-in. Matt shares insights on UJET's BYO-AI (Bring Your Own AI) integration, highlighting their inaugural partnership with conversational AI platform Parloa as proof of their commitment to customer choice.  Coupled with a Headless SDK—which lets brands build custom, native service experiences into their own apps while UJET powers the back-end—and a centralized Agent Assist Hub, UJET is drastically reducing the cognitive load on frontline agents. By aggregating knowledge bases and next-best-action recommendations, agents no longer have to "swivel-chair" between five or more different applications to solve a single customer issue. What's Next: Agentic Experience Orchestration (AXO) Finally, we look ahead to September's highly anticipated launch of Agentic Experience Orchestration (AXO). AXO acts as a persistent AI layer across the entire CX toolchain, using AI agents that can navigate software like a human to automate complex, multi-step workflows across disparate legacy systems. Matt explains how UJET is currently running its own internal support operations on AXO and co-developing with several of UJET’s leading customers to refine the product before General Availability—preparing to offer a solution that promises true ROI through system elimination, scaled operations and revenues, and continual improvement. If you are trying to figure out how to layer AI into your operations without a massive disruption, this is a conversation you cannot afford to miss. Watch the full video interview to discover how to accelerate your CX transformation today.  

Rob Scott sits down with Pasquale DeMaio (VP, Amazon Connect), Deepak Nair (SVP, AI Transformation, Citizens Bank), and Justin Robbins (Founder and Principal Analyst, Metric Sherpa), fresh off the main stage at CCW 2026 in Las Vegas.Pasquale made a deliberate statement on stage: deflection is dead. In this debrief, the three unpack what killed it, what replaces it, and why half of all agentic AI pilots never reach production.They cover the governance conversations that have to happen before AI touches a customer, where agentic AI works in financial services and where it doesn't, and whether CX leaders are even asking the right questions when evaluating this technology.Plus: Justin delivers his verdict on three days at CCW — genuinely different, or the same story told better?The full CCW 2026 coverage is on CX Today.

In this CX Today interview, Rob Wilkinson speaks with Jonathan Barouch, GM of Contact Center at Zendesk, about what “AI-native” and “agentic” actually mean in practice, where enterprise teams get stuck (data silos, authentication, brittle infrastructure), and how to roll out automation without betting the whole operation on day one.The conversation also challenges a common CX metric: containment. Barouch argues leaders should measure resolution, not deflection, and shares how teams can pilot agentic workflows, run A-B tests, and build a learning loop that turns real interactions into better knowledge, self-service, and agent support.

Rob Scott, Publisher at CX Today, sits down with Jeremie Abou, Sales Lead at Diabolocom, on the floor of CCW Las Vegas to ask the question the industry keeps dodging: is AI actually improving customer experience, or just cutting costs?Jeremie doesn't pull punches. From automation hype to the uncomfortable gap between slick demos and live contact centre reality, this conversation gets into what vendors won't tell you — and what CX leaders need to hear.They cover the 89% of CX leaders who expect humans to stay central to support, the 17% who think their agents are actually ready for it, and why Diabolocom believes the future of CX might be more human, not less.If you're navigating AI investment decisions, workforce readiness, or just tired of the buzzwords — this one's for you.Topics covered:The AI hype problem and what it's costing CXWhy "presence" beats pure automation as a CX strategyAI theatre vs. operationally useful technologyAgent enablement and the workforce readiness gapThe "super operator" — Diabolocom's vision for the future contact centreCX Today is the leading news and analysis platform for the customer experience industry.

In this CX Today interview, Marcus Law speaks with Ilan Avner, Director of Product Management at AudioCodes, about the practical reality of moving Voice AI from proof of concept into production.The conversation explores why so many Voice AI projects stall after promising pilots, what enterprises often underestimate about voice infrastructure, and why connectivity, latency, noise handling, scalability, redundancy, and human-agent handoff matter just as much as the AI model itself.Avner also discusses how platforms such as AudioCodes Live Hub and AI Agents can help enterprises build a more resilient production environment for Voice AI use cases, including voice bots, agent assistance, and real-time translation.Watch the full interview to learn what CX and contact center leaders should ask before putting Voice AI into production.

At CCW Vegas 2026, Rob Scott sits down with Jonathan 'JR' Ranger, Chief Customer Officer at CallMiner, to explore the company's latest AI innovation, 'Real-Time AI Guidance,' and what it actually means for agents, customers, and contact center leaders navigating an increasingly AI-driven world. JR breaks down how the technology works in practice, why hold times and transfers are no longer an acceptable fallback, and why he believes agents who embrace AI will thrive rather than disappear. He also gets candid about why so many AI deployments fall short, and what organizations need to do differently to see real results. If you're leading CX strategy, running a contact center, or just trying to separate the AI hype from the reality, this one's worth your time.

In this CX Today interview, Nicole Willing speaks with Jonathan Rosenberg, Chief Technology Officer at Five9, about the role of human-in-the-loop design in AI-powered customer experience.Rosenberg explains why mature AI strategies should not treat human intervention as a failure or last resort. Instead, humans play a critical role in continuous learning, governance, high-risk decisions, and customer interactions where emotion, complexity, or value requires a human touch. The conversation explores why businesses should avoid chasing 100 percent automation, how AI can still support agents when interactions are handed over, and why CX leaders need stronger auditing, monitoring, and performance evaluation as AI agents become more common.Rosenberg also shares practical advice for organizations beginning their AI journey: start with simple, high-confidence use cases, prove value, build oversight structures, and then expand carefully.

Forethought’s Antoine Nasr discusses how outcome-based AI is reshaping the way enterprises measure the true value of customer service automation In this CX Today discussion, Associate Editor Rhys Fisher sits down with Antoine Nasr, Head of AI at Forethought, recently acquired by Zendesk. The pair discuss Forethought’s agentic AI push to tackle one of the most uncomfortable conversations in the CX space right now: is the ROI you're reporting on your AI investment actually telling you anything useful? Twelve months of AI euphoria in the enterprise is giving way to a harder question: was it worth it? Antoine Nasr makes the case that most organizations are measuring the wrong things, and explains what Forethought is doing differently: Deflection is a broken metric: A deflected ticket tells you nothing about whether the customer's issue was actually resolved. Forethought's outcome-based pricing model only charges when the AI agent genuinely resolves a conversation, and shows admins exactly why each one was classified the way it was. The $1B ROI figure? Already outdated: Antoine is candid that Forethought's headline customer ROI number has already been surpassed, and walks through the framework for calculating both the hard dollar savings and the softer but real gains in CSAT, brand value, and churn reduction. AI as a single entry point: User expectations have shifted. Customers no longer want to navigate your org structure, they want one interface that routes intelligently across support, commerce, sales, and beyond. Forethought's RevTech integrations are built around that reality. Self-improving agents are here: Forethought's Discover product automatically identifies support topic gaps, builds agents to handle them, and improves after every interaction, closing the loop between performance data and agent behavior.

How customer feedback has quietly become the most powerful trust signal in the age of AI search CX Today's Associate Editor Rhys Fisher sits down with Alicia Skubick, Chief Customer Officer at Trustpilot, to unpack the platform's latest research. With AI now shaping how consumers discover and evaluate brands before they ever land on a website, the rules of visibility have changed. This is the conversation that makes the business case for trust in real, measurable terms. Trustpilot's latest 'What AI Says About You' report analyzed over 800,000 AI responses, and the findings are hard to ignore. Brands without a Trustpilot profile appear in just 1% of AI-generated answers. Those that actively collect and respond to reviews? 75.3%. Alicia breaks down what that means for CX teams on the ground. AI behaves like a cautious consumer – it checks ratings, reads review distributions, and flags missing profiles as red flags, just like your most sceptical customer would Responding beats collecting – brands that respond to reviews (not just gather them) see citation rates jump from 53% to 75%. Generic replies don't cut it; specificity is what AI crawlers reward The NPS question – Alicia makes the case that open-platform review systems are replacing NPS for many businesses, delivering the same real-time insight with the added bonus of AI visibility Speed to value is real – setting up a profile and inviting customers can shift visibility from near-zero to 53% in weeks, not months, with AI-driven customers worth 4.4x more on average Whether you're a CX leader mapping new customer journeys or an ops manager stretched thin, this one's worth your 15 minutes.

 The Director of Pega's AI Lab breaks down the real mechanics behind agentic marketing operations and why "magical thinking" is killing AI projects before they start. In this CX Today discussion, Associate Editor Rhys Fisher sits down with Peter van der Putten, Director of the AI Lab and Lead Scientist at Pegasystems. With agentic AI dominating the conversation across the CX space, Peter cuts through the noise to explain what it actually takes to make it work in enterprise marketing, and why orchestration, not individual agent capability, is the real differentiator. If you're trying to separate genuine AI progress from hype, this one's worth your time. Agentic AI is everywhere right now, but most of the conversation stays frustratingly shallow. Peter van der Putten goes deeper, explaining how Pega's newly launched Customer Engagement Studio works alongside Customer Decision Hub to give marketers a governed, agent-powered path from brief to live campaign in minutes. Outcome-based pricing: Pega is making a bold move away from token-based costs, betting they can tie agentic AI tightly enough to business outcomes to charge on results instead. Left brain meets right brain: Peter explains how CDH has handled analytical decisioning for over 30 years, with Wells Fargo running 6 billion next best actions a month through it, and how Customer Engagement Studio layers in generative and agentic AI to solve the content and marketing ops bottleneck, not the decisioning one. How the agents actually work together: A conversational agent orchestrates specialized agents across marketing strategy, creative, data science, compliance, and performance, each with a defined role, none operating in a silo. Why 40% of agentic AI projects fail: Peter points to "magical thinking", the assumption that throwing agents at a problem will sort itself out. The fix is embedding agents into real workflows tied to measurable business and customer outcomes. 

Rhys Fisher, Associate Editor at CX Today, is joined by Dave Rennyson, CEO of SuccessKPI, for a candid conversation about what it actually means to run a contact center where humans and AI agents work side by sideAs agentic AI takes on a growing share of customer interactions, Dave makes the case that the standards we apply to human agents must apply equally to AI, and that the organizations skipping that step are already storing up problems. Honest, specific, and refreshingly free of hype.The hybrid contact center isn't a future concept, it's the reality most operations leaders are already navigating.Dave Rennyson breaks down what it takes to manage it properly.AI agents are handling the simpler conversations, which means human agents are increasingly left with the harder, more complex ones. Dave argues this demands more recognition and support for human agents, not less.Quality management for AI agents is non-negotiable. Treating AI like a self-regulating system is, in Dave's words, like letting your builder do his own home inspections. Third-party QM, whether manual or automated, has to sit on top.CSAT isn't dead, it's due a rebirth. Dave makes the case for using AI to score every conversation on a normalized scale, cutting through the "haters and lovers" bias that has always made survey data unreliable."Good" in a hybrid contact center means managing the whole. Dave's vision is workforce decisions made minute-to-minute, based on task complexity, live performance data, and force-to-load, with humans and AI operating as a unified system.

Rhys Fisher, Associate Editor at CX Today, sits down with Dave Rennyson, CEO of SuccessKPI, to tackle one of the most pressing yet underexplored challenges in modern contact center operations: what it actually takes to build an AI-ready data foundation.As AI agents become a fixture of the contact center, Dave makes a compelling case that the real risk isn't the technology, it's the lack of governance, measurement, and rigor underneath it.If your organization is deploying AI without asking how you'll manage it, this is essential viewing.As contact centers race to deploy AI, most are skipping the hard work that makes it sustainable. Dave Rennyson pulls no punches on what's going wrong and what leaders need to do differently.AI agents actually produce more data than human agents, including failure signals and turn-taking data that human conversations never generate. The opportunity is significant, but only if you have the architecture to capture and act on it."Ground truth" is the step almost everyone skips. Dave breaks down what it means to establish a reliable baseline for AI performance, why it demands real scientific rigor, and what model drift looks like when you ignore it.Agentic AI is genuinely different from legacy IVR. The removal of linear flow constraints opens up a new design space, but only if organizations build the right orchestration and monitoring layers on top.Rather than declaring surveys dead, Dave argues that generative AI can now appraise every single conversation at scale, turning a historically biased metric into something far more powerful.For more Customer Experience tech news visit CX Today.

Rob Wilkinson speaks with Jonathan Kershaw, Director of Product Management at Vonage, about how live voice can bring real-time voice transcription and context directly into ServiceNow to trigger workflows during the call, not after it.Kershaw explains where the pain shows up most clearly: agents toggling between up to nine systems, inconsistent case notes, delayed case creation, and AI outcomes that fall short because they are missing the most important customer context. He shares practical scenarios, from IT outages to payment and fraud-related calls, showing how native voice in ServiceNow can support intent-based routing, mid-call escalations, warm handoffs powered by AI summaries, and faster wrap-up with automated dispositions.The conversation also covers what to automate first, how to prove ROI using credible baselines, and which KPIs tend to move earliest, including average handle time, after-call work, data quality, and reductions in follow-up contacts. The core message is straightforward: treat AI like any other business tool. Start with measurable operational gains, then scale.For more Customer Experience tech news visit CX Today.

 Mitel’s Stuart Aldridge discusses why the gap between what IT thinks it's delivering and what agents actually experience is quietly destroying customer service quality.In this CX Today discussion, Associate Editor Rhys Fisher sits down with Stuart Aldridge, Head of UK, Ireland & South Africa at Mitel, to dig into the findings of Mitel's State of Workforce Communication in the AI Era report. With contact center agents juggling upwards of 12 tools on a single call while still being pressured to deliver exceptional customer experiences, the cracks in enterprise communication strategy are getting harder to ignore. If you work in CX leadership, this one hits close to home. Mitel's latest research surveyed over 2,000 IT decision-makers, desk workers, and frontline workers across the UK, US, Canada, Germany, and France, and the results are uncomfortable reading for anyone responsible for agent experience or customer outcomes. The perception gap is enormous: 81% of IT leaders believe they're listening to user needs and delivering accordingly. Only 28% of frontline workers agree, and in healthcare that number drops to 17%. Tool overload is the real villain: Agents are routinely navigating 10-14 applications on a live call, and 61% of workers say switching between tools is actively costing them productivity every single day. Shadow IT is a symptom, not the problem: 76% of workers admit to using non-approved tools, not to break the rules, but because those tools are simply easier. The compliance and data risk that creates in a contact center environment is significant. Consultative selling has gone missing: Stuart argues that vendors and resellers are too focused on closing deals and not nearly enough time sitting with the "Carols" of the world, the actual end users, to understand what they genuinely need before adding yet another layer to an already overwhelming stack. 

 Salesforce’s launch of the Agentforce Contact Center has reignited a familiar debate in customer experience: should enterprises consolidate around one major platform, or keep the flexibility to pick best fit tools.In this CX Today interview, Rob Wilkinson sits down with Baker Johnson, Chief Business Officer at UJET, to unpack what he calls the integration trap. They explore why many organizations feel “stuck” in CRM ecosystems, how switching costs and interdependent integrations slow down change, and why agents often become the human integration layer across four to 10 disconnected systems.Baker also challenges common assumptions about “context” in AI driven customer service, arguing that real value comes from real time journey context, not just historical CRM records. The conversation closes with practical advice for CX leaders building AI strategies: focus on the customer experience first, and treat AI as a forcing function to simplify operational complexity, not a cure all. 

 AI is everywhere in customer experience, but CX leaders are under pressure to prove it is moving the needle. In this CX Today interview, Rob Wilkinson speaks with Brad Birnbaum, CEO and Co-Founder of Kustomer, about the shift from measuring AI by deflection rates and activity to measuring it by outcomes that matter to the business.Birnbaum explains why the right metrics depend on the company, from revenue uplift in retail to upsell and expansion in B2B SaaS, and why traditional CX measures like CSAT and handle time still matter but cannot be the full story. The conversation also digs into AI governance, observability, and trust, including how teams can evaluate non-deterministic models and reduce risk as automation expands.Finally, Birnbaum shares practical guidance for rolling out CX AI without chaos, including why consolidating fragmented tools and starting small beats trying to boil the ocean. He also outlines where human-in-the-loop remains essential and why the goal should be turning humans from creators into reviewers. 

The Principal Analyst at ZK Research breaks down whether Zoom's 'system of action' pivot is the real deal or just clever repositioning In this CX Today discussion, Associate Editor Rhys Fisher sits down with Zeus Kerravala, Principal Analyst at ZK Research. Zeus recently published a deep-dive on Zoom's strategic transformation, and the findings are more surprising than most in the industry expect. If you work in CX, contact center, or IT, and you still think of Zoom as a meetings tool, this conversation will change that. Zoom has quietly built something most of the industry hasn't clocked yet. Zeus Kerravala joins CX Today to unpack what he calls the shift from “collaboration to completion” – and why it could fundamentally change how CX leaders think about their tech stack. Further along than you think: Zeus argues Zoom is closer to its system-of-action vision than most realize, with Zoomtopia later this year likely to be a major milestone – though true end-to-end completion is still a couple of years out. 🔴 CX is where it gets real: From Chelsea FC to Caliber Collision, real customers are already using Zoom to eliminate cold calls, automate case logging, and unify the full customer journey – contact center included. 🔴 Conversation over CRM: Zoom is betting that conversational data is more valuable than what lives in a CRM, and Zeus thinks they might even build their own CRM within the next two to three years. 🔴 The biggest challenge isn't product: Zeus is clear, Zoom's hardest problem right now is getting people to understand what they've actually built. Proof points and customer outcomes will be the unlock. Visit cxtoday.com for more coverage on Zoom and the contact center market Read Zeus Kerravala's full blog at SiliconAngle.com Follow ZK Research for ongoing analysis as Zoomtopia approachesFor more Customer Experience tech news visit https://www.cxtoday.com

CX Today’s Rhys Fisher sits down with Rupert Adair, Director of Product Management at Enghouse Interactive.The cloud migration era has run its course, but for many enterprises, it hasn't delivered the CX transformation promised.With Flexera's 2025 data showing over 20% of workloads being moved back from public cloud to on-prem environments, the conversation has shifted. It's no longer about whether you're in the cloud; it's about whether your architecture is built to win.Rupert Adair explains what that looks like in practice.Cloud got the industry moving. But moving fast in the wrong direction is still the wrong direction. Adair makes the case that the next competitive edge in CX is architectural thinking, not cloud adoption.🔴 The cloud-first playbook has real limits: data sovereignty, uptime requirements, and legacy integration mean that simply lifting workloads doesn't automatically improve customer experience. Rupert shares a real example: a European bank that completed its cloud uplift only to hit data residency issues, latency problems, and lost functionality – making things worse, not better. 🔴 Architecture has to come before deployment: instead of asking ‘what can we move to the cloud?’, winning organizations start with ‘what experience are we trying to deliver?’ As Rupert puts it: “Cloud first asks where should this run. Design first asks what are you trying to build.” 🔴 Hybrid is increasingly the destination, not a detour: Gartner predicts 90% of organizations will adopt hybrid cloud strategies by 2027. Rupert argues that for many enterprises, hybrid is a deliberate architectural end state that delivers both resilience and the flexibility to innovate with AI.For more Customer Experience tech news visit CX Today.

As customer experience (CX) teams push beyond basic chatbot deployments, a new model is emerging: coordinated multi-agent AI systems that can execute end-to-end workflows across teams, tools, and policies. In this interview, Rob Wilkinson speaks with Raj Koneru, Founder and CEO at Kore.ai, about why this shift is happening now and what leaders should demand before they trust AI with real customer-facing execution.Koneru argues that the last 12 months have changed the game because AI models have improved dramatically in both generation and reasoning. That progress moves automation beyond question answering and into task completion, where agents can take action across systems and processes. In regulated and complex environments, he says, a single agent is limited by context and scope. A multi-agent approach better mirrors how organizations actually operate, with specialized functions like billing, fraud checks, fulfillment, and escalation requiring orchestration.Koneru also outlines what tends to fail in single-bot deployments: inconsistent answers, broken handoffs between bots and humans, actions taken without enough context, and heavy cleanup work for frontline teams. Risk and compliance leaders, he adds, often struggle because prompt chains offer limited traceability and control.For CX leaders, he recommends insisting on deterministic policy enforcement, clear permission boundaries, human escalation controls, and runtime observability before going live. He emphasizes that governance should not be bolted on after deployment. It needs to be embedded into the platform and runtime so teams can reproduce, audit, and optimize outcomes.Finally, Koneru shares the production metrics that matter: non-negotiables like failure recovery, auditability, and compliance, plus business outcomes like resolution rates, customer effort reduction, and time to resolution. He also highlights the “soft” impact of better experiences on brand loyalty and long-term value.

Is your board expecting AI ROI in six months while your contact centre needs eighteen? You're not alone — and that gap is producing some genuinely bad decisions.In this interview, Rob Scott sits down with Gautam Vasudev, SVP of Agentforce Contact Center at Salesforce, to get into the real story behind enterprise AI deployments — why 95% of pilots fail to deliver measurable business impact, what the organisations that actually succeed do differently, and how to close the gap between board pressure and operational reality.They cover the data readiness problem most vendors gloss over, the "triple penalty" of deploying AI on stale or badly structured data, a practical 12-month playbook for CX leaders, and why starting small isn't a hedge — it's the only argument your CFO will actually respect.No vendor pitch. Just the honest version.

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?

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.

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.

 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 to find out precisely how a CX vendor delivers an implementation of this scale. 

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.

Blair Pleasant breaks down what this landmark contract really means for the CCaaS market, the hyperscaler threat, and why an eight-year contract is both bold and logical Rhys Fisher, Associate Editor at CX Today, sits down with Blair Pleasant, President and Principal Analyst at COMMfusion, to dissect one of the biggest CCaaS deals ever announced. With HMRC committing to a $670M, eight-year contract via Capgemini and NiCE, Blair cuts through the headline noise to explain what this deal reveals about enterprise procurement, vendor staying power, and whether the likes of AWS and Salesforce can ever truly compete at this level. The HMRC megadeal has sent shockwaves through the CCaaS industry, but what does it actually tell us about the state of the market? Blair Pleasant brings over 30 years of analyst experience to unpack the real story behind the numbers. Two-horse race or open field? Blair argues NiCE and Genesys dominated this deal due to specific procurement requirements around revenue thresholds and systems integration capability – but insists there's still room for others like Five9, Content Guru, and Sprinklr at enterprise level. Why hyperscalers aren't landing deals like this... yet. Microsoft and Salesforce lack the CCaaS-specific expertise, track record, and dedicated revenue that HMRC demanded. AWS, however, is the one to watch. The Capgemini factor. NiCE was the CCaaS engine, but Capgemini won the contract, and Blair is clear that the SI relationship, especially given Capgemini's existing ties to HMRC and UK government work, was critical to securing it. Eight years is 80 years in this industry. Blair explains why the contract length signals HMRC's desire for stability over agility – and why NiCE's acquisition of Cognigy positions them to grow with that commitment.

Picking the wrong AI vendor today could set your contact center back for years.That’s the core message from Rhys Harris, Product Director of AI at Content Guru, who joined CX Today to break down why flexibility needs to be baked into every AI decision — not bolted on later.The conversation covers a lot of ground. Harris draws a direct parallel between the mistakes organizations made during the cloud migration era and the trap many are sleepwalking into now. Over-reliance on a single provider, opaque consumption pricing, and contracts that couldn’t accommodate change all created what he calls “cloud regret.” The same dynamics are already playing out in AI.On the question of what actually separates a genuinely multi-vendor strategy from one that’s just multi-vendor on paper, Harris is blunt: compliance and governance assurance, swappable AI models that can adapt to different languages and use cases, and vendor-agnostic orchestration. Organizations that treat these as checkbox features rather than real requirements will feel it.He also pushes back on the rush to deploy. Forbes data already shows 25% of tech leaders have invested in AI too quickly, and Harris argues the root cause is almost always the same.“A lot of organizations have just tunneled into taking a purely AI strategy without thinking about the outcomes. And I think the decisions that people will make is not about the technology but about the outcomes that they were looking to achieve first.”The bottom line: what works today won’t necessarily work tomorrow, and the vendors worth betting on are the ones who can move with you. 

Salesforce’s Agentforce Contact Center launch has split analyst opinion, and this CX Today debate gets straight to why. Host Rob Wilkinson is joined by Zeus Kerravala of ZK Research and Dave Michels of TalkingPointz to unpack what Agentforce actually is, what problem it is trying to solve, and what it could break.Kerravala frames Agentforce as a serious attempt to reduce “fragmentation hell” by converging CRM, customer interactions, and AI into a single platform layer, so agents stop being the “integration point” between disconnected tools. Michels pushes back hard, arguing the launch is a pivot driven by pressure on CRM’s long-standing model and relevance, especially as generative AI changes how businesses capture and use customer conversation data.Across the discussion, they dig into the operational impact on contact center leaders and frontline teams, including context switching, data quality, and what becomes the real “source of truth” when AI can surface answers directly from live conversations. The result is a grounded look at the stakes for customer service organizations weighing consolidation, reliability, and speed-to-value as AI moves from feature to foundation.For more Customer Experience tech news visit https://www.cxtoday.com 

Ty Givens, Rhona Bradshaw, and Mike Wehrs join CX Today's Rhys Fisher to examine why most contact centers are less resilient than their uptime metrics suggest – and why agentic AI is about to make that a lot harder to paper over.For years, five nines has been the number that kept boardrooms comfortable. It looked clean on a performance dashboard and gave technology leaders a ready answer when executives asked whether the contact center could be trusted.The problem, according to CX Consultant Rhona Bradshaw, is that it was never telling the whole story.“It acts more like a smoke screen with regards to what's actually going on," Bradshaw says in this CX Today Roundtable.The real damage, she argues, isn't the full outages that trigger incident reports; it's the persistent, low-grade degradation that chips away at customer trust without ever tripping a status page.Founder and CEO of the CX Collective, Ty Givens, cuts straight to what resilience actually means on the ground.“There are two questions. Can the customers get help? And can the agents do their job? Those are the two things that actually make an organization resilient.”Everything else, she argues, is a distraction.The shared dependency problem makes it worse. Givens describes organizations rolling out new platforms only to discover their redundancy was illusory all along, with multiple vendors sitting on the same underlying infrastructure, going down together the moment anything is tested.Mike Wehrs, COO of TieTechnology, brings the sharpest focus to where AI fits into all of this:“You can't fix stuff by throwing advanced solutions on top of sub-adequate infrastructure and sub-adequate data.”All three guests make the same point from different angles. AI doesn't necessarily introduce resilience problems into the contact center, but it does have the capacity to find the ones that were quietly there all along.

Everywhere you turn, the conversation about AI and customer experience sounds the same. AI will replace the contact center. Customers don't want to talk to humans anymore. Automation will fix everything. But how much of that is actually true — and how much of it is costing brands real customers, real revenue, and real trust?Nicole Willing sits down with Cortney Jonas Burnos, VP of AI and Digital at Transcom, and Jeff Blair, Chief Growth Officer, to put the industry's boldest AI and CX assumptions under the microscope.Eight hot takes. Two experts with decades of frontline CX and AI experience between them. Zero tolerance for hype.What emerges isn't a defence of AI or a rejection of it. It's something more useful: a clear-eyed, evidence-backed challenge to the assumptions quietly shaping — and in some cases, quietly damaging — CX strategy in 2026.You'll find out why 78% of customers now attempt self-service first — and why self-service is simultaneously ranked the least effective channel for resolving issues. You'll hear why the brands seeing the biggest returns from AI are actually spending more on customer experience, not less. And you'll understand why the biggest barrier to AI transformation isn't technology at all.The conversation covers the moments that matter most — when digital tools fail, when customers escalate, when a bot loop turns a manageable issue into a brand reputation problem. It challenges the idea that outsourcing means losing control. It reframes what great agents actually do in an AI-powered environment. And it draws a straight line between poor automation decisions and the customer churn that follows.If your 2026 CX strategy is built on any of these assumptions, this is the conversation you need to have before your next budget decision.The real question, as Jeff Blair puts it, isn't whether AI will replace the contact center. It's whether organisations are ready to rethink how customer experience actually operates in an AI-powered world.The hot takes are provocative. The hard truths are harder to ignore.Stay ahead of the trends shaping customer experience — explore more insights, interviews, and analysis at CX Today.Learn how Transcom is helping organisations design smarter, AI-powered customer experiences.

 Trust is moving from a soft signal to a hard CX KPI, and the EU AI Act will accelerate that shift. In this CX Today roundtable, Kane Simms, Nerys Corfield, Dr Scott Allendevaux, and Nick Holme explore how the legislation changes the day-to-day reality of deploying AI in customer journeys.The panel breaks down what ‘high-risk’ can mean in practice, why organisations need a clear view of where AI is actually in use, and how documentation, transparency, and accountability will increasingly shape buying decisions. They also discuss the operational knock-on effects: tighter governance across CX, legal, and data teams, more structured testing for conversational automation, and clearer rules for when customers must be told they are interacting with a bot.The takeaway for CX leaders is simple: compliance is not just a legal project. It’s a trust strategy. Teams that can prove control, explain decisions, and show robust oversight will protect customer confidence and reduce risk as AI becomes more embedded in frontline service. 

The network was never supposed to be a CX problem. For years, it wasn’t. Telecom engineers leaned on the PSTN’s built-in inefficiency as a quality guarantee, and the broader industry was happy to leave well enough alone.That era is ending.With the UK’s PSTN shutdown locked in for January 2027, organizations still routing contact center calls over legacy infrastructure now have a hard deadline. But as Zeus Kerravala, Principal Analyst at ZK Research, makes clear in this conversation, the bigger risk isn’t missing the migration window. It’s treating it as a straight swap.The problem is that modernizing means running voice traffic across shared, IP-based networks, exactly the kind of environment where LLM-driven bots add another 200-300 milliseconds of latency on top of existing SIP delay. When the bot feels slow, someone has to explain why.Right now, most CX teams don’t have the tools to answer that question.Kerravala points to Cisco ThousandEyes as one of the few observability platforms that can trace a voice interaction across local, cloud, and public internet infrastructure simultaneously, helping teams move from reactive firefighting to predictive network management. He also flags edge AI inference as a fast-moving development that could significantly cut latency for in-store and regional deployments within the next year.The organizational piece, though, may be the hardest part. CX and IT have historically operated in separate lanes. Kerravala’s view is that the companies that get ahead of this will be the ones that stop managing unified networks through siloed teams.

 From agentic AI to brand intelligence and Firefly's trust-first model, Constellation Research's Liz Miller drops unfiltered insights from the Vegas floor.In this on-the-ground dispatch from Adobe Summit 2026, CX Today Associate Editor Rhys Fisher sits down with Liz Miller, VP and Principal Analyst at Constellation Research. Liz is one of the sharpest voices in the CX and marketing technology space – and she's not here to sugarcoat anything. From the buzz around Shantanu Narayan's succession to Adobe's evolving agentic AI platform strategy, this conversation cuts through the noise and gets into what actually matters for enterprise marketers right now. Adobe Summit is buzzing... and not just about leadership transitions. Liz Miller joins Rhys Fisher to break down what's actually moving the needle for CX leaders on the ground in Vegas. 🔴 Adobe CX Enterprise reframed: It's not a new product, it's a clarified story. Liz explains how Adobe Experience Platform (AEP) has always been the foundation, and why this rebranding is about helping enterprises understand how all the pieces connect in an agentic world. 🔴 Brand Intelligence is the standout: Adobe's new solution lets marketers track how their brand appears across LLMs and AI search, not just the traditional web. As agent-to-agent engagement becomes real, knowing how your agents get found is mission-critical. 🔴 Firefly's trust-first architecture: Adobe didn't bolt on safety after the fact. Liz walks through why Content Authenticity and invisible watermarking aren't lip service; they're structural, and they matter deeply for enterprise brand security. 🔴 The radiologist moment: Jensen Huang's story from the keynote – AI can now read 100% of CT scans, yet demand for radiologists is rising – perfectly captures why Adobe's decade-long AI investment is a strategy, not a slogan.For more Customer Experience tech news visit https://www.cxtoday.com 

Technology Journalist, Francesca Roche, sits down with Hideki Hashimura, CRM and CX Strategist at redk.With MIT research showing 95% of enterprise Gen AI pilots failing to deliver measurable ROI, this conversation cuts through the hype to unpack what's really going wrong – and what genuine AI maturity looks like in customer service. If your organization has launched an AI chatbot and wondered why nothing has really changed, this one's for you.Main DescriptionMost enterprise Gen AI pilots don't fail because of bad technology; they fail because of everything surrounding it. Hideki Hashimura of redk shares a no-nonsense breakdown of where organizations go wrong and how to build AI-powered customer service that actually scales.The isolation problem: Most AI deployments are siloed – a chatbot here, a translation tool there – with no contextual learning or connection to wider service processes, which kills ROI before it starts.AI maturity is an org problem, not a tech problem: True readiness means aligning people, process, and technology together. Agents are evolving into service architects, and closing that skills gap is the most critical step leaders are currently missing.False positives are everywhere: Deploying an AI bot that handles surface-level queries isn't transformation. If customers still can't change a flight or request a refund, the foundation underneath the bot simply isn't built.Pilot success must be tied to business KPIs: Define your north star metrics first – NPS, resolution rates, handling time – then build the pilot around impacting those specific numbers. Speed without strategic alignment is just expensive experimentation.Find out more about redk's AI-readiness workshops here.For more Customer Experience tech news visit CX Today.

Marketing budgets have been flat at 7.7% of company revenue — and over 40% of CMOs pushing for more are losing C-suite influence. Why? They can't prove ROI.In this episode, Francesca Roche sits down with Marie Bahl, CMO of Uptempo, to unpack why enterprise marketing still lacks a proper system of record, how the breakdown between planning and measurement costs brands millions, and what it actually takes to earn a CFO's trust.The pressure on marketing leaders isn't just internal — it reflects a wider industry shift. As AI reshapes how businesses operate and boards demand greater accountability across every function, marketing is being held to a standard it was never structurally built to meet. With martech stacks growing in complexity and economic headwinds forcing leaner operations, the teams that will come out ahead are those investing now in a proper data backbone — not more point solutions. The conversation is moving from "what did we spend?" to "what did we build?".

AI is already reshaping customer service, but Simon Thorpe, Director at Pegasystems, argues the biggest shift is not the technology itself. It is the rise in customer expectations and the pressure on CX teams to deliver consistent outcomes, fast. In this CX Today interview, Thorpe explains why many organisations are treating service as a strategic battleground, tied directly to retention, churn reduction, and trust.Thorpe warns against the idea that AI is a silver bullet. If businesses layer automation on top of broken journeys and fragmented workflows, they will frustrate customers more quickly, not less. The focus, he says, should be on strong foundations: governance, transparency, auditability, and AI that is connected to real processes so leaders can explain what happened, when, and why. That matters even more in regulated enterprise environments where trust is non-negotiable.Don’t miss the full interview for a practical take on building trustworthy, outcome-driven AI in CX.

Speaking with CX Today, Susan Ganeshan, CMO at Emplifi, explores why customer trust in digital community spaces is under mounting pressure, and what brands must do to course correct. As more of the customer journey takes place on community platforms like Reddit, review sites, and social channels, the stakes for getting this right have never been higher. Ganeshan draws on Emplifi’s latest consumer research with 85% of consumers saying they are willing to pay more for brands they consider authentic, and 93% saying that genuine engagement is what builds their trust in the first place.In regard to AI transparency, Emplifi’s recent report found that disclosure has become a non-negotiable for today’s shoppers. Ganeshan highlights that 91% of consumers now expect a brand to be explicit about when and how it is using AI, whether that’s responding to a community post, routing a query, or generating dynamic content on a website. For brands still treating AI-powered interactions as invisible, this represents a significant trust gap. The data suggests that consumers apply the same rigorous expectations to community spaces as they do to direct brand touchpoints, and that inconsistency across channels is one of the fastest ways to erode confidence.Ganeshan also argues that user-generated content is a trust accelerant, where consumers are far more likely to trust images and peer reviews than polished brand photography, they want to see products in real homes, real cars, and real lives, not studio settings. Combined with the growing influence of Reddit and similar platforms, this means brands can no longer afford to be passive bystanders in the spaces where their reputation is being shaped daily. The conversation is happening whether they participate or not, and showing up authentically, with clear privacy guardrails and consistent messaging separating trusted brands from those losing ground.Looking ahead, Ganeshan anticipates that trust will move from being a peripheral concern to a core design principle for CMOs. Governance tools and AI-powered workflows will play a growing role in helping teams identify where human intervention is needed and where automation can operate safely at scale. The brands that win, she argues, will be those that approach every community interaction with the same transparency, consistency, and accountability they bring to every other part of the customer experience.