V.u.x. World

We hit the floor at the European Chatbot and Conversational AI Summit in Edinburgh with a mic and a simple rule: answer a question, then leave one for the next person. What unfolds is a chain of questions and answers from practitioners at Lebara, Lloyds Banking Group, Uber, ElevenLabs, Carrefour, Virgin Money, Tesco, Jaja Finance and more. The result is an organic, unscripted snapshot of what the conversational AI community is actually thinking about right now.Topics spiral from enterprise AI adoption and the talent crunch, through agentic banking and agent metrics, to some surprisingly personal territory, including AI for mental health support, cardiac research and simplifying the mundane parts of everyday life.Show notesFind out more about The European Chatbot & Conversational AI Summit: https://theeuropeanchatbot.comFollow Kane on LinkedIn: https://www.linkedin.com/in/kanesimmsTake our updated AI Maturity Assessment: https://vuxworld.typeform.com/to/a26bf9Rr?utm_source=podcast&utm_medium=audioSubsc

Most companies sit on a goldmine of customer insight and do almost nothing with it. Every conversation holds signals about frustration, churn risk, and broken experiences, yet extracting that value can be a slow and manual effort.In this episode, Shane Lynn, CEO and Co-Founder of EdgeTier, unpacks how conversational intelligence is evolving in the age of large language models and what it means for contact centres.Shane explains how EdgeTier can now model metrics such as resolution rate and customer satisfaction across every interaction, rather than relying on the 10–15% survey response rate most contact centres achieve.We also get into the organisational challenge that underpins all of this: contact centres often hold the richest customer insights in the business, but lack the tools or organisational standing to act on them. Shane argues that data-driven contact centres can shift from being reactive cost centres to genuine strategic assets, influencing product, policy and process decisions across the wider bu

How do you test something that can behave differently every single time?In this episode, we speak with Amitha Pulijala, Chief Product Officer, and Christoph Börner, VP of Engineering, both at Cyara, about one of the most pressing challenges in conversational AI today. The shift from deterministic, scripted IVRs to generative AI agents is changing how conversational systems are built and tested.The episode covers how Cyara approaches testing in a non-deterministic world, including using AI agents to test AI agents, and why traditional ideas like test coverage no longer apply in the same way.Christoph and Amitha share what they are seeing across Cyara’s clients and the wider industry. The discussion unpacks what AI trust means in practice. We talk about hallucinations, model drift, factual accuracy, bias and regulatory compliance.We explore the economics of generative AI. The cost of running it at scale in production and in testing, and how organisations are rethinking where large language models are necessary

Generative AI is changing how customer support chatbots are built, deployed and measured.In this episode, we sit down with Alia Azim, Product Lead for Chatbots at Citation Group, to discuss the company’s shift from traditional NLU chatbots to generative AI conversational agents.Alia brings a wealth of experience in conversational AI, including time spent at Lloyds Banking Group, and she gives us an honest account of what it actually looks like to move from NLU-based chatbots to generative AI in a real business environment. Citation Group provides HR, compliance and business services for thousands of small and medium businesses. Supporting those customers means handling everything from platform troubleshooting to account access issues. Alia explains how their team rebuilt the chatbot strategy around generative AI, focusing on specific use cases, improved knowledge management, and outcomes that actually resolve customer problems.We explore the limitations of traditional intent-based bots, why generative AI

What happens when AI stops being treated like a tool and starts being hired like an employee?In this episode, we sit down with Gabe Larsen, Chief Revenue Officer at Atonom (formerly known as Signals), to explore a bold reframing of AI agents as “cloud employees” hired on salary to perform specific job roles.Rather than selling software seats or charging per conversation, Atonom packages AI as role-based digital workers. You hire an AI SDR, a customer service rep, or a recruiter. You coach them and you measure their output. And if they do not perform, you let them go.Gabe explains why the traditional SaaS model failed to deliver outcomes, how AI agents are shifting from tools to teammates, and why pricing AI like a human employee simplifies adoption. We dive into multi-channel AI employees, autonomous multi-agent systems, role-based templates and the realities of scaling AI across sales, customer service and recruiting.Gabe also shares his views on the broader AI market, where Signals sits relative to other AI

Generative AI has changed how conversations are built and experienced. Georgios Tserdanelis, VP of Conversation Design at JPMorganChase, draws on 15 years of designing voice and chat systems to explain what still holds up, what breaks and why conversation design matters more than ever.Georgios brings years of hands-on experience designing voice and chat experiences across startups and global enterprises, including JPMorganChase, Cigna and Walgreens. With a background in linguistics, he offers a grounded perspective on how human conversation actually works and why those fundamentals still matter in a world of generative AI.We explore how conversational AI has evolved from scripted IVR and NLU systems to large language models and agentic experiences. Georgios explains why many current generative AI deployments struggle with basic conversational principles such as turn-taking, acknowledgement, and context management. Georgios shares practical insights on designing effective voice and chat experiences at a massiv

HBX Group sits in the middle of one of the most complex customer service chains in travel. A single issue can span a traveller, a travel agent, a global booking platform and a hotel on the other side of the world.In this episode, we explore how HBX Group is leveraging artificial intelligence to transform its global customer service operations with Xavier Godoy Moya, Customer Experience & Automation Director, and Adam Tinsley, Global Customer Service Director.We break down how HBX uses AI-driven classification to triage hundreds of thousands of monthly cases across voice, chat, email and ticketing systems. The team explains how generative models replaced traditional intent-matching systems, enabling accurate routing across more than 70 case types while supporting deterministic safeguards required at operational scale.Adam and Xavier share results across several key use cases, including an AI classification system that accurately categorises customer inquiries into 70 different intents, automated handling o

From IVRs to multimodal AI experiences, the hardest problems are rarely technical. In this episode, we dive into the evolving landscape of conversational AI and enterprise automation with Anne Cantera, Senior Product Designer at Optimum. With extensive experience in transforming traditional IVR systems into conversational interfaces, Anne shares valuable insights on the practical implementation of AI in customer service environments.We explore the concept of 'hybrid architecture' in AI implementation, discussing how combining rule-based automation with generative AI often provides the optimal solution for enterprise needs. Anne explains how her team strategically deploys generative AI in low-risk scenarios while maintaining deterministic approaches where precision is critical, particularly in their recently launched NLU routing system.The conversation also covers the importance of customer-centric design in AI implementations, with Anne emphasising that the ultimate goal should be making experiences simpler f

AI has moved from pilot projects to boardroom urgency. Companies feel the pressure to act, hire, and keep up. Many start with tools or chase a single unicorn hire. Chris Morrow, Founder of Digitalent, explains why this approach fails and why the real battle is for people who can drive transformation, culture change and long-term value. In this episode, Chris draws on two decades of experience in tech recruitment and his work with VC-backed startups, global enterprises, and governments. He breaks down why AI hiring is unlike any previous talent cycle. Roles are ill-defined, expectations are inflated, and the best candidates command eye-watering compensation, especially in the US. He describes the AI talent market as an arms race, with startups, big tech and even nations competing for the same small pool of elite engineers and researchers. The conversation goes beyond salaries and job titles. Chris shares what AI-ready companies do differently, why small proof-point projects matter more than grand 18-

Cars are becoming one of the most competitive frontiers in AI, and most people don’t realise how complex it really is.In this episode, we’re joined by BalaKrishna Kolluru, Senior Director of AI at Cerence, the company powering conversational AI in over 500 million vehicles worldwide. With over 25 years of experience in machine learning and speech recognition, Bala brings deep insights into how generative AI is transforming the in-vehicle experience.We explore how voice AI in vehicles has evolved from basic command-and-control systems to sophisticated conversational interfaces powered by hybrid cloud-edge architectures. Bala explains how Cerence's technology serves around 80 car manufacturers globally, and how their agentic AI approach enables seamless integration with external systems while maintaining functionality even without cloud connectivity.We address the technical challenges of implementing voice AI in vehicles, from microphone placement to processing capabilities, and explain how Cerence collaborates

What does it really take to build AI that can resolve customer support at scale reliably, safely, and with measurable business impact?We explore how Intercom has evolved from a traditional customer support platform into an AI-first company, with its AI assistant, Fin, now resolving 65% of customer queries without human intervention. Intercom's Chief AI Officer, Fergal Reid, discusses the company's journey from natural language understanding (NLU) systems to their current retrieval augmented generation (RAG) approach, explaining how they've optimised every component of their AI pipeline with custom-built models.The conversation covers Intercom's unique approach to AI product development, emphasising standardisation and continuous improvement rather than customisation for individual clients. Fergal explains their outcome-based pricing model, where clients pay for successful resolutions rather than conversations, and how this aligns incentives across the business.We also discuss Intercom's approach to agentic AI

In this episode, Joe Kim, the new CEO of DRUID AI, unpacks what might be the biggest shift in technology since the internet.We discuss the evolving landscape of artificial intelligence and its growing impact on businesses. Joe, who has been in his role for 70 days, brings fresh perspectives on how DRUID AI positioned itself as a workflow automation platform years before the market caught up, a bet that's now paying off as companies move beyond AI experimentation into real implementation.The discussion covers the current state of the AI market, including the challenges of customer adoption, why some customers actively prefer interacting with AI over humans, and the importance of maintaining a balance between generative and agentic AI.Joe also shares his vision of AI as the next major distribution platform. Just as Amazon has tried to make Alexa the operating system of our lives, OpenAI’s ChatGPT and similar platforms could become the primary gateway to accessing services in the future.Chapters00:00 - Meet Joe

Everyone's slapping 'agentic' on their AI products, but what does that even mean? Anne Jenkins, Vice President of Solution Architecture at Teneo, helps us separate substance from buzzwords.In this episode, Anne shares her expertise on agentic AI and the evolution of conversational AI technologies. We explore what truly makes an AI ‘agentic’ versus the marketing hype all over your LinkedIn feed and beyond. Anne explains why Teneo's hybrid approach, combining traditional NLU capabilities with large language models, creates more reliable, cost-effective, and latency-friendly solutions than pure LLM implementations.We also discuss the challenges organisations face when adopting AI solutions, including the misconception that LLMs alone can solve all problems without proper conversation design or business rule integration. Anne shares valuable insights on how companies can prepare for AI adoption through education, competitive pilots, and architectural considerations.We touch on many best practices when it comes to

Once switched off during busy periods, Lloyds Banking Group’s chatbot now handles more than 15 million conversations a year. Learn what it really takes to build AI solutions that customers trust with their money. We sit down with Cainan Wright, Senior Product Owner, and John Young, AI Lead - Chatbots and Generative AI, from Lloyds Banking Group, to explore their remarkable nine-year journey in building one of the UK's most successful banking chatbots. From handling 3 million conversations in 2021 to over 15 million in 2025, they share the hard-earned lessons of transforming a rather "unloved" virtual assistant into a mission-critical service for almost 27 million customers.We cover how the team stabilised their service by focusing on the basics, investing in design expertise, and securing organisational buy-in through demonstrating clear value.Cainan and John also share valuable insights into their pragmatic approach to generative AI, explaining how they combine deterministic processes with generative la

In this episode, we dive into the art and science of context engineering with Martin Cross, President of Connect, a company that empowers enterprises to transform through the use of AI and automation.Martin shares how most businesses still approach AI with a technology-first mindset, deploying solutions before clearly defining the customer problem they’re solving. He explains why successful AI experiences begin with understanding the user journey, designing the right interaction, and then selecting the appropriate tools, not the other way around.We also unpack Connect’s acquisition of Elerian AI and why contact centre voice recordings represent an untapped goldmine of training data. Martin explains how fine-tuning models with real-world conversations, including dialects, accents, and customer intents, can dramatically improve AI accuracy and empathy.The conversation delves into the various layers of context - from session-level to journey-wide to CRM-integrated, and how they work together to transform generic

Voice AI is having a breakthrough moment. With large language models delivering unprecedented understanding and next-gen text-to-speech achieving near-human fidelity, the possibilities for immersive, scalable, and personalised customer experiences are greater than ever.We’re joined by Andrei Papancea (CEO & Co-Founder, NLX) and Kylan Gibbs (CEO & Co-Founder, Inworld), who break down how their companies are working together, making studio-quality voice experiences accessible to developers and enterprises at scale.The conversation traces how voice technology has progressed from basic assistants to today’s lifelike AI voices. We also discuss the shift from brand voices to brand personalities, and how voice experiences can be tailored to different demographic segments and eventually to individual users.This episode is brought to you by NLX.NLX is a conversational AI platform enabling brands to build and manage chat, voice and multimodal applications. NLX’s patented Voice+ technology synchronizes voic

What happens when one of the world’s leading analysts on customer service and conversational technologies sits down to unpack the future of AI?We explore the profound implications of AI adoption with Ian Jacobs, VP, Lead Analyst at Opus Research. We discuss how AI is transforming contact centres and customer service operations, from agent augmentation to process automation. Ian shares insights on how businesses are navigating the balance between AI efficiency and human empathy, including the fascinating concept of when non-empathetic AI might actually be the more empathetic choice for customers in certain scenarios.Along the way, the conversation zooms out into deeper territory, touching on human happiness, the future of work, and whether regulation can ever keep pace with innovation.Show notesLearn more about Opus ResearchKane Simms on LinkedInDiscover VUX ConsultingTake the updated AI Maturity AssessmentSubscribe to VUX WorldSubscribe to The AI Ultimatum Substack Hosted on Acast. See acast.com/privacy

Gartner's Magic Quadrant for Conversational AI platforms is back in 2025! This is a must-watch for CX leaders seeking to make informed decisions about their AI tech stack. Here, we provide deep technology market analysis for artificial intelligence in customer experience. Whether you're looking to build AI chatbots, AI agents, Retrieval Augmented Generation applications, these conversational AI platforms are the best of breed.Show notesKane Simms on LinkedInDiscover VUX ConsultingTake the updated AI Maturity AssessmentSubscribe to VUX WorldSubscribe to The AI Ultimatum Substack Hosted on Acast. See acast.com/privacy for more information.

As one of the world’s largest car manufacturers, Toyota is giving its machines a voice using AI as a trusted partner to transform how cars are built and serviced.In this episode, we speak with Kordel France, Principal AI Engineer & AI Architect at Toyota, to uncover how artificial intelligence is reshaping production and maintenance globally.We explore how Toyota has moved from technicians spending hours sifting through thousands of pages of manuals to intelligent systems that can diagnose faults in seconds and even predict breakdowns before they happen. Kordel explains the technical architecture behind these solutions, blending classical machine learning with generative AI, and the challenges of creating specialised systems from general-purpose models.You’ll also hear why high-quality data ingestion is more important than the model itself, how even a relatively small number of users can drive asymmetric improvements in efficiency, and what Toyota’s collaboration with NLX means for service technicians wor

The AI arms race in customer experience just got serious. We’re joined by industry legends Nerys Corfield (Injection Consulting), Jon Arnold (J Arnold & Associates), and Henry Iversen (boost.ai) to unpack one of the biggest AI moves in recent memory: NiCE’s $955M acquisition of Cognigy.We break down what this deal means for the future of AI-first contact centres, the fate of best-in-class point solutions, and the broader shift toward an AI-led customer experience strategy. From questions of market consolidation and vendor lock-in to the culture clash between product-led innovation and marketing muscle, we share some real, unscripted insights into the implications of the acquisition for enterprises, vendors, and buyers alike.This episode is brought to you by NLXBuild and deploy sophisticated chat, voice, and multimodal applications for any purpose with NLX. NLX works seamlessly with any LLM and existing tech stack, freeing you to create, not configure. Trusted by individual builders and leading teams at Co