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, which enables their systems to perform complex, multi-step tasks, such as processing refunds, by integrating with various APIs. Fergal shares insights on testing methodologies, the balance between customisation and standardisation, and the challenges of building AI products in a rapidly evolving technological landscape.

Finally, Fergal shares what excites and honestly freaks him out a bit about where AI is heading next.

Timestamps

00:00 - Intro

02:31 - Welcome to Fergal Reid

05:26 - How to train an NLU solution effectively?

08:56 - What gen AI changed for Intercom

10:57 - How would you describe Fin?

14:30 - Fin’s performance increase

17:18 - Intercom’s custom models

22:14 - Large Language Models vs Small Language Models

30:40 - RAG and 'the full stop problem'

40:08 - Agentic AI capabilities at Intercom

50:40 - Intercom’s approach to testing

1:04:46 - About the most exciting things in the AI space

Show notes

Learn more about Intercom

Connect with Fergal Reid on LinkedIn

Follow Kane Simms on LinkedIn

Article - The full stop problem: RAG’s biggest limitation

Take our updated AI Maturity Assessment

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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.

Chapters

00:00 - Meet Joe Kim

00:33 - Celebrating 70 days at DRUID AI

01:35 - What attracted Joe to DRUID

03:06 - The real value of AI

06:43 - What Joe learnt about the market

11:19 - The AI God Box for enterprises

14:08 - The state of the AI market

20:29 - Why you should learn about AI as much as you can

23:47 - Generative AI adoption among enterprises

27:36 - The concept of agent washing

36:05 - Is AI bigger than the internet?

39:11 - ChatGPT as the new distribution platform

48:52 - Will chatbots replace websites and apps?

50:31 - The next 6–12 months for DRUID AI

56:59 - The biggest AI ultimatum facing businesses today

1:01:29 - AI replacing people is not growth

1:05:33 - The systems of record at enterprises and LLMs

1:08:46 - The future of AI automation

1:14:13 - LLMs could replace apps

Show notes

Find out more about DRUID AI

Follow Joe Kim on LinkedIn

Sign up for our webinar: How to run AI like your business depends on it

Follow Kane Simms on LinkedIn

Take our updated AI Maturity Assessment

Subscribe to VUX World

Subscribe to The AI Ultimatum Substack

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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 implementation, with Anne emphasising the importance of proper context engineering, state management, and dynamic prompting.

Chapters

00:00 - Meet Anne Jenkins

05:01 - AI is now a boardroom conversation

06:48 – OpenAI’s agentic AI platform

08:48 – What is an AI agent?

21:38 – The hybrid AI model or end-to-end LLMs

26:49 – AI in debt collection

34:55 – How Teneo helps implement agentic AI

42:39 – Context engineering

47:19 – State management and LLMs

55:40 – How Teneo designs AI experiences

01:00:32 – Demo – teaching Teneo something new

01:10:26 – How businesses should adopt AI

01:16:44 – What sets Teneo apart

Show notes

Check out Teneo

Follow Anne Jenkins on LinkedIn

Read Kane’s article - What agentic AI actually is: a deeply researched and definitive explanation

Follow Kane Simms on LinkedIn

Take our updated AI Maturity Assessment

Subscribe to VUX World

Subscribe to The AI Ultimatum Substack

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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 language capabilities to deliver the best customer experience while maintaining brand consistency and ensuring regulatory compliance.

The team's journey offers important lessons about perseverance and the importance of striking a balance between innovation and responsibility when deploying AI in a highly regulated industry.

Timestamps

00:00 – Intro

01:34 – Meet Lloyds Banking Group

03:18 – The unloved virtual assistant era

05:30 – AI before ChatGPT

06:50 – Stabilising the service and earning trust

14:23 – From underloved to mission critical

16:55 – Buy-in from stakeholders to scale AI capabilities

18:41 – Defining new AI roles in banking

20:51 – Scaling from 3 to 15 million conversations

25:15 – How to handle a 5x increase in three years

27:43 – Experiments with generative AI in banking

30:24 – Using an LLM classifier

31:07 – Improving tools within teams

32:45 – Using generative AI for value and impact

34:56 – Valuable design research sessions

38:56 – Meeting customer expectations with generative AI

46:04 – Maintaining consistency in probabilistic landscape

49:30 – The right tool for the right job in conversational AI

55:26 – How do you measure the impact of generative AI?

56:13 – Responsible AI and proving business value

1:01:10 – The next 12 months

1:07:02 – Magic wand moments

1:11:34 – If the team could start over again

1:14:03 – Closing remarks from Kane

Show notes

Follow Kane Simms on LinkedIn

Discover VUX Consulting

Take our updated AI Maturity Assessment

Subscribe to VUX World

Subscribe to The AI Ultimatum Substack

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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 explore different layers of context - from session-level to journey-wide to CRM-integrated, and how they work together to transform generic interactions into deeply personalised, proactive experiences.

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.

Additionally, we reflect on why the industry continues to repeat old mistakes and how businesses can design AI that truly understands and anticipates customer needs.

Show notes

Follow Martin Cross on LinkedIn

Find out more about Connect

Follow Kane Simms on LinkedIn

Discover VUX Consulting

Take our updated AI Maturity Assessment

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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 voice with digital channels, making it possible to automate complex use cases typically handled by a human agent. When a customer calls, the voice AI guides them to resolve their inquiry through self-service using the brand’s digital asset, resulting in automation and CSAT scores well above industry average. Just ask United Airlines.

Show notes

Learn more about Inworld

Kane Simms on LinkedIn

Discover VUX Consulting

Take the updated AI Maturity Assessment

Subscribe to VUX World

Subscribe to The AI Ultimatum Substack

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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 notes

Learn more about Opus Research

Kane Simms on LinkedIn

Discover VUX Consulting

Take the updated AI Maturity Assessment

Subscribe to VUX World

Subscribe to The AI Ultimatum Substack

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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 notes

Kane Simms on LinkedIn

Discover VUX Consulting

Take the updated AI Maturity Assessment

Subscribe to VUX World

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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 working across increasingly complex powertrains.

Show notes

Kane Simms on LinkedIn

Discover VUX Consulting

Take the updated AI Maturity Assessment

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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 NLX

Build 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 Comcast, Saks Fifth Avenue, Toyota, and United Airlines, NLX helps you turn AI concepts into working conversational experiences.

Show notes

Follow the episode guests on LinkedIn:

Nerys Corfield - Director, Injection Consulting

Henry Iversen - CCO & Co-Founder, boost.ai

Jon Arnold - Principal, J Arnold & Associates

Kane Simms on LinkedIn

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