The Conversational AI Podcast

So, today I got access to ChatGPT's Agent feature and I wanted to record something for posterity. This one is best viewed on Spotify or YouTube if you'd like to see the live screenshare as I'm talking, otherwise I do my best to describe things as we go. My chosen task for Agent was this: Login to my LinkedIn, accept some recent connection requests and say "Thank you for the add, [Firstname]" to each connection. Simple, I know, but I wanted to keep things simple and easy. It handled things really, really well -- so much so, that I felt myself being 'upgraded' (or wanting to upgrade) to the $200 ChatGPT subscription as I watched it work. See what you make of it!

In this episode, I'm talking through a case study about how NatWest Bank in the United Kingdom is using Generative AI to analyse the output of their Conversational AI (chatbot) system, Cora. The source is a post by Wendy Redshaw on LinkedIn. Wendy is the bank's Chief Digital & Information Officer. You can find her post right here. TakeawaysI'm a fan of NatWest and follows their executive output.NatWest is using generative AI in a careful and controlled manner.Generative AI adds value primarily through conversation.Cora, NatWest's chatbot, is a key use case for generative AI.7,000 conversations have been summarized using generative AI.Human review is essential for evaluating AI performance.The average rating for AI-generated summaries is 4.95 out of 5.Understanding customer complaints is crucial for financial institutions.NatWest uses the Lama 3.3 model from Meta through Watson X. Chapters00:00 Introduction to NatWest and Generative AI02:51 Exploring NatWest's Chatbot Cora and Its Impact05:44 Evaluating AI Performance and Customer Insights09:08 Technology Behind NatWest's AI Initiatives

I'm taking a little bit of a departure in this episode because I'm talking about some of my activities today to create an app that I wanted to use for myself. And I did this using Claude across the space of about two hours -- and although I've been doing this very regularly, I can't help but be incredibly impressed and enormously reflective on what the power and capability of these tools means for commerce, enterprise and society. So this is a Stream of Consciousness episode. And in case you were wondering, I used my own little piece of software to dictate this text. Watch or listen to the episode to find out more.

In this episode I had the pleasure of interviewing Paul Walker, Global Solutions Director at iManage. With 25 years of experience in legal tech, Paul offered valuable insights into how AI has evolved in the legal and professional services sectors.We discussed how iManage specialises in knowledge work industries, particularly legal and accounting, and explored the revolutionary impact of generative AI. Paul explained how AI has transformed the way organisations manage unstructured data, significantly reducing the lead time for extracting answers from this information.A key point Paul highlighted was how AI now provides crucial context to unstructured data, substantially enhancing its value. Throughout our conversation, he emphasised that curiosity is essential for effectively adopting and leveraging AI technologies.Looking to the future, we discussed how AI interfaces might evolve beyond traditional prompts toward more intuitive interactions. One of the most practical takeaways was how AI can boost productivity by automating laborious tasks, with Paul predicting that the integration of AI into workflows will become increasingly seamless over time.Check out Paul's LinkedIn profile and find out more about iManage at www.imanage.com.

In this episode, I'm looking at a very, very simple query I put to Google's Gemini regarding my email inbox. Oh dear. Hold the Agentic AI Revolution for a few minutes.

In this episode, I'm sitting down with Kit Cox, Founder & CTO of Enate, exploring Kit's journey from a young coder (BBC Basic anyone?) to the founder of Enate's workflow automation platform. We discuss the evolution of Enate, its applications in service delivery, and real-world use cases, particularly in the B2B sector. Kit explains how Enate helps organizations operationalize AI, improve customer experiences, and drive business growth. Our conversation highlights the importance of sentiment analysis and the need for organizations to adapt to new technologies to remain competitive. Chapters 00:00 Introduction to Conversational AI and Innate AI 00:09 Kit's Journey: From Coding to AI Solutions 04:01 Understanding Innate AI's Workflow Platform 08:08 Real-World Applications: Case Study of TMF 12:16 The Role of AI in Service Delivery 15:57 Extensibility and Integration of Innate AI 16:00 Innovative Use Cases and Customer Success Stories 24:14 Operationalizing AI in Business 26:33 Deployment Strategies for Innate AI

In today's episode, we're meeting ⁠Darren Ford⁠, the Founder and Director of ⁠The CAI Company⁠. Darren and his team are amongst the most experienced Conversational AI experts around, having driven the strategies and implementations for some of the largest players around. Our discussion is wide-ranging. We start first with Darren's background and the origin story of ⁠The CAI Company⁠. Then we get into some key use cases, he talks about how consumer acceptance is really changing (for the positive) and he highlights some of the key requirements for any successful implementation -- namely, executive sponsorship and commitment, data-led decision making and the importance of talent development. Reach out to Darren ⁠at his company website⁠ or ⁠via his LinkedIn Profile⁠. Chapters 00:00 Introduction to Conversational AI and CAI Company 02:47 Darren's Background and the Origin of CAI Company 04:10 Use Cases and Growth of Conversational AI 10:08 Consumer Acceptance and Chatbot Horror Stories 12:30 Generative AI and Executive Awareness 15:48 Talent Development in Conversational AI 18:44 Ethics in Conversational AI 20:59 Internal vs External Chatbots 23:46 Key Considerations for Executives in Conversational AI Keywords Conversational AI, CAI Company, chatbot, generative AI, voice technology, user experience, ethics, talent development, executive awareness, use cases

In today's episode, I'm speaking with Ellen Keenan-O'Malley, a commercial IP lawyer at EIP, about the legal challenges surrounding Artificial Intelligence and Conversational AI. We discuss the current state of AI law, the implications of GDPR on Conversational AI, and the importance of understanding liability in AI solutions. Ellen emphasizes the need for companies to consider legal aspects from the outset of AI development and highlights the evolving role of legal professionals in the tech landscape. If you've got any questions around the topic of intellectual property and AI, I would strongly recommend reaching out to Ellen for a conversation via her corporate profile on EIP.com or her LinkedIn profile. Takeaways AI law is currently ambiguous and evolving. Companies often approach lawyers at the last minute. Data protection is a significant concern in conversational AI. Existing laws like GDPR still apply to AI technologies. Indemnity provisions are crucial for AI vendors. Legal considerations should be integrated from the start of AI projects. Human intervention is necessary to mitigate AI risks. AI can enhance efficiency in the legal profession. The legal profession must adapt to the rise of AI. Engaging with legal experts early can save time and resources. Chapters 00:00 Introduction to AI Legal Issues 03:38 Navigating AI Regulations and Compliance 08:36 Understanding Liability in AI Implementations 11:15 The Role of Legal Professionals in AI Development 15:17 Future of AI in the Legal Profession

In this episode, I'm speaking with Neil Marley, CEO of Qualyfi, about askQ, the dedicated AI assistant built for technology delivery and consulting teams. AskQ is an LLM/RAG-enabled solution that provides 24/7 contextual answers for anyone working in your technology environment - so it's especially useful for consulting and tech delivery teams. We discuss the evolution of technology delivery, the role of AI in training and development, and the challenges faced by organisations in standardising processes. Neil shares insights on how Qualyfi aims to democratise knowledge and provide opportunities for individuals from diverse backgrounds to excel in tech delivery. We also explore the future implications of AI on the tech industry and how organisations can leverage these advancements for competitive advantage. You contact Neil on LinkedIn or via the company's website at qualify.co.uk. Takeaways AI is at a similar maturity stage as the public cloud was in its early days. Qualyfi aims to open opportunities for individuals without traditional academic backgrounds. The AskQ service combines Qualyfi's IP with an LLM to provide relevant answers to users on demand. Training and mentoring are crucial for early career development in tech. AI can significantly reduce the time required for tasks like creating statements of work. Standardization in tech delivery is essential for efficiency and risk management. Qualyfi's approach focuses on empathy and determination in selecting candidates. The future of tech delivery will involve smaller teams using software agents. Organisations need to adapt their talent acquisition strategies to include AI tools. Chapters 00:00 Introduction and Background 00:31 The Rise of Public Cloud and AI 02:30 Qualify's Mission and Methodology 05:26 The Role of Conversational AI in Training 08:22 Humanising the Learning Journey 10:47 Challenges in Tech Delivery 13:49 Qualify's Service Offerings 16:26 The Future of Tech Delivery with AI 19:38 Implications of AI on Workforce Dynamics 22:40 Navigating the Current AI Landscape 25:28 Conclusion and Call to Action

In this episode, I'm meeting Tom Sherwood, CEO of Koios to discuss the bleeding-edge field of emotionally intelligent AI. This is definitely worth a listen. Tom shares his unique background (the Army, Recruiter, Snap, Spotify!) and then goes on to explain the formation of Koios, and how their technology leverages voice analysis to understand personality traits. We explore some of the applications of the Koios technology in the recruitment and sales markets, we discuss the business model behind the Koios API, and I ask Tom about the future of human-machine interaction. Tom finishes by discussing the importance of human connection in AI systems and offers insights for those developing conversational AI interfaces. If you'd like to know more, I strongly recommend reaching out to Tom directly via his LinkedIn profile. Takeaways Emotionally intelligent AI can enhance human interactions. Voice analysis can reveal personality traits effectively. Recruitment processes can benefit from personality insights. Sales strategies can be tailored based on personality understanding. Koios uses acoustic and linguistic data for analysis. The business model is based on API calls for analysis. Human-machine interaction is evolving with AI advancements. Understanding the human element is crucial in AI development. AI can help scale coaching and training in organisations. Future applications may include personalised virtual coaching. Chapters 00:00 Introduction to Emotionally Intelligent AI 02:40 Tom's Unique Background and Journey 05:52 The Birth of Koios and Its Mission 08:43 Understanding Personality Through Voice 11:30 Applications in Recruitment and Sales 14:39 Business Model and API Functionality 17:33 Ethical Considerations and Use Cases 20:46 Future Roadmap and Human-Machine Interaction 23:45 Enhancing Conversational AI with Emotional Intelligence 26:16 Final Thoughts and Recommendations