What Shared Intelligence Really Fixes in Enterprise AI - with John McMullan of Observe.ai

Yolandi de Weerdt (0:12)

Welcome everyone to the Emerge AI in Business Podcast. Today's guest is John McMullan, Head of Product Marketing and Strategy at Observe AI. Observe AI is a CX native AI agents platform that enables enterprises to deploy specialized agents that understand context, reason and take action across the customer experience lifecycle. The platform includes orchestration, integrations and governance features that support consistent and reliable automation across CX operations.

In today's episode, John unpacks why so many enterprise AI investments in customer experience fail to deliver measurable returns. He explains why rollouts without operational discipline leave frontline teams rechecking the tools work, and how a shared layer of interaction data lets every AI agent and human pick up where the last one left off. Today's episode is sponsored by Observe AI. In this episode, we cover how AI investments in customer experience fail to deliver measurable returns. To go deeper on this topic and learn how to identify real AI trends by tracking where venture funding is flowing, and by listening to how leading CEOs describe risk and competitive strategy, download our free PDF report, three ways to discover AI trends in any sector at emerge.com/ait1, that's emerj.com/ait1 to download your copy. Now the conversation with John.

John, welcome to the Emerge AI in Business Podcast.

John McMullan (1:54)

Thank you. I'm excited to be here and look forward to our conversation.

Yolandi de Weerdt (1:57)

Yeah. I think this is a conversation that really needs to happen because we have gone past that part, what was it, two, three months ago, where we were still talking about, oh, we need AI, and why do we need AI? And I think everyone now has some sort of AI built into their platforms. And I like to think of CX as the first part where we really saw AI popping up even before what it is now. But something that we keep on hearing these days is that there's a lot of AI interest, there's a lot of budget, but the results still aren't there.

So I want to get into what is that bottleneck, what's been preventing enterprises from getting real, measurable value out of their AI in for the customer, front line, and their back office workflows.

John McMullan (2:41)

The noise is feverish, right? And the fun part, I've been in conversational AI somehow some way 15 plus years. A lot of these promises aren't new, but with obviously the advent of LLM and these frontier models that are coming out, there's a lot of hype and a lot of FOMO driving a lot of these decisions. So companies have made investments, jumped in feet first to say we're going to adopt AI. Some have even gone as far as saying we're going to be AI native, but a lot of that ROI has not come to fruition. And I think that really stems from interest without discipline. And what I mean is it's not that AI is not prevalent and available, and there's certainly no shortage of problems to solve with AI, but this isn't the old world where you'd buy like a SaaS application and say, oh, we need a new billing system or a new CRM and grab it off the shelf and implement it or cut over from your old one, and it just works and goes. AI is like continuous learning cycle, a continuous investment where the system is going to uncover new edge opportunities, need constant tuning and tweaking. So there's been a lot of interest. I think companies have scrambled to bolt on AI or put it into workflows, but they don't fully understand what it means to adopt AI and what goes behind the scenes to make it work. And yeah, we can get into some of that more, but I think it's not an uncommon problem, right? Everybody's moving fast, there's a lot of noise, there's a lot of hype, but really it comes down to what are the tangible next steps for a business, and that comes with thoughtful experience design, which we can talk about here.

Yolandi de Weerdt (4:10)

Yeah, I want us to get into that some more, and especially I think what you just mentioned is very relevant. That AI FOMO was so real, and thinking about the platforms that we were used to back in the day, it had the functions that the box set, and that's it, and that's what we expected of it. With AI, it's kind of like introducing new employees to your organization, and they need constant learning, and they need to, professional development is part of their annual training and things like that. So we should be thinking about it. Is that the only friction points or the only reasons that we see our CX environment really flourishing and getting real ROI from AI?