How CX Leaders Should Own AI Agent Performance

Hello and welcome. I'm Rob Wilkinson at CX Today and today we're taking a closer look at how CX leaders can take ownership of AI agent performance. If you're challenged with proving the impact of AI beyond deployment or if you're exploring AI as an opportunity to improve customer outcomes through clearer goals uh measurements uh and frontline orchestration and stay with us because today I'm joined by Gal Rimon, CEO and founder of Centrical whose AI orchestration system helps organizations connect strategy to execution across both people and AI agents. Welcome, Gal. Thanks for joining me again. Good to see you. Thank you for having me, Rob. Gal, just kind of set the scene a little bit again for the audience today. When um when an AI agent starts handling this frontline work, which we're starting to see really happening right now, um what does the real accountability look like in all of this? The accountability today is with the owners of the AI agent. So the big question would be if uh there would be technology people that will understand better business the business process or it would be the business process people that will understand better technology. I think that eventually it would be you know from both ends. you know people that have technology background will be less um required to to write code right and on the other end everyone should understand the engineering mind engineering mindset of algorithms of uh how to define better the business goal and and the processes. So this is the first question of ownership. It's like who are the people that are actually designing the AI agent and the second thing whether it would be the same people or not. How would they keep the observability part around the AI agents and keep improving the process? Basically this is like the operational part and uh the optimization of the process because thing keep things things keep changing constantly. So this is the first question about uh accountability and ownership is like who owns those processes of creating and maintaining. The second thing is the boundaries, the handoffs between the different actors in a big process like what we had you know before a few like few years before we had this omni channel big question. how to maintain the same experience for the customer across multiple channels and not just that it would be multiple channels but it would be the same conversation and I want needed to explain again and again what's the what's my problem uh because it's a bad experience. So once you've got that that ownership in place though, how do CX leaders then start to measure the the AI agents performance? Um especially in a way that's going to link the AI as activity to a strategic business outcome because this is the the challenge right now, isn't it? Linking these together. How how do we do that? Yes. So it's a it's a very very challenging question because the question is uh I'll use one term uh attribution. The question what's the attribution of the single component in a big chain right you have a chain a value chain of a full process sometimes multiple chains and and this is the reason why we start to use the term workforce orchestration system over coaching or performance management or observability because it's much more complicated and will become even more complicated. Just to kind of call out some recent research, the the actionaries research that we talked about previously. Um that said that every AI initiative will create a human ripple effect um which is like kind of what you're talking about I think there. So, how should human agents and their managers um basically work alongside AI agents? If we're going to do this in one singular performance model, the accountability of organization leaders, business leaders would be to help their employees, whether they're the agent, the supervisor, the operational manager, and even executives relevant to the future. What should CX leaders do now though? um if they want to close a gap between the insight, the AI insight that they've got and the action on the front line um because that's how they're going to prove the value of these AI investments. So how do they do that? They they need to put the focus on the two main actors. One is the human actor to make them better, to make them to help them grow, to help them reskill and upskill, to help them be mobilized to different roles, to help them adopting AI, to help them understand that their role is no longer performing according to the process, but sometimes even understanding how to be creative with the process like the previous example and uh designing even redesigning different processes. So basically you will have a new type of driver that might have not might have but have AI agents to help them. Okay. And they will work also aside aside uh uh beside of uh uh different AI agents right as a as a team or maybe AI managers probably right uh and and and be relevant. So I think this is one very important task or or strategic task for leaders to address. The second is again and I think this is um a very simple to explain a very hard to execute is how to build the relevant orchestration layer around the agentic workforce and then how to connect the two. how to create a flawless or frictionless experience between the different actors in the process. And and I think it's it's not easy. It's it's understanding better the your process, your business goals and uh redesign it. So, so you need to break the mold and not to create a humanoid uh AI agent over that you can utilize truly AI and human and make them work as a one team to help your customers. It's so exciting this time we're we're in. It is uh truly fascinating. Um and um I I love everything you've shared there. It's been a super valuable discussion on what it really means to own that AI agent performance. I think um for me the key takeaway today is that AI agents um need more than just deployment. They need clear goals, measurement, feedback, governance, uh a place within the wider frontline performance model. Um you know we should treat them you know with as much respect as we do our human agents. But uh for CX leaders, I think the opportunity is going to be to manage people and AI agents together um so that that AI investment can turn into better execution and better most importantly of course customer outcomes um which is ultimately the delivery that we want to see. Uh before we close uh G what what's the the sort of one practical step that CX leaders should take now to prepare for this sort of hybrid front line would you say of course work with Centrical right but besides that um they need to look at the ability to create an orchestration layer to to look at the top down bottom up process with a compounding feedback loop otherwise they will keep failing. They will keep doing the tasks well but fail with the overall process. So basically the ability to declare the business goal, create planning, observability and and course correction and then compounding feedback loop that will write a kind of a codex set of skills, set of playbooks that that would be dynamic and dynamically would be built and be relevant all the time and not become obsolete like all of those PDFs or how to run the business PDFs that are obsolete before you even uh finish writing it. So definitely an orchestration layer or system is critical to create this type of success for the long term and for scale and and just one last thing and arrive to the big game of course. Of course yes um the big game uh that Centrical's event in uh in October 15th in London. Um that's awesome. Uh also don't forget that you can find more articles and resources uh videos just like this one at cxtoday.com. Uh but now that's all we have got time for. Thanks again to Gal at Centrical for sharing. Uh I'm Rob Wilkinson. Thanks very much for watching.