How AI in the Contact Center is Powering Real-Time Insights, Smarter Agents & Better ROI

In this CX Today interview, Nicole Willing speaks with Steve Blood, VP of Market Intelligence at Five9, about how AI is evolving into the connective layer across the modern contact center.

As organizations move beyond disconnected tools, Steve explains how combining AI with a unified CX platform enables real-time insights, smarter routing, and more personalized customer interactions. By bringing together interaction data, operational data, and customer history, enterprises can gain deeper context and make faster, more informed decisions.

The conversation explores how AI-driven systems analyze customer intent and sentiment in real time, enabling dynamic routing, immediate coaching insights, and continuous optimization across the entire customer journey. Steve also discusses how AI is augmenting agents with real-time guidance, helping them deliver better outcomes while reducing burnout.

Watch the full conversation to learn how to unlock real-time insights, empower agents, and deliver more connected, intelligent customer experiences.

For more Customer Experience tech news visit https://www.cxtoday.com

Transcript

SPEAKER_00 0:07

At CX today, we've been exploring how companies are moving off legacy platforms to the cloud, introducing AI responsibly and empowering agents along the way. So today we're looking at the next step, which is how AI isn't just an add-on anymore, it's becoming the connective tissue that unites people and operations across the Modern Contact Centre. I'm Nicole Willing, and I'm joined today by Steve Blood, VP of Marketing, Market Intelligence at 5.9, to explore how organizations can unlock smarter agents, more meaningful customer interactions, and measurable ROI in this new era. Steve, it's great to have you with us.

SPEAKER_01 0:40

Thank you, Neil. Nicole, good to be with you.

SPEAKER_00 0:42

So when it comes to the status of AI adoption, you know, in 2026 now, one of the themes is that AI is evolving from a bolt-on feature to something that connects systems. So what does a truly connected AI-driven context enter look like in practice?

SPEAKER_01 0:58

Yeah, I think that's a really that's a really good question. I think, you know, to your point, you know, it I think we see various pieces that are that are disconnected right now. Self-service, especially, right? That's very much disconnected. Doing good things, but it's a own specific AI, same thing with routing coaching, you know, things like that. So for us, I think, you know, um, we think that um that that really challenges the consistency for a customer journey. It's all disconnected and and what have you. So we think that what we need to look at is uh combining the power of AI with a unified CX platform. So if you put those two things together from a data perspective, we're able to fuse interaction data with operational data and customer history. And that the AI then gives us contextual intelligence. What's happening? What are they what's the customer trying to do? How do they feel? What should happen next? All of that is important from a bringing that together from a data perspective. From a people perspective, you know, we've already using um tools like you know, productivity tools, agent assist, uh summarization, but that same underlying AI capability we have from a data perspective, uh, we can now start looking at uncovering nuggets in the service reps conversations. Somebody knows something important. It's not written down anywhere. Oh my goodness, this is this is gold. We've got to get that into the knowledge sources. We can use it to power better self-service experiences. Supervisors as well, right? They no longer have to look at the or listen to the two or three calls that get listened, you know, that get recorded at the end of the month. They're getting real-time insights, everything's being updated, and so therefore they can see there who's struggling, who needs more coaching. Um, which of the reps didn't listen to the new product training that we had last week? As I can tell in the conversation they're having with customers. So I think then from a process perspective, um, you know, that contextual intelligence means we can start getting more personalized, understanding where the customer is in their specific journey, and applying the best uh the best case for that. So, you know, yeah, for us, the C a unified CX platform tells you what's happening, the AI tells you what you should do about it and what to do next. So a combination of those gives the customer a better end-to-end experience, and from a company perspective, they can maximize the value of a common AI investment across multiple use cases.

SPEAKER_00 3:21

Yeah, absolutely. So then to build on that, obviously, we hear a lot about Agentic AI now and that it's moving, you know, not just the um automation but the orchestration aspect of it. And of course, there's a lot of debate around the human role. Um, so how does that change what agents are going to be doing day to day?

SPEAKER_01 3:38

Yeah, I mean, obviously, agentic is really uh, you know, about um uh uh understanding, actioning, and and making decisions, you know, on behalf. And then and that um that's in its infancy, it's emerging, and I think that's the really important piece. We mustn't get too far ahead of ourselves, especially in Europe, right, where um an agentic system is would now be regarded as a high-risk AI. Um and and that and if a company gets it wrong, if they make the wrong decision on a mortgage application or penalize an employee because they used agentic to quality school them, they're big fines uh from the EU regulators as a result of that. So we need to be a little bit careful about that. But I think you know, when we look at it, we um we look at it sort of like you know, as a continuous learning journey, if you like. So we put those pieces together. Each customer interaction, whether it's a voice or a message, is analyzed in real time to understand intent, sentiment, and and things like context. That intelligence then informs genius routing, so we can ensure that customers are matched to the best resource, not just at that moment in time, but based on uh historical performance as well as live. Each of those interactions is then automatically evaluated through AI-driven quality assurance, generates coaching insights and improvements that could be pushed back to the employer or to the supervisor, and then those quality and performance signals flow into unified analytics, where business leaders get their perspective on how we're performing, and then those are fed back into uh routing and engagement strategies. So it's about optimizing the entirety, and as that gets better, we can trust the AI to do more um automation or autonomous activities. So for us, that that's the approach that companies would take to getting to that point where they can start utilising agentic more in the future. I won't say where some companies are moving quite rapidly, others are more cautiously. So certainly we expect to see more this year.

SPEAKER_00 5:36

Oh, yeah, absolutely. So it sounds like it's a scale where you've got people moving at different speeds and paces depending on their own individual situations. So then, but it also sounds like really you've got this system then with AI connecting the dots between all these um different elements. So then what kinds of insights or actions become possible that weren't achievable with the past um the kind of disconnected systems?

SPEAKER_01 6:01

Yeah, yeah, great question. So I think you know what we have to think about here is um if we um we set up we set up a set of skill plans, say, for an employee, okay? So genius routing, great example. We've got skill-based logic, uh, we've got their you know, customer intent, um uh employee behavior, and so on. So we use those elements to decide who we should be connecting to. Uh, but then what we're able to do is um is to kind of look at well, um how is uh how is the custom what's the customer's sentiment as they're going through the earlier stages of their journey, and then using that to influence how we route them moving forward. So you know, if there's a we're detecting a frustrated customer during an interaction, the AI analyst piece will will dynamically rebalance the workload, uh, you know, keep things like wait times down, things like that. And as I mentioned earlier, if you've got an employee that wasn't listening on that training program, they're giving wrong information as they're going through. That's a bad experience, that's picked up immediately, not at the end of the month when they do the the three or four quality uh assessments. And so you're able to then change the skill mapping. So, okay, this employee needs to go back on training, let's take them out of that skill set until they're they're they're proved themselves that they're ready for their product. So that's I think where we would see those pieces starting to come in. And again, it's because we're using the insights and and the data and the analytics from from each step of the journey that we feed that back in to make that work.

SPEAKER_00 7:33

Yeah, so it really comes ultimately, it's about the customer, isn't it? And how how their experience is affected by all that. So then um, building on what you were just saying, how does the this AI-driven ecosystem kind of support real-time um insight interactions and real-time personalization?

SPEAKER_01 7:52

With uh with things like people for humans, yeah. Um I you know, I mean, I think um we we have to kind of get over this myth. I think we're almost over it now that AI is about replacing humans. It was big last year, it was it was pretty scary and things. I I think you know, towards the end of last year and and you know, into this year, we're very much understanding that uh across all workloads, not just the customer service, but you know, digital workplace as well, the real breakthrough comes when you augment employees with with AI. So um, you know, we we've been uh with Genius AI, but service reps are supported by real-time guidance, post-interaction insights, personal coaching. We believe that helps them learn faster and provide better answers and support to customers. So customers spend less time on hold, uh, they they they get um, you know, the employees are less burnt out because they really feel that they're providing a a better level of service to them. Um so you know, that for customer experience is also good. They think, oh my goodness, they yes, they I got an answer to my question, I got it quickly, and they they didn't sound like they were reading from a script. So, yeah, those sorts of things are quite important. I think at a leadership level, um AI kind of compresses the the decision-making cycles. Those, you know, as I mentioned earlier, those insights come through in the moment or certainly you know much faster. Um, and and and they're getting context and recommendations in terms of what they should do next. So, you know, again, leaders are still deciding, but they do so with the insights that that are made available to them so they've got clarity and speed and they can do it, do it with confidence. So um, and I think the other piece also to think about is the the turnover in service centres is quite high. So we're expecting to see a reduction in the number of people. Now, what that means is that people uh staff are gonna take on different roles. You know, if if we we do have self-service doing a lot of the front-end stuff, um, then staff are gonna need new roles. And there was an interesting statistic that I got from a Cavell survey into agent experience. They did this at the end of last year, and uh two-thirds of those service reps said they were ready and prepared to supervise uh and coach AI assistants. And I thought that was now, I I don't think they've necessarily got the skills today to do that, but that's something that service leaders can build on to say, right, those people who at one point was kind of dead against it and said, oh my goodness, you know, this is bad and uh it's gonna take away my job, they're now thinking, actually, I can work with this and I can be a supervisor of AI. So they're gonna start moving into those roles. Uh, far more important. We're also expecting some staff to move into knowledge areas. You know, knowledge, when we do self-service, the most important thing is does the AI agent know as much as the employee? Um, and can it index and use that data easily to provide a quick response, right? You know, we don't want them waiting two or three minutes. You know how long it takes for Chat GGBT sometimes to come up with an answer. We can't have that in certainly in voice or even in chat for that matter. So working out what the knowledge sources would be, though these are new roles that these people are going to be taking on. So I think we will end up with smarter people, um, and they'll be providing more, you know, as a result, customers are gonna get more meaningful uh uh um results and things.

SPEAKER_00 11:09

Yeah, that's so interesting because uh, like you mentioned, obviously there's the scaremongering about losing jobs, but it does create new opportunities, right? Um but does that also then change the type of um skills and abilities that um recruiters would be looking for in the people that they hire into the contact center?

SPEAKER_01 11:27

Yeah, we would we would expect them to be looking at certainly um sort of more understanding of uh I talk about intellectual curiosity. Okay, so the employee's done a great job, they've closed down that request onto the next one. But why did it happen? Um looking into the reasons as to well, what could we do to fix that? What could we do ensure that the next customer doesn't have that issue? And then more importantly, that same customer doesn't come back with the same issue and things. So there is that level of coaching, I think, required, or understanding of different employees. Things like um certainly better at empathy. I mean, you must have experienced this, Nicole. Some people just are not very empathetic, are they? And if you've been through a horrible uh self-service experience, you're gonna want to uh you know to improve on that, and and um, and and you're gonna want someone that sort of understands and and you know, and not only understands, because I I have this thing, empathy isn't just about saying I'm sorry, empathy is uh that's sympathy, by the way, I'm sorry. Empathy is I understand the problem, you've explained it to me, this is what I'm gonna do about it, and at some point I'm gonna call you up or message you and tell you I've fixed it for you. That's empathy end to end. And so having those skills, now that means taking time away from being on the phone or uh messaging away. So they these skills, you know, this is gonna uh and and so career recruiters have to look at these different skill sets that employees are gonna need to sort of you know to to to be able to in that sort of role.

SPEAKER_00 12:52

Oh yeah, yeah, absolutely. Um, so then all importantly, you know, talking about ROI, uh it always comes back to ROI. Um so you know, in the in the context of this um migration that we're seeing, how has the equation changed now? Um now that we're saying that AI can scale across different capabilities instead of just these pilots or you know, proof of concepts that there's been so far?

SPEAKER_01 13:15

Yeah, so I mean this is this is I mean, we do believe there's a broad range of capabilities, but we would coach um customers not to move too quickly. Um, you know, take uh basically successful companies start out but have a very clear understanding of what their service issues are, right? You know, technology is useless if you haven't got a problem to solve. There's nothing's nothing's going wrong, we can't sell you anything, right? And we know there are things going wrong, so we've got lots to sell. But so it is about understanding what are the problems that we've got and then coming up with a prioritized roadmap of where should we focus first, because these are multiple projects that we're effectively going to be doing. I think also success comes when there's a mutual understanding between IT and the business. So when they're understanding together what does operational efficiency mean and what does a great customer experience mean as well. And you know, that's really key because we've seen so many failures where companies built as an inside, we're building for us, we're building self-service for us. And that didn't work for the customer. So good experiences are when you say, What does the customer want? And we build this for the customer, they will then use it, and then we will achieve the efficiency and the cost savings, etc., that we'll be expecting to. So I think you know the idea that you you you you do all that, you understand what your issues are, you have this agreement between the business in terms of the focus you're going to have, you prioritize those engagements, and then you start rolling them out. And you and you start small, and then you build them out, and and you you're successful with one use case, and you use the the funding or the cost in the inefficiency savings on that to then go into the next one. So it's a continual flow from that perspective. I think what's really interesting though, the scary thing is what happens sometimes is that um good uh good AI uh solutions means more contact. So customers connect with you more because they're getting answers that they want. And that's pretty scary because companies are thinking, oh my god, no, we're trying to reduce the number of connections. But if you think about that, the other what a great opportunity to offer value. So, you know, if you get your AI service, if you get your AI agents working correctly, then customers get the self-service they need and you deflect the peer-to-peer engagement, leaving those employees to add value where it's where it's going to be more important. So, yeah, done right, we think, you know, um AI on the front end in terms of supporting customers in self-service, and then moving it through to supporting the employees that in turn then do a better job of supporting the AI agents on self-service. So it's definitely cyclical from that perspective, and uh, you know, I think a good opportunity.

SPEAKER_00 15:55

Yeah, I think that's something that uh is does seem to be changing, like you say, going from that inward outward perspective to flipping it the other way and saying, okay, let's start with the outward, and then obviously that brings the benefits to the business.

SPEAKER_01 16:10

Absolutely right, yeah, yeah. And the and to the customer. Brings the benefits, and that's the thing. If customers use it, then you're achieving your objective. If you build it and they don't like it, they're not gonna use it, and then you've wasted your money. So, you know, it's it's easy to say, but you know, it's so often, it's so internal focused. Oh my, we must save money. How are we gonna do that? We're gonna and we've experienced it ourselves, right? Some of those chatbots are awful.

SPEAKER_00 16:35

I think we've all had the painful experience of the case. Yeah, yeah, that's right.

SPEAKER_01 16:39

Yeah, we can totally relate to this.

SPEAKER_00 16:42

Yeah, yeah, absolutely. So then um, what would you say are the signs of maturity that show that a contact center has moved from being AI-enabled to genuinely AI-led? Like, you know, how would leaders be able to tell they're succeeding?

SPEAKER_01 16:57

I think I think that certainly better data. Uh, so the various touch points as you move through this unified platform we talked about, um it is true. I mean, you know, um you can integrate and create uh a level of unified data with disparate platforms. Um, but the reality is it's really expensive, not only to build, but also to maintain, because you're dealing with different vendors with different products. So the reality is it doesn't happen. And that's the problem. So, you know, um, I'm not gonna say it can't be done. What I'm saying is if you use a unified approach with a single CX platform, it comes kind of out of the box, right? It's there and you can just use it. So the data sources uh enable you to be more effective, you get a better idea of where the where where the benefits are. Every time you make an improvement um in say uh the the knowledge sources for the employees, that that gets fed back into self-service as well as being used by the employees. So I think it's um yeah, the benefits come really through um just a more a more uh a customer um journey that is far more connected. Um, you know, they they they do some stuff in self-service, they get stuck, or the next step is to move to assisted service, all of that context goes with them, the employee carries on, they're supported by uh agent assist to get that interaction done, and the result is the customer is happy. We can detect that in sentiment during the conversation. We don't have to rely on a uh a survey afterwards, which by the way, Qualtrics said nobody wants to do they're fed up with surveys, no one's doing them. So it is important that we've understand the voice of the customer and uh customer sentiment through other means, and obviously doing that while you're engaged with the customer is one of the best ways to do that. So I think put all that together, then we can start to see start to see some success uh maturing.

SPEAKER_00 18:52

And also when it's all working right, they should see that in in growth, right? Higher revenues. Well, yeah.

SPEAKER_01 18:58

I mean growth is still a growth is still an objective. Uh companies are being told that you know, not only is this about improving customer experience, it's also about growing the business. And so, you know, coming back to the point about if you do self-service or AI and self-service well, customers are going to connect with you more. That's then the opportunity to say, okay, we can now set up better engagements. And of course, that then goes back to are our staff ready to do this? What sort of training do we need to give them so they can be more effective from that perspective? But yeah, it's uh we make it sound so easy, don't we? I know it isn't. It's a tough, but you know, the the opportunity's there, and and so uh I think you know there we we're gonna see some some greater success this year.

SPEAKER_00 19:42

Yeah, no, absolutely. I mean, I think you know, in a way it's become overcomplicated in in the way that companies are approaching this, and like you say, it's actually I mean, it's not as simple as it sounds, but it if it's approached in a logical way, it kind of can be. Absolutely, yeah.

SPEAKER_01 19:59

And and you know, it'd be wrong of me not to mention trust, right? Yeah, companies have got to trust the model they're using is gonna work, and you know, for us, that's all about the dial of trust. Okay, so you know, um, effectively what we're saying to customs is if you're a highly regulated industry, you might want to err more towards scripted, um, more controlled um answers that that come through scripted dialogue. Um, and then if you if you're if you're not so regulated, or uh you would be able to move that dial the other way. So you can start to use conversational um and generative AI to start working out intent and then start working out the responses and so on. So we've got this dial of trust, um, and and that's we think that's important. So companies can dial it down, do the work that work the business cases, work the use cases, get the success, and then slowly dial that uh you know, move the dial up and then test again and and confirm that things are working um before you know as they move to higher scale. So it's definitely a combination of both. Um and um yeah, uh putting those together again, if the trust is there with with our customers, then uh we're gonna see more use use cases evolving.

SPEAKER_00 21:12

Yeah, that makes sense. Um so then I always like to ask the forward-looking question, and I mean in a year or two in AI, anything can happen. But um, what do you think are the key capabilities or innovations that will define this next generation of contact centers?

SPEAKER_01 21:28

Um I think beyond where we are now, I think so. Right now, um, you know, we we've we've we've we've got this opportunity to to use more autonomy um in the way that um uh uh engagement's created, especially in in self service. I think I'm really um intrigued by uh Google's launch of Universal Commerce Protocol for Um for Gemini and and and and and and other uh large language models and things. So just as you are online, say you Using using Gemini perhaps to uh book your next flight, you can then use the UCP to actually go ahead and do it. So, this is what we call a machine customer. I've been I've been a big fan of machine customers. This idea that there is um a an actor working on your behalf, a robot working on your behalf to do things that you say it can do. I mean the simplest one is obviously um HP Instant Inc., right? When the ink drops down to a certain level, it automatically reorders new new cartridges for you. We're moving way beyond that now, but I think UCP is important because it starts to change that perspective of um who's actually the who is the customer going to be. And the big challenge for service organizations are gonna be by the way, there will be still errors, right? Machine customers may go and buy something or try and buy something or transact, and there will be an error, there'll be an escalation. Um, and that escalation will come to a human, and you then have to ask the question well, um, there's no point uh exhibiting empathy, bots don't care. It's black and white, it's you know, it's one and zero to them. So what you now have to look at is how do I respond? Um, what's the best way to respond to uh a machine customer rather than a human customer, and how do those things work together? So I can see a lot more, uh a lot more understanding of the customer, knowing that they've got they've got machines when they're likely to be engaging with those, that's going to be important. The idea of um one machine talking to another is you know, obviously the agent-to-agent protocol, uh things like that will start to. So I'm I might be getting a bit ahead of myself, but I think it's fascinating what could start to evolve over the next uh next two or three years. But I think you know, we've got plenty on our plates now, uh, plenty of technology that we need to mature. And we need to move beyond the uh beyond the hype of the you know, the oh my goodness, uh, you know, the we can do anything uh and get into the reality of what is feasible, um, and then start rolling those out. And and and that's really you know where we are, I think. And this year could be quite productive from that perspective.

SPEAKER_00 24:05

Yeah, no, absolutely. And I mean, you we're saying that um the machine customer might be away off, but then these things move so quickly that it could be it could catch um you know leaders unawares if they're not prepared for it. So, what kind of advice would you give to tech buyers who are looking at all of these things coming at them and how they need to prioritize?

SPEAKER_01 24:25

Well, I think I think you should be asking, you should be asking your supplier about you know where their where their strategy is, what what is their plan for the next next few years? I think also you should talk internally. So, you know, machine customers aren't gonna happen in every industry. Um those that are heavily digitally centric, so retail, finance, um, there's a lot of um machine customers going on also um in manufacturing. So some sectors are gonna be likely need to look at how they adopt that faster than others. So I think looking internally in terms of what are the what are the needs, what are the requirements. Um and then so I think you know that then sort of tempers and scales uh the the the need and the necessity. Um and then it's a case of looking at okay, what's out there on the market. Integrations and um connections are going to be really, really critical. So, you know, marketplaces, um API sets, so you know, libraries and uh developer environments, these are all very important to enable those integrations that take place. Seeing companies launch um partnerships in in certain verticals, etc. Uh, you know, those are those are well underway right now for the more traditional sets of services, but we can see that evolving moving forward. Uh so yeah, I think uh you know it's very much about looking at um how open and ready that company is to make those right connections. And are they talking to the right partners and and potential partners uh you know in your in your specific sector?

SPEAKER_00 25:53

Yeah, it sounds like there's a lot of exciting things ahead. So happily um you know Steve, I could go on for hours on this, but um that's all we've got time for now. Thank you so much for sharing your your perspective.

SPEAKER_01 26:03

Thank you, Nika. I'll get to speak to you.

SPEAKER_00 26:05

We really uh appreciate that. So for anyone who wants to learn more about how to modernize their contact center with AI, you can visit Five Nine's website. And of course, for more insights and stories from us, visit CXToday.com.