Breaking the Blueprint

Human Vs AI

• Vinay Parmar & Iqbal Javaid • Season 1 • Episode 2

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AI is no longer just a tool—it’s changing everything. From customer service to real-time business decisions, AI is disrupting industries in ways most people don’t even realise. But is it a force for good, or could it be leading us into dangerous territory?

In this episode of Breaking the Blueprint, Vinay Parmar and Iqbal Javaid break down the AI revolution and its impact on businesses, jobs, and even critical thinking. With AI now handling cold calls, personalising experiences, and even coaching employees, the big question is: what happens to the humans?

We’ll explore the Klarna AI controversy, the hidden dangers of over-automation, and how AI could actually be making people worse at decision-making. Plus, we’ll reveal surprising insights about AI avatars, the EU AI Act, and the secret tool CEOs wish they had.

If you want to stay ahead of the AI curve, this episode is essential. Don’t get left behind—watch now to see how businesses are already adapting, and what it means for the future of work.

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Show Links:
Vinay on LinkedIn: https://www.linkedin.com/in/vinayparmar/
Iqbal on LinkedIn: https://www.linkedin.com/in/iqbal-javaid/
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customer experience strategy for executives
 future of contact centres
 AI in customer service operations
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 CX transformation in large enterprises
 how to improve call centre performance
 leadership in digital customer experience
 customer retention strategies for brands
 contact centre trends 2024
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 data-driven customer experience
 AI automation in contact centres
 employee experience and CX
 optimising BPO operations for CX
 customer loyalty through service design

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Vinay:

Hey everybody, welcome back to this episode of Breaking the Blueprint. It's great to be here with Iqbal ready for our next episode. We've got a really good one lined up for you. So just before we get into what's going on this week, just wanted to say a big thank you to everybody for the brilliant response on the first episode. We had lots of great messages and comments and people have been really, really positive about it. So I'm glad. Those of you that listened have really enjoyed it. Those of you haven't yet, subscribe, click on the button below if you're on YouTube and if you're on Spotify or any of the other music platforms such as Apple Music, please make sure that you subscribe. So, What have you been up to since the last episode? What's been going on?

Iqbal:

A lot. And look, great to be here again and doing this, this second episode with you. I think we've got a lot to get through today, but yeah, obviously this time I'm in your neck of the woods. So, walking the streets of Birmingham to come to you and do this, this, this, this second version of what we did. I think we certainly enjoyed that first episode and great feedback, by the way, from a lot of people. It was, it's quite quite, I was quite overwhelmed by some of the reactions I was getting from people. So it's good, good to see that it resonated. I think this, this thing will continue to take shape and, based on what people want to hear, hear about. Progression over

Vinay:

perfection, as we always say, right?

Iqbal:

Exactly. And I think today we want to drill in a little bit more into some of the areas that we covered on

Vinay:

the last episode. Yeah, cause we went quite broad last time. It was a bit of a, a bit of a whistle stop tour through lots of CX subjects and areas that we touched on a little bit. Our plan today is to go deeper. And today we've got a subject that lots of people have been looking at for a while. It is two letters and again, it's not CNX, it's AI. We're going to take a deeper dive into the world of AI, the world of tech and really Contemplate the question. Humans versus machines, right? So this is the conversation that seems to be happening everywhere. Humans versus machines, conversations about displacements of jobs and what it's really going to do for the experience that people have of organisations, both as Customers and also as employees because remember it's, two sided coin, right? So yeah, we're going to explore that today But before we do that, you know We always learn things from when we do things the first time and one of the things that i've learned about podcasting is that I need to sit still and not move around so much. It's like one of the things you don't really realize When you're recording stuff like this, it should sit still so the sound was Paul did a great job of making the sound You Really good but hopefully I've made his job easier this time around by not Not moving around all over the place.

Iqbal:

Yeah, I've noticed you're, you're, you're much more of a statue today than you were last time I do, it's more natural to be moving around and having a conversation. So yeah, it was Hopefully this time we'll get it right.

Vinay:

Yeah, well, there's a little voice in my head just telling me to stay still So let's kick off shall we? Iqbal, I'm going to fire the first question across to you. So human versus machine, right? Yeah Is it really a versus? Is it really a battle? Or are we Missing the bigger picture here, do you think?

Iqbal:

I think the obvious thing to say is we're missing the big picture here, but It can be a bit of both, right? It could be that AI is overcoming humans in some capacity. The problem is I think us as humans, we're having to adapt to accommodate this new thing that's there to support us right now to, to potentially make us better and help us do better work.

Vinay:

Yeah.

Iqbal:

I think that, I think we all appreciate and understand that it is there to complement us and get us, get us to drive better outcomes. That's, that's the ultimate goal. I think the fear comes from the fact that we're accustomed to doing certain jobs and we've been doing them for a long time. And now AI can pretty much replace. That particular work that you've been doing, and so there's that fear of, that insecurity of, okay, well then that means I'm out of a job. So what do you do in that situation? Do you go and skill, skill up in a different area where you can deliver value alongside AI, and I think that's that's where we all need to be shifting our mindset to. Yeah is how can we as humans get the best out of AI?

Vinay:

Yeah, I think that's that's a really great way of framing it. I think if you think about the last 18 months two years since AI really hit the the The mainstream, It's been around for a little while back in tech world, people have been playing around with chatGPT and things like that for a while, but as it's really become a more prominent mainstream thing, I think it feels like someone's taken this snow globe, shaken it, so we've got all this stuff happening around us. It's finally starting to settle and we're starting to see some really interesting use cases come through. People are starting to understand it a little bit better. I still think there's a real misunderstanding, in the main around is it ai, is it a robotic process, automation, is it, predictive analytics? Like what is it really ai and what, what is and what isn't. So I think there's still a bit of that figuring out, but as that dust is settling, we're starting to see some really interesting, things come through and how people are starting to deploy I mean I first noticed it last year when I was speaking at conferences that went from people getting really excited about We're gonna do stuff for customers and self service and stuff to actually it became more Internally deployed as a co pilot for agents and frontline staff And people across the business, more in that context, almost saying, we're not quite sure about this enough yet to deploy it externally. We'd like to test it internally to see what we kind of productivity gains we get and how we help people. And I don't know if you've seen this, seen the same.

Iqbal:

Yeah, I mean that, During my time at Zoom working with many customers at that time where that's, that was the priority is how can we leverage AI to help us as agents, as supervisors, as somebody who's running a business to be more efficient. And actually you also get a chance to govern it before you expose any of those capabilities to customers. We now. I think in the last six months, starting to see AI being exposed to the end consumer. I mean, I myself am getting cold calls by AI. I mean, since our last podcast, I must have had three calls. Maybe they were listening. I don't know what it was, but it's strange. I've had cold calls just, about random things like, I've heard that you've got a problem with your housing or something. Can we help you? Completely random. But the point here is we're now starting to see this get exposed to, to the end consumer. The, the problem is, in my view, I still think it's not being well thought through or designed in, in a way that, you know delivers that consistent experience that humans do. I think the technology's there personally. Yeah. If you design it right, yeah. And you ensure that your, your, your gov, your, you've got all the right governance and, and, and, and, and your, your brand personality built within that tech to be able to deliver the kind of service you need for your, for your customers.

Vinay:

Yeah. I, I, I think two really interesting things, so. Did the AI that called you from an outbound call, did it have an Indian accent or a Nigerian accent or a South African accent?

Iqbal:

It's interesting, it was a London accent and I think that, I mean, we were discussing this the other day, weren't we, where we talked about the fact that we can now provide a much localised service to every demographic out there because you've got the ability to deliver any accent. So if you are from Birmingham, And you get a cold call. You might appreciate that the AI is using your own accent to interact with you.

Vinay:

The Bromley Twangle come out. And I guess the second thing in what you just said, the other observation I make, you're right about I think what's happening now is people are using processes to do the AI, so they're deploying the AI as a process would be deployed internally. They're not necessarily designing it from the customer's perspective, which is why it's still probably a bit clunky, not as fluid, because it's following an internal process or diagram or flowchart because of what the company wants to do, rather than, again, understanding fully what the customer's trying to do.

Iqbal:

Yeah, and I think the way you overcome this and the way you do this properly from experience now is You you feed the large language model all your conversations You've had you can go back five years ten years whatever you like and get AI to really understand what those interactions are like between your customer and your agents and And that's really the data that you need to feed it, as well as making sure your knowledge and all of your systems are correctly up to date with the right data. To, to then be confident enough to be able to expose this to your customers, because it's learned enough to know what to do in certain situations. Because actually what we want is, as you pointed out, rather than have workflows that are very rigid, we need Agents, AI agents to be more autonomous in terms of being able to provide an end outcome for you as a consumer rather than having to shift you to a human agent. Just because, oh, I can't answer this question.

Vinay:

And we've seen that already with badly deployed voice bots, poor, poorly executed voiceover, sorry, poorly executed natural language IVR systems, and these kind of things that are just still quite rigid in terms of I don't understand, computer doesn't understand, let's move it along. So just building on that, and I, cause remember this podcast is all about how do we win and keep customers, it's about relationships, right? So when we think about the building customer relationships, does it build them? Does it, does it stimulate them? We saw some couple of really interesting examples. So you and I were on a demo with a company that demonstrated a voice AI agent for a it's for an electrical car, electric car company, a charging, a charging, Thing. And it was a helpline. And this guy was having a full conversation with this AI. interrupting it mid flow. He had an accent, a regional accent as well that made it, that could have made it a bit tricky. But from what we saw, it was quite a It was quite a well developed, I thought, quite a more, more, a more natural flow of conversation than I've heard a lot of times when I've heard, AI agents being deployed.

Iqbal:

Yeah, I mean, look, it was a demo, so, it's obviously been fed the right data to be able to deliver that kind of experience, but and, and, and that's why in the real world, it's not so easy to implement, but, but absolutely right. Yeah, we, the demo that we. Experience, showed us that as a consumer, he kept shifting context. And in some cases had multiple intents in that conversation. So in one sentence that he would mention two or three completely different things for a, for the AI to go and search some of those. the answers to those questions across multiple data points. So it demonstrated that, which is really cool because it takes the data from different places, summarizes it as we, you know, we're used, we're familiar with that. We chatGPT, right? And being able to ask multiple questions, it'll go away and then it will summarize a response for you. And that's exactly what we're seeing. But the thing to do it in real time in a voice conversation can be tricky because That can still take a bit of time. So it's making sure that, if it is going to take time, you, you respond accordingly. And the response should also be in line with how you, you would speak to a customer in real life as well. So all of these things need to be built into the platform to be able to deliver that natural, as you say, natural conversation. Because as a consumer, when, when you know you're speaking to a bot, You're already a little bit,

Vinay:

I

Iqbal:

just want to speak to somebody.

Vinay:

Yeah.

Iqbal:

But, actually, if you feel that the bot's understanding you, Yeah. and it's giving you the right answers, that confidence will build.

Vinay:

Yeah.

Iqbal:

And you'll feel like you're getting the service that you want.

Vinay:

Yeah, and you're Seeing that tech firms, Are framing that that's what you can do If you look at the way that Gemini is being promoted right now and the advertising is all about Just speak to me like a normal human being Just speak to me like and so I think we're training people out of that or trying to Influence people out of that. Oh, i'm speaking to artificial intelligence. Therefore I've got to act different. I've got to have a different mindset to actually I can speak to it naturally and just you know, there's been you know, clearly The question is, you know around relationships, and and from a loyalty perspective there are you There are obviously things here that you need to consider when you're developing your solutions. You know, loyalty is multifaceted and not all loyalty is created equally. There are four key types of loyalty. There's transactional loyalty, which is all linked to. Price, so as long as you're priced in the right bracket for me, I stick with you. There's habitual loyalty, which is you're convenient and easy to use as long as you keep doing that and nothing better comes along, I'm going to stick with you. There is loyalty program loyalty, which is I'm sticking with you. And as long as my points with you win me prizes and I can use it well, I'm going to stick with you. Those three still are quite transactional. They will still, if something better comes along, will shift you, right? The fourth quadrant, and where we, where we try to get organisations to move to and which, what's, what all this is geared around is, the emotional loyalty. That is when you get beyond price, product and you get beyond those gimmicky things, and you really have a connection with the brand, cause there's a deep rooted trust, and trust comes from the interactions that we have with brands. This is why I'm Bringing it up. And, recently, I think you, you pinged across to me a case study from Klarna, in which they have deployed AI across their workforce. Controversially, there hasn't always been lots of good comments about this, tell us a little bit about what you know about that and what they're doing.

Iqbal:

It's fair to say, ahead of their time, like they went and built this, And one more thing, I know that you've been in the early part of last year and exposed it to the employees in the summer, in 2024. And as you say, they mixed response to that, it's twofold. One, one, one is that, and I posted this on LinkedIn today, is there, there's, a bit of a battle going on at the moment, amongst I. T. people in organizations and employees, because we are, Bye bye. All now starting to leverage chatGPT just to be able to do our work, right? Just the basic things that we're doing. And the reason why we're doing that is because our employer's not giving us the right tools to be able to do our thing, our work more efficiently. Because in our personal life, we're using those tools. Why are we not being offered them at work?

Vinay:

Yeah. So

Iqbal:

what Klarna have done, they've gone and built their own AI assist for their employees. It is using OpenAI and their large language models. But they've been trained or they, trained on their knowledge, their data, and they're, they're able to action on some of these things as well. So they've been very proactive in being able to offer this type of capability to their, to their people. And we've not really seen that well adopted. I mean, just on the BBC yesterday, they reported that an international law firm was restricted or prohibited chatGPT because they discovered that 32, it was being used like 32, 000 times in a month or something. And they're worried that it's not being used in the right way and it's using publicly available information to help support people. I mean, at the day, it's like a search engine, right? But there is this fear at the moment. So in Klarna's case, they've gone and done that. Now, the negative side of this is that The, the the guy who, who owns Colano, who's running it has now been vocal about the fact that I can now reduce my headcount. I can stop hiring. So this obviously, leaves a bad taste amongst people within the organization because going back to that point around human versus AI, it, it does, Start to impact people. Yeah, you can't deny that.

Vinay:

Yeah, it does. Just before I move on that, a thought came to my mind when you were talking about, The usage of that law firm, 30, 000 times been used. I saw a great clip online, and it just framed the dangers of AI in a really nice way. And it said that, when we used to search on Google We'd get 15 to 20 results come up. We would then look through all of those results and make our mind up of what best served our purpose, best answered our question, best met our needs. The thing with chatGPT now is that you put the question in and you get one answer back. And that's the machine that's, that's presenting the answer to you based on what it understands and what it considers to be the truth. And I think there's a danger about that loss of critical thinking and the ability to question that people will just take that answer as the gospel and say, well, that's the answer there. So I just, I, I was just in my mind. I thought, I thought I'd just share that at that point. So I think there's something interesting. also I've got a great tip on chatGPT if you listen till the end i'll tell you right at the very end. It blew my mind yesterday I was with this incredible guy Who was sharing some phenomenal AI stuff, which we'll get on to in a second And he shared with me this tip at the end and i was like, wow I'm, definitely going to do that. Right? So make sure you listen to the end and I will definitely share That tip but back to the point around, The relationship. So yeah I think You That, that whole thing about displacement of jobs and people undoubtedly is going to come up. And, and look, you can look at it, one of two things that people. There might be, there might be less of those types of jobs that are needed because the AI can do some of them. We've seen, it's not the first time it's happened in history. Every revolution in, industrial revolution brings about this kind of thing. My dad worked on the JLR on the assembly line for years and they were always introducing robots and, and other things to automate some of the build. And then those jobs change from being assembly workers to being quality. And we, we've seen that kind of conversation play out. Yeah. and then I think the, the other thing that's really interesting is, is, if you've seen, I mean, you've seen me share this message and both from speaking and, my writing, I always say that inconsistency is the killer of trust across brands. It kills brands, it kills trust, because when you're interacting consistently backwards and forwards with a, with a, with a company, each of those interactions should, in theory, Be fairly uniform to the point that when I say uniform, I mean convey the same values, the same confidence, the same trust in you at each of those kind of things, but we know in reality that doesn't happen for a number of reasons. And one of those reasons is a lot of the time it depends on the person you speak to, what side of bed they got out in, how well they've been trained, What kind of mindset they're in on that day. Using AI takes that out. You no longer have somebody who's dependent on what time of the day they woke up, how much sleep they had, whether they went the night before. You no longer have somebody who's either engaged or not engaged because they've had a horrible conversation with their manager or a previous customer. You're basically getting that repeatable, consistent thing, and from a trust perspective, and a building relationship perspective, that starts to really bring up an interesting, I guess an interesting thing, cause it does drive that consistency. And so the connection to the next bit that I want to talk about is, like I said, yesterday I was at a thing. With an agency OWB and DRP. They're, Based in, in, Kidderminster in the West Midlands, Andy Wilkinson. And, and Dale and his team gave us a, a really good, there was about 70 of us there. We went through a bunch of workshops and there was, there was one at the end around ai, which I've gotta say was mind blowing. Mm-hmm. With, even with the things that I've seen and had to look out online, it really was mind blowing. So they, they were showing, three things. So once they, one, they showed, How they're deploying AI, multiple different AI, sorry, multiple different AI's together with their own IP and way of working to create avatars. Now this is an avatar of a real human. It's not a generated one. It's 15 minutes of video, four minutes of audio, and you can pretty much create and you create an avatar that's lifelike. They demoed this avatar. So it's a real person and it can be a member of your staff. It can be a real person in your office. And this avatar was able to pretty much take anything you told it using OpenSource and then answering it using OpenSource AI for demo purposes, right? But you can imagine that in a, in an organizational sense, you could train it on your own knowledge base and what you have that it could answer those questions. Not only that, but it was able to do it in multiple languages at speed I mean, at scale. At one point we thought, ah, it's thinking, it's thinking, it's delayed. And it wasn't, it was because the person that was asking it was still talking. So it was waiting for the person to finish. So that he could start processing, right? So I thought that was quite an interesting one, but the one that really got my brain firing. I mean, if you could look inside my head, there was literally a fireworks display going on as this thing was being shown to me. And so they talked about the concept of having cameras. From a presenter's perspective, so they use the example of a presenter. You've got a camera looking at your audience, and as you're delivering the message, and remember that I do a lot of speaking, right, so I was really interested in this. Yeah, of course. And it monitors people's facial cues, and it uses those facial cues and body language and other signals to predict and determine how engaged they are, how happy they are, what emotional state they are in, and give you real time feedback. So you can see in the screen in front of you, 88 percent happiness score. Now, you've got to be pretty skilled as a speaker to be able to respond to that in the moment. I know for a few, it would paralyze them. I'm sure it would do for me at some stage as well. But if you take that a stage further, maybe not so much from a speaker's perspective, but then I started to think about CEOs, all hands meetings, you often deliver your message The you, you come off the web core, you look around the rest of your team, go, how did that go? How did that go? Do you think that all went well? And you ask your team and everyone goes, yeah, that went really well. And you think that it's gone well. And then you might ask send a survey out to your team and say, how engaged were you with the CEO's message? Imagine that CEO o being able to deliver that message to his people or to shareholders. Mm-hmm.And in real time get feedback Yeah. About how that message landed.

Iqbal:

Yeah. And by the way, I have been asked this question in the past, when senior people are delivering that kind of message over video, can we get, can we get an idea of what, what are people doing? Because the fact is most people are multitasking, they're not fully engaged. So that level of metric is available, but not the way you've been Just described it right, where you're in a, in a physical event environment, your, your, your audience is being analysed, hopefully they've been made aware that that's what's going on, but, but as a speaker, you've got to be incredibly thick skinned to be able to deal with, cause sometimes I, I mean, you're very experienced in public speaking but you, you, you almost sometimes well, it's better if I don't know, because then I've got to, I can stick to the script, because if you know that, hang on a minute, Only 10 percent of the audience is engaged. I'm gonna have to pivot what I'm saying or change it up and, and that can be quite disconcerting. So, but, that's obviously a verse from somebody who's quite inexperienced, but that, that would overwhelm me. I mean, I don't know, how would you deal with that?

Vinay:

Well, I mean, look, it's a skill that you develop, right? So, I think, an experienced speaker, a professional speaker would have stories and ability to pivot away from their scripts. That's just, that's how we do stuff. It's never a kind of thing. I think what it does do, without going down a rabbit hole, it's People that are presenters that use PowerPoint as a crutch, that will have their slides up and only know one way of delivering their content, they do that. But coming back to that human versus machine thing, what that then does, is it drives the human to learn a different set of skills. The ability to adapt, pivot, move quickly, And understand that kind of thing. But then you think about What if you're a Michelin star restaurant, right? And you're bringing out the food. What if you had cameras placed in the restaurant that could monitor people's facial cues? You could see in real time how your food is landing, how the dishes are landing. Imagine your maitre d being able to monitor in real time how the tables are, what the emotional state of those tables is, being able to send somebody over to be able to, To go and put things right now. You could go, oh, well, that's intrusive and the cameras are looking at people and that kind of thing. Well, there's two things. One, well, three things. One The cameras, Don't actually, if you're viewing it, you don't actually see the faces, it's blurred out. It's almost you have the blurred background on your Google, so it blurs the faces, so you can't actually see, the cameras can see the faces, but you can't actually see the faces, you just get the feedback and the data. The second thing is, it's happening naturally anyway, so anyone who's worked in customer service, sales or whatever, you're taught about body language, cues, looking at people's text, Tells and stuff. So you're having to do that manually to look around and what's going on But this is helping to supercharge that by giving you even more data. So you become even better at it

Iqbal:

It's a great example the problem as you say is the that whole personal space right, I might I'm in a private conversation with my wife in a restaurant. The last thing I want to know is that I'm being analysed, even if my face isn't being recorded. In fact, you've got, recently, the EU AI Act has been enforced, and this is one of the things that actually needs to be called out, is that organisations are not allowed to use that kind of data to be able to, provide a particular type of service. So this kind of, they're going to depth, but it it opens up a can of worms because you're not using that type of data to do anything bad. You want to offer a better service.

Vinay:

Yeah.

Iqbal:

And that's why it's, it's You're on thin ice with this, and I think, over time, I think we'll develop it. Where I'm seeing this actually already being implemented is just in traditional call centres, where you have agents who are, dealing with customers. They've obviously got, AI running in the background, assisting them with knowledge. I mean, that's something that's become very, very common. But what we're now starting to see is where you've got AI, coaching the agent. So, traditionally, you'll be a supervisor. Even now, as a supervisor, you can see your agent, the sentiment is low. So you might want to listen in, and then you can whisper and have a conversation with the agent. But actually, now you can get AI to do it across your whole agency state, right? So they can go in, and really actively coach them, see what's going on, listen to what the customer's saying. Yeah. And if the agent is stuck on something, being able to just coach them or worse yet, in many situations where agents are having to deal with difficult customers, that's the hardest part of the job. I mean, I've done this for many years and early on in my career and

Vinay:

it

Iqbal:

defined me in this space, but now you've got Potentially AI supporting you, saying, look, actually, you're doing really well. You're saying the right things and that's all you need. Sometimes you just need somebody to tell you that actually, yeah, this is a difficult situation. You couldn't have done any, any, any different or any better or maybe even advise you to do something else.

Vinay:

Yeah. I mean, look, there are, there are, it's not a perfect solution. There are flaws to it, but it's interesting. Like I remember in my early, in my contact center career, when I first started working in the contact center taking credit card applications, my supervisor, Pat would pick up the phone from the end of the desk that she was in. She'd be able to talk to me in my ear without the customer hearing me and give me encouragement and hear the call I'm doing. So. I guess it's building on that. And imagine that then application in education, your kids are studying at home, they're doing their homework, they're interacting with an AI that's able to coach them and encourage them. So that there is, there really is some opportunity there. But just going back to that restaurant example, I just thought what you were saying about the conversation with your wife. There is that awkward moment when the maitre d comes over to check If the emotion on the table, having had the data, says it's okay and it's not the food and it turns out you've just upset your wife, there is a danger to it, right? So yeah, yeah,

Iqbal:

no, 100%. I think it leads us nicely to that, to our next kind of point in the conversation is, can AI become, we know it can be helpful. I think that's obvious, but can it cause harm?

Vinay:

Hmm.

Iqbal:

What are the, what, are there any kind of examples or anything that we should be worried about? I,

Vinay:

I, I think I think it's broader than just an AI question. I think any technology deployment can cause harm. There is, there are times that we can over digitize, there are lots of companies that have driven towards centralization, driving efficiency, driving productivity, driven by trying to achieve cost savings and productivity gains and all those kind of things, which feels like the right thing to do or is driven by the right intent, I guess, at the but you can often lose that localized Appeal, like I was talking to a leader of a, an organization just the other day, and she was telling me She'd joined an organisation that had been through This years and years of centralise, centralise, centralise, and digitise. And what that did was it kind of alienated their customers that were more local. And these are businesses that are based in certain communities. And she was saying that actually by redeploying stuff back to the local depots or the local centres that are around those areas, They've been able to resolve queries quicker because the local knowledge is there and building stronger relationships with customers. Whereas previously those customers just felt we're just speaking into a big black hole that nobody was really listening. And, and so the danger with technology always is, is there is that tipping point of pushing it that bit too far. I think the AI can do us harm because it can, it can suppress our abilities to do critical thinking. We can become over dependent on it. We can just take it as fact rather than, and we become lazy and we lose that. And I think, as humans, the thing that we have uniquely that's different from machines is that ability to think critically, that ability to assimilate information and to have that sense that this isn't quite right. To be able to to be able to pick out things that don't feel right because we've got that kind of, you've got those neurons in your, I think you've got thousands of neurons in your belly, that gut instinct that comes out, from a, from a, from a flight or flight perspective, yeah, flight perspective. We have that built in us that can spot that. And I don't know whether AI will ever get trained to be able to do that natural human thing. So I think it can do that. Also, from that mental health perspective, if you're replacing jobs and things are happening, there is that impact, societal impact on people. And then you have, I guess, the other part, which is when we become overly technology driven, there are parts of society And our communities that don't have digital access, they don't have the luxury of three or four iPads in the home, a couple of iPhones and a, and a laptop. We saw it during COVID, when kids were learning from home, people had to donate phones, or there were three kids in a, in a, in a, in social housing or in a flat or in a home. It doesn't have to be any of those things, but there were three kids sharing a smartphone between them. for different schools learning. So we have to remember that there's an accessibility piece here as well. So that responsible rollout, taking people on the journey with you, designing from the customer's perspective, understanding those emotions, understanding those different groups of customers and how they interact with you and your brand and ensuring that you're not alienating one group as a result of doing this. Tech rollouts are notorious for, you know, People roll out, they go, they will build, we'll build it and they will come and then they'll figure it out. And I, and I saw this in the, in the, in the sort of the mid 90s when banks were In a shutting down the number of counters at lunchtime in branches and hoping that people would start to use these machines. They mysteriously placed in the corners, right? And what we what they actually saw was the queues stayed about the same. People just waited longer. And then they suddenly twigged that they've got to teach people how to use a technology. So, Auntie Beryl, who's in the queue with a cheque, who's waiting to pay to a human, cause that's what she trusts, once she's been taken out of the queue, shown how to use the machine, sees the cheque going in and then appearing in her account, does that a couple of times to be delivered. To develop trust will then default to, that's a real easy channel. I can use that. And he's less likely to stand in a queue and wait for somebody because she's got confidence. Yeah. So I think all those kind of factors come into it as well. Yeah.

Iqbal:

I think that you make a really important point there is the demographics, right. And the societal, impact this technology can have, because I think right now it, what's clear to me is everybody's seeing dollar signs, right? You've got Trump talking about 500 billion investment, you got the EU just announcing 200 million, the British government, it's a lot of money being pumped in and there's going to be a lot of people that will benefit from this. And the tech's just going to continue to take off the way it is, but it's important we don't leave people behind.

Vinay:

Yeah.

Iqbal:

And people that don't have access to the technology, how can we get AI to help everybody? And I think that's the, the challenge that everybody faces today. Um, and, and just just concluding the, the helpful and the harmful, I came across a situation recently and I don't know what to make of it. There's this there's this company I mentioned who they are on the brink of bankruptcy. And they can't afford to keep their call centre staff. So they've got 30 or 40 people. And they've now decided to remove all 30, 35 people and replace with a digital chatbot and a voicebot. Backed with AI to serve their customers. Very risky strategy. It could go either way, right? When we talk about helpful harmful, it could, you know, that if it's not designed correctly, not implemented properly, it may accelerate that bankruptcy because actually now there could be The customers that they've got left, that they've got to

Vinay:

serve,

Iqbal:

may end up walking away quicker than they would if they had humans managing that. So it's a very difficult situation for the organization, but they've made a decision. They're going full AI. But this to me is both helpful

Vinay:

for

Iqbal:

the business, but harmful to the people. So I think going back to that question, It depends on where you are in that situation, right?

Vinay:

Yeah, I think it does depend a lot. And I think for that organisation, my advice to them, if they happen to be listening, would be that you've made the decision and you're going completely AI or tech driven, right? But the thing here is, to whatever you're deploying, deploying it from the customer's perspective. And using the data and the feedback to understand how you do that. People will learn to use the technology, they'll make, they'll self select and make their choice as to whether they do continue to use you or not. But if you do a good job of understanding your customer's problems and designing the solution deliberately backwards, then that's Then that, that's going to be a great thing. Go back to, it's all about that consistency point about how do you continue to do that. And look, I've worked with some amazing people over the years, on the frontline, in contact centers, in retail, wherever. But I've also worked with people that feel like they're just in the wrong job. They shouldn't be in frontline and they grunt at customers that don't deal with them well. And so, the AI can smooth that out, and those people just didn't belong in that job in the first place, no matter how much training you give. We all know people like that I don't think I'm saying anything out of turn. Every one of us has known a colleague or a friend that we think, God, maybe we shouldn't be in a job where you're interfacing with people, Or servicing customers. So I think there is that there is that balance as well. It will drive consistency, it will improve productivity. We've got to take people on that journey with us. Like any change program, design from the customer's perspective, not just the internal processes and expect people to follow your processes. And, and use the data in the feedback loop effectively to help you to pivot that constant iteration, Progression over perfection. You've got to get into that rhythm of Test and learn, test and learn, one of the great things about technology is that you don't have to deploy everything to everybody in one go, you can run small proof of concepts and you can scale over time, the agile methodologies is built for that and adopting more of that mindset and just rather than having to go, right, we're just going to do it all in one go might be a step that organizations can take.

Iqbal:

Yeah, I think most do take that pragmatic approach is, identifying. particularly use cases that they can go and, die there. Test out and, and maybe trial out with a certain type of customer base there, there's, there's, there's a lot of opportunity, I think, and, and we're, we're now starting to see that come to the fore. I think right now, it's making sense of, what, what technology partner or vendor to use to help them. Deliver this the market is flooded with, with vendors in this space. Everybody's competing for, for, for time. I think the, the biggest challenge that in all honesty, I think we get the benefits, but actually what's the true ROI? I think that's, that's the question that's always being asked is because this stuff doesn't come free, by the way, it's a, it, it, it does good work for sure. Can deliver great outcomes, but all those outcomes. paying the way for you to leverage that technology.

Vinay:

Yeah, I completely agree. It doesn't come free. There are, there are, Consequences, environmental as computer processing power is needed greater and greater levels. Cooling plants, server plants, all of those things happen. You've got, you, you have to invest in technology. Then you've, then you're trusting the vendors that you're using their technology don't suddenly, ramp up their prices because they've now got you by the short and curlies and so you're now stuck having laid off people, stuck paying those, Licensees and there's a whole set of stuff to unravel here. It

Iqbal:

is, yeah, cause just, I mean, one of the things is like, everybody's got a different strategy to this at the moment and this is what I'm observing is you've got technology vendors building great outcomes but They're so complicated to build. So they'll build, they'll build something that, that looks great today. They'll implement it for you. And then here you go, have fun with it. And then suddenly something's got to change or the market circumstances have shifted. And now you've got to make changes to that. You're gonna have to go back to that same vendor because they've overly complicated it. So it's really important for organizations to take ownership of this. And what I'm finding is now, the roles within CX is shifting to AI prompt engineering developing people within a, a, this space to be able to manage this because it's now, you'll end up in my opinion, the contact center is going to be managed completely by AI people, like that's where we're headed. And, and look, I think before we conclude this I'm eager to hear this, this example of yours that you mentioned earlier.

Vinay:

Yeah, yeah, yeah. I'm just, yeah. So, yeah, so, Prompt Engineers is a great way to finish, so it's, it's correct. So, We hear lots about, it's about, writing the right prompt. And he took us through this process of going, right, if you're going to, if you've got to give the AI context, who are you writing for? What kind of image do you want? If you just went, generate me a picture of a, a grandma, it might just generate, your really biased view of a grey haired white woman, old white woman, and that would be a grandma, right? So you need to teach it. That's true. So. You can prompt engineer, the thing is that you would have to prompt engineer every single time you ask it to do something, you'd have to create the right prompt. So he went, what do you do, is you use AI, to teach the other AI. You ask Gemini to help you write a prompt for chatGPT to generate blah blah blah. Gemini writes you the prompt, you copy and paste it from Gemini, you put it in chatGPT and you get a better result. So

Iqbal:

AI working with AI. Yeah, and you know what, this is exactly what's happening right now, where you've got you've You know, some organizations that are really far ahead on this journey, they're building multiple agents that where, where those AI agents are supporting each other, they're not interfacing with any humans, they are there to deliver a very specific task. And they'll, they'll do that. And you can expose those APIs across all of your agents to then, Deliver a much bigger outcome for your customers. So, yeah, it's happening right now already, right? But it's early days. Really exciting to see, where, where, where this journey takes us. And it's in a sense, I hope we stop using the word AI because actually it's not, it's just, It's just a technology, right? It's just we're referring to it as AI today, but I think there'll be a time where it's just, it is what it is, right? Yeah. We will focus more on the outcomes and what it can actually deliver.

Vinay:

Definitely. So answering the question, is it human versus is, it a human versus the machine? Is it a battle? I think from the conversation today, what we are saying is, is that it's an and conversation, not an all conversation, Look, the reality is there will be jobs and roles displaced as a result of technology coming through AI or otherwise there always will be. It's the speed at which it happens. That's the thing that's, I think, the thing we've got to be really live to. And I think the quality of the deployment And how that happens, if it's just deployed from a pounds and pence internal process perspective, as we've said, we're likely to get more of it wrong than we are to be right, but it's done in a way that you take people on the journey with you and driven from the customer's perspective. Well, we can create some quite compelling, Use cases that can help support. Customers and employees and create different jobs and improve the results we get Both as employees and customers. So I think that's a great place for us to end and we'll see you next time on episode three

Iqbal:

Thank you, Vinay. It was a good episode today. Thank you. Thanks.