CRSP04: Reimagining Telecom Industry pt.4 - Data & AI with Osman Peermamode, Vodafone Group
[00:00:00] Only 140 episodes, and we've finally got a professional co host. Don't tell them. Nobody tell wrong.
Welcome to Cloud Realities, an original podcast from Capgemini. And I'm delighted to say we're here with the fourth episode of our mini series on reimagining the telecoms industry. And today we're going to talk about data. How can it act as a differentiator? How does regulation both help and hinder that progress?
What might data as a service in the future look like? I'm Dave Chapman. And I'm Esmee van de Giessen. Now we haven't got Rob with us today, but I'm delighted to say that we have got a professional co host with us. So Praveen, good to see you, mate. How are you? Awesome to be here, mate. It's always, always a pleasure to record with you, man.
You, you, you well today?
Yeah, great. Sun is back again. [00:01:00] So I'm a happy man.
You know, it's bright today, isn't it? It does feel like that we're, uh, we're heading out of the dark times into the summer. I am very glad about that. And I am also delighted to say that we have got a fascinating guest with us today, Osman Peermamode. He's the head of data and AI for Vodafone Group. Osman, how are you today? I'm very good. Thank you. As for being very happy that the sun is out, the vitamin D that starts pouring in, so hopefully the dark mornings is now over. Amen to that. Now whereabouts in the world are you joining us from this morning, Osman?
So basically, I'm based in Chesham. I moved here a couple of years ago. What a fascinating place. Lot of green around, lot of nice walks, which I'm looking forward to do over the weekend.
Yeah, how nice. Well, wish you well for that. Let's hope the weather holds out. So look, Praveen, fourth episode. We're getting towards the conclusion of the mini series.
We're on data today. Do you want to set the scene for us a little [00:02:00] bit?
Yeah, sure. Thank you, Dave. Let's start with, again, our usual recap. Reimagining the telecom industry is a five part podcast series where we explore the five critical areas that require reimagination by telcos. So far, we have covered simplification, risk and regulation, and network transformation, which leaves us with data and AI, and growth.
As we stated day one. Our focus for today is data and AI, a topic that sits at the core of Telco's transformation. Telco's are sitting on gold mine of data, and it is not only an enabler for internal operations, helping optimize network performance, enhance decision making, improve customer experience, but it is also the key to unlocking new revenue streams for them.
Additionally, data security is a fundamental obligation for telcos. As the custodians of our digital lives, telcos process a huge amount of personal and enterprise data, making cybersecurity and fraud prevention more [00:03:00] critical than ever. So the key question is, are telcos fully utilizing their data? And from my experiences, I would say, Dave, Not yet.
Not to the full potential. So what is holding them back? How can telcos unleash the full power of data and transition from being connectivity providers to AI powered data leaders? And who better to discuss this than my friend Osman, Head of Data and AI for Vodafone Group. Osman, I'm excited to hear your thoughts on this.
Over to you, Dave.
So, Osman, why don't we start with just your personal journey into telco? I know you were working on the on the West Coast, I think, and looking at the telco industry. Just give us a sense of your journey there. What were you observing that interested you particularly in the world of telco?
So basically for me is I started my journey with telco. I was working, as you said, in a major technology company. headquartered on the west coast. And over there, I [00:04:00] was interacting quite a lot with, uh, with the telecom providers, with the telecom, et cetera. And what I noticed working with the telecom is they have a vast amount of data.
But the insight of the data was lacking, and this is what, for me, is I took it upon me as a challenge on [4:22] how do we create insight on the vast amount of data in the telecom industry. A typical telecom, if ever you look at it, produce almost terabytes and petabytes of data on a daily basis. As a data professional, that's heaven. [4:40] To most people, they'd be completely overwhelmed and terrified by it. So I'm glad you, I'm glad you exist, Osman.
So Zephyr for me is, it's a wealth of data available. It's not at an aggregated level. It's at the granular level, each and every [00:05:00] interaction a customer has on the network creates and produces data, whether it's around location data, device data.
Usage pattern, everything, all of those is recorded. So it's not only the quantity then, Osman, but also the quality, because I think we all know organizations have loads and loads of data, but the quality is actually the issue.
Yes, so basically is you have sometimes too much information, too much data to be able to create insight.
Something very simple, is a buffering of a YouTube that you might have in your journey in this morning. That also we know what kind of buffering it has been happening, what kind of issues you happen to on those quality of data, all of those we will capture.
It sounds like that the data set itself, you know, every second it's growing and it's tracking point [00:06:00] to point information, information that every user and every provider is creating across the internet. Is that, is that the extent of the data? I think question one, and then question two is what were you envisaging could be done with that data?
So basically is, you mentioned about the internet, it's more than the internet. It's your interaction on the mobile network. So if ever now you are, you're sitting right now, you might be enjoying this podcast right now, you are streaming it or you might have downloaded it on your device already, but someone needs to be.
Able to call you whenever they want to. A person might not be on the internet or anything like that, they should be able to con, uh, contact you. As a result. Device will have always online with the cell site to be able to ensure where you [00:07:00] are to be able to route any phone call to you. This is over and above whether you are using the internet or not.
Because that makes sense. It does. It does. And so what did you envisage as being the insight that you could drive out of that data that will be differentiating? So clearly there is lots of kind of individual profiles you could build up. Is that what you're thinking could be leveraged to create say customer experience?
So basically the keys Based on this one, based on the interaction, a cohort of customer will have on the network. Then we can have more personalized type offers for that cohort of customers. What are the services we can provide to the customers? And if ever that customer is going through a black zone or a dark zone where potentially we are going to have issues around the service you're going to have from the provider.
How can the provider now send a signal [00:08:00] to you or be able to provide you with some some sort of devices or something? You are now traveling or you are staying in an area that potentially is a dark zone. How can you now have any sort of devices that we can provide you to be able to have all of those always to online, uh, for you to be able to deliver.
Praveen, what do you think? Is that a bit too much information about the super Wi Fi, et cetera? I don't think that is, that is, that is too much information, but you know, when, when, when I was just hearing about all those kind of. Bits that you're talking about the quality of data, the quantum of data, everything that we do passes through a telco other thought was coming.
Actually, for me, that is what is holding telcos back because you're sitting on huge amount of data. The quality is great. You have the resources. Um, why the data has not been leveraged for both internal [00:09:00] operations to optimize that to the extent and Yeah. More importantly, the monetization of data, of course, there are great examples of each one of them, but has it been realized to its full potential?
I would say not yet. But your views, Osman, on that?
That's a very good question. So now we are starting back again. If I look at telecom, et cetera, we sit on a vast amount of data. The question might arise, is the telecom providers really leveraging it or not? Telecom is a very highly regulated industry. And what for me is A bit weird, the over the top services that we have out there, whether it's the social media or any video streaming platform, they use our network, they get to know more [00:10:00] information, but we are not able us as an industry in the telecom use that data to be able to help the customer to be able to monetize that data.
However, the over the top players, the social media providers, social media companies. are able to be able to push and have more information. So they're using the data more because that area is less regulated. I'm sure any one of you guys who have gone on any social media platform, I'm not going to name that today, but a few hours later, We have that conversation
going on at the moment, don't we?
Yes. Yes, we do. Trying to work out what we're doing with the show, in fact. Yes. What social media platform we're going to leverage for the show. So, yes. Absolutely. It's live in our conversation. Exactly.
So therefore, those over the top players, they are able to have more of that monetization of the data. But the enabler of all of those, the telecom, we are all [00:11:00] now based on those regulations we have in most geographies, in a lot of geographies where we are quote unquote handcuffed on how are we be able to look at the data, monetize the data.
So we are able to use it internally for a lot of insight. But we are not sometimes able to push it forward and able to monetize that type of data. That being said, IoT is a good example where now we can start to look out on how can we start to monetize the data on the IoT platform.
And do you see that, do you see that changing over time, that regulation, or do you see that as something that is going to be present in the industry for the, you know, for the foreseeable future?
Uh, it all depends on geographies. Uh, I was just in a, in a major market, right? A major telecom market, uh, not so long ago, last week, actually. And over there, I saw that the culture and the mindset has pushed the regulation to allow that to happen. Whereas in Europe, [00:12:00] that mindset on how a telecom can use my data to provide me with better service, so that then we can push more for that.
Relax of that regulation. This is slightly, uh, missing today in a lot of the geographies. But in my opinion, we're now with the advancement of A. I coming whatever we are doing right now, in my opinion, it's a matter of time that this will be hopefully it won't be fully deregulated, but hopefully people will be allowed to use the data.
Well, it does. It does feel like And we'll come on to AI properly in a second, but it does feel like we are moving into the, to the promised world of data being the new oil. Do you remember that phrase was knocking around about 10, 15 years ago? And everyone was like, what does that even really mean? But, but in, but in a world where data sources for um, kind of AI front [00:13:00] ends are going to be highly sought after if you're trying to create particular insights in a particular role or in a particular industry or whatever it might look like. You can imagine resale of data being something that's, you know, very, very, very valuable. So it does feel like even though it might not be tapped now that it's not going to sit there untapped for much longer.
I don't think so. The advancement of AI is going to really push this one. And I just wanted Dave to, to just refer back to what's said, data was a new oil when big data was a la mode. That was maybe seven to nine years ago.
Yeah. That sounds about right. Yeah. Now agents are the new oil. , all the AI agents and now the whole, we have now over the last few months, agents, ag, uh, ize, all those things around agents, et cetera.
All those AI agents. And now, yeah. You can't go to any AI [00:14:00] conversation where you don't talk about agents anymore. That is true. That is the truth. And like last year, you couldn't, you couldn't go walk down the street without seeing a gen AI or generative AI poster somewhere or somebody banging on about that.
And now all of a sudden it's, it's a, it's a gen tick. And I think there is, I, you know, just to digress slightly onto that, my, my sort of take is that this year we're going to see. Scaling frameworks for AI that will include both Gen AI in its place within the framework. Agentic being something that's scalable across organizations and really brings AI scaling to the enterprise scale to the forefront. Along with more traditional forms of it like machine learning. and deep learning. To me, they all sit within a scaling framework for AI and can be pulled together to help transform organizations.
So basically, the interesting thing is what happened over the beginning of [00:15:00] this fiscal year. It's very fascinating.It has now completely going to change the economics of AI. Where AI was as if only for big companies where you needed very big bucks to do it. And now, you know, from beginning of this year, Yeah, DeepSeek. I don't want to mention the name, but you mentioned it. It's all right. We can, we can reveal it. But the business model now has changed.
And if ever you remember when that was announced. How many billions was wiped out from the, from the capital markets?
Right, right. Well, because it was all built around a certain model of AI that was going to be highly processor intensive, highly energy intensive. And then this new thing comes along. I think it's maybe a little early to tell whether it's actually changed the game, but the potential of something, I think, at minimum, not being as energy intensive has got to be a good thing, isn't it, even before you get to [00:16:00] the, even before you get to the sort of the economics of it.
I was reading in the news again earlier this year. Do you know what are the two things that is going to be generate, that is going to be needing more electricity and power? One is EV cars. which is going to be producing lots of data again. And the second one is going to be data centers that would need to process all those AI and all to be able to deliver on those agents.
And again, those two things. which is going to be producing vast amount of data would also be needing over. So this is where now the world is starting to completely change upside down.
Well, I was going to ask you that. I think there's at least two really interesting threads in that for me. The first is, and maybe a different conversation today, but the first is like how the energy then gets [00:17:00] produced.
Cause it seems to me that the, The conversation around nuclear, for example, has very much changed in the last 12 months as a result of needing to power these data centers like Amazon invested in nuclear, you know, I think a number of the other hyperscalers I have, Facebook has to train its large language model so you can see the emerging energy supply chain changing.
I wonder if you've got a view on that, but actually where I, where I was mainly going to go next, and this connects to your earlier point about the, just within the teleco industry, the amount of data that's created multiplied many times in the way that you've just described. How on earth do you get your arms around that data?
What, what's your view, Osman, of controlling that data and driving insight from it?
So this is where. The lack of those agents that we have discussed would have to be able, because you won't be able to, as a human [00:18:00] being, as we see the human people, they won't be able to just go and mine that data to be able to create insight.
You would need to start to have those auto insights generated for you based on those data. This is where now the advancement of AI as a whole is a complete game changer. We were all talking last year. About democratization of data. Now we are talking more of democratization of AI. This is something that I feel is going to be coming.
And if ever you look at a recent report produced by a, uh, by Gartner not so long ago, it says that by 2027, 3 billion U. S. dollars. will be spent on AI.
So do you envisage a model where say in, in a, in a model of democratized data in the, in the most simplest terms, which are the ones that I generally can grasp, um, you have a giant data [00:19:00] set, you have. Given tools that are very, you know, kind of very non technical to use and sometimes even plain, plain language to use to business users who can then create queries on that data in a way that if you try to centralize that you just wouldn't be able to create the amount of insight and volume because you'd be putting it in a queue in a backlog and you'd be stymied by a central group.
One, is that your, you know, does that resonate with you as a, as a, as a broad, sketch of what democratized data looks like. And then secondly, in your agentic view of the world, do you see those agents being the ones that are effectively replacing humans in that system?
So that's a very, very good point. If you look at it right now, the data will have to be curated and governed because of the regulations that we are going to have, et cetera.
But We won't have enough data [00:20:00] professionals to be able to create those insights that is needed for people in the different business because I don't know the data and they speak to insight. Would be a big differentiator, uh, for any, for any organization, for any telecom or for anyone in the, in, uh, in any industry on how are you going to be able to increase the speed to insight and for you to be able to increase the speed to insight your business analyst within the business need to be able to interact with the data directly.
Gone are the days of dashboards where you have fixed format reports, where every morning someone would refresh the data for you and you'll be able to to look at those dashboards. Yeah. In my opinion, gone are those days. Yeah. So as a business analyst would be able to create an agent to give him or her every morning over coffee.
Yeah. The information that [00:21:00] they're going to be needed. For them to be able to go through the day and to be able to put that and to be able to look at
it. Yeah, I sort of have in mind a model where, like in each boardroom, there is a, you know, an Alexa type device that is actually an artificial intelligence representation of the company. E. g. it's got access to the data of the company and maybe it's even got a UX that's been designed around the values of the company or the tone of voice of the company and you could ask that AI questions about the company and you would get real time information back that it's drawing from the data and insight in the company.
And then one step further it seems to me that that could be a bi directional conversation. So right now you could create that one way. You know, tell me about shipping in the South China Sea. Um, in future it might, the answer to that might be actually there's an issue there and we need to reroute ships.
And it'll be, okay, we'll reroute [00:22:00] tankers one and three via different directions. And agentic AI and hyper automation could even, could even take that two way query. Exactly.
So for me is, in my opinion, the boardroom of the future. Is going to change. And again, for me, is if ever we have a Q and is a question and then you get the answers.
And for me, is that might be a bit of the past. As we say that, as you were mentioning, is the system, the agents, AI would know that potentially you're going to have an issue in the, in the, in the South China Sea. Maybe you are going to have an issue about some of those issues. So whenever you go to the boardroom, you're going to be able to see now, these are the five issues we need to be discussing.
Yeah. So this would already be pushed to you. And then if ever you want to know a little bit more on how you can start to answer questions, and that also is going to be quite supplemented in terms of [00:23:00] the information that is going to be available. So for me is you're going to have way more information at your fingertips.
The real time information that we are going to be having in the future is going to really reshape the boardroom because there's going to be a lot of noise. from the information that is needed for you to run your businesses. Right. So that is now going, in my opinion, going to be the biggest challenge of the future.
And how do you now really focus on what is the right thing for today instead of focusing on everything?
If I, I also want to circle a bit back to that customer experience because that's what you said, if you tap into that data and we can really feel as a consumer that we're being helped and proactively and we're not facing struggles, etc.
What does it do to the profession of marketing? Because we're talking about agents and AI, but the real understanding of [00:24:00] customer experience, service design, marketing. Do you see anything happening in the telco industry on that level? Are you talking about data?
So basically is when you're going to be looking at a data right now, how about you look at your customer acquisition journey on how are you going to be going in and acquiring a customer based on the data that you're going to be having, in my opinion, is a future Cost of acquisition of a customer would potentially go down instead of going up because you will be able to target your cohort of the customer much easier, much simpler based on leveraging the data rather than just spending generic.
Type of advertisement on any sort of platform. So how do you now provide more type of targeted information to be able to look at it? So for me, I'm hoping that the acquisition [00:25:00] costs of a customer. Would go down. But on the other side, also, what you were talking about customer experience, how can you use data to be able to provide proactive customer experience in the telecom industry?
The FCR, first call resolution, is a KPL that is always looked at. But why do you need to even call? A call center. Why do you have to always interact? How can that be a push? We believe that right now you're having an issue in, uh, in buffering or, or right now you're having, uh, an issue you've had over the last day, five drop calls and this is what the measures we are going to be putting in place for you to be able to look at it differently. So how is that going to be tailored interaction? Yeah. We use a different, uh, customers that will be quite important.
I wonder also, maybe just go a level deeper on that. [00:26:00] So if, um, if we have this scenario in the future where you're interacting with A.I. s in the boardroom and it's providing you with information and maybe that's a two way conversation through which you can, um, kind of enact changes to your business in an automated way, what do you think the role of the telecom provider is? in that world, because it seems to me that you've got the giant infrastructures, you've got a, you've got a great amount of information about how, and, and let's assume just for the sake of, you know, kind of the nature of the innovative conversation, that we can park regulation for a second.
What could the role of the telecoms provider be in creating those hyper automations, for example?
So basically, this is where now telecom would have a big role to play in the future because everyone would need that bandwidth to be able to have those agents to work on. to be able to deliver on those things.
So yes, you're going to have [00:27:00] it in the boardroom, but it won't only be on the boardroom. Self driving car would be a reality in the UK. I think next year, if I'm not mistaken, in 2026, it's going to be a reality. So now that latency that you need to be able to have. the data that needs to flow on that backbone for that to enable that, uh, self driving car to, to really happen.
How would that happen? How would that go? And if you look at all devices, that's becoming smart, smart fridges, smart homes, everything now is becoming so smart, smart and smart. All of those would start to put. pressure on, uh, on the boundaries that the telecom needs to be providing. Before you were okay of having a, uh, 50 MB broadband, no one advertises a 50 MB broadband anymore.
Yeah. So Osman, is there a role beyond the connectivity also for the telecom provider in this? Connectivity is clear. It is a [00:28:00] backbone. Anything more than that?
So basically this is where for me is, if ever you look at it, I'm hoping that the whole on how customers can use their data and be able to use the data that is be able to capture by the telecom provider to be able to help themselves to be able to make the right type of decision. Something very small.
Uh, we all go on vacation somewhere and we know therefore that if ever you're going to go to that place, et cetera, et cetera, say if ever you go to Paris tomorrow and now based on that cohort. That I'm sitting in, what are the people in Paris doing, which restaurants they have been going to, what kind of things they have been, they have been looking at, uh, et cetera.
So that is one thing. Second is you want to go and, and visit the Louvre. [00:29:00] So right now you are maybe on the Metro to go to the Louvre and based on this one, you know, already. There's too many people there. And the waiting time is two hours. Right. Don't even bother going. Right. So now can you start to see now some potential services that in the future can start to come and be able to, to help me to make a decision on my own life.
And this is a data that telecom, in my opinion, should be able to provide in the future to be able to make your life
easy. Also, if you take a step back and look at, take it from the. other perspective, right? So telecom is the backbone and it is had handing massive amounts of personal enterprise and mission critical data.
That also makes them a prime target for cyber threats and also the regulatory scrutiny. So they have a significant obligation to protect the data, both from the regulatory and ethical point of view. So that's one side. And then we are talking about extracting the value from [00:30:00] data. How do you balance both of these?
Your obligation? and extraction of the data.
So for me is in my opinion, uh, privacy, uh, and security, uh, a report that was recently published by a, uh, major firm says that cyber attackers now is really going to come off to the telecom people because as you know, we have a lot of those data and they're using AI.
to get smarter and smarter on their attacks. So I don't know if any one of you guys who listening to me today have been on the dark web. Uh, but if I can't possibly, can't possibly disclose that kind of information, I think Rob is because he's not here. So that's why he's like, Oh my God, he's going to ask that question. I can't make this one.
Exactly. So basically, from where you look at it, this is going to be the biggest threat [00:31:00] right now, data privacy, data security, followed by ethical implication. That would be, I think, the biggest concern that is going to face the telecom industry on how are we going to be using data, leveraging data in the, in an agentic world.
It's such a fascinating topic, actually, I could keep going, but just in the interest of time, I'm going to bring it to a little bit of a close for now. In the world we've been talking about, what do you see as the one or two core differentiators that telecom organizations are going to need to develop?
I'm assuming in this that there is some basic foundations in place in terms of modernized infrastructures and being able to deal with capacity, but what do you think those up the stack differentiators are going to be?
So basically, however, I look at it. Is on how a telecom operator or a telecom provider is able to use [00:32:00] data to give a differentiate to the, of the service, to the customer, to a different customer.
Because, let's face it, uh, telecom now is very much a utility. industry. Let's face it, it's a, it's a huge industry. So now what would be the differentiator for people to get hooked on, on to, on to the telecom provider, et cetera. So for me, my opinion is as part of the offering of just providing something as connectivity, simple connectivity to your customers.
Maybe you would now to start to say, okay, how can you now bundle data as a service? to you as a customer. So how are you going to be able to run some potential type of agents on some of the data? So it could be all anonymized, everything. So how can we now expose that data to be able to have it to our customers and to be able to look at it?
In [00:33:00] again, as we have seen into DeepSeek, all the chip providers, et cetera. So now you don't need big, big chips to run an AI model. You should be able to hopefully do it. in the smartphone itself. So this is what now and how are you going to leverage it and how telecom can allow that to be able to expose some of the data for people to be able to have an agent and to be able to query that of the data.
And that would also require quite a lot of regulation and regulatory changes. Or we're going to be allowing maybe a cohort of data to be available and to be able to for customers to be able to look at it. So these are the changes that I believe that hopefully we are going to see in the next few months slash years, which is able to put the data of the service of the customer.
And I believe this will be a major differentiator. [00:34:00] Yeah, so we're talking about the telco industry, and especially we're talking a lot about AI, but I think it really is about connecting it to industries, right? So taking other industries as an inspiration is, I think, a good thing. So I want to bring in the topic of the healthcare industry, which is always tricky when it comes to data.
Yeah, this integrative. Healthcare sector offers a compelling model for AI driven industry collaboration, because we're all talking about cross collaboration, sharing data, uh, where data is not controlled just by one entity, but shares amongst, well, in healthcare patients, providers, AI developers, and it's the same with Telco, right?
You have all these different entities that, yes, we all want to collaborate, but at the same time we have competition, we have regulation. Uh, so that brings me to the question, if AI models are trained. on an industry wide data, who truly owns the intelligence they generate? [00:35:00] So is that the data contributors, the AI providers, the businesses applying it, the users using it?
What are your thoughts on that? Osman? Who's, who's owning the intelligence?
That's a very good question. And for me is, uh, the verdict is, is out on this one and who really would own the AI and who would really own the agent and if ever you look at, at the healthcare. And, uh, I was, I was, uh, uh, uh, I was looking at observing what I was, I was, uh, on the tubes already.
And you can feel that someone was starting to get sick on that tube. Someone was starting to get sick. And if another person was having a small device on the watch, how can you now, based On the vital that the smartwatch is providing based on the connectivity that is providing and based on the AI that is being generated, [00:36:00] how can we already provide a proactive care to that person instead of that person just collapsing in the middle of the.
of the tube. So now the question is, who is going to monitor and who is going to own the data? Is it the smartwatch provider? Is it the healthcare provider that is getting the data? Or is it the telecom provider that is bringing all of those together? This is where you're going to have now on how are you going to have those type of collaboration.
So now. Each and every industry in itself has a lot of data, but the cross collaboration amongst industries is not very mature yet, in my opinion, because data sharing, again, in a lot of jurisdiction is very regulated. Health, telecom, uh, et cetera, et cetera. It's all very much regulated. [00:37:00] How do you now start to look at those type of use cases and how can we now Type of, of collaboration among and across industries.
And I think this is something that we'll have to think about especi when we, when we're drafting all those type of regulation and how are we gonna be able to deliver? And now even further, your smart watch when you're wearing, it's not going be only in your whole country, you're going to wait everywhere in the world.
How do you then have that global nature? How do you start to look at all of them? Before we were having roaming only as a telecom provider. How do you have now a healthcare roaming? How do you have all of those? Which potentially industry might not have thought about and how are you going to go in that area?
I mean, I think the other interesting thought in that Is the difference between source data [00:38:00] and then information that has been generated by the intelligence, whatever that intelligence looks like, and then who then owns the data that's been, or the information that's then been created by that, the intelligent entity?
Is it the owner and developer of the intelligent entity, or do the underlying Source data orders have a slice in that because their intelligence has been used. And I think, in my mind, this is maybe where things like data as a service will come in. So for example, you know, like a Vodafone or a Gartner or any other research agency or, or health or hospitals make data available that can then be consumed by intelligences, whatever those, whatever those are.
And it's the act of then procuring that data from the That means that then I, as the owner of the intelligent entity, can then own [00:39:00] wholesale the information that's then created by the intelligent entity. It seems that that's, that feels like the sort of model that could evolve in this sort of space. I think where it gets really tricky, and you see this in the entertainment industry, uh, with what, you know, the actors strike, for example, whenever that was a couple of years it was all about their likenesses being used.
And it was like, well, so let's say Universal Pictures own data about me as an actor. They sell that on to an organization that's then going to create a movie with me in it that I've actually had nothing to do with. That gets even more fine grained and difficult, I think. So, Osman, I guess, do you see that kind of, that sort of, you mentioned data as a service in the main conversation, but do you see that as the kind of relationship between the data provider And the intelligent entity.
So for me is again, if you look at a few years [00:40:00] ago, data monetization was a big topic. You sell the data.
Yeah. Yeah. But now I think the biggest thing that is going to come now is data as a service. So you're providing that type of data as a service. So then. As we have the paper use, uh, how are you going to then, if you're using the data, you give a token for that use of the data you're trying to use, et cetera.
So if ever you look at it, if ever I put it parallel right now, you're going to have influences on social media who make money out of content. So the, for me is I see that in the future, people, the data providers, the data. Stop also going to make money based on how the data is being used as a service in the grand scheme of thing when, when that would be an input to some other agents to be able to make it more intelligent.
So yes, people would have to be able to deliver more of those intelligent [00:41:00] platform, but then instead of just acquiring the data once and then Forgetting about it. And the more you use the data, the data provider that makes more money also out of it. And I think this is what, for me, I believe the data as a service would be a big opportunity for telecom provider in the future.
So basically is, if I look at it, 30 percent Of all data, total AI spending in by 2027 will be on Gen AI. That's very astonishing. Telecom is going to be the leading industry for Gen AI adoption and from a SAS press release in October, it says that 70 percent of all of telecom are currently using Gen AI.
Compared to an average of 50 percent across all the sectors. So 20 percent different. The next higher up doctors or retail, followed by banking. And if [00:42:00] ever you look at all the KPL that I do, I'm data, data is my friend.
If ever we look at it is, 94 percent of any leaders have said that they want to increase the investment in AI leading to a greater focus of data.
Another interesting point, 58 percent of data and AI leaders said that the organization are going to be achieving exponential Productivity and efficiency, okay, that's a huge thing to be able to really put those things out there.
I mean, it does, it does feel like, you know, you look back on the last 10 years or the last 50 years of technical change and think, you know, a lot's happened in the digital age.
Um, and that's for sure, but it does feel like as we move into the [00:43:00] intelligence age that we're only just beginning this journey, doesn't it?
Yes, indeed. And also another report I'm going to now, uh, refer to the Gartner Emerging Tech by 2030, 100 percent of global IT spending will be directly or indirectly be invested to support AI. Wow. 2030 is only five years away and we're just starting.
Well on that note, uh, and, and what a note, uh, what, what a few years to come. Um, I'll just say thank you, Osman, for such a fascinating conversation this morning. It was good to see you. Thank you very much. Now we end every episode of this podcast by asking our guests what they're excited about doing next and that could be something like you've got a great restaurant booked at the weekend or something in your professional life or maybe a bit of both.
So Osman, what are you excited about doing next? May dashboard rest in peace. [00:44:00]
How does that work? Basically is why do I need to have and spend time and money to create dashboard? If ever we have agents out there that allow my business users and my users to interrogate the data based on what they need.
Why do I have? Why do I need to have it? So I'm right now creating that vision and creating the journey with a fantastic team that I have globally. On how do we provide the data, democratize the data and make it available to agents for our business analysts to be able to ask a question and our business leaders to already get the insights of the data instead of having to digest it and look at themselves Industrials. I actually very much agree. It is a, it is a new dawn in terms of business automation. I think that you're talking about and, and I agree. I think it's, valuable now. [00:45:00] Um, a little difficult right now because there are still some elements of things like data as a service that don't exist at the level of maturity, but, but there's nothing stopping you starting the journey towards what you're talking about.
I don't think like right now, the technology is available.
And, uh, Us as data leaders, we need to push the technology we want. Otherwise, the technology is going to push us in other directions. And now how does the data leaders influence that trajectory? And how can we work with system integrators that, uh, Capgemini or any other companies to be able to help us shape that future?
And how can we influence the technology? to be able to allow that for us to happen.
If you would like to discuss any of the issues on this week's show, and how they might impact you and your business, please get in touch with us at cloudrealities@capgemini.com. We're all on LinkedIn. We're still figuring out whether we're going to go for Blue Sky or Mastodon, so stay with us on that.We'd love to hear from you. So feel [00:46:00] free to connect and DM if you have any questions for the show to tackle. And of course, please rate and subscribe to our podcast. It really helps us improve the show. A huge thanks to Osman, to Praveen for being the substitute of Rob, and we've never missed him the entire episode. So I'm sorry for that. I mean, look, a professional co host as, I mean, I know, I know. We should, we should hire him, you know. Let's talk about that offline.
Yes, indeed. Let's do that. And also, of course, our sound and editing wizards, Ben and Louis, thank you again for making us sound perfect. Our producer, Marcel , and of course all our listeners.
See you in another reality next [00:47:00] week.
