Telefonica Tech Reimagines Itself for the Hybrid Cloud Era

Telefonica Tech Reimagines Itself for the Hybrid Cloud Era

Show Video

We continue the global tour here at the Microsoft  Hybrid Cloud Partner Podcast. I'm Fede Pacheco and   this is Adam Burke. How you doing, Adam? Hey,  I'm great Fede. How's it going? It's great.   Today we're heading to London in the UK with a  partner called Telefónica Tech and I'm excited   to hear about their transformation story and  especially the impact that they're having on   their customers. Yeah, we've got Alex and Martyn,  both based in London. Looking forward to the   conversation here. Thank you, Alex and Martyn,  so much for joining us. Thank you for having us. Yeah, no problem. Glad to be here. Would you mind  introducing yourselves a little bit? Tell us about   your role at Telefonica Tech, please. Yeah,  so I'm Alex. I'm a cloud chief technologist  

within our cloud practice and look after  our go-to-market strategy and portfolio   around public and private cloud. And I'm Martyn  Bullerwell, officially vice president of data   and AI for Telefonica Tech, UK and I. I look  after our data and AI practice within the UK   helping our customers drive real value out of  data and AI programs and projects. Formerly,   I was a founder of a company called Adatus that  was a niche specific company in data analytics   and data engineering. And we've been  through that process where Telefónica   required us. And we're now heavily embedded  within Telefónica Tech, helping drive even  

more value to a broader range of customers  through the Telefónica Tech ecosystem. Amazing. And we have a third guest, but before we introduce  her, I'll make everybody wait a little bit. I also   want to highlight that for the first time in  this podcast, we use the co-pilot researcher   agent to learn more, not only about Telefonica as  preparation for this conversation and Telefonica   tech and that transformation, but also about  our guests here. So Alex, you said very well,  

you're the cloud chief technologist.  Here it said also that you're helping. Telefonica Tech become an industry leader in  cloud optimization and FinOps. And you also   won an award last year as the MSP Partner of  the Year, validating your leadership driving   cloud cost efficiency and innovation. And you  often emphasize that reinvesting these savings   into new cloud innovations for customers is the  key. Is that accurate or not? It's all true,   absolutely. We've been really driving FinOps  quite hard since I joined. So I've only been  

here sort of 18 months, didn't found a company,  unfortunately, that got acquired. But yeah,   I joined and really sort of started to focus on  some of those enterprise use cases and driving   sort of FinOps optimization. yeah, we got to a  good place with IBM. We were the first, I think,   MSP customer for them in terms of signing up to  the new program and then bringing that to a lot   of our CSP customers and also sort of midsize  customers as well that want to get into FinOps.

Yeah, it's been a real success and we  picked up the Partner of the Year Award   and that's part of it. All true, definitely.  Congratulations. Thank you. Co-pilot win,   we'll take it. Yeah. Let's see if it goes  two for two here. So Martyn, it says that   your leadership has led Telefonica Tech to  attain the Microsoft Analytics specialization,   demonstrating extensive expertise in  designing and managing analytic solutions,   which for your title of Vice President of Data and  AI, I think that's right around your wheelhouse. It also says that you're a thought leader in AI  and you shared recently insights on aligning AI   projects with business goals and highlighted  the importance of data quality and governance   for successful AI outcomes. How does that  sound? mean, this is fundamentally why I   love AI because it makes everything sound  so awesome, should we say. But yeah, mean,  

all those things are factually correct. If you  ask an Englishman to say what they've done and how   they've achieved it. I'm sure they'd be a lot more  modest than that. But this is why we use CodePy.   This is why we use AI to help us upsell. But no,  it's all factually correct, yeah. Wonderful. Well,  

we have actually a question for you about  your use of AI. But before we head there,   as I hinted before, we also have a very special  guest. For the first time in our podcast,   we're featuring a partner development  manager, which are really a key strategic   pillar of building those relationships with  our partners. have Tijana Ellis with us today,   also in the UK. Tijana, how are you doing? Do  you want to tell us a little bit about you and   your role as a Partner Development Manager, also  known as PDM? Thanks for having me, Fede and Adam,   and great to be here with you today. So yeah, my  role as a PDM and Partner Development Manager is  

all about working very closely with partners to  drive joint success and deliver for customers. And the way we do that, I've been working with  Telephone Architect for close to three years now.   So we basically align our strategies, we co-create  solutions, we work on co-selling with our teams   and unlock new opportunities. And so my role is  really all about building these strong, trusted  

relationships and helping partners grow through  mutual collaboration and innovation. That's   exciting. So Fede alluded to it earlier, but  we've really been working to integrate Co-Pilot   both into the preparation of the episodes and  then into the conversations as well. We'd love   to hear from all of you, how you're kind of  integrating Co-Pilot and AI into your daily   lives. Maybe Tijana, you want to go first,  then we can hand it over to Alex and Martyn.

So from my perspective, I use Co-Pilot every day  and what I find with it is the more I use it,   the more I find, keep finding new ways how  it can help me. Whether that's catching up   on meetings, using it actually to  craft the documents, I use that a lot.   And also for searching things and connecting the  dots, I find it absolutely saves me tons of time   just in everyday work. Obviously that's  very much related to the nature of my role,  

but I'm sure Martyn Alex may have slightly  different ways of how they use it. Yeah, I guess I'll go next. So my journey with   generative AI. So I'd like to split our use  of generative AI and what I call traditional   AI out. Because obviously generative AI is  the cause of all the hype of recent years,   which is obviously copilot is very much  part of that generative AI piece and the   traditional AI. But I guess my first interaction  with generative AI was, I think I was on holiday. My brother actually runs a holiday villa company  over in Cyprus. He was saying he was struggling  

with marketing and actually wasn't very good  at writing marketing content. None of his team   were very good at writing marketing content.  ChatGPT had been released and we said, well,   let's have a go with it. We're looking at work.  It's quite interesting. Let's see what we can use   it for. What we started doing was asking him to  write advertisements and marketing material for   his website that would sound exciting, help sell  villas or rent villas with hot tubs. And actually,  

I think we probably spent 12 hours and 12 shots  later, a good kind of time trying to look at   it and have a really good laugh with it. And  actually, what we found was it was impressive,   really impressive for that kind of  content generation. And, you know,   that was my first dip of my toe. And what we did  ask it to do, was write some of these adverts in   Cockney rhyming slang. I'm not sure if you guys  are familiar with London Cockney rhyming slang,   but chat GPT is, it's, you know, if you've  ever watched any of the films like Snatch or   those kinds of films around about London  gangster type films, they use this kind   of slang word. And it wrote these adverts  in Cockney rhyming slang. And I was like,   this is going to be a fascinating game changer for  us and marketing and how it's all going to work.

And that was our first kind of dipping the toe  into the water. But since then, internally for us,   Generative AI we use, we've built our own  Generative AI solutions that help us do   bid management, bid processing, help us write  responses for bids. Our answer to AI at the   moment is just roll it out, start using it, start  using Copilot. It's going to become the next word.   And again, all of you are probably a bit younger  than me, but when I first started my career in IT,   word processors were kind of going out and Word  Perfect and Microsoft Word was being released   and they were like, go on training courses, do  we need to adopt this new technology? It feels   like that with Copilot, everyone is going  to be using it. So let's just hurry up and   get everyone adopted on that so we can start  doing the real game changing stuff. So yeah,   my whole team within Daytrain AI use Copilot.  They use the GitHub Copilots to help write code.

They use the Copilot in Outland to help manage  their lives. We use the, we use it a lot in   teams and summarizing of documents and creating  presentations. So we use it all over the business   very successfully. And as I said, kind of most  customers we get an opportunity to speak to is   look, don't delay, get on it and you're going  to be behind if you don't start using these   technologies. So yeah, we're using it a lot.  That's exciting. That's exciting. Yeah. I guess   just to sort of echo, I guess a lot of that, yeah,  it's become part of everyone's sort of day-to-day   life. I mean, copilot for me, especially  being a more of a technical person, you know,   my brain when it comes to being creative, isn't  always as good. So having a tool like that,  

that can just quickly pull something together,  review something, maybe change the format in   condensed words when we're trying to get responses  and bids out the door. And not so much, you know,   come up with the content itself, but just give us  the outline, the framework of what we want to use   for that piece of content and give us some ideas  and stimulus and then review it with Copilot, that   for me is awesome. I know there's a lot more we  can do to it, but when we're looking at trying to   build solutions and explain technical concepts or  even just to get an explanation of how something   works from Copilot to start with, you can get it  in a format that works for you and interrogate   it and question it. And it just saves so much  time where you'd have to do all that yourself.

So that's been the real game changer, the  speed that you can access information and   we can go back to the old days of tech net and  things like that, but we had CDs and things that   we were loading. Now you can just sit and have a  conversation about a technical subject and yeah,   love it. Yeah, it's fascinating. I would  agree with you, Alex. I find myself all   the time where the speed at which you can get  to an 80 % solution with Co-Pilot or ID8 and   kind of like get your brain unlocked instead  of just staring at the screen and saying,   where do I start is amazing. yeah, thank you  all for sharing that. That's always exciting   to hear kind of how this journey continues as we  all sort of watch it evolve in real time. Yeah.   And watch ourselves evolve with it as Martyn was  saying, you know, comparing to the adoption of   Word. Now going from the individuals to the  organization. And I think our researcher put   it in the same way that Tijana put it when we  were preparing for this conversation, which was   Telefonica's evolution from Telco to Techco.  Can you tell us a bit more about that story?

And the why behind it, why do you evolve that  mission? Yeah, I'll put that up. So the history   of Telefonica Tech is still quite a young company  overall. I it was carved out of Telefonica to   really just provide that technology services  back into the organization. And within Spain,   obviously with the dominance that Telefonica  has there in that market, that's quite a big   operation. So Telefonica Tech became like  this sort of huge tech services company   sort of overnight and that's continued to evolve  and grow. And then the expansions that have then   happened through acquisitions as Martyn pointed  to as well, building out the UK capability has   then given us these five practices that we  have in the UK. So around cloud, data and AI,  

we business applications, which is another  acquisition around dynamics and power app.   We have a strong cyber security practice as  well that leverages a lot of the Spain market   and the big cyber business  that Telefonica has there. And then digital workplace as well, we're  looking at Copilot and Office 365 and we   have a quite a heavy sort of Microsoft  slant, but also been able to build   quite a strong presence off the back of those  acquisitions that came with things like a strong   data center and infrastructure  background as well on managed services.   So we've kind of evolved from that state, I guess,  and integrated those acquisitions and over the   last sort of few years really built up really  what our story is. And that has really focused   on solving complex business problems, which  really focuses around bringing all of these   elements together. So very much how Microsoft  operates and being a bit ex-Microsoft myself,  

understanding the landscape of, here's all the  tools, here's all the products. And now for us as   partners, let's build something out of that that  addresses a customer outcome. And that's where we   are and our new sort of wave of portfolios and  offerings and with our new practices that have   come online over the last year, that's  really starting to accelerate and grow. It's an exciting time for Telefonica and  Telefonica Tech. There's a lot happening.   There's a lot of globalization as well and  understanding how things that are being   delivered in Brazil and Peru and Chile can  be then leveraged and adapted into the UK as   well makes it really interesting.  So for me, we're like a mini-GSI,  

but with a lot of power. Anything you want to  add to that, Moin? Yeah, I think I was going   to pick up on the mini-GSI piece because, you  know, being acquired, I guess, from a founder   owner of a relatively small niche, I'm to call  ourselves a Be-Like Consultancy for those that   remember business intelligence. You know, one  of my main concerns for my team and for me was,   you know, we don't want to be swallowed by a  large corporate that are just kind of come in   and tell us how it needs to run and kind  of become dominating. And I think what's   really nice about what we've done, certainly  in the UK, is we've kept those five practices.

And we've kept the nimble agility that we can't  with a smaller kind of organization. But we've   got all the backing of Telefonica Tech in Spain  and Telefonica as a kind of global company. So   we kind of think big, but still act small, if  that makes sense. So we still got the agility   that helps really us drive value through our  customers, be innovative and pivot when things   aren't where they should be and we've always,  from a data AI perspective, we've built the whole   business for the last 19 years based on Microsoft  technology. And it's always been great to us. it's   even better that we can continue and grow beyond  the reach that we had before, being able to help   drive data AI solutions into a number of other  organizations we may not have access to prior   to being part of this bigger group, while still  maintaining the culture and having fun doing it.

That's great. It's certainly impressive just to  see the breadth of offerings that you all bring   to your customers, really kind of across, I you  mentioned your five practice areas and having kind   of that robust offering. I think is really is key  to help your customers drive that modernization   that we know they're all seeking. One of the  specific questions we'd love to learn a little   bit more about is kind of what drove your decision  to move your customers from your data center and   into Azure and then beyond the migration. If  you look at sort of the both modernization and   incremental value add capabilities that you've  been able to either offer your customers or   maybe that your customers were coming to you  and saying, hey, I need this or I want this.  

Would love to like learn a little bit more about  that journey and then really kind of some of the   key outcomes and benefits that you were able to  deliver for your customers as a result of that. I think from a cloud migration perspective,  and certainly we look at the DCO program,   which has been a real advantage for us and has  been really helpful in driving that and being   able to finance some of that as well in terms  of giving us an incentive and a motivation to   really push customers towards cloud. That's  been great, but I think the customer at the   end of the day drives that strategy. And one  of the things that… we've seen is, I guess,  

the days of those big, huge migrations maybe  has gone and it's now becoming a much more of   a workload conversation. Customers are looking  for the right place to put workloads that suit   them. And I suppose our job at the moment is to  give them all those options. And that's where our   philosophy is. certainly from my point of view,  workload freedom is a key part of our strategy   and our message is to say, look, where's the best  place to put this workload and let's put it there.

but we want to make sure that customers have  access and understand how they can build those   sort of hybrid multi-cloud strategies and  get the best out of Azure and say, right,   I want them to have a cloud option  to me. I want to look at these cloud   technologies. I want to look at the  innovation I can do with cloud native.   So help me get started in that space. Help me look  at this and then we can help them move workloads  

from on-premise data centers into Azure  and then start leveraging some of the data. I had capabilities that are available  there as well as getting them started   on DevOps and automation and just trying  to optimize a lot of what we do. As I say,   the programs and things that we have, and  that's not just DCO from a partner perspective,   but access to the Azure migration funding and  Azure Innovate funding are key levers to help   customers explore that world. And that's what  really drives the acceleration of those moves. We are still seeing those migrations happen  and we've got large customers that are sat   within our data centers that we host critical  workloads for, especially around the NHS. And   now we're starting to see them pivot some of  those workloads to Azure and start to leverage   some of the capabilities within Azure to be able  to innovate and modernize and also optimize those   costs. And we mentioned FinOps, that's obviously  a big part of it, but we also applied a lot of  

security around that as well given that platform  then to go and explore and modernize. yeah,   I don't want to say that we're really sort of  driving customers out of data centers because   if they want to stay, they will. There's been  some interesting developments in the market   that may accelerate some of those decisions around  cost and price increases on certain hypervisors. But that's what's so great about us as a partner  having these options, being able to present   all these different capabilities to customers,  give them that freedom to pick the right place,   give them the incentive funding to say, right,  let's go and start up that assessment and do   that migration, and then reap the benefits of that  overall in terms of reducing the cost of operation   of their workloads. And I think from a data and  AI perspective, we were a very early embracer,  

should we call it, of Azure. And actually, a lot  of that was if we roll back to the time where   we were talking about Azure Data Warehouse when  it first came out and prior to that, was Azure,   not Azure, there was FastTrack on-prem and there  was stuff you'd have to buy to manage huge data   warehouses and large volumes of data transactions.  And it was huge upfront costs for customers. So actually from a data platform and BI analytics  perspective, Azure was a very simple scalable   answer to helping customers move large volumes of  data with our huge great technical investment in   on-premise architecture that they knew would grow.  Obviously, we used the term limitless scale at the   beginning. I'm not quite sure that's a fair term  to use because I'm not sure anything's limitless,   but I think we've got to be realistic and  customers really very quickly and even some of the   customers I like to talk about at the NHS realize  that when they've got huge volumes of data,  and they need to spend too much capex to scale  something that will be fit for purpose for the   next five years, the cloud solution made a huge  kind of obvious step for Azure. And to kind   of bring that to life and I'll roll back a huge  amount of years, I'm trying to think when we did   this piece of work, but we worked for a large  music label, I won't say who it is, in fact,   I don't know any longer in business sadly, but  they ingested data from Spotify, from iTunes,   from all the streamers, everyone remembers Deezer  and all of those seven digital, there was loads of   them that came out. So every stream of any music  was owned by this music label who happened to own  

the Beatles, so huge amounts of streaming.  We ingested that data and we were trying to   analyze that data. We were looking at types of  customers that this label had. We helped use   that data for marketing. And there was billions  and billions of rows of data, as you can imagine,   this is worldwide data from every streaming  device in every one's home office location.

And what we found was if we had to reload  one of the major tables, the FAT tables,   on the single kind of processing kit we had  on-prem, it was taking up to seven to eight   days to reload this FAT table. Whereas when  we first started using Azure Data Warehouse,   we put it into Azure and said, let's see how  quick we can scale out using a parallel threads.   We could load that thing that took seven days in  about two or three hours which was game changing   for them, even though it cost them a lot of  money, it means they could actually test and   answer the questions much, much quicker. So, you  know, for us, was, was from that point onwards,   it is a no brainer, lower cost of entry for all  our customers is scalable. We don't have to worry,  

you know, gone were the days of having  to go, how much sand storage do we have   to buy to take the warehouse for the  next six years? You know, that's a,   that's a dim and distant memory for the data and  AI projects, thank God. So really driving driving   a lot of value from day one. So unlike Alex, where  we have a lot of customers that have to think,   well, you which one do we use and stuff, actually  just the benefits to scalability and performance   outweigh almost every other, every other problem  you may have from a data platform perspective. And then when you move that to AI, when you  think about the amount of processing and GPUs   and things you'd need to run that on-prem, most  organizations, unless they've got reasons to be   have things processed in the edge or to have  things processed very, very securely, again,   would you want to invest in that kit at the moment  with it being new and work out what you need to   do? So again, for us in the day-to-day practice,  Azure is a very straightforward answer to a   problem. Yeah, yeah. I think that's really well  said. think especially too, and that's a benefit  

we hear from a lot of partners that have gone  through this transformation is really just the  new tools and capabilities that are  at your fingertips with really no   or very limited development costs, right?  In the sense that the solution's built and   it's more about how do you adopt that and  then bring that value to your customers. So   I love that story. Thanks for sharing that,  Martyn. We did have another customer actually,   sorry, I could talk for hours on this,  but we did have another customer who   wanted to do everything on-prem, this is  again going back a little bit of time. SQL Server, SSIS, all of the kind of old data  platform stuff that you put in. And we could,   we said, what we'll do is we'll turn it on and  stick it into Azure, we'll scale it up in Azure,   and we'll wait for you to get your hardware ready.  We got to six months and they still hadn't managed  

to rack their hardware and their data centers. And  we developed the program, finished the project and   put it into production because we couldn't wait  for them to rack the kit that they needed and the   storage they needed. So obviously they sat that  off and realized that Azure was the way forward.   And since then, that customer has moved loads of  their workloads across to Azure because they've   realized that actually just the speed of being  able to get stuff up and the lack of having to do   capacity planning is super important. Yeah, yeah,  it just takes that whole headache off the table. Yeah, that's exciting. Tijana, I'm curious  from your perspective too as a PDM,  

how you've kind of seen the relationship evolve  with Telefonica as they've made these investments   and these incredible transitions. Yeah, I mean,  what I was going to jump in there, so thank you   for following up, is I mean, you have heard the  way Telefonica Tech is set up and just the sheer   breadth of capability and depth of capability  as well is very much aligned to Microsoft. So,   you know, even the type of practices they have  is very much aligned to how Microsoft is set   up. So it's been quite easy to just have the  alignment of strategy as well, because know,   the telecommunication has been very, very  intentional and focused on where to build   a capability, how to be, you know, how to acquire  the deep boutique capability like Datis that Mati   was a part of. So… the capability was there,  but what has also been really, really great,   you know, in the last couple of years since  we've been working together is just that   speed and agility at which the phonic  attack have reacted to the, you know,   to the technology advancement, but also from our  perspective, like the programs, like DCO and the   others that got mentioned earlier, like being  very quick to adopt those, to make usage of them,   to embed them in their own, you know, go to market  and how to give the most value to the customers.

So there've been like that alignment of  strategy has been absolutely critical naturally,   but just the way the speed of execution, like  on the operational level has been absolutely   key as well. And for me, having that strong AI  data and AI capability, especially in the last,   I would say probably 12 to 18 months, has been  absolutely critical because the customers want   to hear, want to understand what can AI do for  them. The reality is their maturity of adopting   AI there and then is not, you know, it's on a  full scale. Some customers are really mature,   some are not quite yet there. And the good  thing is, Terraformica could just bring them   on the full journey. It didn't matter  almost where they were. So, you know,   if the customer wants to use AI and their own  friends, they can take them on the whole journey,   migrate them into Azure and then help them adopt  workloads. If the customer is already in Azure.

And then they want AI because they don't have  it yet. Again, guys can help them with it. So   just that flexibility in terms of how deep  do you need to go with the customer on their   journey has been just, I mean, it's been  fantastic to work with them as as a PDF.   And the other thing is what like the ratio  goes both ways, right? What's, what has been   really helpful for us is to just hear from the  ground, what do the customers need? So we can,   you know, we can feed that back internally  to our engineering and product teams. You know, we have to find the challenges,  you why don't you have this and, you know,   customers are asking for that. And can we have  this selling be quicker to market? So for me,   it's been true partnership, you know, that has  worked both ways. Thank you for sharing that. And  

I forgot to mention in the beginning, this whole  conversation is happening because of you, Tijana,   because you reached out and said, I got a great  story to tell. And so far in the few minutes that   we spent together, I can see very well what  you said, the great alignment that we have,   the strategic pillars that are very well aligned  between the two companies and how both of us are   benefiting from that. So really appreciate  you making this happen. And going back to the   stories that you all were sharing, I actually  want to pivot a little bit because I know that   our listener may be saying, yeah, you're just  throwing the highlight reel, right? Like the   best customers, the best stories and the most  biggest achievements that you've all had. But  

if we were to... switch that a little bit as the  customer or the listener is thinking about how to   apply this with their customers, right? They might  be thinking, okay, this might not happen because   of this, or this is the biggest roadblock that we  have. So tell us a bit more about those challenges   or those roadblocks that you've faced and how  have you overcome that as Telefónica Tech? I   think it is, there are definitely challenges  and I think we've all experienced that.

Customers do engage with, have their  own preferences and their own sort   understanding of what they do. I think, you  know, you look at cloud, as Martyn said,   some of the stories that we've seen, you know,  there's clear benefits of moving the cloud and   leveraging cloud, but you've got to be  ready and set up to be able to do that,   to take advantage of it. If you haven't  gone through that, that thinking time,   built a strategy, really started to understand  about what you're looking to achieve,   you can hit some real problems. And certainly  customers that have gone in maybe a bit too quick   or just try to migrate a bunch of workloads and  then suddenly seeing costs getting out of control   is something that's happened quite a lot.  obviously, we can help with those situations   with those spin ops type tools and solutions to  get a handle on costs because it is a challenge.

But also just having that confidence that  actually you're not going to get yourself   locked into a situation where you don't have  the ability to move or bring things back or   you're taking a step too far that puts your  company at risk should there be problems. So   our job is to really help customers navigate  that wider challenge and do that evaluation   that they do. If you've worked on the customer  side, you have to look around, you have to try   and understand and make a judgment on where the  best place is to put your key applications. And   that's where the partnership really comes to  bear because it isn't just then us coming in,   we go in alongside Microsoft and present  the whole Azure story and what it can do   and help to define solution architectures and  patterns that can really address their need,   whether that's specific to a sector or to a  particular use case that we're working on.   That's where we can kind of really work and that  sort of three-party relationship with the customer   comes to bear. that's sort of where things  are at the moment. It is a challenging market.

There's a lot of pressure on cost and customers,  I think, looking for some real sort of certainty   and flexibility and portability in that.  And the more those solutions that come out   that enable that ability to not get stuck  and not get locked in or get caught out,   maybe that's holding back a little bit of the  acceleration of workloads. And there's quite a   bit of governance and bureaucracy around of  cloud at the moment. But we try and take a   workload approach to it so we can unlock that and  say, right, this workload makes a lot of sense.  There's a lot of tools out there we can take and  modernize the application, whether that's through   containerization or cloud native capabilities,  we can show the cost and give that confidence   to then make that jump into cloud and drive  the innovation. And that's the challenge I  

think for all of us at the moment is to keep that  momentum going and keep that innovation flowing   and not get caught out that sort of fear of  not knowing whether to make a jump or not   or take a big commitment. We drive that  flexibility approach and that's working. It's not easy at the moment, it's a difficult  climate. And I think from the AI perspective,   there's some real challenges around the  hype. Everyone is talking about it. I   did a presentation at our UK kickoff around, I  don't know if anyone remembers Generation Game,   in fact, you probably won't because it's  a very British program. But fundamentally,   it's a program where you put up a number,  they used to have to remember a number of   different items, and every item they'd  remember, they'd get with a surprise.

So I put all of those up, these  pictures of things up and there   was a bed, some roller skates, a washing  machine, a fridge freezer, a teddy bear,   mattress. There was all sorts of random things  that you wouldn't go. And the thing that they all   had in common was they were all powered  by AI or AI enabled. And you're like,   how am I roller skates AI enabled? I really,  just don't need, I just need the wheels spin.   That's it. I don't need anything else.  you know, this is about when they stop. Well, yeah, and maybe what resistance they have  and maybe what maximum speed you're in, all sorts   of stuff. But I think that this has been  a real challenge for us and businesses is  

that you've got people who going, you've got to  adopt AI, you've got to adopt AI. And we've got   people who have come into us, customers that  come to us and go, we need to adopt AI. So I   had a conversation at a CDO summit recently  with a customer who basically said, I've been   given the role of chief AI officer, and I've been  asked to implement AI in the business by the CEO   but I don't know what I can roll out copilot,  which might tick that box, but he wants like   game changing AI without any use cases, without  any understanding of what data you want to have,   what problems you need to solve. There's some real  challenges and there's some real challenges around  

going to customers and doing AI proof of concepts  and pilots and programs that should drive value. But they look at the return on investment and  actually they're just not there because running   AI is expensive especially if you're building  large complex things. Or we've got a number of   customers that have come to us and they've come  to us with specific use cases, but they just don't   have the data and the quality of data to back  that up. And I think within the AI landscape,   this is one of the biggest challenges. The  co-pilots are absolutely brilliant and they   get adopted and they should just be adopted and  we need to roll out and train people and get them   to adopt those. But what I call the game changing  AI, the stuff that's unique to us in each business   that needs some thought, needs that quality data  isn't just plug and play. It is, let's actually  

think about what we're to build, what we're going  to achieve, how much it's going to cost to run.   And we can't be looking at it in a big challenge.  You can't be looking at it, in my opinion,   like a way to trim down people. It's not a way,  should not be replacing people, in my opinion.   It should be augmenting and improving productivity  and improving what we do and the outcomes of what   we do, but not it shouldn't be looked at as a  cost reduction. And that's a challenge. That's   a real challenge. Yeah, I completely agree.  And I think the one thing I'd add to that,  

because it's a conversation we're having  with lot of partners right now and customers,   is the fact that you start with copilot,  right? And you essentially look to push   copilot as far as you can go from an agentic  standpoint and say, what can I get out of this? And I think the thing we are seeing is it's so  powerful, just like that researcher capability   that Fede mentioned it can do so much for you  before you have to take that next step into   more enhanced AI services. I think it's great to  hear you mention that and validate that because   that's really how we are seeing our customers and  partners maximize their success. Yeah, absolutely.   You see headlines all the time, but I saw a  headline yesterday, the day before 80 % of AI   projects are failing. And I think that's because  no one's setting them up for success. The real big   push is and we've had a couple of POCs we've put  out that actually would have driven real value,   but haven't gone through the right governance,  haven't gone the right process before we get   there. One, we couldn't roll out because of  ethical usage of data. We had a really good  

use case to actually help individuals not  drop out of courses, educational courses.   Really powerful use case, but ethically,  were we using the data in the right way? They hadn't approved and signed up for the  data to be used in that right way and also   who was going to go and have those conversations.  So they hadn't thought about the whole process. I   think governance, when you're trying to roll out  things beyond copilot, mean, copilot still needs   a lot of adoption and governance. There's  a lot of security risks around it, making   sure that you're not exposing it to the wrong  people. had examples, sorry I'm babbling, but   we had examples of when copilot first came out, we  had employees, I won't mention any names, but some   employees that were saying, oh, we use it for put  the code in to help us write our code. We're like,  

no, no, no, no, you can't do that. You need to be  on an internal Azure one. So there's all sorts of   interesting challenges with AI. It's opening  a whole new world of arguably productivity,   but pain as well of security and management  of data and quality of data and governance   and ownership and all of the stuff that I frankly  have been banging on for 18 years, but no one's   been listening. So yeah, we're finally there.  We're finally talking about data quality. We're   finally using Purview to...to drive customers  and it's a conversation we have all the time.  

It's preparing them for kind of, I'm going to  keep going game changing AI. But you know, the   stuff that's really going to make the difference  in my opinion, the stuff that you can uniquely   identify yourselves with as a client. And along  what you were saying, Martyn, in terms of security   and compliance, can you tell us a bit more about  what Telefónica Tech is bringing to the table? So we mentioned we have a cyber practice and  that's definitely a key part of our cloud story as   well. Everything we do has to be secure by design,  which is the tagline that we attach to everything   in cloud. But it's really fundamental, as Martyn  mentioned, with new technologies, especially AI,   where it's accessing a lot of data, those tools  and those guardrails have to be in place. And  

we're entering this new world of automatic  code creation. And we're enabling a lot of   developers that we'll suddenly start developing  applications. I'm still waiting for that moment   where we can really start building applications  just from a prompt. And then they're going to go   off and do all kinds of things. And we need  to have that security in place. So building   secure landing zones, following the CAF, using  the enterprise scale patterns becomes really   important. And then as we're starting to optimize  customers, there's a lot of drive to again,   to save money by using automation, by getting  self-service in place to customers that want to   spin up sandbox environments to do all kinds of  data research. we have customers that do those  

sort of trusted research environments and they  have to be really guarded well. And what we try   to do is leverage those patterns and technologies  and bring that to the wider enterprises as well. So we're taking best practices from specific  niche use cases and then trying to feed that   in as part of our core messaging around cloud  adoption. It's certainly challenging. I think  

it's been challenging for a while, but now we've  got new vectors that we need to be aware of and   make sure that we're taking that holistic view.  We're feeding that back into the strategy as well.   Strategy, no matter how much we talk about  cloud strategy, it won't go away. You still   need to be doing it. And it's something that  you think would have evolved over the years,   but just having a clear view of your cloud  security policy, setting yourself up with a   strong foundation is still the key to getting it  right. And that's what we try and help customers   do. And I think that's the story of being kind  of stronger together. The kind of data and AI  

practice, we've always very much focused on the  business outcomes and the value that we can drive   from data. And with Alex's team in cloud and with  the cyber team, we can really make sure that… the   customer environments are secure and set up as I  said by secure by design. And then the data and   AI team can be safe in the knowledge that what we  then build is securing it internally and helping   make sure the customers and their employees are  well-trained, well-managed and look after the   kind of platforms and the data that we put into  there. And I think from a governance perspective,   that has been a challenge I think from a data  platform perspective for the 18 years I've been   doing this, or 20, sorry, 22 years I've been doing  this. So, I think Microsoft have recently bought   out Perview, which I've talked, I think I touched  on earlier, and that's really helping bring data   governance to the forefront. And what AI is  doing is making customers really realize that   the data will be available to the masses, their  business data will be available to the masses   within their business, and they need to ensure  data is accurate and secure and trustworthy.

And that's leaning really well back into the story  with Purview to say, actually, we need to put   Purview and we need to put platform and we need  to make sure your data is secured through a kind   of sensible design. But we all know what's in it  and we have data owners. So what we've been doing   recently with a lot of our customers is starting  to talk about kind of data culture and data   products which is kind of an evolution of the data  mesh, if anyone's familiar with data mesh design.   And it's allowing businesses within the defined  security principles that Alex was talking about   earlier within cloud and the governance we can put  in place to actually start building their own data   solutions, own reports, their own analytics and  their own AI output. But it does take time and   effort to get that quality governance in place for  customers. And what's really nice is that AI is  

bringing that to the forefront and making us all  very aware of how important security governance   is. I'll just add as well, just to that, one of  things that I really liked what the Alfonico team   did, and I know some of the partners who had  a similar approach, security is embedded and   it's almost like the customers have to opt out if  they don't want certain security to be embedded   by default. And it just it's a small tweak, but  it just gets the customer, the customers really   think like, why wouldn't I want this? And if I  don't want this particular security solution, do   I have something alternative? It just needs to be  there every step of the way, because we know from   our perspective how paramount security is maybe  now more so than ever. It's just, really like that  

slight change in approach that Telefónica embedded  a little while ago, but because it just sets the   bar with customers where they really need to be.  And if they don't want to be, they kind of need to   really think hard, why not? And what is going  to suffer if they don't go, you know, if they   don't really secure their environment, whatever it  is, whichever aspect of it it is. Yeah. Yeah, no,   absolutely. I think we all agree like security  is just paramount now. It's table stakes.

You have to have it and we're continuing  to invest heavily in that. And we see our   partners that make security practices, you  know, a core component of their customer   offerings I would say are frequently  driving the highest growth. So it's   great to hear you all are focused on that area  as well. So maybe one final question here,   because I know we're about at time. How do  you see the role of hybrid cloud evolving?   And maybe as part of that even adaptive cloud  where we are really working to build a world   where our customers can leverage solutions across  multiple environments, hybrid, multi-cloud, Azure.

How do you see that evolving from your perspective  and what are your customers, what signals are   you getting from your customers there? Yeah, I  think the hybrid multi-cloud is really the new   norm because I think we've gotten from the cloud  first mentality a few years back where the larger   migrations were being done at scale. I think  there's been a step back from that and a bit   more of a mature approach to how you're setting  up your cloud strategy and leveraging the right   environment. And that creates a heavy complexity  for customers, which I think is why some of the,   maybe the pace has dropped a little bit around  just making sure that we're doing things right,   making sure that we've got control of our costs  and making sure that we understand what we're   going to get out of these investments in cloud.  Those decisions are taking a little bit more time. But absolutely, the hybrid multi-cloud is the  way forward. It's just now sorting out what   exactly do you need. I'm sure Martyn can talk a  bit about those sort of AI outcomes and use cases.  

And that's driving a new set of requirements into  that thinking and into that strategy. So how the   customers then sort of work out where we want to  do that. And it may be that there's things still   on-prem and in the data center and then there are  things in cloud. And then how do I get some common  

management around that, whether it's, you and  tools like Azure Arc and different options that   everyone's bringing out sort of help to bring that  world together. And I think that common control   plane and the cloud management platform, which I  think a few years ago we probably thought might   go away, but it's now sort of come back with a  bit more vengeance because there's real value   in now being able to manage multiple environments  and multiple clouds and on-premise data centers   through a single control plan and then optimize  your support and management costs around that. Yeah, it's a new sort of world in a way. obviously  with hypervisors being shook up and some of the   ball-corm acquisition that's made some real  noise around VMware has created a bit of a   land of opportunity for suppliers and Microsoft  within that as well. Look at AVS and that's   becoming a real candidate for even smaller type  of workloads that give customers more flexibility,   more opportunity. So the options of a vast and  I think that's the challenge for partners like  

us is to really step up into this space and  help translate what the hyperscalers and what   the vendors are all saying and what they can  offer and what they can do and then align that   to the customer's requirements and their use  case and their strategy and we kind of stitch   the thing together into an overall approach and  a solution and a service that really gives them   what they want in as fast a time as possible. I  think that's our challenge as much as anyone's. I guess from the AI and data perspective, mean,  really most of our workloads are sat in Azure. And   one thing we remember is that telling all of our  customers that cloud isn't necessarily the cheap   option. It may be the flexible option and it may  be the option that gives you the full scalability,   but it's not always going to be cheaper  if you're willing to run your on-premise   architecture for longer and sweat it a bit more  but when it comes to the world of data and AI,   typically stuff gets put in the cloud because  of the scalability, because of the flexibility   of it. But increasingly, we're having some  interesting conversations around machine   learning and where you may decide you have  very point models that need to be very low   latency. And you may need those kind of  at the edge or on-premise near machinery.

We've got some manufacturing customers that  want to have those kind of AI predictive   models for predictive maintenance, predictive  breakdowns closer to the machines where they   need sub-second kind of response times. So we  train the models in Azure and then we kind of   push the output of that into maybe a kind of  more local system. A lot of our customers are   still kind of playing with that idea. But I  think that's where the AI thing's going to   take us is a lot more stuff at the edge, a lot  more stuff kind of on your devices. You know,   we've seen it with, better not pick that device  up. But we've seen it with certain devices where,  

you know, they're pushing more and more stuff  within to your device. think I was chatting to   someone from Microsoft yesterday, day before last  week, around the Co-Pilot Plus PCs, where we're   pushing a lot of the AI functions back down to  the kind of device right in front of you, rather   than you having to submit it to the cloud and it's  come back. So I think that's all going to evolve   over time. again, as Alex said, making sure that  the right workloads, AI is an interesting one,   at the right point in the right place to support  a customer's needs which may be on their device,   it may be on their own data center, or might  be next to a particular hardware they've got.

So I think it's going to be fascinating how it all  pans out. But yeah, it still definitely all in on   this year. Well, thank you so much because  you've shared not only about your personal   and individual journeys along this Kyri Cloud,  cloud and now AI transformation, but also the   evolution of Telefónica Tech from Telco to Teco.  And of course, thanks to Anna for bringing this   story up to life and letting us share it with our  community. And Martyn and Alex, really appreciate  

you staying up late today in your UK time zone  to chat with Adam and I. Thanks very much, guys,   for the opportunity. We appreciate it. Yeah,  thank you. Thank you all. Much appreciated. We hope you enjoyed today's episode.  Stay tuned for more insights and stories  

from Microsoft's data center optimization team.   Be sure to stay connected at dco.microsoft.com  or wherever you get your favorite podcasts.

2025-05-30 04:58

Show Video

Other news

Nvidia Shrugs Off China Concerns With Upbeat Forecast | Bloomberg Technology 2025-05-30 11:26
What's new in Flutter 2025-05-27 08:21
Varun Chhabra, Dell & Kari Briski, NVIDIA | Dell Technologies World 2025 2025-05-27 02:08