Google Cloud Next '24 | Siki Giunta & Alan Flower | HCLTech

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Siki Giunta

EVP, CloudSMART, Industry Cloud Consulting, Google Ecosystem Unit

HCLTech

Alan Flower

EVP & Head, Cloud Native & AI Labs

HCL Technologies

Gen AI unleashed: Transforming industries through tailored tech solutions

Having sped past the speculation and exploring phases, artificial intelligence is now nearing maturity. From the manufacturing to telecom and life sciences fields, companies are taking steps to implement gen AI in aller valuable operational area possible.As the gen AI wave sweeps through, how is the tech poised to overhaul industries and drive efficiency, productivity and profitability?“We have a great solution with the Cloud Native Labs; we just funnel all our requests to one spot and [they] help us understand the magic use cases,” said Siki Giunta (pictured, left), executive vice president and head of CloudSMART and industry cloud consulting at HCL Technologies Ltd

play_circle_outline Exploring the Riveting Live Coverage of Google Cloud Next & Its Thriving Ecosystem Partnerships

play_circle_outline Focus on the impact and potential of industry-specific AI solutions

play_circle_outline Highlighting HCLTech's AI Force platform and its role in automating software development

play_circle_outline Importance of a hybrid multi-cloud approach for AI deployments

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Siki Giunta & Alan Flower | HCLTech

Siki Giunta

EVP, CloudSMART, Industry Cloud Consulting, Google Ecosystem Unit HCLTech

Alan Flower

EVP & Head, Cloud Native & AI Labs HCL Technologies

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(bright music)

>> Hello, everyone, and welcome back to theCUBE's Live coverage of Google Cloud Next, here in beautiful Las Vegas, Nevada. I'm your host Rebecca Knight, along with my co-host, John Furrier, also, Rob Stretchay and Savannah Peterson.

>> Yeah. >> On with us. This has just been a great conference. We're nearing the end of day two, and one of the things that is just so striking

are these partnerships. >> Yeah.

>> And the strategic alliances that Google Cloud.

>> Yeah, HCLTech's coming on. Now, we're going to have a great conversation, and what's really exciting is that they're at the forefront of accelerating solutions, and it's unfolding right in front of us. Also, one of the guests has been a CUBE alumni going back to 2011.

>> Yes. >> Okay, OG.

>> Oh, let's introduce her, let's meet... (laughs)

>> Okay, let's go, go ahead. >> Siki Giunta, she is the Executive Vice President, Cloud Smart Industry Cloud Consulting Google Ecosystem Unit at HCLTech. Thank you so much for coming on the show.

>> Thank you.

>> And Alan Flower is the EVP and Head of Cloud Native and AI labs at HCLTech.

Thank you both. >> Lovely to join you today.

>> Yes, and, Siki, again, distinguished CUBE alumni who remembers when it all got started.

>> Yeah, I remember it was tiny. It was a laptop, and the camera, and, now, look at the spread of the production.

>> Yeah, it's fun, I remember we were actually talking about cloud at that time, and we were, actually, talking about some of the same things now, but it's gotten so big. It's now the business model, and I think the AI wave is here for sure. We just had a previous guest on from Google who runs all the container stuff, 10 years of Kubernetes.

>> Yeah. >> Okay, so all right. Things are moving along. Now, the biggest problem everyone's trying to solve is what's my solution look like? How does Gemini, and Google's case, AI, impact? How do I infuse that into it, and how can I get it deployed? As with use cases that are identified, then there's the what does it mean in the future? So help us understand where your customers are at right now because as vendors bring stuff to the market, we're seeing a lot of announcements here, customers are in a different spot.

>> Siki: Yeah.

>> Especially in the enterprise.

>> Yes, we have a great solution with the Cloud Native Lab. We just funnel all our requests to one spot and help us really understand the magic use cases, and, now, we have a year of experience, and Alan will give you a lot of really good insight, but we, I think, have decided that the upper layer of AI, the industry specific, is the one that is going to impact the business the most. There are some horizontal use cases, We are, you know, taking to market. The last thing is we partner with Google on Gemini and in the floor, we got in, you know, manufacturing solutions. We are looking after telecom and life science. These are the area where we have got clients that went to see Alan, and they want to do it, and, now, we are ready to just prioritize and industrialize.

>> Alan, you got the keys to the kingdom. You got the AI Labs, all the actions coming to you. What are you seeing? Tell us some stories. Give us the update.

>> Well, look, it's quite remarkable, isn't it, really? I think in the space of barely a year, we've seen our clients go from kind of tepid kind of exploration, maybe looking at some horizontal use cases, but then rapidly gaining confidence. Maybe they've deployed GenAI into the software engineering domain, for example. They rapidly get confidence, then they move on to how is this going to transform my business? So as Siki says, what we've seen in barely a year is these clients now expecting to do significant business transformation enabled by GenAI.

>> Is there ever any overconfidence? I mean, as you said, they've seen some immediate benefits which have inspired them to do more, but is there ever a time when it's...

>> It's a good question, isn't it? Because we often joke that chatGPT, best sales tool the industry

has ever developed, right? >> Yes.

>> And it does give you a lot of confidence,

most of which is justified. >> Sure, sure.

>> So it's done a very good job-

>> John: A lot of enthusiasm, for sure.

>> Huge amount. >> Double the enthusiasm.

>> Huge amount of enthusiasm and the rest, so the remarkable thing is, right, we've done well over 1,000 workshops with clients now around the globe. So we think we've got pretty good insight into what those use cases are. Fundamentally, it's the business leadership.

>> Yes. >> That are driving GenAI. It's not the technology estate. Business leaders very rapidly saw the business, you know, potential. Fundamentally, you know, they're thinking about improvements in productivity, quality, velocity, right? That brings a significant impact to their business, hence they're coming to us. They know the use cases. They think they know where they want to deploy GenAI. They need a partner like HCLTech to accelerate the journey and build the solution.

>> You know, that reminds me of that famous Steve Jobs video where he says, "It's not about the technology trying to find a a solution.

You got to work backwards." >> Yeah.

>> And I think the recognition that we're seeing is similar is that people see the bridge to the future.

>> Yes. >> But they got to build it. It's like it's not built yet.

>> I'm building on Rebecca. It's a double-edged sword because, sometimes, people are very confident, and then the build model, and these are hallucinating to them straight away, and the problem is that they retrench very fast, and they lose credibility with the business. The other big area, especially, for instance, in financial services, they need to have things like 99% governance and security and then the right country. So there is a little bit of a hesitation on things that impact private information, money, and everything to go, but anything that is process acceleration, like I have to do a loan applications, that things will go fast. It just... I give my advice is just understand what the business need if I talk to IT, and I talk to business, say, just temper your enthusiasm. This is not a magic wonder of things happen, and the data is not there. Not all the data is there, and that's a big challenge.

>> So, Alan, you got all the use case, thousands of workshops. Okay, business leaders see it. We got to get to the future. The wave's here, it's a no break. Kind of like the web, it's coming. We got to get there, start tooling up. What happens next? What's the progression, and what are some of the pre-work requisites that need to be in place

to go to the next level? >> Uh-huh.

>> Take us through a little bit of the journey-

>> It's a really good question, right? So we've seen this rapid acceleration of client journeys. They've gone from we've got a good idea, let's build a POC, let's build a minimal viable product to don't switch it off. All right? (Rebecca laughs) We see value-

>> John: Because they like it, and it's working.

>> Yeah. >> Yes.

>> And we've got plenty of examples where we've built, let's call them POCs for clients.

>> John: Yeah.

>> They asked to experiment maybe for a few weeks. Turns out, the whole workforce starts using, and then two weeks later, the client is saying, "Don't switch it off. We've got value already," but the challenge for the industry, quite frankly, is clients are now moving so rapidly.

>> Yes. >> Is the industry ready to take these solutions into scaled production?

>> Yes. >> All sorts of challenges. A very good example, of course, is in traditional IT, the way we operate solutions.

>> Yes. >> It tends to be quite static. We sign these things called SLAs that defines our behavior for the next five years, for example. With GenAI flavored solutions, it's an organic infrastructure. Someone has to be looking at the accuracy of the solution, the underlying models. Who's going to decide to replace this model with a better one tomorrow? Who's going to make sure that we keep control of the cost of executing some of these models as well? So it's become a very complex landscape as we now contemplate what production looks like.

>> It's like the nexus of FinOps meets system engineering,

DevOps, SecOps. >> Yes.

>> And then (laughs) IT. >> And by the way-

>> All rolled into one.

>> This magic person does not exist. (Rebecca laughs) It does not. So you need to have a very coordinated type of skills, skills that can talk to the business, and we are all chasing the same skills, the cloud provider, our partners, us, and I think the things that all my client says, scale means around the globe is who's going to support it and how can the business learn how to use it and be confident in there? And I know that everybody thinks that GenAI is going to take the job of everybody. I say no. We are going to move up the ladder and change our skills to be there because, you know, as automation and GenAI is going to make the business better. It's just we have to change the workforce, and we have to have a extremely good governance, I think.

>> Right, so going back to that, I mean, it really will take entirely different kinds of skills, entirely different kinds of analytical thinking. We've talked a lot on this show at Google Cloud Next about how we're going to see this explosion in creativity because we've reduced the toil and automating so much, so many tasks, but you also brought up an excellent point, Alan, which is is the industry ready for how fast clients want to move? So how are you walking through, your customers through these very difficult questions?

>> Well, I take the view that all of us, it doesn't matter which business we work within, there's a growing expectation from clients, stakeholders, peers, managers, leaders that we now all start to leverage and take advantage of this productivity gain. It applies to us as just like any other business, of course. Now, a very good example of where we're taking advantage of that is we've recently launched something called AI Force. Now, AI Force is really HCLTech taking the lead, taking the industry to the next stage of application of GenAI. We're all very comfortable, for example, with the use of GenAI in the software development realm. For many people, the journey starts there, doesn't it?

>> Yeah. >> You download a copilot. Well, our clients expect us to go well beyond that. We're expected now to use GenAI to really automate and enhance the entire software development lifecycle. So you could look at AI force, for example, as a change of posture to an AI-led delivery model.

>> Is AI Force a platform or a methodology? Can you explain what it is?

>> It is an IP that we use to deliver our code transformation for clients, and it's a little bit of an end-to-end. You generate code depending on which model.

>> So it's technology, too. >> Yes.

AI is technology. >> Yeah.

>> You have to do that, then you test it. There is a good element of security because when you auto generate the code, you could insert a lot of security liability in it. So we have that, we have a cost model in there. It's used in conjunction with our clients-

>> It's how you guys execute your delivery.

>> Yes, yes. >> Absolutely.

>> Siki: And the clients, too.

>> And how do they get involved? Is it part of every engagement or does it have a certain pipeline for criteria?

>> Well, so we've already started to deploy it.

>> Yeah. >> Okay. So clients are already seeing very significant gains. We ran a session here today, for example.

>> Yes. >> Where we actually shared some of the productivity gains, and on some of our projects, we've recorded an excess of 60, 70% productivity acceleration through the use of AI Force. So we've already convinced ourselves, right? We already have clients using this, but don't forget, of course, that HCLTech has been building AI-enabled technologies and solutions for over a decade, right?

>> Yeah, yeah. >> We are the industry's, of course, preferred engineering partners.

>> Mmm, yeah. >> So this is a landscape that we know particularly well. So we've just taken, you know, the opportunity not just to consume copilots off the shelf. Anyone can do that, but we've built this entire platform and framework to ensure that we can deliver engineering projects now with greater productivity, better quality, and, of course, we can take features to market

for our clients. >> Faster.

>> Far quicker than ever before.

>> Siki, you do the ecosystem side of HCLTech as well. With Google, they're very open. We have great stuff, but, also, we work with other environments. The Clouds Edge is huge. We mentioned that briefly. As multi-vendors come into the play here.

>> Yes. >> That becomes a big part of maybe air force, I mean AI Force and the tooling. What's the ecosystem involvement? What is there, you just join? How do you... Is it part of the process or...

>> I think, you know, Alan and I.

>> John: Yeah.

>> We know that is a multi-cloud, hot, private, and-

>> Multimodal. (Rebecca laughs)

>> It's a mold that is going to be like that. At the moment, the more disciplined clients pick a platform of choice, and they develop models on that, but I can tell you there are models where chat is better than Gemini, and that Gemini is strong. It is like, you know, the beginning of cloud.

>> Yeah. >> When you had it, it's going to be that way, and I find that the ecosystem partner, they're all picking their own lanes, and for instance, in the case of Google, everything that we get in Gemini 5, in some, 1.5, they've been using internally at Google for a long time.

>> Yeah. >> And, now, they put it on their strength is search, and, obviously, Microsoft as a, you know, a different value proposition is more, you know, users-friendly and things like that. Our job is to navigate the clients to get the best bet.

>> You got the industries. You got all the interactions and engagements. We've been hearing, I'd love to get your thoughts, if you hear the same thing or react to it, we're hearing here on "theCUBE" and our other events, optionality is job one, and this new design, because they saw the cloud game, if they over rotate into a cloud even outside of the core compute stuff, the multi high-level services, if they didn't actually need them and AI stayed with the more optional approach.

>> Yeah. >> Do you hear the same thing?

What's your reaction? >> Yeah, I think that, fundamentally, AI is a hybrid multi-cloud journey.

>> Yeah, yeah. >> You've heard that before,

right? >> Yeah.

>> It's exactly the same. Clients expect to be able to run their AI workloads wherever they need to run, and don't forget AI moves to the data not the other way around. So we see interest in on-prem deployments. We interest in multi-cloud deployments, and some of the announcements, of course, that we heard yesterday play really strongly to this. For example, Google distributed cloud.

>> Yeah. >> That ability to run Gemini in my data center aligns perfectly to what clients expect.

>> Yeah, and then they got the new process with 130 miles in Vertex is interesting, too.

>> Yeah. >> And you got Gemini 1.5 is looking really strong.

>> I have to tell you the story. Last year, and, sometimes, I'm baffled about my Googler, and I tell him why you make it so complicated, and I tell to TK, I was in line to do my hackathon on Vertex and bar it at the time, right? It took me long to line up than actually build the entire system, and it's crazy. It is actually very easy. The problem that we, in the tech world, we are actually making it more complicated, and everybody thinks (John laughs) that AI is just Google and Microsoft.

>> Rebecca: Yeah.

>> Oh, there, Adobe does a great job

for anything that is text. >> Of course.

>> And then SAP has a lot of AI in their system. So ServiceNow for... So again, it has to be a multi-environment because the business has multi-partners.

>> It's got to be simple, too. >> Ah, yes.

>> It's like the old enterprise joke. How do enterprise solutions solve problems?

By making it more complex. >> Yes. (John and Siki laugh)

>> I think this is a remarkable thing, right? Because we've moved on so much in the last year or so that we've got this point where GenAI is fundamentally consumable, but it's remarkably easy to build solutions on it, isn't it? As a general guide, I mean, we often struggle to spend more than four or five weeks building a complete solution. A really good example of one we did here in the States with a healthcare provider is we now have a GenAI-enabled clinical advisor. If you are a medical professional.

>> Yeah. >> You're struggling to spend enough quality time with your patients.

>> Yeah. >> We've now enabled GenAI to give guidance to clinicians, treatment plans, other advantages, and this is a really good example where we leverage a technology like Gemini. We enhance it with more accurate data from the client's estate. We blend those together into a specialized solution, and if you think about some of the inherent advantages that GenAI offers from a conversational perspective, our clinical advisor, you can ask it to perform the role of a cardiologist. You can ask it to perform the role of a diabetes specialist. It's the same application.

>> Right, whereas medicine is so siloed.

>> Yeah. >> In real life that it's taking away those things. I'm curious about how your relationship with clients has changed now that, as you were talking about earlier, you're finding all these new ways for them to be more productive. Are you helping them and advising them on, "Oh, you can make this a new source of revenue. This could be a new business model for you." Are you advising them in those ways?

>> Absolutely, and, you know, at HCLTech, we've been vertical aligned and domain because our engineering, if you build, you know, large scale and, you know, system for a client, you need to know that client, but the other interesting thing is the clients themselves are now realizing that they have this amazing value that is their data, and then they're starting up to understand, "Oh, if I use it there, I can win on a competitive venture. Oh, if I use it there I can enlarge,

you know, my marketing." >> Yeah.

>> And it's phenomenal to us to see how fast they get on understanding what's the potential, as well, in our strategy, as though we have a very conscious, you know, charter to create ethical AI and to be very mindful of the creation of IPs and to be very mindful that we are dealing

with data of clients. >> Yeah.

>> And this is a... We all have to govern well, and, you know, the European community has put out very strong directions and everything. So we do global clients. You have to understand how to deal with the dimension

of that as well. >> Well, also, you mentioned the value, the time to value, that's a cliche in the industry. To your POC model, you can get really quick proof points.

>> Yes. >> And those little wins that you do internally with your data also show the boss, "Hey, we got momentum.

Get more budget." >> Yes.

>> Right, so you're starting to see budgets. Dave Vellante reported on the ETR spending data that budgets, now, are being allocated on AI. A year ago, they're being allocated, stolen from other budgets. Now, it's like, "Okay, we see a little bit of wins."

>> Budget isn't a problem for anyone, quite frankly. I mean, one of the things that we've seen, right, we use our Cloud Native and AI Labs uniquely as a place where our clients can come in for a trusted advisor type relationship, to your point, we help them understand what's going to work best for them, but it's also a place of innovation and acceleration, but the remarkable thing that we've seen is we'll do an engagement with a client. We'll build, call it a POC, and the client then sticks to the lab thereafter, right? It's really interesting. Once the client sees value, the ideas just keep flowing.

>> Right, right. >> You know, I think the angle that your product model is genius because that gets them into the discovery side

of the solution, okay? >> Yeah.

>> And it's not your old-school IT transformation playbook.

>> Alan: Yeah.

>> It's we're building it with you, and I think that speeds the process up, and that is actually... You're building the bridge to the future with them, and that's part of the engagement I think people need the most.

>> And in GenAI is 100% value creation, the business lever that they want to have. There is some cost reductions, but in the long run, the the one that they really go for is exactly what you said, "How is it going to change my business? How I'm going to accelerate?" We have, as an industry, I don't think we have been able to capture very well, diminished cost and business value,

but here. >> Yeah.

>> In this technology, we really need to learn how to do it for our clients.

>> Excellent. >> Siki, great to have you on. We could go for another hour.

>> I know. (laughs) >> Just on your... We should do a whole segment on the customer stories.

>> Yes. >> Yeah.

>> Because that's real data that you could share with the field and would get more motivation to get the confidence up.

>> Rebecca: And elicit the best practices.

>> Yeah, the confidence. >> What we know, yeah.

>> Confidence is critical. >> Yeah.

>> Enthusiasm, check. Everyone's enthused. (Rebecca laughs) Confidence is a great point, and we'll have to have you back on.

>> Yeah. >> To end the segment, I'll give you both the final word, final statement. What's the big relationship with Google, how is that helping HCL, and what's the benefits to customers? What should they know about?

>> So HCLTech was probably the first partner that all in on Google Cloud when Google was still very small and a strong challenger. So we have a long-lasting relationship, and HCLTech, as engineers, we like to code on Java. It's a very natural environment for us, and there is a little bit a geek affiliation.

>> Yes, yes, yes. (laughs) >> A lot of that, and we have a very open relationship. We invest on the new releases, and we do a lot of engagement in the market. It is pleasant to work with. They're very... They are challengers, so it's always fine to win

as you're challenging. >> Yeah.

>> They have good AI, too. >> Oh, yeah, no, this, I told to TK, "Now, the pack is getting your way. You just got to push it through because it's enterprise."

>> Yeah. >> They got the right formula.

>> Yeah. >> And it's a good point. I mean, I think Google have done a particularly good job at making GenAI consumable, and that's really important to our clients. They like that ease of consumption.

>> Yeah. >> Yeah

>> And, clearly, you know, from a a Gemini perspective, all of the capability that we expect is there. One thing that I wouldn't want to overlook though is a lot of clients have got a very strong interest

in open source approaches. >> Yes, a lot.

>> So the ancillary availability of Gemini, for example, as an open source, you know, model approach does actually resonate really strongly with clients who favor that opportunity, too.

>> Yeah, yeah. >> Love the AI Force. Love the AI Labs. It's a great formula, congratulations, and it's just getting started.

>> Yes! >> Moving quickly.

>> Thanks for coming on the show.

>> All right. >> Thanks, thank you, guys.

>> Yes. >> Thank you. Thank you for having us.

>> I'm Rebecca Knight for John Furrier. Stay tuned for more of theCUBE's live coverage of Google Cloud Next. You are watching "theCUBE", the leading source for enterprise tech news. (bright music)

Siki Giunta & Alan Flower | HCLTech

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(bright music)

>> Hello, everyone, and welcome back to theCUBE's Live coverage of Google Cloud Next, here in beautiful Las Vegas, Nevada. I'm your host Rebecca Knight, along with my co-host, John Furrier, also, Rob Stretchay and Savannah Peterson.

>> Yeah. >> On with us. This has just been a great conference. We're nearing the end of day two, and one of the things that is just so striking

are these partnerships. >> Yeah.

>> And the strategic alliances that Google Cloud.

>> Yeah, HCLTech's coming on. Now, we're going to have a great conversation, and what's really exciting is that they're at the forefront of accelerating solutions, and it's unfolding right in front of us. Also, one of the guests has been a CUBE alumni going back to 2011.

>> Yes. >> Okay, OG.

>> Oh, let's introduce her, let's meet... (laughs)

>> Okay, let's go, go ahead. >> Siki Giunta, she is the Executive Vice President, Cloud Smart Industry Cloud Consulting Google Ecosystem Unit at HCLTech. Thank you so much for coming on the show.

>> Thank you.

>> And Alan Flower is the EVP and Head of Cloud Native and AI labs at HCLTech.

Thank you both. >> Lovely to join you today.

>> Yes, and, Siki, again, distinguished CUBE alumni who remembers when it all got started.

>> Yeah, I remember it was tiny. It was a laptop, and the camera, and, now, look at the spread of the production.

>> Yeah, it's fun, I remember we were actually talking about cloud at that time, and we were, actually, talking about some of the same things now, but it's gotten so big. It's now the business model, and I think the AI wave is here for sure. We just had a previous guest on from Google who runs all the container stuff, 10 years of Kubernetes.

>> Yeah. >> Okay, so all right. Things are moving along. Now, the biggest problem everyone's trying to solve is what's my solution look like? How does Gemini, and Google's case, AI, impact? How do I infuse that into it, and how can I get it deployed? As with use cases that are identified, then there's the what does it mean in the future? So help us understand where your customers are at right now because as vendors bring stuff to the market, we're seeing a lot of announcements here, customers are in a different spot.

>> Siki: Yeah.

>> Especially in the enterprise.

>> Yes, we have a great solution with the Cloud Native Lab. We just funnel all our requests to one spot and help us really understand the magic use cases, and, now, we have a year of experience, and Alan will give you a lot of really good insight, but we, I think, have decided that the upper layer of AI, the industry specific, is the one that is going to impact the business the most. There are some horizontal use cases, We are, you know, taking to market. The last thing is we partner with Google on Gemini and in the floor, we got in, you know, manufacturing solutions. We are looking after telecom and life science. These are the area where we have got clients that went to see Alan, and they want to do it, and, now, we are ready to just prioritize and industrialize.

>> Alan, you got the keys to the kingdom. You got the AI Labs, all the actions coming to you. What are you seeing? Tell us some stories. Give us the update.

>> Well, look, it's quite remarkable, isn't it, really? I think in the space of barely a year, we've seen our clients go from kind of tepid kind of exploration, maybe looking at some horizontal use cases, but then rapidly gaining confidence. Maybe they've deployed GenAI into the software engineering domain, for example. They rapidly get confidence, then they move on to how is this going to transform my business? So as Siki says, what we've seen in barely a year is these clients now expecting to do significant business transformation enabled by GenAI.

>> Is there ever any overconfidence? I mean, as you said, they've seen some immediate benefits which have inspired them to do more, but is there ever a time when it's...

>> It's a good question, isn't it? Because we often joke that chatGPT, best sales tool the industry

has ever developed, right? >> Yes.

>> And it does give you a lot of confidence,

most of which is justified. >> Sure, sure.

>> So it's done a very good job-

>> John: A lot of enthusiasm, for sure.

>> Huge amount. >> Double the enthusiasm.

>> Huge amount of enthusiasm and the rest, so the remarkable thing is, right, we've done well over 1,000 workshops with clients now around the globe. So we think we've got pretty good insight into what those use cases are. Fundamentally, it's the business leadership.

>> Yes. >> That are driving GenAI. It's not the technology estate. Business leaders very rapidly saw the business, you know, potential. Fundamentally, you know, they're thinking about improvements in productivity, quality, velocity, right? That brings a significant impact to their business, hence they're coming to us. They know the use cases. They think they know where they want to deploy GenAI. They need a partner like HCLTech to accelerate the journey and build the solution.

>> You know, that reminds me of that famous Steve Jobs video where he says, "It's not about the technology trying to find a a solution.

You got to work backwards." >> Yeah.

>> And I think the recognition that we're seeing is similar is that people see the bridge to the future.

>> Yes. >> But they got to build it. It's like it's not built yet.

>> I'm building on Rebecca. It's a double-edged sword because, sometimes, people are very confident, and then the build model, and these are hallucinating to them straight away, and the problem is that they retrench very fast, and they lose credibility with the business. The other big area, especially, for instance, in financial services, they need to have things like 99% governance and security and then the right country. So there is a little bit of a hesitation on things that impact private information, money, and everything to go, but anything that is process acceleration, like I have to do a loan applications, that things will go fast. It just... I give my advice is just understand what the business need if I talk to IT, and I talk to business, say, just temper your enthusiasm. This is not a magic wonder of things happen, and the data is not there. Not all the data is there, and that's a big challenge.

>> So, Alan, you got all the use case, thousands of workshops. Okay, business leaders see it. We got to get to the future. The wave's here, it's a no break. Kind of like the web, it's coming. We got to get there, start tooling up. What happens next? What's the progression, and what are some of the pre-work requisites that need to be in place

to go to the next level? >> Uh-huh.

>> Take us through a little bit of the journey-

>> It's a really good question, right? So we've seen this rapid acceleration of client journeys. They've gone from we've got a good idea, let's build a POC, let's build a minimal viable product to don't switch it off. All right? (Rebecca laughs) We see value-

>> John: Because they like it, and it's working.

>> Yeah. >> Yes.

>> And we've got plenty of examples where we've built, let's call them POCs for clients.

>> John: Yeah.

>> They asked to experiment maybe for a few weeks. Turns out, the whole workforce starts using, and then two weeks later, the client is saying, "Don't switch it off. We've got value already," but the challenge for the industry, quite frankly, is clients are now moving so rapidly.

>> Yes. >> Is the industry ready to take these solutions into scaled production?

>> Yes. >> All sorts of challenges. A very good example, of course, is in traditional IT, the way we operate solutions.

>> Yes. >> It tends to be quite static. We sign these things called SLAs that defines our behavior for the next five years, for example. With GenAI flavored solutions, it's an organic infrastructure. Someone has to be looking at the accuracy of the solution, the underlying models. Who's going to decide to replace this model with a better one tomorrow? Who's going to make sure that we keep control of the cost of executing some of these models as well? So it's become a very complex landscape as we now contemplate what production looks like.

>> It's like the nexus of FinOps meets system engineering,

DevOps, SecOps. >> Yes.

>> And then (laughs) IT. >> And by the way-

>> All rolled into one.

>> This magic person does not exist. (Rebecca laughs) It does not. So you need to have a very coordinated type of skills, skills that can talk to the business, and we are all chasing the same skills, the cloud provider, our partners, us, and I think the things that all my client says, scale means around the globe is who's going to support it and how can the business learn how to use it and be confident in there? And I know that everybody thinks that GenAI is going to take the job of everybody. I say no. We are going to move up the ladder and change our skills to be there because, you know, as automation and GenAI is going to make the business better. It's just we have to change the workforce, and we have to have a extremely good governance, I think.

>> Right, so going back to that, I mean, it really will take entirely different kinds of skills, entirely different kinds of analytical thinking. We've talked a lot on this show at Google Cloud Next about how we're going to see this explosion in creativity because we've reduced the toil and automating so much, so many tasks, but you also brought up an excellent point, Alan, which is is the industry ready for how fast clients want to move? So how are you walking through, your customers through these very difficult questions?

>> Well, I take the view that all of us, it doesn't matter which business we work within, there's a growing expectation from clients, stakeholders, peers, managers, leaders that we now all start to leverage and take advantage of this productivity gain. It applies to us as just like any other business, of course. Now, a very good example of where we're taking advantage of that is we've recently launched something called AI Force. Now, AI Force is really HCLTech taking the lead, taking the industry to the next stage of application of GenAI. We're all very comfortable, for example, with the use of GenAI in the software development realm. For many people, the journey starts there, doesn't it?

>> Yeah. >> You download a copilot. Well, our clients expect us to go well beyond that. We're expected now to use GenAI to really automate and enhance the entire software development lifecycle. So you could look at AI force, for example, as a change of posture to an AI-led delivery model.

>> Is AI Force a platform or a methodology? Can you explain what it is?

>> It is an IP that we use to deliver our code transformation for clients, and it's a little bit of an end-to-end. You generate code depending on which model.

>> So it's technology, too. >> Yes.

AI is technology. >> Yeah.

>> You have to do that, then you test it. There is a good element of security because when you auto generate the code, you could insert a lot of security liability in it. So we have that, we have a cost model in there. It's used in conjunction with our clients-

>> It's how you guys execute your delivery.

>> Yes, yes. >> Absolutely.

>> Siki: And the clients, too.

>> And how do they get involved? Is it part of every engagement or does it have a certain pipeline for criteria?

>> Well, so we've already started to deploy it.

>> Yeah. >> Okay. So clients are already seeing very significant gains. We ran a session here today, for example.

>> Yes. >> Where we actually shared some of the productivity gains, and on some of our projects, we've recorded an excess of 60, 70% productivity acceleration through the use of AI Force. So we've already convinced ourselves, right? We already have clients using this, but don't forget, of course, that HCLTech has been building AI-enabled technologies and solutions for over a decade, right?

>> Yeah, yeah. >> We are the industry's, of course, preferred engineering partners.

>> Mmm, yeah. >> So this is a landscape that we know particularly well. So we've just taken, you know, the opportunity not just to consume copilots off the shelf. Anyone can do that, but we've built this entire platform and framework to ensure that we can deliver engineering projects now with greater productivity, better quality, and, of course, we can take features to market

for our clients. >> Faster.

>> Far quicker than ever before.

>> Siki, you do the ecosystem side of HCLTech as well. With Google, they're very open. We have great stuff, but, also, we work with other environments. The Clouds Edge is huge. We mentioned that briefly. As multi-vendors come into the play here.

>> Yes. >> That becomes a big part of maybe air force, I mean AI Force and the tooling. What's the ecosystem involvement? What is there, you just join? How do you... Is it part of the process or...

>> I think, you know, Alan and I.

>> John: Yeah.

>> We know that is a multi-cloud, hot, private, and-

>> Multimodal. (Rebecca laughs)

>> It's a mold that is going to be like that. At the moment, the more disciplined clients pick a platform of choice, and they develop models on that, but I can tell you there are models where chat is better than Gemini, and that Gemini is strong. It is like, you know, the beginning of cloud.

>> Yeah. >> When you had it, it's going to be that way, and I find that the ecosystem partner, they're all picking their own lanes, and for instance, in the case of Google, everything that we get in Gemini 5, in some, 1.5, they've been using internally at Google for a long time.

>> Yeah. >> And, now, they put it on their strength is search, and, obviously, Microsoft as a, you know, a different value proposition is more, you know, users-friendly and things like that. Our job is to navigate the clients to get the best bet.

>> You got the industries. You got all the interactions and engagements. We've been hearing, I'd love to get your thoughts, if you hear the same thing or react to it, we're hearing here on "theCUBE" and our other events, optionality is job one, and this new design, because they saw the cloud game, if they over rotate into a cloud even outside of the core compute stuff, the multi high-level services, if they didn't actually need them and AI stayed with the more optional approach.

>> Yeah. >> Do you hear the same thing?

What's your reaction? >> Yeah, I think that, fundamentally, AI is a hybrid multi-cloud journey.

>> Yeah, yeah. >> You've heard that before,

right? >> Yeah.

>> It's exactly the same. Clients expect to be able to run their AI workloads wherever they need to run, and don't forget AI moves to the data not the other way around. So we see interest in on-prem deployments. We interest in multi-cloud deployments, and some of the announcements, of course, that we heard yesterday play really strongly to this. For example, Google distributed cloud.

>> Yeah. >> That ability to run Gemini in my data center aligns perfectly to what clients expect.

>> Yeah, and then they got the new process with 130 miles in Vertex is interesting, too.

>> Yeah. >> And you got Gemini 1.5 is looking really strong.

>> I have to tell you the story. Last year, and, sometimes, I'm baffled about my Googler, and I tell him why you make it so complicated, and I tell to TK, I was in line to do my hackathon on Vertex and bar it at the time, right? It took me long to line up than actually build the entire system, and it's crazy. It is actually very easy. The problem that we, in the tech world, we are actually making it more complicated, and everybody thinks (John laughs) that AI is just Google and Microsoft.

>> Rebecca: Yeah.

>> Oh, there, Adobe does a great job

for anything that is text. >> Of course.

>> And then SAP has a lot of AI in their system. So ServiceNow for... So again, it has to be a multi-environment because the business has multi-partners.

>> It's got to be simple, too. >> Ah, yes.

>> It's like the old enterprise joke. How do enterprise solutions solve problems?

By making it more complex. >> Yes. (John and Siki laugh)

>> I think this is a remarkable thing, right? Because we've moved on so much in the last year or so that we've got this point where GenAI is fundamentally consumable, but it's remarkably easy to build solutions on it, isn't it? As a general guide, I mean, we often struggle to spend more than four or five weeks building a complete solution. A really good example of one we did here in the States with a healthcare provider is we now have a GenAI-enabled clinical advisor. If you are a medical professional.

>> Yeah. >> You're struggling to spend enough quality time with your patients.

>> Yeah. >> We've now enabled GenAI to give guidance to clinicians, treatment plans, other advantages, and this is a really good example where we leverage a technology like Gemini. We enhance it with more accurate data from the client's estate. We blend those together into a specialized solution, and if you think about some of the inherent advantages that GenAI offers from a conversational perspective, our clinical advisor, you can ask it to perform the role of a cardiologist. You can ask it to perform the role of a diabetes specialist. It's the same application.

>> Right, whereas medicine is so siloed.

>> Yeah. >> In real life that it's taking away those things. I'm curious about how your relationship with clients has changed now that, as you were talking about earlier, you're finding all these new ways for them to be more productive. Are you helping them and advising them on, "Oh, you can make this a new source of revenue. This could be a new business model for you." Are you advising them in those ways?

>> Absolutely, and, you know, at HCLTech, we've been vertical aligned and domain because our engineering, if you build, you know, large scale and, you know, system for a client, you need to know that client, but the other interesting thing is the clients themselves are now realizing that they have this amazing value that is their data, and then they're starting up to understand, "Oh, if I use it there, I can win on a competitive venture. Oh, if I use it there I can enlarge,

you know, my marketing." >> Yeah.

>> And it's phenomenal to us to see how fast they get on understanding what's the potential, as well, in our strategy, as though we have a very conscious, you know, charter to create ethical AI and to be very mindful of the creation of IPs and to be very mindful that we are dealing

with data of clients. >> Yeah.

>> And this is a... We all have to govern well, and, you know, the European community has put out very strong directions and everything. So we do global clients. You have to understand how to deal with the dimension

of that as well. >> Well, also, you mentioned the value, the time to value, that's a cliche in the industry. To your POC model, you can get really quick proof points.

>> Yes. >> And those little wins that you do internally with your data also show the boss, "Hey, we got momentum.

Get more budget." >> Yes.

>> Right, so you're starting to see budgets. Dave Vellante reported on the ETR spending data that budgets, now, are being allocated on AI. A year ago, they're being allocated, stolen from other budgets. Now, it's like, "Okay, we see a little bit of wins."

>> Budget isn't a problem for anyone, quite frankly. I mean, one of the things that we've seen, right, we use our Cloud Native and AI Labs uniquely as a place where our clients can come in for a trusted advisor type relationship, to your point, we help them understand what's going to work best for them, but it's also a place of innovation and acceleration, but the remarkable thing that we've seen is we'll do an engagement with a client. We'll build, call it a POC, and the client then sticks to the lab thereafter, right? It's really interesting. Once the client sees value, the ideas just keep flowing.

>> Right, right. >> You know, I think the angle that your product model is genius because that gets them into the discovery side

of the solution, okay? >> Yeah.

>> And it's not your old-school IT transformation playbook.

>> Alan: Yeah.

>> It's we're building it with you, and I think that speeds the process up, and that is actually... You're building the bridge to the future with them, and that's part of the engagement I think people need the most.

>> And in GenAI is 100% value creation, the business lever that they want to have. There is some cost reductions, but in the long run, the the one that they really go for is exactly what you said, "How is it going to change my business? How I'm going to accelerate?" We have, as an industry, I don't think we have been able to capture very well, diminished cost and business value,

but here. >> Yeah.

>> In this technology, we really need to learn how to do it for our clients.

>> Excellent. >> Siki, great to have you on. We could go for another hour.

>> I know. (laughs) >> Just on your... We should do a whole segment on the customer stories.

>> Yes. >> Yeah.

>> Because that's real data that you could share with the field and would get more motivation to get the confidence up.

>> Rebecca: And elicit the best practices.

>> Yeah, the confidence. >> What we know, yeah.

>> Confidence is critical. >> Yeah.

>> Enthusiasm, check. Everyone's enthused. (Rebecca laughs) Confidence is a great point, and we'll have to have you back on.

>> Yeah. >> To end the segment, I'll give you both the final word, final statement. What's the big relationship with Google, how is that helping HCL, and what's the benefits to customers? What should they know about?

>> So HCLTech was probably the first partner that all in on Google Cloud when Google was still very small and a strong challenger. So we have a long-lasting relationship, and HCLTech, as engineers, we like to code on Java. It's a very natural environment for us, and there is a little bit a geek affiliation.

>> Yes, yes, yes. (laughs) >> A lot of that, and we have a very open relationship. We invest on the new releases, and we do a lot of engagement in the market. It is pleasant to work with. They're very... They are challengers, so it's always fine to win

as you're challenging. >> Yeah.

>> They have good AI, too. >> Oh, yeah, no, this, I told to TK, "Now, the pack is getting your way. You just got to push it through because it's enterprise."

>> Yeah. >> They got the right formula.

>> Yeah. >> And it's a good point. I mean, I think Google have done a particularly good job at making GenAI consumable, and that's really important to our clients. They like that ease of consumption.

>> Yeah. >> Yeah

>> And, clearly, you know, from a a Gemini perspective, all of the capability that we expect is there. One thing that I wouldn't want to overlook though is a lot of clients have got a very strong interest

in open source approaches. >> Yes, a lot.

>> So the ancillary availability of Gemini, for example, as an open source, you know, model approach does actually resonate really strongly with clients who favor that opportunity, too.

>> Yeah, yeah. >> Love the AI Force. Love the AI Labs. It's a great formula, congratulations, and it's just getting started.

>> Yes! >> Moving quickly.

>> Thanks for coming on the show.

>> All right. >> Thanks, thank you, guys.

>> Yes. >> Thank you. Thank you for having us.

>> I'm Rebecca Knight for John Furrier. Stay tuned for more of theCUBE's live coverage of Google Cloud Next. You are watching "theCUBE", the leading source for enterprise tech news. (bright music)