Nimesh Akhauri of The DDC Group, chief executive officer, joins theCUBE at the NYSE Wired studio to discuss how The DDC Group evolves from a people-based business into an artificial intelligence plus platform-led organization. Akhauri draws on three decades of experience in business process management and deep domain expertise across shipping and logistics, retail, automotive and energy. They explain DDC’s transformation, practical milestones, and the role of theCUBE Research and John Furrier of theCUBE in framing implementation realities.
Discussion emphasizes co-design with customers, preserving meaningful human oversight for agentic AI, and leveraging domain-specific platforms as a competitive advantage. Akhauri stresses that prioritizing targeted use cases and tailored change management drives scalable outcomes rather than focusing solely on cost reduction. theCUBE analysts note that chief financial officers and chief people officers assume an increasingly central role in AI strategy, capital allocation and workforce planning.
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Nimesh Akhauri, The DDC Group
Nimesh Akhauri of The DDC Group, chief executive officer, joins theCUBE at the NYSE Wired studio to discuss how The DDC Group evolves from a people-based business into an artificial intelligence plus platform-led organization. Akhauri draws on three decades of experience in business process management and deep domain expertise across shipping and logistics, retail, automotive and energy. They explain DDC’s transformation, practical milestones, and the role of theCUBE Research and John Furrier of theCUBE in framing implementation realities.
Discussion emphasizes co-design with customers, preserving meaningful human oversight for agentic AI, and leveraging domain-specific platforms as a competitive advantage. Akhauri stresses that prioritizing targeted use cases and tailored change management drives scalable outcomes rather than focusing solely on cost reduction. theCUBE analysts note that chief financial officers and chief people officers assume an increasingly central role in AI strategy, capital allocation and workforce planning.
play_circle_outlineC-suite evolution: CFOs and CPOs becoming operational partners in AI-driven strategy.
replyShare Clip
play_circle_outlineDDC Group's Global Shift: From People-Based BPM to AI-Plus, Platform-Led Operations in Philippines, India, Colombia, Bosnia, Serbia
replyShare Clip
play_circle_outlineAI Integration: Shifting Culture, Pricing Models, and Domain Expertise as Competitive Moats in Shipping, Retail, Energy, and Automotive
replyShare Clip
play_circle_outlineProductivity translating to top-line revenue, not just cost reduction.
>> Welcome back, everyone, to theCUBE here at our New York Stock Exchange studio. Of course we have our Palo Alto studio, connecting Silicon Valley to Wall Street. This is part of our NYSE Wired program. It's a CUBE original, of course, the NYSE Wired open community is a network of practitioners. They're builders, they're operators, they're investors, all trying to figure out how to move forward in the world as we live in today. We've got a great guest here who's going to talk about AI transformation. Nimesh is the CEO of DDC Group. Recently took the helm, and is involved deep into a transformation project. Business model transformation, technology transformation, people transformation, is the topic. Thanks for coming on theCUBE. Really appreciate it.
Nimesh Akhauri
>> Thank you. Thank you for having me over.
John Furrier
>> So, first of all, I know you've got a very busy day here. Thanks for coming on theCUBE as you do the tour through the NYSE, so appreciate that. One of the hottest topics outside of the developer buzz and frothiness of developers, AI-native developers, and the deep tech, is that the C-suite is changing. The C-suite is changing. It's not just CISOs and CIOs. I mean, they've always been kind of plugged into the tech through IT. But now that AI infuses all aspects of the organization, you're starting to see the CFO play with the CIO. They're operational. They're not just the stewards and the guardians of the books. They're involved a lot in how capital is formed, directed, leveraged. So, that's a huge role. The Chief People Officer is involved, because there's cultural change. So, you're starting to see this power dynamic happening at the C-suite, directly tied into the deep tech technology.
Nimesh Akhauri
>> Absolutely.
John Furrier
>> You're in the middle of this right now. What's your view on this? How do you see this? Because when you think about transformation, we'll get into some of the specifics, but I want to get your thoughts on how you see the role of the C-suite, and how that's impacting these technology AI transformations?
Nimesh Akhauri
>> You hit the nail on the head, John. The erstwhile CFO, just to give an example of the CFO organization, the erstwhile CFO would largely be a number keeper, who manage the accounts. But now the CFO is deeply involved in terms of leveraging tech and AI, in terms of predicting what, in the case of a private company, what the forward number would look like. And in the case of a listed company or the stock, what we should do internally, which will impact the stock price. That calculation is not simple. That calculation is based upon a lot of forward thinking, and implementation of those ideas and technology. Similarly, for the CPO, for the Chief People Officer, the workforce construct has completely changed. The workforce construct used to be... You used to have particularly a job description earlier, and you used to go and hire them, and train them, and up-skill them, and cross-skill them, and make them productive. But of late, in the last, I would say 18 months or 24 months, and going forward, the predictability factor has largely diminished. Because now, you have to plan for the future, and what kind of talent and what kind of skills would you need for the future? That's become all AI-driven.
John Furrier
>> Talk about the DDC Group. Explain the business you're in, and specifically the transformation journey that you're on?
Nimesh Akhauri
>> Sure. So, DDC Group is a 30-year-old business, and it started off as among the first BPM players in the market. So it's as old as 1989 was the year when we got started.
John Furrier
>> Yeah. Big mini computer days. Open systems came right after that.
Nimesh Akhauri
>> Absolutely. Broadly speaking, we deal with the backend processes, managing them, optimizing them, bringing in more efficiency, bringing in more productivity. And we, of course, do data capture and data analysis and data projection, as well. Among the largest sectors which we handle is, for example, shipping and logistics. In the trucking industry in the US, we handle about one-third of the bills of lading which are processed in the country. We have got an offshore center in Philippines. We have got an offshore center in India, nearshore center in Columbia, and Bosnia and Serbia in the Europe.
John Furrier
>> Global IT footprint.
Nimesh Akhauri
>> Yeah.
John Furrier
>> You have a global IT footprint.
Nimesh Akhauri
>> .
John Furrier
>> So you have a global IT footprint, transforming to GenAI and agentic.
Nimesh Akhauri
>> AI workforce, right?
John Furrier
>> Okay.
Nimesh Akhauri
>> I would call it transforming from a people-based organization, into an AI plus platform-led organization. That's a cultural shift, that's a skillset shift, that's a mindset shift. That's also a shift in terms of how you operate, and how you work with your clients to price your opportunities. So, it's a whole lot of shift which is happening right now. We are in the midst of it. I started this shift in 2024, and we have covered a significant distance, but there's a long way to go as well, I would say.
John Furrier
>> What are your biggest milestones, accomplishments, that you would want to flex? Because I think... I'll give you the progress. You say you've got a long way to go. But what have you accomplished so far? Give us a progress report. What's worked? What did you learn from? Were there new techniques you deployed, given? We see people have different mechanisms now with AI. As Amazon says, "Create two-way doors, not one-way doors." So what have you learned, and give us a progress report?
Nimesh Akhauri
>> Sure. The first thing we have learned is that we have to be very careful, in terms of what we choose to be, right? Because we cannot be everything for everybody. I'll give you an example. You cannot be a startup, you cannot act and behave like a startup, because their DNA and their culture is different. Typically, a startup company which has got only platform and technology in their DNA would behave completely differently. Sometimes they're becoming your biggest disruptor and your biggest competitor. So, gone are the days when you exactly know what kind of competition you will face when you go for a particular opportunity with a client, because these new disruptors, they are creating a new blue ocean strategy for themselves. So that was the first learning for us, that we cannot predict what is coming our way, and we cannot be everything for everybody. And there, deep domain expertise really matters. So, we have built some excellent domain expertise in shipping and logistics, in retail, automotive, and in energy and utilities. And so, we are focusing on building upon those domain expertise to create platforms, which the clients understand, because they can see domain being infused into it in a big way.
John Furrier
>> And that comes out in the results, too. AI loves domain experts.
Nimesh Akhauri
>> Exactly. Exactly. So, in my view, the biggest differentiator which we have, and which we'll continue to build upon, is our domain knowledge and domain expertise, because that is very difficult to replicate very quickly. I mean, you can go and buy talent from the market, but then the use cases is something which is what we have, is difficult to replicate very quickly in the market.
John Furrier
>> Talk about the workflows, because I can get a sense from your conversation that you guys have well-defined workflows. You have a good data estate, IT operations, okay? You've got a lot of databases. I'm sure you have that nailed down. How did that prepare you for being ready for an AI and AI agentic future? Because the new workers will be agents. They'll be in the transformation plan. How has your preexisting legacy position and/or your data estate prepared you, and what'd you learn?
Nimesh Akhauri
>> Well, I mean, obviously there was a big tectonic shift, in terms of how we were looking at data, how we were managing it. Going back to the learning phase, we have not yet completely moved towards agentic AI. It's still a combination of human and agentic AI. And to be honest with you, I don't mind that position, because there needs to be-
John Furrier
>> Well, it's practical. It's not ready. It's getting there.
Nimesh Akhauri
>> No. It's getting there. And we want to have a significant "human intervention" as well. Because if you lose the human touch completely, then that dependence only on AI can sometimes be very counterproductive. So we have to carefully balance it out.
John Furrier
>> Last week at Google Next which was a hot agent conference. Obviously they're a big platform, like AWS says. A lot of work still needs to get done on observability, observing the agents, tying them, making sure that the humans can manage them. And they're going to start talking, so it's a little bit... In a good way, it's growing, but not yet ready for prime time. I think it will be, because the coding has come in. Seeing AI coding really augment teams' capabilities.
Nimesh Akhauri
>> Yeah. Absolutely.
John Furrier
>> Turbocharge their superpower.
Nimesh Akhauri
>> Absolutely. But I have a very strong viewpoint on that, John.
John Furrier
>> What's that?
Nimesh Akhauri
>> My viewpoint is that the human intervention will definitely be required, no matter how much we evolve, right?
John Furrier
>> Yeah, I would agree with that.
Nimesh Akhauri
>> Yeah. Because that intelligence is very difficult to replicate and replace. That's my view.
John Furrier
>> Nimesh, I think you're right on that, and that's consistent. I believe this, too. I think people who let AI wire them, versus humans wiring the AI up, will get it wrong. I've seen examples of that. So every single successful AI startup that I've seen, every successful enterprise that's adopted it in a pragmatic way, has thought about the human's role with the AI, in the sense of making the human better.
Nimesh Akhauri
>> Absolutely.
John Furrier
>> Because it scales human intellect.
Nimesh Akhauri
>> Absolutely.
John Furrier
>> Intellect plus intellect scales human intellect.
Nimesh Akhauri
>> It should be used as an enabler. It should make sure that we do work more efficiently and the output is much more quicker, and not what it used to be earlier. That's the whole idea about infusing AI in platforms.
John Furrier
>> Well, it's a great vision. I think that you're right on the money. Let's talk about culture, because now you have the people side of it. I want to get to the business model transformation a little bit after this, because, at the end of the day, we're seeing evidence where the productivity is translating to top-line revenue.
Nimesh Akhauri
>> Sure.
John Furrier
>> Not just cost takeout, which tends to be an IT thing, but culture, people, process, technology. Process and technology perfectly aligned to this AI world. The people side, culture, getting people to change, effect change, pull people through, leadership skills for management. These are all now boiling up. This isn't like some Harvard Business Review. This is actually real challenges and opportunity.
Nimesh Akhauri
>> And there's no template.
John Furrier
>> What's your vision on this? There's no template. You're a pioneer. You're a frontier leader.
Nimesh Akhauri
>> Yeah. I spoke about that earlier, in terms of having very difficulty in predictability of the talent pool which you want to hire for the future. All you can do is, you can get the right raw material, as I call it, in terms of talent pool, and have the right amount of training, internal training and up-skilling, and cross-skilling ability to make that raw material worthy for what the future looks like. But then, the evolution will continue to happen, and you will continue to make sure that people are getting cross-skilled and up-skilled. So, as I said earlier, earlier you used to hire talent, because I've been in this industry for 27, 28 years now, you used to hire talent, and you would probably put them in a task, and you would expect a certain linear kind of a movement, in terms of their skillset developing. That is finished now. That is not the case going forward, right? The linear predictability is finished, because all of a sudden there's a new disruptor, and you have to make sure that your talent pool is geared to handle that. So, that's the first bit which is the most unpredictable.
John Furrier
>> The good news is, we're all using AI. We can see the benefits. It's getting it operationalized in the company is the challenge. Okay. On that front, let's talk about your customer, okay? You mentioned you have guys some areas you're really doing well in. How is the customer experience impacted? How has some of these transformation efforts translated into positive outcome for customers?
Nimesh Akhauri
>> Very positive. The fact that the customer wants to change, at the same time, they need somebody to come in and do it with them, not for them. That's a big difference. Because a lot of customers, not every customer has evolved, in the sense that they're in different journey parts at every point in time. So you have to understand that, okay, this customer, customer X, is at this point in time, and I have to hold the customer's hand to take from X to a certain point. Similarly, this customer may have evolved completely into a different orbit, and you have to manage that. So that level of flexibility, I call it co-creation, has to-
John Furrier
>> Yeah, Partnership.
Nimesh Akhauri
>> Partnership. Yeah.
John Furrier
>> I mean, co-design. Nvidia uses this term a lot, extreme co-design. But they make semiconductors.
Nimesh Akhauri
>> Exactly.
John Furrier
>> They have a longer time horizon with their suppliers, and also they have an ecosystem, but they're co-designing it. Why? Because they want to bring their partners in. Business is now co-designing with the customers.
Nimesh Akhauri
>> Exactly.
John Furrier
>> The relationship has changed.
Nimesh Akhauri
>> Exactly.
John Furrier
>> Because the stakes are super high.
Nimesh Akhauri
>> Exactly.
John Furrier
>> You see that same picture?
Nimesh Akhauri
>> Absolutely. Absolutely. My underlying theme is co-design, because, as an organization, we have to be very flexible. We cannot be going into the client, "This is the way you have to do it. Take it or leave it." It doesn't work like that. So we have built that culture in our organization, and we are constantly evolving from that culture as well. We are adopting new technologies. We are adopting new platforms and new tools which are coming out of the market. We want to be flexible on that front as well, so that we are ahead of our competition. And at the same time, we are flexible with the client.
John Furrier
>> Nimesh, this is one of the biggest things I feel is a critical, under-reported dynamic. The technology used to be, here is some product, and then the customer have to bend around it. Now you're seeing not just hyper-personalization, just ease of use. So, the customer experience is not your classic customer experience, website experience, or mobile app. It's direct value proposition to the customer.
Nimesh Akhauri
>> Exactly.
John Furrier
>> That's the opportunity.
Nimesh Akhauri
>> Exactly.
John Furrier
>> I mean-
Nimesh Akhauri
>> Sorry to interfere, John. But if you remember, the great Steve Jobs said this long time back, right? In one of his interviews, that we are used to making products, and then pushing it down the customer's throat. He was a genius, and he said that, "Look, that doesn't work."
John Furrier
>> It's not about the technology.
Nimesh Akhauri
>> Exactly.
John Furrier
>> Work backwards from the customer.
Nimesh Akhauri
>> Work backwards from the customer.
John Furrier
>> Steve Jobs started, and then Jeff Bezos took at AWS.
Nimesh Akhauri
>> Exactly.
John Furrier
>> And then outcomes are now possible. You're seeing the word outcomes, people, process, technology, we talked about that. The word outcomes has been said more on theCUBE in the past six months on my show, than 10 years. Because now, that is the number one business discussion. If you know what your outcome is, for some it's production workloads at scale, could be customer satisfaction and revenue. You can actually get there. These north stars don't become way elusive goals.
Nimesh Akhauri
>> Absolutely.
John Furrier
>> So, I think that's motivating people. So I think that's going to be... It's interesting to see how the culture and the people side react. There'll be skeptics and naysayers. They'll probably fall to the side. I think people who lean in will understand that that's gettable.
Nimesh Akhauri
>> And the outcome is only possible when you're working with the client, collaborating with them, and understanding where they want to be. Because not every client wants to be at the same point at a particular point in time. So, to work with them on the journey, and help them navigate the journey very...
John Furrier
>> It's very liberating. I talked to a CFO, and this is a great example, because it's almost in every department. The CFO, who was a skeptic, signing the checks for that, "Here's your IT budget," and then, "I need more." And they would manage it as a budget item, collaborate, maybe teammate, certainly somewhat a partnership, basically started doing their own shadow AI, and realized that they could close the books with no IT involvement.
Nimesh Akhauri
>> No IT involvement.
John Furrier
>> They become believers. And then they go, "I get it." So that's happening, and "I get it" moments happening in all departments. I think this is a liberating psychological advantage for the change management.
Nimesh Akhauri
>> Yes. Absolutely.
John Furrier
>> Which you've lived, in your career.
Nimesh Akhauri
>> Absolutely.
John Furrier
>> Change management. What's your reaction to change management? This is one of many examples. How do you leverage that? How do you create that magical moment?
Nimesh Akhauri
>> Absolutely. Again, I mean, it is to be tailor-made. That's my first reaction to change management, because what worked for a particular organization may not work for a different organization, right? The underlying facts and the underlying reasons could be similar, or same, but then they're like chalk and cheese. You have to first understand what will work in this organization and then make it happen. So always don't rush into change management just for the sake of it. First understand where you are headed to, and what your outcome looks like, and then go for the change management.
John Furrier
>> Nimesh, thank you so much for coming on. Congratulations on your journey. You've got a lot more work to do, as you say. It's early days in AI, so a lot of upside potential.
Nimesh Akhauri
>> Absolutely.
John Furrier
>> Thanks for coming on. Appreciate it.
Nimesh Akhauri
>> Thank you, John.
John Furrier
>> Okay. I'm John Furrier, host of theCUBE, here at the NYSE studios of theCUBE, the NYSE Wired program. Thanks for watching.
>> Welcome back, everyone, to theCUBE here at our New York Stock Exchange studio. Of course we have our Palo Alto studio, connecting Silicon Valley to Wall Street. This is part of our NYSE Wired program. It's a CUBE original, of course, the NYSE Wired open community is a network of practitioners. They're builders, they're operators, they're investors, all trying to figure out how to move forward in the world as we live in today. We've got a great guest here who's going to talk about AI transformation. Nimesh is the CEO of DDC Group. Recently took the helm, and is involved deep into a transformation project. Business model transformation, technology transformation, people transformation, is the topic. Thanks for coming on theCUBE. Really appreciate it.
Nimesh Akhauri
>> Thank you. Thank you for having me over.
John Furrier
>> So, first of all, I know you've got a very busy day here. Thanks for coming on theCUBE as you do the tour through the NYSE, so appreciate that. One of the hottest topics outside of the developer buzz and frothiness of developers, AI-native developers, and the deep tech, is that the C-suite is changing. The C-suite is changing. It's not just CISOs and CIOs. I mean, they've always been kind of plugged into the tech through IT. But now that AI infuses all aspects of the organization, you're starting to see the CFO play with the CIO. They're operational. They're not just the stewards and the guardians of the books. They're involved a lot in how capital is formed, directed, leveraged. So, that's a huge role. The Chief People Officer is involved, because there's cultural change. So, you're starting to see this power dynamic happening at the C-suite, directly tied into the deep tech technology.
Nimesh Akhauri
>> Absolutely.
John Furrier
>> You're in the middle of this right now. What's your view on this? How do you see this? Because when you think about transformation, we'll get into some of the specifics, but I want to get your thoughts on how you see the role of the C-suite, and how that's impacting these technology AI transformations?
Nimesh Akhauri
>> You hit the nail on the head, John. The erstwhile CFO, just to give an example of the CFO organization, the erstwhile CFO would largely be a number keeper, who manage the accounts. But now the CFO is deeply involved in terms of leveraging tech and AI, in terms of predicting what, in the case of a private company, what the forward number would look like. And in the case of a listed company or the stock, what we should do internally, which will impact the stock price. That calculation is not simple. That calculation is based upon a lot of forward thinking, and implementation of those ideas and technology. Similarly, for the CPO, for the Chief People Officer, the workforce construct has completely changed. The workforce construct used to be... You used to have particularly a job description earlier, and you used to go and hire them, and train them, and up-skill them, and cross-skill them, and make them productive. But of late, in the last, I would say 18 months or 24 months, and going forward, the predictability factor has largely diminished. Because now, you have to plan for the future, and what kind of talent and what kind of skills would you need for the future? That's become all AI-driven.
John Furrier
>> Talk about the DDC Group. Explain the business you're in, and specifically the transformation journey that you're on?
Nimesh Akhauri
>> Sure. So, DDC Group is a 30-year-old business, and it started off as among the first BPM players in the market. So it's as old as 1989 was the year when we got started.
John Furrier
>> Yeah. Big mini computer days. Open systems came right after that.
Nimesh Akhauri
>> Absolutely. Broadly speaking, we deal with the backend processes, managing them, optimizing them, bringing in more efficiency, bringing in more productivity. And we, of course, do data capture and data analysis and data projection, as well. Among the largest sectors which we handle is, for example, shipping and logistics. In the trucking industry in the US, we handle about one-third of the bills of lading which are processed in the country. We have got an offshore center in Philippines. We have got an offshore center in India, nearshore center in Columbia, and Bosnia and Serbia in the Europe.
John Furrier
>> Global IT footprint.
Nimesh Akhauri
>> Yeah.
John Furrier
>> You have a global IT footprint.
Nimesh Akhauri
>> .
John Furrier
>> So you have a global IT footprint, transforming to GenAI and agentic.
Nimesh Akhauri
>> AI workforce, right?
John Furrier
>> Okay.
Nimesh Akhauri
>> I would call it transforming from a people-based organization, into an AI plus platform-led organization. That's a cultural shift, that's a skillset shift, that's a mindset shift. That's also a shift in terms of how you operate, and how you work with your clients to price your opportunities. So, it's a whole lot of shift which is happening right now. We are in the midst of it. I started this shift in 2024, and we have covered a significant distance, but there's a long way to go as well, I would say.
John Furrier
>> What are your biggest milestones, accomplishments, that you would want to flex? Because I think... I'll give you the progress. You say you've got a long way to go. But what have you accomplished so far? Give us a progress report. What's worked? What did you learn from? Were there new techniques you deployed, given? We see people have different mechanisms now with AI. As Amazon says, "Create two-way doors, not one-way doors." So what have you learned, and give us a progress report?
Nimesh Akhauri
>> Sure. The first thing we have learned is that we have to be very careful, in terms of what we choose to be, right? Because we cannot be everything for everybody. I'll give you an example. You cannot be a startup, you cannot act and behave like a startup, because their DNA and their culture is different. Typically, a startup company which has got only platform and technology in their DNA would behave completely differently. Sometimes they're becoming your biggest disruptor and your biggest competitor. So, gone are the days when you exactly know what kind of competition you will face when you go for a particular opportunity with a client, because these new disruptors, they are creating a new blue ocean strategy for themselves. So that was the first learning for us, that we cannot predict what is coming our way, and we cannot be everything for everybody. And there, deep domain expertise really matters. So, we have built some excellent domain expertise in shipping and logistics, in retail, automotive, and in energy and utilities. And so, we are focusing on building upon those domain expertise to create platforms, which the clients understand, because they can see domain being infused into it in a big way.
John Furrier
>> And that comes out in the results, too. AI loves domain experts.
Nimesh Akhauri
>> Exactly. Exactly. So, in my view, the biggest differentiator which we have, and which we'll continue to build upon, is our domain knowledge and domain expertise, because that is very difficult to replicate very quickly. I mean, you can go and buy talent from the market, but then the use cases is something which is what we have, is difficult to replicate very quickly in the market.
John Furrier
>> Talk about the workflows, because I can get a sense from your conversation that you guys have well-defined workflows. You have a good data estate, IT operations, okay? You've got a lot of databases. I'm sure you have that nailed down. How did that prepare you for being ready for an AI and AI agentic future? Because the new workers will be agents. They'll be in the transformation plan. How has your preexisting legacy position and/or your data estate prepared you, and what'd you learn?
Nimesh Akhauri
>> Well, I mean, obviously there was a big tectonic shift, in terms of how we were looking at data, how we were managing it. Going back to the learning phase, we have not yet completely moved towards agentic AI. It's still a combination of human and agentic AI. And to be honest with you, I don't mind that position, because there needs to be-
John Furrier
>> Well, it's practical. It's not ready. It's getting there.
Nimesh Akhauri
>> No. It's getting there. And we want to have a significant "human intervention" as well. Because if you lose the human touch completely, then that dependence only on AI can sometimes be very counterproductive. So we have to carefully balance it out.
John Furrier
>> Last week at Google Next which was a hot agent conference. Obviously they're a big platform, like AWS says. A lot of work still needs to get done on observability, observing the agents, tying them, making sure that the humans can manage them. And they're going to start talking, so it's a little bit... In a good way, it's growing, but not yet ready for prime time. I think it will be, because the coding has come in. Seeing AI coding really augment teams' capabilities.
Nimesh Akhauri
>> Yeah. Absolutely.
John Furrier
>> Turbocharge their superpower.
Nimesh Akhauri
>> Absolutely. But I have a very strong viewpoint on that, John.
John Furrier
>> What's that?
Nimesh Akhauri
>> My viewpoint is that the human intervention will definitely be required, no matter how much we evolve, right?
John Furrier
>> Yeah, I would agree with that.
Nimesh Akhauri
>> Yeah. Because that intelligence is very difficult to replicate and replace. That's my view.
John Furrier
>> Nimesh, I think you're right on that, and that's consistent. I believe this, too. I think people who let AI wire them, versus humans wiring the AI up, will get it wrong. I've seen examples of that. So every single successful AI startup that I've seen, every successful enterprise that's adopted it in a pragmatic way, has thought about the human's role with the AI, in the sense of making the human better.
Nimesh Akhauri
>> Absolutely.
John Furrier
>> Because it scales human intellect.
Nimesh Akhauri
>> Absolutely.
John Furrier
>> Intellect plus intellect scales human intellect.
Nimesh Akhauri
>> It should be used as an enabler. It should make sure that we do work more efficiently and the output is much more quicker, and not what it used to be earlier. That's the whole idea about infusing AI in platforms.
John Furrier
>> Well, it's a great vision. I think that you're right on the money. Let's talk about culture, because now you have the people side of it. I want to get to the business model transformation a little bit after this, because, at the end of the day, we're seeing evidence where the productivity is translating to top-line revenue.
Nimesh Akhauri
>> Sure.
John Furrier
>> Not just cost takeout, which tends to be an IT thing, but culture, people, process, technology. Process and technology perfectly aligned to this AI world. The people side, culture, getting people to change, effect change, pull people through, leadership skills for management. These are all now boiling up. This isn't like some Harvard Business Review. This is actually real challenges and opportunity.
Nimesh Akhauri
>> And there's no template.
John Furrier
>> What's your vision on this? There's no template. You're a pioneer. You're a frontier leader.
Nimesh Akhauri
>> Yeah. I spoke about that earlier, in terms of having very difficulty in predictability of the talent pool which you want to hire for the future. All you can do is, you can get the right raw material, as I call it, in terms of talent pool, and have the right amount of training, internal training and up-skilling, and cross-skilling ability to make that raw material worthy for what the future looks like. But then, the evolution will continue to happen, and you will continue to make sure that people are getting cross-skilled and up-skilled. So, as I said earlier, earlier you used to hire talent, because I've been in this industry for 27, 28 years now, you used to hire talent, and you would probably put them in a task, and you would expect a certain linear kind of a movement, in terms of their skillset developing. That is finished now. That is not the case going forward, right? The linear predictability is finished, because all of a sudden there's a new disruptor, and you have to make sure that your talent pool is geared to handle that. So, that's the first bit which is the most unpredictable.
John Furrier
>> The good news is, we're all using AI. We can see the benefits. It's getting it operationalized in the company is the challenge. Okay. On that front, let's talk about your customer, okay? You mentioned you have guys some areas you're really doing well in. How is the customer experience impacted? How has some of these transformation efforts translated into positive outcome for customers?
Nimesh Akhauri
>> Very positive. The fact that the customer wants to change, at the same time, they need somebody to come in and do it with them, not for them. That's a big difference. Because a lot of customers, not every customer has evolved, in the sense that they're in different journey parts at every point in time. So you have to understand that, okay, this customer, customer X, is at this point in time, and I have to hold the customer's hand to take from X to a certain point. Similarly, this customer may have evolved completely into a different orbit, and you have to manage that. So that level of flexibility, I call it co-creation, has to-
John Furrier
>> Yeah, Partnership.
Nimesh Akhauri
>> Partnership. Yeah.
John Furrier
>> I mean, co-design. Nvidia uses this term a lot, extreme co-design. But they make semiconductors.
Nimesh Akhauri
>> Exactly.
John Furrier
>> They have a longer time horizon with their suppliers, and also they have an ecosystem, but they're co-designing it. Why? Because they want to bring their partners in. Business is now co-designing with the customers.
Nimesh Akhauri
>> Exactly.
John Furrier
>> The relationship has changed.
Nimesh Akhauri
>> Exactly.
John Furrier
>> Because the stakes are super high.
Nimesh Akhauri
>> Exactly.
John Furrier
>> You see that same picture?
Nimesh Akhauri
>> Absolutely. Absolutely. My underlying theme is co-design, because, as an organization, we have to be very flexible. We cannot be going into the client, "This is the way you have to do it. Take it or leave it." It doesn't work like that. So we have built that culture in our organization, and we are constantly evolving from that culture as well. We are adopting new technologies. We are adopting new platforms and new tools which are coming out of the market. We want to be flexible on that front as well, so that we are ahead of our competition. And at the same time, we are flexible with the client.
John Furrier
>> Nimesh, this is one of the biggest things I feel is a critical, under-reported dynamic. The technology used to be, here is some product, and then the customer have to bend around it. Now you're seeing not just hyper-personalization, just ease of use. So, the customer experience is not your classic customer experience, website experience, or mobile app. It's direct value proposition to the customer.
Nimesh Akhauri
>> Exactly.
John Furrier
>> That's the opportunity.
Nimesh Akhauri
>> Exactly.
John Furrier
>> I mean-
Nimesh Akhauri
>> Sorry to interfere, John. But if you remember, the great Steve Jobs said this long time back, right? In one of his interviews, that we are used to making products, and then pushing it down the customer's throat. He was a genius, and he said that, "Look, that doesn't work."
John Furrier
>> It's not about the technology.
Nimesh Akhauri
>> Exactly.
John Furrier
>> Work backwards from the customer.
Nimesh Akhauri
>> Work backwards from the customer.
John Furrier
>> Steve Jobs started, and then Jeff Bezos took at AWS.
Nimesh Akhauri
>> Exactly.
John Furrier
>> And then outcomes are now possible. You're seeing the word outcomes, people, process, technology, we talked about that. The word outcomes has been said more on theCUBE in the past six months on my show, than 10 years. Because now, that is the number one business discussion. If you know what your outcome is, for some it's production workloads at scale, could be customer satisfaction and revenue. You can actually get there. These north stars don't become way elusive goals.
Nimesh Akhauri
>> Absolutely.
John Furrier
>> So, I think that's motivating people. So I think that's going to be... It's interesting to see how the culture and the people side react. There'll be skeptics and naysayers. They'll probably fall to the side. I think people who lean in will understand that that's gettable.
Nimesh Akhauri
>> And the outcome is only possible when you're working with the client, collaborating with them, and understanding where they want to be. Because not every client wants to be at the same point at a particular point in time. So, to work with them on the journey, and help them navigate the journey very...
John Furrier
>> It's very liberating. I talked to a CFO, and this is a great example, because it's almost in every department. The CFO, who was a skeptic, signing the checks for that, "Here's your IT budget," and then, "I need more." And they would manage it as a budget item, collaborate, maybe teammate, certainly somewhat a partnership, basically started doing their own shadow AI, and realized that they could close the books with no IT involvement.
Nimesh Akhauri
>> No IT involvement.
John Furrier
>> They become believers. And then they go, "I get it." So that's happening, and "I get it" moments happening in all departments. I think this is a liberating psychological advantage for the change management.
Nimesh Akhauri
>> Yes. Absolutely.
John Furrier
>> Which you've lived, in your career.
Nimesh Akhauri
>> Absolutely.
John Furrier
>> Change management. What's your reaction to change management? This is one of many examples. How do you leverage that? How do you create that magical moment?
Nimesh Akhauri
>> Absolutely. Again, I mean, it is to be tailor-made. That's my first reaction to change management, because what worked for a particular organization may not work for a different organization, right? The underlying facts and the underlying reasons could be similar, or same, but then they're like chalk and cheese. You have to first understand what will work in this organization and then make it happen. So always don't rush into change management just for the sake of it. First understand where you are headed to, and what your outcome looks like, and then go for the change management.
John Furrier
>> Nimesh, thank you so much for coming on. Congratulations on your journey. You've got a lot more work to do, as you say. It's early days in AI, so a lot of upside potential.
Nimesh Akhauri
>> Absolutely.
John Furrier
>> Thanks for coming on. Appreciate it.
Nimesh Akhauri
>> Thank you, John.
John Furrier
>> Okay. I'm John Furrier, host of theCUBE, here at the NYSE studios of theCUBE, the NYSE Wired program. Thanks for watching.
John Furrier