Data Analytics Chat

What Happens When We Adopt AI – The Change Management Journey

• Ben Parker

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Kartick Kalaimani, VP Enterprise MDM Data and Transformation Lead at Dentsu, joins Ben Parker to demystify AI adoption and its critical human element. This insightful episode delves into common misconceptions about AI, highlighting the importance of clean data, clearly defined use cases, and strong change management. Kartick shares his extensive career journey and provides actionable advice on bridging the gap between technology and people, emphasizing that successful AI transformation is ultimately a human journey focused on belief and adoption.

In this episode, you will learn:
*   Kartick's four key career phases: mastering operations, quality and transformation, scaling transformation across finance and media, and data transformation.
*   The importance of pushing beyond your comfort zone for career growth and leadership development.
*   How to overcome major career setbacks by learning from challenges and focusing on the human side of change.
*   Kartick's unique edge in connecting business value, technology, and people.
*   Common misconceptions about AI adoption, such as viewing it as "plug and play" or self-sufficient.
*   Why AI transformation is fundamentally a human journey that requires active engagement and belief.
*   How businesses can effectively align AI adoption with real business problems rather than just chasing trends.
*   Strategies for leaders to address fear, resistance, and cultural challenges during AI transformation.
*   The crucial role of reskilling and upskilling the workforce for successful AI integration.
*   Advice for non-technical professionals on how to effectively participate in the AI journey.
*   Why the biggest myth about AI is that it serves as a "silver bullet" solution.
*   Kartick's vision for a future AI-ready organization where humans and AI co-create value.

Timestamps:
00:02:00 Welcome and Introduction
00:02:40 Kartick's Career Journey: Four Key Phases
00:05:45 Pushing Beyond Your Comfort Zone for Growth
00:08:00 Gaining Leadership Expertise and Mentorship
00:09:20 Major Career Setbacks and Their Lessons
00:12:30 Finding Your Edge in a Competitive Environment
00:13:50 Common Misconceptions in AI Adoption
00:18:10 Aligning AI with Real Business Problems
00:21:50 Human and Cultural Challenges in AI Transformation
00:24:00 How Leaders Can Approach AI Challenges
00:26:00 Advice for Non-Technical Listeners on AI
00:27:30 Busting the Biggest Myth About AI in Business
00:30:10 What a Well-Transformed AI-Ready Organization Looks Like
00:32:00 Turning Point in Successful Change Initiatives
00:33:15 Closing Remarks

Thank you for listening!

kartick:

One of the common misconception is that AI is plug and play A lot of people see gen AI as a magic button but without clean data and clearly define use cases it quickly becomes more of a shiny distraction than a real solution. Another misconception that AI runs on its own. In reality, AI needs people to train it, contextualize it, and drive adoption. It augments human intelligence. It doesn't replace it. I've seen incredibly well-designed solutions technically brilliant but they failed to deliver impact simply because the teams weren't aligned, trained, or even aware why the change was happening. So you can build the best AI model in the world, but if no one uses it, it has zero value. It's like building a rocket with no launchpad. A big part of making change stick is how we communicate it. If we only talk about productivity or efficiency it can trigger fear especially around job security in today's environment. But when we shift the conversation to value creation, growth and freeing up time for more meaningful work. People start to see AI is an enabler, not a threat. And at the end of the day, AI transformation isn't just a tech rollout, it's actually a human journey. The real win is when people believe in the value it brings, and feel like they're part of the story.

ben parker:

Welcome back to Data Analytics Chat, the podcast where we discuss the world of data, ai, and the careers shaping it. I'm your host, Ben Parker, bringing you real stories, expert insights, and practical advice to help you thrive in the industry. Today I'm excited to welcome Kartik Kani, VP Enterprise MDM Data and Transformation Lead at Dentsu. In this episode, we'll explore his exciting career journey, pivotal moments that shaping his career path, and discuss what happens when we actually adopt ai, the change management journey. Kartik, welcome to the podcast.

kartick:

Thank you. Thank you so much, Ben. Thank you for having me. It's great to be here and I'm really looking forward to this conversation. And a big hi to everyone listening. I hope Ben and I can make this as an insightful and fun session.

ben parker:

Yeah, definitely. I think it's definitely an interesting topic with everyone going through this at the moment. So yeah, looking forward to this.

kartick:

Absolutely.

ben parker:

So do you wanna start off with just sharing your career journey?

kartick:

Sure. If I had to sum up my career so far, I would break it into four key phases and with each adding something new. To how I think and lead today, phase one was all about mastering operations. So I started my career a little over two decades ago in operations at a company called Genpact, which is a leading global professional services firm. And those early years were incredibly hands-on. And I led client engagements across core operational areas like order to cash, procure to pay and supply chain. And over time, I became a true domain expert. That phase gave me a solid foundation, not just in how processes are supposed to work, but how they actually work on the ground. And it really taught me the value of good execution and the importance of getting the basics right. Then comes phase two, where I stepped into the world of quality and transformation and I was lucky to have had some incredible mentors who recognized my analytical strengths and passion for process improvement, and they steered me towards the world of quality. That shift turned out to be a game changer for me and I went on to become a certified Lean Six Sigma black belt, and mentored multiple green belt projects while driving a culture of continuous improvement and operational excellence across the organization. And that blend of domain knowledge and transformation mindset led to a big opportunity. I got the chance to lead initiatives across Europe and Africa. Tackling cross-functional challenges that pushed me out of my comfort zone. And it was here that I started thinking more strategically beyond process efficiency to organizational impact. And that's where my transformation mindset really took shape. Then comes phase three, which was all about scaling that transformation across finance and media. So after 15 years being at Genpact. I then joined Densu, a leading media agency to lead transformation programs on a much, much bigger canvas. I started with finance transformation and then moved on to automation and process redesign across the media capability wherein I streamlined operations, built automated solutions, and drove impact at scale across multiple pockets. And then finally, phase four is where I'm today, which is all about data transformation. And today as Vice President Densu, I lead global digital and data transformation focusing on enterprise mass data management, process standardization, automation and AI driven innovation. And it's where clean connected data starts to power everything from better decisions to stronger client delivery. Now, each phase has taught me something new and as we deepen our journey into this next wave of AI driven transformation. I'm excited to keep learning, adapting, and hopefully shaping the future of how businesses operate through smarter data and human-centered design. So that's been my career journey so far. Ben.

ben parker:

Brilliant. It's fascinating, obviously, your approach and yeah, thanks for breaking it down. I guess for yourself then, is your career journey, has it just been natural progression or have you pushed yourself, I mean you mentioned you, you pushed yourself out, you more in pushed yourself into more like risk adverse type positions. Has it just been more career progression that's pushed that, or have you been pushed by managers? How's it worked for you in your career?

kartick:

So there are two moments that truly shifted the trajectory of my career. And those two moments would be the ones where I was pushed out of my comfort zone and had to lead with both courage and creativity. Now one of the most exciting chapter was leading the quality function for a healthcare client based out of France. Now picture this, I'm sitting with PhDs and medical engineers. Most of them are French speaking. Challenging them on defects in medical equipment and collaborating to align on fixes and upgrades. Now, every day there felt like a mix of negotiation, problem solving and continuous learning. But with a bit of Google translate and a lot of expresso it was definitely a crash course in cultural intelligence, technical position, and staying calm when surrounded by people who are way smarter than you. Now it pushed me far out of my comfort zone, a new country, a new culture, and extremely smart stakeholders. Another pivotal moment came when I joined densu and took on the challenge of transforming finance operations. Now, this was before the RPA wave. It mostly was around desktop automation. Yet we were able to drive around 15 to 20% efficiency gains year after year by standard standardizing finance processes and building globally scalable best practices. Proving that you don't need flashy technology to deliver real value. You just need smart execution and business alignment. Now, both these experience shaped the way I approach transformation today. One taught me how to lead with humility and adapt quickly in unfamiliar territory. And the other showed me that even the modest tools when applied with clarity and intent can unlock big results. And they reinforce a lesson I carry with me. Real growth doesn't come from staying in your lane. It comes from leaning into challenges that stretch you, surprise you and sometimes scare you a little. And honestly, those are the moments that have made the journey so rewarding.

ben parker:

Brilliant. I see that's obviously important to you and it's good to see that you've obviously pushed yourself. I guess how did you, obviously you've worked in multiple countries as well. How did you gain. The leadership expertise then was it through learning on the job? Do you get mentoring? How do you gain your leadership skills? Because there'll be people that are in that technical capacity, but then they wanna make the step up, but either they feel they've not got the right skills, or they're not got the enough experience yet. How do you overcome that hurdle?

kartick:

So obviously I've been fortunate, as I said, to have had a lot of good mentors who helped me in this change management journey as well. So obviously as we go about in this journey, we come across folks of different nature with different perspectives. And obviously one, one kind of thing that I always focused upon was a change management journey. How do we go about getting all the folks along with you in this journey? And that might mean upskilling them, re-skilling them, and also setting the right expectations. So obviously with the right kind of leadership, the mentorship. And with the right kind of engagement with the people giving them or setting the right expectations with them ensuring that they understand what the change was that was coming along in their way. It was setting the right expectations, right communications, right leadership bin and obviously having the right support and guidance from your mentors, your managers. That was really helpful in this entire journey for me.

ben parker:

Brilliant. I like that. And yeah, I think it's important, isn't it now, to be able to story tell in the right manner articulate your technical knowledge into, layman terms business.'cause people wanna understand what you're saying it and make it easier. So you can translate that knowledge.

kartick:

Absolutely. That's key in this entire journey.

ben parker:

So then with yourself, have you faced a lot? Major career setback?

kartick:

Absolutely. Who doesn't fail face a major career setback. So obviously one that really stands out for me was when I was leading an ERP implementation early in my career. Now on paper, everything was solid. The technology was right, the roadmap was tight and it had leadership buying as well. But despite all of that the rollout did not land the way expected. The issue wasn't the system it was the people side of the change. We hadn't invested enough in communication training or stakeholder engagement. We underestimated how much fear, resistance, and fatigue could creep in where you are introducing big changes into day-to-day workflows. Now that's when Peter Drucker's quote really hit home for me. There's a quote saying, culture eats strategy for breakfast. It didn't matter how good the strategy was but without culture and people on board, it just didn't stick. Now looking back, it was humbling. But it completely changed how I approach transformation. Today. Whether I'm working on automation, mass data, or AI pilots, change management is never an afterthought. I bring people early into the journey. I focus on building trust and I make sure we are not just implementing tools, but building belief. That setback taught me that successful transition transformation is 50% design and 50% adoption. And that second half, which is 50% adoption, is all about culture, communication, and care. That experience really grounded me in and in one of the most important lessons of leadership. No matter how sophisticated the solution. Transformation is ultimately a people story. And if you can get that part right, the rest tends to follow. So that's been a major learning for me.

ben parker:

Yeah, I think it's quite special, isn't it, in life, where you face difficulty, setbacks and then,'cause that is instilled in your brain, isn't it? And you learn from that. You, that's like your foundation for future. It should be if you learn properly, but it's like the foundation for your future. Thinking, isn't it?

kartick:

Absolutely. Change, change. If that's one of the I think change management is something that is underestimated today and hence, I it's been a quite a key learning for me in the early part of my journey itself.

ben parker:

Yeah, no, I completely agree. I think, especially with the pace the industry's going at the minute you need, if you're not on board with change management or no fully on board with it. Gonna be challenging, isn't it? Because you've gotta, you've gotta move quick today, denying.

kartick:

Yeah. There's a very le less room for you to breathe and understand what's happening in the industry right now because things are evolving so fast with new tools coming every day it's easily that it's easy that you can get distracted towards the shiny tool and then compromise on change management journey.

ben parker:

Yeah, definitely. So I guess obviously you've me, you mentioned a couple of key points already, but in sort this competitive environment, what do you think has given you like a genuine edge?

kartick:

If I had to boil it down I think my edge has always been in connecting the dots between business value, technology and people. I built deep domain experience as I stated earlier in areas like finance and media. And paired with that with real hands-on work in automation and transformation, while it's tempting to chase the next shiny tool I have always focused on building the right foundation first solid processes, clean data, and a strong change management approach to ensure adoption and scale. For me it's always about outcomes that actually stick whether it's making work easier, unlocking new value or creating room for growth. My mindset has always been about value over hype. And I think that's definitely made a real difference in how I approach every transformation. And that has certainly given me a genuine edge.

ben parker:

Brilliant. I like that. Okay. So let's move on to the data topic then. So we're gonna look at like

kartick:

Yeah.

ben parker:

the, like when we adopt ai, the change management journey. So we're going into a bit deeper that. So this, in your expertise, what are like the most common misconceptions companies have when starting their AI adoption journey?

kartick:

One of the common misconception is that AI is plug and play. A lot of people see gen AI as a magic button but without clean data and clearly define use cases it quickly becomes more of a shiny distraction than a real solution. Another misconception that AI runs on its own. In reality, AI needs people to train it, contextualize it, and drive adoption. It augments human intelligence. It doesn't replace it. I've seen incredibly well-designed solutions technically brilliant but they failed to deliver impact simply because the teams weren't aligned, trained, or even aware why the change was happening. So you can build the best AI model in the world, but if no one uses it, it has zero value. It's like building a rocket with no launchpad. A big part of making change stick is how we communicate it. If we only talk about productivity or efficiency it can trigger fear especially around job security in today's environment. But when we shift the conversation to value creation, growth and freeing up time for more meaningful work. People start to see AI is an enabler, not a threat. And at the end of the day, AI transformation isn't just a tech rollout, it's actually a human journey. The real win is when people believe in the value it brings, and feel like they're part of the story.

ben parker:

And do you, so is it just because obviously I know stakeholders have a lot of put of emphasis on obviously especially AI now. Do you think it's a lack of knowledge or. Just trying to speed things up or should, should leaders who are AI like managers, should they take more responsibility for these misconceptions?

kartick:

I think AI is evolving at a very fast pace and if you look into LinkedIn, there is a new tool that is introduced in the market every day and every organization is trying to grapple with what's coming their way. And obviously there's like customer pressure as well who want to see AI in every solution that the organizations provide. So I think in this journey everyone's trying to figure out where they stand, so it's very important for organizations to understand their own maturity level where they are in this AI journey. It's easy to get distracted and look at shiny tools but it's very important for you to start off from the basics, figure out a kind of a valid use case. Identify the processes that, that kind of need to be redesigned. Look at data clean it, master it, ensure that the systems are integrated so that you can get good clean systematic data. And then identify the tech that solves that business case and not the other way around. So I think, everyone's getting distracted a little bit, but I think this is a time where organizations need to look at their maturity level, take a couple of steps back, create strong foundations because I always believe that you need to crawl, walk, run, and then fly. And you need to go through that journey.

ben parker:

Yeah, I think it is easy to be reactive as opposed to being proactive in. As well as just, I think sometimes you just need that breather just to think where you're at. I think you've been self, like you've mentioned, self-awareness where you're at is I think, a massive skill to have.'cause then you know where you're at, you know what direction you're at, and then you can adjust accordingly from there. Can't you?

kartick:

Absolutely. Absolutely. So I think every organization needs to do that. Check and understand where they are in this entire journey and create strong foundations. Before they can embark or accelerate in this journey. It's very important and crucial in today's world.

ben parker:

Yeah, definitely. I think I said, communication in the change management journey is so important. I think it's the biggest thing, I think where businesses struggle is the communication bit.

kartick:

Yeah absolutely. Communication is key. And as, as I said earlier you need to take people along with you in this journey. And you need to engage with folks right at the beginning of this journey, whether it be senior stakeholders, whether it's your employees who are going to see that change. Everyone needs to be taken along in this journey, and they need to be communi. They need to be communicated of what's coming their way at each and every phase of this journey, or you lose them. And without them understanding the change, no one's going to adopt the solution. How how good the design is, how good the model is. How good the solution is. If it's not getting adopted, as I said earlier, you will have just zero value.

ben parker:

Definitely. Okay. And so how can businesses align their AI adoption with real business problems then rather just chasing these trends?

kartick:

Sure. When it comes to ai, the key is to start with, as I said, real business challenges and not the flashiest tool in the market. Too often companies fall into the trap of trying to retrofit a process around a new solution. And hoping the outcomes will follow. But as I said, it doesn't work that way. So that's why what I always advocate for is a fit for purpose approach. Now start with the problem, not the tech, and identify a high impact use case, fix a broken process, clean the data, and then AI, apply AI and automation not the other way around. For example embedding AI into a media plan validation in a media agency should not be about chasing a trend. It should be about solving a real problem. Now it has the potential to eliminate around 35% of the manual effort and free up planners to focus on strategic client work. Now, that's value creation, not just automation. And it's the same across industries. In finance you might use AI for real time risk lowering in supply chain, it could predict stockouts or optimized route. But the question must always be what friction can we eliminate to unlock value? And if you follow that question, your AI roadmap will practically design itself.

ben parker:

Interesting. And it's, yeah, it just, you hear it so many times that. People trying to create a problem with their, with ai, isn't it? When it really is. What where you at? But again, going back to where are you at now? What's your biggest problem? And then how can you go about solving it?

kartick:

Absolutely. Absolutely. Mo what I have noticed is organizations just identify a tech and then try to find a use case that could be applied towards a technology because they want to prove a point. So it's or they identify a tech and then design a process around it. But the, it should be the other way around. Start off with the real problem where there is genuine issue and which is a problem across your clients, across all your markets, which is actually going to if solved it's actually going to create customer satisfaction, employee satisfaction, real value. So I think you should always start off with the business problem your use case. And then go about identifying a check once you have the process and data aligned towards it.

ben parker:

Yeah, it's, I know it just sounds, it's business basics really, isn't it really?

kartick:

Absolutely.

ben parker:

But I guess so many people get, there's so much talk going on, whether it's LinkedIn or events, it is always, the flashy toys are getting discussed and I guess either people want to get involved or they need to start getting involved'cause it's. gonna get left behind, basically. But again, you need to stay with what's your business problem at the minute. You may not need generative AI necessarily right now, or whatever your prob problem is, but in the future, yeah, it can be. It's just, you need to think of the, actually, what's gonna be the biggest impact for your business right now?

kartick:

Absolutely. No one wants to be left behind in this AI journey, so they want to make, prove themselves out. And in that mad rush obviously they take this route of identifying a tech and then going about finding a business use case for it.

ben parker:

Yeah. And I hear you hear it so much. So from your experience, what are the key human or cultural challenges businesses face during AI transformation?

kartick:

The biggest barrier in tech, as I said, it's fear. People worry about job loss, skill gaps are just not being able to keep up. And often they don't openly resist the change. They just quietly disengage. And that's a serious problem. What worked for us was creating safe spaces for learning. In our organization, we launched automation awareness programs. Internal hackathons built digital communities where people could ask questions, experiment, and even learn together. Transparency is key. Celebrate all the small wins. Share your success stories and most importantly bring employees in this journey Early. And as I always say, you just don't build bots. You build belief, and that's very important in this in this rapid evolving environment.

ben parker:

So that sounds interesting. So is it like bringing business and technology data teams together then so they can have that bounce ideas off each other and learn? I.

kartick:

Absolutely. That is what is key in this environment. You cannot create solutions in silos anymore. So in, and so ideally what you should be doing is getting your business folks, your operation folks, finance folks, technology folks in a room and then look at business cases. And then try to co-create solutions. And that's a wonderful environment wherein even operations folks start understanding a bit of technology. Technology folks understand the business lens and even the finance lens. So it's all coming together and then co-creating these solutions which could always be promoted and scaled further.

ben parker:

Yeah. And it is going that way, isn't it? Look, tech. There's tools out there that can do a lot of heavy lifting. So tech people need to become more business related. And then obviously on the business side, people need to actually start understanding the, these new tools'cause it's getting wrapped into the business processes

kartick:

Absolutely very much agree.

ben parker:

and, okay. Brilliant. Then I guess, so how could. Leaders address like approach to these problems? Like the fear, is it just more communication doing these sort of like what, like events where the teams are training together. How can leaders be approached to this?'cause obviously, like you said, there's a lot of fear in people. Also, you're gonna get the media ramping it up as well. So how can leaders go about approaching this?

kartick:

I think the most important thing is to focus on your people on reskilling and upskilling them to ensure that there is successful AI adoption. Reskilling and upskilling are just nice to have in this AI driven world. They are actually essential. You simply can't scale AI automation unless your people are empowered to work alongside it. You can't automate at scale without building a digitally fluent workforce. So you need to make education and transparency central to your chain strategy. Organizations should work towards launching an enterprise wide awareness program around automation and ai and supported by regular webinars, interactive training sessions and even internal hackathons wherever possible. Now, as I said, such opportunities would serve as co-creation labs where cross-functional teams get hands-on with tools. Explore use cases and see how automation could make their jobs more impactful. So organizations can also look towards building digital communities. Now, today, if you see, most of the organizations are on teams, so they can have teams, channels, they can have intel portals and forums where employees could ask questions, share ideas, and see success stories from their peers. Now, that kind of a grassroots engagement would help reshape the narrative from job loss to job elevation. And many employees were transform from being skeptics to champions. So I, I do see that's what leaders should actually start focusing on. How do they look at their workforce to be in this environment where they are continuously reskilled and upskilled and they take them along in this kind of AI journey.

ben parker:

I think obviously reskilling and upskilling can play a massive role in successful AI adoption. I guess for the non-technical listeners. Who, how, I guess if they wanna be a part of the AI journey again, like they're gonna feel so out their depth, what would be your advice to them?

kartick:

I myself am a non-tech employee. So when all of this. Got started like couple of years back, AI was introduced. Even I was a little bit nervous. What am I supposed to do? And it's a constant discussion that's happening I would say in the business world today. As to how the non-text folks can partner in this AI journey. So my advice to all those non-tech employees just like me. Start with curiosity. You don't need to become a data scientist overnight, but you do need to understand how AI fits into your world and how to answer the right questions. Build on that curiosity to become a domain expert. And then invest in learning to speak both languages, which is business and tech. Now, that's where the edge lies. Play the role of a facilitator what the Japanese call as an egio. Someone who brings stakeholders together, connects dots across disciplines and helps bridge the gap between strategy and execution in AI driven environments. That role is absolutely critical. Now, these are the skills that future ready professionals will need. Not just coding or deep tech, but the ability to translate, collaborate, and drive outcomes.

ben parker:

Brilliant. And then if I move to the next question then, what would you say is the biggest myth about AI and business today that you'd like to bust?

kartick:

The biggest myth that AI is a silver bullet, the truth is AI is a powerful enabler, but only when you pair it with the right problem, clean data, and a clear outcome in mind. Many executives believe that once you plug in an AI tool, be it gen, ai or predictive models it'll magically deliver insights or automate operations. But the truth is AI is only as smart as the ecosystem around it. Your data quality, your process maturity, and your people's willingness to adopt it. Another mis major misconception is that AI doesn't need human involvement. That once it's deployed it runs on its own. But the reality is AI needs human oversight training context, and judgment to be effective. It's not replacing people well, it's augmenting them. And without that human input, AI can easily go off track or underdeliver. Now, as I said earlier, I've seen companies rush into AI pilots that fail, not because the tech wasn't good, but because the foundation wasn't ready. The data was fragmented. Teams weren't trained, and the use case wasn't well defined. So AI isn't magic. It's actually a capability you build just like a muscle. You train over time through experimentation, feedback loops, and continuous learning. So if I had to sum up AI won't fix broken processes or disconnected teams, you have to fix those first.

ben parker:

Yeah. And do you think it is just people, businesses just trying to rush to get things delivered as opposed to actually getting the foundation set?

kartick:

Yeah, obviously there's a lot of customer pressure peer pressure in today's environment. Everyone wants to showcase that they are in a position to, prove out the new gen AI tool in the market, new machine learning tool in the market, predictive models in the market. So I guess there's a lot of pressure as well, but that's what I said. You need to focus and really know how mature the organization is in terms of processes, in terms of the system landscape, in terms of data. So set your foundations right and then go about proving yourself or proving out a particular tool.

ben parker:

Brilliant. Yeah, no, I think it's, yeah, I obviously it's obviously, it's always gonna be the pressure, it's always challenges in business, isn't it? It's just, I guess being able to effectively manage everyone's expectations because I guess you going over overdeliver it or underdeliver when it's, you need these certain things done. It's just if you're not, if you're so far away, you just need to be a bit more realistic, don't you?

kartick:

Yeah, absolutely. Absolutely.

ben parker:

So if we fast forward three years, what would a well transformed AI ready organization look and feel like?

kartick:

Good question. Watching how AI is evolving every day I can't help but imagine what could the workplace look like in just three years? And I've always been thinking about this, so let me paint you a picture. It's Monday morning. A finance analyst logs in with his or her coffee, opens a dashboard, and sees that Gen AI has already drafted the narrative for her month-end report tailored, accurate, ready for the person to review and refine. In the next room, you'll find a supply chain planner working side by side with a predictive model. Together they have identified a potential stock out in a key market. And the system has already suggested an optimized purchase order to fix it before it becomes a real problem. And then when it comes to media picture, there's a campaign manager watches as AI dynamically shifts ad placements in real time based on performance data. Freeing up to focus on the big picture strategy and the client relationships. No one's overwhelmed. No one's afraid. Everyone's engaged, empowered, and honestly a little excited Now, that's what I think the future feels like.

ben parker:

Cool. Nice painting.

kartick:

Yeah, of course. Yeah. Not just more efficient, more human. People co-creating with ai, not com, competing with it. And data will flow freely across teams. No more silos, no more gatekeeping. And the biggest shift, people won't be asking, will AI replace me? They'll be asking, how can I do more with it? That's how I see this getting involved in over three years time.

ben parker:

Yeah. Brilliant. So then looking back at a successful change initiative you've been involved with, what was the turning point that made it work?

kartick:

One of the most meaningful AI chain initiative I've been part of started with a simple question, how do I, how do we make AI useful? Not just impressive. We had built a prototype that brought together automation and machine learning to improve decision making in a core business process. The turning point wasn't the algorithm. It was when we focused on trust and usability. Once the business teams could see how this tool could reduce manual effort, improve accuracy, and fit seamlessly into their workflows, the momentum for adoption took off. That's a pattern I've seen repeatedly. Success doesn't come from the smartest model. It comes from how well it's integrated into everyday work how much the users trust it and how clear the value is. And that initiative taught me that success will change is less about the tech and more about how people experience that change. You need to embed the change management from day one, as I always said align your processes and data. And most importantly, build for humans, not just machines. And that foundation is what sets the stage for sustainable enterprise level transformation.

ben parker:

Brilliant. And Kartik, that's all the questions. I really appreciate your insight shared today. I think it's been extremely relevant in today's current market. And yeah, thanks for your time. It's been a pleasure having you on the podcast.

kartick:

Thank you so much for having me, Ben. It's been a blast. And to everyone listening, if you have made it to this far congratulations. You have officially survived by Ted talk on transformation and the wild ri right of change management. But in all seriousness, the future is exciting and it's us to shape. And we need just need to stay curious, stay bold and always remember transformation isn't a one-time project, it's actually a mindset. So until next time, take care and keep building forward.

ben parker:

T thank you.

kartick:

Thank you so much, Ben