AI Leadership Vs Automation: The 4 L’s Every Modern Manager Must Know with Praveen Kamsetti

How AI Is Reshaping Leadership: The 4 L’s Framework Explained with Praveen Kamsetti #aileadership #empatheticleadership #futureofwork

In this episode, Praveen Kamsetti breaks down how AI is transforming leadership, accountability, and business decisions. With over 20 years of experience in IT, Praveen shares practical insights on applying empathy in an automated world. Please visit our website to get more information: https://swangroup.net/ 

He explains his Four L’s of leadership, a model he’s used to help teams navigate uncertainty and transformation. From human-in-the-loop systems to real challenges like poor data quality, this conversation focuses on what it takes to lead in a tech-driven world while keeping the human element alive.

We also cover key themes like leadership in AI, data governance, ethical implementation, and why some AI projects fail. If you care about the future of responsible AI and leading with empathy, this is for you.

🔔𝐃𝐨𝐧'𝐭 𝐟𝐨𝐫𝐠𝐞𝐭 𝐭𝐨 𝐬𝐮𝐛𝐬𝐜𝐫𝐢𝐛𝐞 𝐭𝐨 𝐨𝐮𝐫 𝐜𝐡𝐚𝐧𝐧𝐞𝐥 𝐟𝐨𝐫 𝐦𝐨𝐫𝐞 𝐮𝐩𝐝𝐚𝐭𝐞𝐬.
https://www.youtube.com/@Biotech_Bytes/?sub_confirmation=1 

🔗 Stay Connected With Us.
Linkedin: https://www.linkedin.com/company/the-swan-group/ 
Website:  https://swangroup.net/   

=============================

🎬Suggested videos for you:

▶️ https://www.youtube.com/watch?v=T6EzJ1F_6pg 

▶️ https://www.youtube.com/watch?v=be8szNVFrNk 

▶️ https://www.youtube.com/watch?v=_Be6WEEy2JM 

▶️ https://www.youtube.com/watch?v=mqpB3pGywkU 

▶️ https://www.youtube.com/watch?v=w9QyuG6p3Ys

=============================

#aileadership #ethicalai #techmanagement #empatheticleadership #futureofwork #humancenteredtech

Chapters

• 0:00 Introduction
• 1:11 About Praveen Kamseti
• 4:56 How AI fits into business today
• 6:42 The role of governance in AI decisions
• 10:18 Human-in-the-loop and explainability
• 15:07 Why most AI projects fail
• 25:50 Praveen’s 4 L’s of leadership
• 30:44 Accountability in flat teams

Transcript

Steve Swan [00:00:00]:
Hi, I'm your host Steve Swan with Biotech Bites. Tune in to the next episode with me and Praveen Comsetti where we talk about AI and then we talk about Praveen's tried and true model of management success is four L's. Hope you enjoy. Welcome to Biotech Bites where we talk to IT leaders within biotech about current trends and their thoughts and feelings around them. I'm your host, Steve Swan, and today I have the pleasure of being joined by Praveen Kamsetti. Praveen, thank you for joining us today.

Praveen Kamsetti [00:00:34]:
Thank you, Steve. Thanks for having me here. I'm excited now.

Steve Swan [00:00:38]:
Good, good, good. Well, I love your background. It's my first virtual background I've been able to see on this platform. So thank you very much for doing that for us.

Praveen Kamsetti [00:00:47]:
Yeah, that's how the technology leaders work, right?

Steve Swan [00:00:50]:
That is how the technology leaders solving the problems. Very good. I like it. Well, so Praveen, what I always like to do at the onset of the podcast is just to give our listeners a quick sort of synopsis of you. So why don't you give us a quick rundown on you and how you got to, you know, the, the leadership role roles that you've been in in the recent past.

Praveen Kamsetti [00:01:12]:
Yes, very good. So my journey started in this country back in 1999. Steve, born in India, I did my engineering there.

Praveen Kamsetti [00:01:20]:
I. Right.

Praveen Kamsetti [00:01:21]:
And then I moved to this country in 1999. I moved to Big Apple. That's in New York City.

Praveen Kamsetti [00:01:26]:
Right.

Praveen Kamsetti [00:01:27]:
I worked for the financial industry, insurance industry for almost like a decade there. And then I moved to healthcare industry, as in a Stryker, which is a medical device company. I got the leadership role there too. I can talk about that later. But. And then I moved to pharmaceutical company, which is a Novartis, it's a biomedical research firm in Cambridge, Massachusetts. In 2016, I moved to Austin, Texas. I worked for the data analytical company and then now in Austin, I work for the microwave backhaul communication system company heading their IT department.

Praveen Kamsetti [00:02:11]:
So all these years, almost 25 plus years working in various diversified industries. Right. You know, financial industry, pharmaceutical, healthcare industry, which is basically very regulated industries. Right. So I kind of got into these very disciplined environment. The other part of it is I was very fortunate and lucky to work with one of the finest leaders in the industry during the very early stages of my career. So the financial industry worked with some of the leaders. They later on became the top executives in the United States.

Praveen Kamsetti [00:02:53]:
So I was always into the people person, always into the curiosity how things Work. So when I worked with these finest leaders, they kind of identified that I have some leadership roles and that's how they encouraged me into leadership roles I got into. That's how I came in from last 24 years and then today heading the IT department for close to half a billion dollar company. That's where my journey.

Praveen Kamsetti [00:03:21]:
Very good. Cool.

Steve Swan [00:03:22]:
Very good. Thank you.

Praveen Kamsetti [00:03:23]:
Thank you.

Steve Swan [00:03:24]:
So to, to. To kind of take that time frame, right. And think about what's been going on in IT and technology over all that time. A lot's changed, right? Yeah. Saw the Internet come and, and Y2K and all that stuff.

Praveen Kamsetti [00:03:40]:
Right.

Steve Swan [00:03:41]:
But more recently we've had some, I think developments in, in the industry, in, in the regulated industries, whether it be finance, whether it be pharma, whether it be medical devices, what have you. But what are your thoughts and feelings around some of the things that are going on now and how do you feel about where we are right now?

Praveen Kamsetti [00:04:02]:
Right.

Steve Swan [00:04:03]:
I guess maybe I'll start with that.

Praveen Kamsetti [00:04:04]:
Yeah, I think it's a great transformation from last to 24 years.

Praveen Kamsetti [00:04:09]:
Right.

Praveen Kamsetti [00:04:10]:
The technology. So in a very simple word, technology used to be a cost center before.

Praveen Kamsetti [00:04:17]:
Right.

Praveen Kamsetti [00:04:17]:
The it now it's great to see that in 25 years in my journey that technology has become part of the business now.

Praveen Kamsetti [00:04:26]:
Right.

Praveen Kamsetti [00:04:27]:
So we are enabling the technology for the business growth to take the competitive edge in the market.

Praveen Kamsetti [00:04:33]:
Right.

Praveen Kamsetti [00:04:33]:
That's where the transformation happened.

Praveen Kamsetti [00:04:36]:
Right.

Praveen Kamsetti [00:04:37]:
So that transformation is a long journey.

Praveen Kamsetti [00:04:40]:
Right.

Praveen Kamsetti [00:04:41]:
If we look at, in my career from mainframe systems in the financial industry.

Praveen Kamsetti [00:04:46]:
Right.

Praveen Kamsetti [00:04:46]:
From client server technology to.

Steve Swan [00:04:48]:
Which they still have, by the way. They still have the.

Praveen Kamsetti [00:04:50]:
Yeah, we still have. It's working.

Praveen Kamsetti [00:04:51]:
Right.

Praveen Kamsetti [00:04:52]:
And then there is ERP transformation happened and then the infrastructure modernization we have and then it went from, you know, your own data centers to cloud computing, right. Where you can take some advantage of cloud offering edge computing. And today we are in a stage where we should be able to leverage the big buzzword in the industry, which is artificial intelligence. So I think a lot of things have changed Steve, in this one. Not just the productivity wise. We are in a situation where we are going towards the agentic AI which means that AI should be able to take some decisions for us.

Praveen Kamsetti [00:05:34]:
Right.

Praveen Kamsetti [00:05:35]:
There is no more a blind decision anymore. We do have a data enough of data processing power to make a data driven decisions and solve some of the world's, you know, big problem.

Praveen Kamsetti [00:05:47]:
Right.

Praveen Kamsetti [00:05:47]:
Whether it's a healthcare problem.

Praveen Kamsetti [00:05:49]:
Right.

Praveen Kamsetti [00:05:49]:
Whether it's a supply chain problem. I think we are in the right shape and Right format, right direction, how we transform from industry, transform from two to five years to today.

Steve Swan [00:06:00]:
Let's talk about that for a minute. The whole AI transformation, right? I talk to a lot of leaders, right, and they have a lot of different angles on how it can be used or should it be used, some of the rules around it being used, so on and so forth. But globally, I mean, do you believe that in the near future going to start replacing folks? Is it going to enhance folks? Is it just going to be a tool that we use for a long time as something that, I don't know, helps us writing and doing analytical work? Tell me where you think it fits in now and in the future.

Praveen Kamsetti [00:06:34]:
That's a great question, right? This is everybody's questions today.

Steve Swan [00:06:37]:
So it is, it is.

Praveen Kamsetti [00:06:39]:
So what it can AI can do, it has a lot of potential, right? With the unprecedented speed and scale, it can process the data. So it has a lot of potential. It can probably make a lot of world problems to solve, right? Especially in healthcare industry, as long as we have a guardrails put in place for us, a good governance put in place, whether it's from government side, whether it is from the internally, from within organization, right? So my take on is AI has a lot of potential, AI can help augment, right? So but there must be some kind of governance, right? So if you look at the framework, ISO 4200 framework we have, right? AI100NIST has some frameworks, right? And every organization, you know, healthcare industry has internally their own governance, right? The guardrail. So as long as we have a right guardrails in place, AI can make our things better and help us to solve the problems. These are the big problems, not this, not the small problem. Very complex healthcare industry problems, very complex supply chain problems. It has definitely will help us transform another decade. But it's just that as any leaders, it's a leader's responsibility to make sure that we have that collaboration between machine and man to just to make sure we have proper guardrails in place.

Steve Swan [00:08:06]:
I feel like some groups, whether it's companies or individuals or groups within companies or departments within companies. Now this is Steve Swan talking. I feel like they're out over the front of their skis a little bit, right on this thing. I think that it feels to me like some are either A being pushed from the higher levels who think that it can do more than it can, or B are buying into maybe some sort of hype that might not be there yet, but we'll get there, you know, so some of it to me feels like some folks are just out in front of themselves and, and, and, and why they putting too much emphasis on this, are they? I'm not quite sure how to phrase that. But you know, it just feels like some folks are trying to overutilize where they, where it's just not capable yet.

Praveen Kamsetti [00:08:57]:
You know, I think it's right, right. There are both ways. Right. There are some, you know, folks, leaders also that trying to push the product out. Product out. There are some folks who wanted to make sure that when we make a product, make sure that we have a proper ethics in place for AI, especially in healthcare industry.

Praveen Kamsetti [00:09:19]:
Right.

Praveen Kamsetti [00:09:20]:
So my take on is when you make a decision with the AI, especially in a financial side of it and you know, healthcare industry, we should be able to transparently tell how we made the decision and why we made the decision.

Praveen Kamsetti [00:09:34]:
Right.

Praveen Kamsetti [00:09:35]:
So for me that transparency builds the trust. You know, that trust is between employees, stakeholders, even more importantly with your customers. So as long as we have that explainability in place for AI, especially in these two industries, I am talking about healthcare and financial industry because that can make a big difference for the individuals.

Praveen Kamsetti [00:09:57]:
Right.

Praveen Kamsetti [00:09:58]:
So that's what my take on it. So you have to have some kind of explainability in place and that's where I call this as hitl. Human in the loop.

Praveen Kamsetti [00:10:10]:
Right.

Praveen Kamsetti [00:10:10]:
So when you make a decision with the AI, somebody has to review it is the right decision or not. And then we should be able to tell that why it is made that decision. Like the AI has a lot of, like I said, it has a lot of potential but it has some challenges. Right. For example, arithmetic bias. Right. Whether it is an hiring process, whether it is in a financial industry where you make the decisions on loans or credit scores. Right.

Praveen Kamsetti [00:10:35]:
Whether it's in a healthcare industry. So that's where you kind of have that guardrail in place and at the same time you have that hitch, the human in the leap loop process. Then you're, you're solving a lot of problems.

Steve Swan [00:10:48]:
I think that it's, you know, like you said, human in the loop. Right. So I mean, I think that's great. I love that. I haven't heard that yet. So with the human in the loop, I mean, I think that what we're doing, in my opinion, based on what I've seen is where we are, where we should be right now. Where let's say Steve Swan got an eight hour day. He's the human in the loop.

Steve Swan [00:11:09]:
He's using AI, he takes AI and AI's taken two hours of his day. Because it's taken some tasks that are kind of lower level tasks, whether it's reviewing contracts or whatever it is.

Praveen Kamsetti [00:11:20]:
Right.

Steve Swan [00:11:20]:
So free Steve up for another two hours a day. So his, his eight hour day got cut down to six. But then he can focus on higher level, higher ROI tasks Right. Later on down the road. And I think that that's, I feel that that's where we are, you know, as opposed to, like I said, being out over our skis where we're replacing people again. Maybe someday we'll get to that. But right now I think it's human in the loop. It's helping humans as opposed to replacing them.

Praveen Kamsetti [00:11:45]:
Right.

Steve Swan [00:11:45]:
You know.

Praveen Kamsetti [00:11:46]:
Yeah. I think, I think at the end of the day, Steve, the technology should be betterment of human.

Praveen Kamsetti [00:11:53]:
Right, Right.

Praveen Kamsetti [00:11:53]:
It should help humans. Right. Not to replace. I strongly believe that AI will help augment the human force rather than replacing. There may be some situations where probably can be replaced some of the jobs.

Praveen Kamsetti [00:12:08]:
Right.

Praveen Kamsetti [00:12:08]:
Very. Some of them. But the plus point there is once you have this upskill people, the resources you have, if you can upskill them and you can definitely augment it rather than replace you.

Steve Swan [00:12:22]:
Yeah. Just like everything else. Right.

Praveen Kamsetti [00:12:25]:
That transition has to happen. The transition is super important.

Praveen Kamsetti [00:12:28]:
Important.

Praveen Kamsetti [00:12:29]:
That's why the IT leaders or any business leaders, it's their responsibility. I feel that you know that making sure that your teams. Right. Your organization go through the transition process and if you have to upscale some people. Yes, we should do that and that will help us.

Praveen Kamsetti [00:12:44]:
Right? Right.

Steve Swan [00:12:45]:
Yeah. And I've had some leaders talk about like you talked about having that human in the loop and then. But being able to have a set of rules or understanding how AI made their decision to make it explainable, to make it consistent. And some of the leaders that I talked to say that they should even they being AI should even be included in when. When the testing and things go on with AI tested, as it almost said. Well, not almost as if it's an employee because you're on the hook as if it were an employee. You're responsible, Mr. Leader, for the decisions that AI makes.

Steve Swan [00:13:19]:
Right?

Praveen Kamsetti [00:13:20]:
Yeah.

Praveen Kamsetti [00:13:21]:
It is a super important that readers should take some responsibility on this one. Otherwise it can damage the reputation of the organization.

Praveen Kamsetti [00:13:30]:
Right.

Praveen Kamsetti [00:13:31]:
And individual damage is one that's going to be irreversible damage. Sometimes you can make it, especially in healthcare industry, but even for the organizations it's a reputation issue. So whatever decisions we make, which is good, but making sure that you review that process with your HITL or Whatever guardrails you have. So take out that arithmetical bias process from the decision making.

Steve Swan [00:13:53]:
Now to step back a little bit. We all know that, I mean the old adage garbage in, garbage out, right? So we all know that it's only as good as the data that we put into it, right? So each organization puts in its own data, right? So it learns from its own data, whether it's images, whether it's resumes, whether it's tabular data, whether it's contracts, whatever it is. So they put all their own data in, which makes each one of them, you know, individuals. But I guess my question to you is, you know, a lot of organizations seem as if this is going back to my experience and my conversations. A lot of 80% of these projects are failing right now, these AI projects, because I think, because data's not ready, folks, aren't they? Build the shiny, cool, awesome best thing. You know, they got the Ferrari, but they don't have any gas for the motor, right?

Praveen Kamsetti [00:14:49]:
Yeah.

Steve Swan [00:14:50]:
So what are your, what are your thoughts around that? I mean, how have you. I don't know, how have you tackled that? Or has that been something that you've been able to address or. I don't know, just give me your thoughts there.

Praveen Kamsetti [00:14:59]:
It's a great question. So I actually a couple of weeks ago I wrote an article in LinkedIn about it.

Steve Swan [00:15:04]:
Oh, really? Okay.

Praveen Kamsetti [00:15:05]:
How do we protect these most intelligent systems, right. In these AI systems? So if I look at it, Steve, there are at least three different areas we have problems right, from, especially from the data point of view. If you look at the agents, right. You know, the agents where the productivity right. Deficiency comes, for example, Microsoft Copilot and Gemini from Google, all these agents, they're working very well. People are, you know, everybody are taking, leveraging the technology. It's fantastic, right? They're loving it improves your efficiency, your productivity. There's no caution, but there are some challenges, like especially the data, right? There is a problem if the sensitive data leakage happens.

Praveen Kamsetti [00:15:46]:
Like you said, everything comes from out of the data. Data is a key ingredient component in AI. So if you leak, if there is a problem of sensitive data leakage, that can be personal data, it can be financial data, it can be your intellectually property data, right? So you need to have your secured environment for data leakage, right. Whether it's your technologically or process wise. Organizationally, there are a lot of things we can talk about it, but that's one area, sensitive data leakage. And there is the biggest problem for the data Which I think it's going to be a problem if we don't address that is poisoning the model. You know, today we have a lot of data models, right? Functional Data models, right. LLMs, a lot of LLMs.

Praveen Kamsetti [00:16:36]:
If we have a poisoning of data, right. In whatever way they could.

Praveen Kamsetti [00:16:39]:
Right.

Praveen Kamsetti [00:16:40]:
Then we're making all bad decisions, right. Every decision you make with AI, you have to protect that not happening. There is another way is injection attacks. I talked about in my article as well. How do we. People can make giving the prompt, injection different. Different prompts getting out of the data, which you are not supposed to. Right.

Praveen Kamsetti [00:17:00]:
So all these are all telling us that data is super critical and not just for making the decision, but even protecting the data and model itself is important. And sometimes people. There's another attack people probably don't talk about is, you know, putting the triggers in the data itself.

Praveen Kamsetti [00:17:19]:
Right.

Praveen Kamsetti [00:17:20]:
This data is not a poisoning, but there is a trigger. They put it in that. So when you make, you know, prompt something and then it probably gives based on what they put a trigger inside what the design.

Praveen Kamsetti [00:17:31]:
Right.

Praveen Kamsetti [00:17:31]:
So there are a lot of data challenges. So as a leader, I think it's super important to make sure that your data is filtered or right data. And it's not just one time, right. It's ongoing effort continuously. You monitor the data, audit your data.

Praveen Kamsetti [00:17:46]:
Right.

Praveen Kamsetti [00:17:46]:
You know, use encryption and technologically encryption and whatnot. But in terms of. As a leader, I think auditing every, you know, regularly monitoring your data and keeping the data is probably the biggest challenge going forward.

Steve Swan [00:18:01]:
Well, that's one of the big mistakes I see people make. And they don't, maybe they don't know they're making it. I gotta tell you, and coming from me, I mean, who am I, right? But like you just said, continually monitoring their data. I mean, your data set's a living and breathing thing, right?

Praveen Kamsetti [00:18:15]:
It's always changing like oxygen for you.

Praveen Kamsetti [00:18:17]:
Right.

Praveen Kamsetti [00:18:17]:
It's like oxygen for you. And if that oxygen has got corrupted, then everything goes wrong.

Steve Swan [00:18:22]:
Yeah, because they, they, some of the folks think they develop their data, put their data together, if it works, leave it alone. But that's not. You can't. Yeah. You're in trouble if you're doing that because now all of a sudden you're, you're. Something's getting to your point, you know, something's going to happen down the road or it's, it's. Things are going to get all twisted up because it's going to. It continues to feed data into itself as it, you know, puts all that data together, those are new data points coming in.

Praveen Kamsetti [00:18:48]:
You know, that's why the hitl, the human in the loop, right? Makes a lot of sense when you're making a big decisions and especially for the people's lives, right? And that impacts on the people's lives. So it's super important to have hitl, they were auditoring, auditing in place, monitoring, continuous monitoring and guardrails. I think that's a key for AI success.

Steve Swan [00:19:11]:
Yeah. Well, so just as an anecdote, I had one leader come to me and then I'm just, and maybe I'll ask you this question. So think about this for a sec. So I had a leader come to me, he said, listen, you know, I've got these directors say of data science, right? And my data, which is good, but I, I have these directors and such going in and triaging my data as, as I need a triage. And I said, listen, you, whatever you're spending on those folks, a lot of money, 200, 250, whatever the number is, that's too much. You don't need that person to triage your data. I said, you know, there's kids that come out of school that are data science majors and you could probably pay them half that or less than half that. You know, put them in a two or three year program or two year program where they're doing that for you and then you know, move them into another group or into it, but have sort of a, I don't know, make that your minor leagues or something.

Steve Swan [00:20:00]:
I don't, this is just me, you know, and, and kind of go, you don't need to spend that, that kind of horsepower on triaging your data, but you do need to take care of it, you got to babysit it. And somebody at that level would be glad to do that, you know, and they can do that. You know. What are your thoughts on a program? Something like that?

Praveen Kamsetti [00:20:19]:
I think it's important, right? It's super important to guard the data, protect the data, right. And then people like, you know, who can continuously monitor, if you have that human touch on top of it, to making sure that we're making the right decision, protecting our data, filtering the right data problem. I think that's, that's going to help, right? At the end of the day, like I said, you know, AI should help humans, right? It's not to replace the humans, make humans life better, right? Societal betterment, that's what I call it as. And that's the leader's responsibility, Steve.

Steve Swan [00:20:53]:
Absolutely. 100% yeah, no, and then. But like I said earlier, I do feel pressure. I do feel it from some of my IT leaders where they're getting pressure from up above. You know, my friends, I heard about it on the golf course, my friends are making a lot of money using AI or they're replacing a lot of people and that's not the case. You know, it's just not a lot.

Praveen Kamsetti [00:21:16]:
Of times, you know, AI can do a lot of IT can do wonders as long as you, you know, cautiously implement it.

Praveen Kamsetti [00:21:23]:
Right.

Praveen Kamsetti [00:21:23]:
Don't just rush it. You know, there are areas where you can implement right away like productivity wise we can. But when you are making the decisions, that's where.

Praveen Kamsetti [00:21:31]:
Right.

Praveen Kamsetti [00:21:31]:
You know, if you're writing some, you know, marketing analysis, something that you can instead of taking four hours, it get cut down to an hour. Yeah, that's great.

Praveen Kamsetti [00:21:40]:
Right?

Praveen Kamsetti [00:21:41]:
If you are reviewing, you know, the workflows and instead of manual work, make that as automated to, you know, cut it into one third of your time, great. But when you are making the decision on your, you know, healthcare X rays or your records, and that's something that we need to be really careful because one is you need to have a proper data, making sure the data is correct. Second is you make sure that you don't have algorithmic bias included intentionally, unintentionally in your decision. And that's where somebody has to review that. That's called HITL for me also too.

Steve Swan [00:22:18]:
You know, remember that we all have to get to it, but from an AI perspective, lots of organizations don't even still allow folks to indulge or use it.

Praveen Kamsetti [00:22:28]:
Right.

Steve Swan [00:22:29]:
Because they're too scared of using any data breaches or any technical, you know, whatever it is. But eventually you're gonna have to get there. You know, I mean, I've had some leaders say to me, listen, I don't want to do it, but I gotta do it because they're gonna have a machine over here, right? They're gonna be doing. So they're gonna use it either way.

Praveen Kamsetti [00:22:46]:
You know, I think it's a transition, Steve. Everybody, every leader, I can tell you that everybody wants to have these, what I mentioned, the, the guardrails, the governance. Right, yeah, the hit. Every leader wants to do that. Some wants to move a little quicker, some wants to take a little cautious approach. It's because there's a learning curve. We are in the transition curve. We are in, I think in couple of years from now I think people will be sorting out all these data related issues.

Praveen Kamsetti [00:23:12]:
But again, it's Not a one time, it's always continuously monitoring. But we are in a better shape in a couple of years. People have all these guardrails built in. People realize that the cautious approach of AI is better for the results. Making sure that your data, your intellectual property is protected.

Praveen Kamsetti [00:23:30]:
Right.

Praveen Kamsetti [00:23:30]:
Your PIA data is protected. But it's just transition. I think that like any other technology takes a transition when it comes up. Right. Especially things like AI, which can have a lot of potential. So the transition is a little complicated, but I think we'll get there.

Steve Swan [00:23:44]:
So you believe in it to the point where let's put guardrails in place, let's do it at a measured pace. Because I have some that don't do it. I have some that say let's do it and let's just let everybody beat it up and keep beating it up. And that seems like maybe a little too much, right?

Praveen Kamsetti [00:23:59]:
Yeah, it's definitely a little too much rushing it. I am in the middle of it. I want to leverage this technology. I want to make sure that we use for the betterment of the, solving the problems. I do believe that it's a lot of potential to solve a lot of problems. We have. The only thing I will tell you is just to make sure that we have a proper guardrails in place like any other technology. That's all I believe in.

Praveen Kamsetti [00:24:22]:
And that cautious approach will help for the better results, for the long term results also.

Steve Swan [00:24:27]:
Yeah, sure. Well, I mean the governance, right, the governance of it, you know, the boards of directors and such are real interested in that right now. You know, thinking about how we're going to watch this and then the security of it. I mean, I've had people call me and you know, talk about security of AI, but I don't think they mean typical. When I listen to them and I talk to them, they're not talking typical cyber security. What they're really talking about, data security. You know, if you boil it down, you know. Yeah, they don't know that, but that's what they're talking about.

Praveen Kamsetti [00:24:55]:
That's what they're talking about. And I actually did. It's a good point. I actually did. Recently there's a course I did, it's called AI Empathy and Ethics. It's fantastic. Oh yeah, yeah, that's good.

Steve Swan [00:25:06]:
And you. So you, you did, you did the course?

Praveen Kamsetti [00:25:10]:
Yeah, I did the course. Yeah, I did the course. There's a course, I think it's from University of Pennsylvania, Upenny.

Praveen Kamsetti [00:25:16]:
Yeah.

Steve Swan [00:25:17]:
Is there, are there any, are there any links to that can we, can, can our listeners find that anywhere? Can they see it anywhere? Is there a YouTube? I don't know.

Praveen Kamsetti [00:25:24]:
Yeah, I can send it to you. I don't know that they're offering now, but I can send it to you.

Steve Swan [00:25:28]:
Yeah, send me something and I'll attach the link to this. I mean, why not, right?

Praveen Kamsetti [00:25:31]:
Absolutely, yeah.

Steve Swan [00:25:32]:
It's great stuff.

Praveen Kamsetti [00:25:33]:
Yeah.

Steve Swan [00:25:33]:
I mean, the more I don't know. And if someone doesn't want to read it, they don't have to read it.

Praveen Kamsetti [00:25:37]:
Right.

Steve Swan [00:25:38]:
If they want to, at least we can, you know, quench their thirst. Right.

Praveen Kamsetti [00:25:42]:
So I'm a big believer in empathy. If you look at my LinkedIn or my leadership style is I created a 4L leadership framework. I call it as 4L leadership framework, which I practice and demonstrate every time.

Praveen Kamsetti [00:25:58]:
Right.

Praveen Kamsetti [00:25:59]:
So the four L's is L lead with empathy, lead for business results, lead by example, lead with emotional intelligence. So this is a framework, I've been, you know, practicing this for almost like two decades now. Fantastic results for, you know, bigger goals, for long term results. Not just for me as a leader, even for the team, even for the business, it transforms you who are achieving the bigger goals. I think even now it's even more with the AI, it's a disruptive technology, right. Like you said initially when we started this, that oh, is it going to replace the human?

Praveen Kamsetti [00:26:36]:
Right.

Praveen Kamsetti [00:26:37]:
So there's a lot of anxiety, right. When you have this big disruption, technology comes in. I think as a leader, the best way to lead them with empathy, right? But when you have that empathy with the, you know, lead with the business result, empathy with accountability. That's where my second part, which is lead with the business results. So you will get a wonderful results.

Steve Swan [00:26:57]:
And you've been practicing this, your, your four L's for a while. Yeah, yeah, yeah. Good, that's awesome. And so I guess part of my questions when I talk to folks that you just led right into it, you know, what makes working with and for you different. And you just gave us a good entree into that. Right. You know, leading, leading with, leading with that kind of stuff. I mean, I don't hear that every day.

Steve Swan [00:27:18]:
You know, like I said, you know.

Praveen Kamsetti [00:27:20]:
When I started my career in the very early stages, I worked for one of the finest, finest leaders in the industry, which I'm very fortunate for that. And that's what I learned from the leaders. Right. When you are working for the big company, big changes, you want to, you want to drive the bigger results, right? Bigger teams and make some impact on, from the business point of view, the best way to influence and lead your team is with empathy. And as long as the empathy has your accountability associated with that, you will see a wonderful results.

Steve Swan [00:27:52]:
You gotta have accountability, otherwise what are you doing?

Praveen Kamsetti [00:27:54]:
Yeah, of course.

Praveen Kamsetti [00:27:55]:
Yeah, yeah.

Praveen Kamsetti [00:27:56]:
And even for the, you know, I have these mergers and acquisition experience and when you have mergers and acquisitions, same thing goes on, Steve. Like, you know, people are very anxious. You know, a lot of ambiguity goes on.

Praveen Kamsetti [00:28:06]:
Right.

Praveen Kamsetti [00:28:06]:
Mergers and acquisitions happens with a lot of unknowns.

Praveen Kamsetti [00:28:09]:
Right.

Praveen Kamsetti [00:28:09]:
That is truly unknown. So you don't know.

Praveen Kamsetti [00:28:11]:
Right.

Praveen Kamsetti [00:28:12]:
And that creates a lot of anxiety on the people.

Praveen Kamsetti [00:28:14]:
Right.

Steve Swan [00:28:14]:
It's awesome.

Praveen Kamsetti [00:28:15]:
Best way to lead during that time is empathy. Lead with empathy for, with accountability and use a communication as your empathy tool and you will see wonders.

Steve Swan [00:28:26]:
You know what I've seen some places do and this. I'm just kind of, my head just goes to. I've been doing this for a long time, 26 plus years.

Praveen Kamsetti [00:28:32]:
Right.

Steve Swan [00:28:33]:
And so sometimes I see companies where essentially everybody leads.

Praveen Kamsetti [00:28:39]:
Right.

Steve Swan [00:28:39]:
There's no, there's no. If everybody leads, nobody leads. That's kind of what I always say when, when I hear that. It's a group consensus. It's always a consensus.

Praveen Kamsetti [00:28:47]:
Yeah.

Steve Swan [00:28:47]:
Let's say I'm in an organ and I'm totally sidetracking here because my head just went there. Let's say I'm in a group like that, I'm in a team like that. But I want to have accountability. Can I have accountability in a team like that like you're talking about? Probably not. Right? Not, not, not, not really measurable accountability. Can I?

Praveen Kamsetti [00:29:03]:
So when you have, in a situation like this where there is a. I'm, I'm guessing that you're talking about, or at least I'm understanding that you're talking about a flatter organization.

Steve Swan [00:29:12]:
Yeah, yeah. Or they're trying to be. They're not.

Praveen Kamsetti [00:29:15]:
We see that.

Praveen Kamsetti [00:29:15]:
Right.

Praveen Kamsetti [00:29:16]:
Especially when, you know, mergers and acquisitions happen. A bigger company, smaller company, that's the cultural difference we see. You know, you have a lot of these, you know, organization structure in the bigger companies and smaller companies probably have that flash structure.

Steve Swan [00:29:31]:
Right.

Praveen Kamsetti [00:29:32]:
The best way to deal with that, Steve, which I got fantastic experience on this one, is making sure that your goals are clearly defined for individuals, for teams. So when the goals are clearly defined and you make the unified goal driven approach with your communication, then you should be able to get that.

Steve Swan [00:29:53]:
Okay.

Praveen Kamsetti [00:29:54]:
You need to make sure that your goals are defined and you know, drive those goals.

Steve Swan [00:29:58]:
Everybody's going.

Praveen Kamsetti [00:29:59]:
Direction.

Praveen Kamsetti [00:29:59]:
Yeah.

Praveen Kamsetti [00:30:00]:
Otherwise, like you Said, you know, people don't take that accountability.

Steve Swan [00:30:03]:
Yeah. Then you don't know where you're going.

Praveen Kamsetti [00:30:05]:
Yeah. And then the other one is, you know, when you have that kind of, you know, cultural difference between you make, make sure that you assess the culture before, you know, when you take it into, you know, what kind of culture that company has, what kind of structure they have.

Praveen Kamsetti [00:30:18]:
Right.

Praveen Kamsetti [00:30:19]:
The values, the working style. So once you have that in place, once you understand it, then put a proper goal and making sure that you have alarms for your team altogether, and then you should be able to drive that change. That's a big. It's a challenge. Especially when you have that different culture.

Praveen Kamsetti [00:30:36]:
Yeah.

Steve Swan [00:30:36]:
And the bigger the organization, I'm sure. More the challenge. Yeah, absolutely.

Praveen Kamsetti [00:30:40]:
Yeah.

Steve Swan [00:30:41]:
So. Well, great. So now I always have one, one question that I usually ask folks right near the end. It's the same question for everybody. So if you watched any of my podcasts all the way through, you'll know what that is. But before I get to that, what other trends or things do you think we should be thinking about within, you know, technology to our, to our industries here and any other trends, any other things we should, in your opinion that you want to, that you want to chat about here today?

Praveen Kamsetti [00:31:07]:
I think technologies are. Will come, but I think AI has probably just started doing it. AI will have a lot of things right today. Majority of the applications or majority of the usage of AI technology in just very early stages of the productivity, efficiency side of it. We are still not there yet. Agentic AI, where AI itself is making the decisions. I think that's going to be a big trend in probably next two to five years.

Steve Swan [00:31:40]:
Yeah, they're trying to get to that.

Praveen Kamsetti [00:31:42]:
Yeah. I know a lot of times we hear people talking about AI is writing the code, which is all right, but I don't think that's in mainstream yet. It's in for technology companies. But if you look at, in supply chain companies and, you know, traditional areas, we still have a lot those are not early adopters yet. They're taking cautious approach. So. But a lot of potential for AI to make. Think about it, if you can optimize supply chain, that will dry down your costs.

Praveen Kamsetti [00:32:14]:
Right.

Praveen Kamsetti [00:32:14]:
Your efficiency will go up. So supply chain optimization will be a big one when you go going forward with the agentic AI. Yeah. And probably the other areas is maybe we should be looking into AI not just for the bigger organization, but even for the edge computing people can do something. Today it's super expensive to build your own infrastructure. So if you can bring down that GPUs and all that to the lower level where individual can have. That probably is going to take five, 10 years going forward, but I think it's going to come.

Steve Swan [00:32:53]:
Yeah, yeah. Well, I mean, you know, all the companies that utilize all those things, the infrastructure for example.

Praveen Kamsetti [00:32:59]:
Right.

Steve Swan [00:32:59]:
I mean they're not technology companies, they're. They're transportation companies or logistics companies or pharmaceutical companies or whatever it is, you know, so they don't need to be doing all that. Right, yeah.

Praveen Kamsetti [00:33:10]:
And then people today, you know, yeah, you can write a code but if you have an intellectual property at risk and they're still not going to the AI approach yet, probably it's going to take, take little. Yeah. So those are all the trends we see in next two to five years.

Steve Swan [00:33:25]:
I had an instance with one of my interviews with one of my CIOs where he told a story about messing around in the early days, this is about a year and a half ago with chat GPT and he was playing and you know, doing his thing. Up popped the intellectual properties, the, the basically the, the formulas for competitive pharmaceutical company, one of their competitors and their formulas and stuff. I mean we're talking your proprietary data and.

Praveen Kamsetti [00:33:53]:
Yeah, yeah, that's a different property data.

Praveen Kamsetti [00:33:55]:
Right.

Praveen Kamsetti [00:33:55]:
It's not just, if you look at that into monetize that it's like billions of dollars of. Trillions of dollars.

Steve Swan [00:34:01]:
Yeah, he took it, he took a screenshot, a couple screenshots, got it off to the CIO and said I think you got a little issue here. You know, and they tackled it, they.

Praveen Kamsetti [00:34:10]:
Got rid of it.

Steve Swan [00:34:10]:
But still, you know, that's, that's everybody's nightmare right there.

Praveen Kamsetti [00:34:14]:
Right?

Steve Swan [00:34:14]:
You know.

Praveen Kamsetti [00:34:15]:
Yeah, that's everybody's nightmare. But like I said, you know, I think we are transitioning to that area. Once we have those guardrail, the security data cleaning everything is in place. That trend will come into the picture where people can take, you know, a decision saying hey, we should be able to safely go ahead and implement some of the AI technologies safely without any compromise of the intellectual property, without any data sensitive data leakage. So that's where the big advantage of the technology.

Steve Swan [00:34:45]:
Yeah, yeah, absolutely, absolutely. So, all right, I got one final question for you. All right. It's more of a personal kind of question. So I ask it of everybody. So I like music, I like going to see live music, I like going to see concerts and things like that.

Praveen Kamsetti [00:34:59]:
Right.

Steve Swan [00:35:00]:
So what I ask folks is I say hey listen, you know, I like going to see music and different concerts and things. So I asked folks, you know, if they go and see live music or if they have at any point in their life, would they say that there's any musical act or any concert that they've ever been to that would be the favorite one that they've ever attended that they would ever say, you know what? Back when I was 15, it was this one, one person gave me that they were one guy who was the CIO of a place that when I was 15, I saw this band or someone else was like, you know, a bunch of guys here in New Jersey like, ah, Bruce Springsteen. You know what I mean? So is there, is there any musical band at concert you could say, you know what, Steve? That was my number one and I like that one. And it was at whatever age.

Praveen Kamsetti [00:35:42]:
I don't have much of the music side.

Steve Swan [00:35:45]:
Not a music guy.

Praveen Kamsetti [00:35:47]:
I love the Bollywood music.

Steve Swan [00:35:49]:
Okay.

Praveen Kamsetti [00:35:50]:
I'm pretty old. Romantic songs. I love it, right? Not, not a big band. I, I love the sports, right? If we. I, I want to go and watch the super bowl one day live.

Steve Swan [00:36:03]:
Ah, yeah, yeah, that'd be fun. That's crazy. I, I don't know. I, I'm okay with crowds, you know, so some of these concerts get crowded, but with a Super bowl or something, you know, I don't know. But yeah, that's a lot. That's a lot. You know, some of them get a little nutty. You know, I see some of those things on tv where over in Europe with their soccer games.

Steve Swan [00:36:28]:
Those are fans. Holy smokes.

Praveen Kamsetti [00:36:30]:
Yeah.

Steve Swan [00:36:33]:
I don't, I mean, we don't get it to that extent, I don't think here.

Praveen Kamsetti [00:36:36]:
But yeah, I think it's again, the same thing, like cultural thing, right? Each, each. You know, Europa is a soccer, you know, we have NFL and all kinds of sports course. India has, you know, cricket and cricket's awesome.

Steve Swan [00:36:49]:
I like watching because I like baseball, right? So it's. Yeah, it reminds me of it. And you know when, like if I'm at friend's house, like, and, and I'm watching stuff over a series of two weekends or something, right. I'll forget if I watch it again in six months. I'll just forget, you know, like, okay, let me wrap my head back around the game. You know what I mean? But it's so, it is, it's cool. It's fun to watch. It's, it's, it's like baseball, right? It's, it's got the mental component to it.

Steve Swan [00:37:14]:
You got to be a true athlete to be Able to play because you can't. A lot of that stuff you can't train for. You can't train for the hand eye coordination, you know? You know, some things are innate.

Praveen Kamsetti [00:37:23]:
Right.

Steve Swan [00:37:23]:
You know, so I, I love sports.

Praveen Kamsetti [00:37:26]:
I love the sport. I love baseball too. I am a big Yankees fan when I was in New York City. Went for a couple of games there too.

Praveen Kamsetti [00:37:34]:
Were you?

Steve Swan [00:37:34]:
Yeah.

Praveen Kamsetti [00:37:35]:
And then Giants fan for NFL and you know, I'm big. Yeah. Big fan of sports. Course.

Steve Swan [00:37:40]:
So Giants hurts now.

Praveen Kamsetti [00:37:42]:
I know.

Steve Swan [00:37:45]:
That'S true. Dedication right there.

Praveen Kamsetti [00:37:47]:
Yeah.

Praveen Kamsetti [00:37:48]:
So I was there when, when Eli Manning won the championship.

Praveen Kamsetti [00:37:54]:
Right?

Steve Swan [00:37:55]:
You were there. You were, you were. You were at. Yeah, yeah.

Praveen Kamsetti [00:37:58]:
Not there, but.

Steve Swan [00:37:59]:
Okay. You were a fan.

Praveen Kamsetti [00:38:00]:
Yeah.

Steve Swan [00:38:00]:
Okay, got it.

Praveen Kamsetti [00:38:02]:
So we moved to Austin in 2016. Right. So that happened, I think 18 to nine, 2008 or nine at that area.

Steve Swan [00:38:08]:
Yeah. Yeah.

Praveen Kamsetti [00:38:09]:
Jersey, New York type.

Praveen Kamsetti [00:38:10]:
Yeah.

Steve Swan [00:38:11]:
How do you like Austin? You like it?

Praveen Kamsetti [00:38:14]:
Yeah, I like Austin. Austin is nice, you know, it's just. It is, yeah. I'm big into, you know, the exploring, the things. Like I said, I'm all. I always have a curiosity to learn new things, new places, new technology. I'm a people person everywhere. So wherever I go, I make friends and, you know, all that good.

Praveen Kamsetti [00:38:33]:
I love to adopt.

Steve Swan [00:38:36]:
I used to travel to Texas every other week, all week for a few years, and had the pleasure, I would say, of going to Austin. And I always said if I ever had to go to Texas, I'd go to Austin. I'd liked it. It was nice.

Praveen Kamsetti [00:38:49]:
Yeah, I think Austin is nice in terms of the terrain. It's almost like a little bit of California hill. It is New Jersey, New York area. The greenery. We always have greenery. So you don't feel especially. We are in a hill country area this side of Austin. So it's all.

Steve Swan [00:39:09]:
Well, you got topography.

Praveen Kamsetti [00:39:11]:
Yeah.

Steve Swan [00:39:11]:
And you got trees and stuff. You're not like Dallas or Houston, where.

Praveen Kamsetti [00:39:13]:
Not like flat area.

Steve Swan [00:39:15]:
Yeah, it's not flat like that. You know, it's got some, some, you know, some undulations and stuff. Makes you feel more at home. But anyway. All right, cool. Well, Praveen, thank you very much. That was awesome. I appreciate you taking some time with us today.

Steve Swan [00:39:29]:
All right.

Praveen Kamsetti [00:39:31]:
No, thank you, Steve. I truly enjoyed this conversation. I think we're looking forward for the AI innovation going forward, how this is going to help and change betterment for our human being.

Steve Swan [00:39:41]:
Yeah. And we'll do a follow up at some point. All right.

Praveen Kamsetti [00:39:44]:
We do, yeah.