Ben Pearce (00:02.446)
Hey everyone and welcome to the Tech World Human Skills Podcast. Thank you so much for checking out the show and what a show we have for you today. AI is still on everyone's mind, whether you're trying to understand how it's useful to you, whether you're using it for basic productivity or whether you're a full power user making yourself a mega human. It's changing the way we do things and it's evolving fast.
So how do you be a leader in the AI age? What does leadership look like? That's what we're talking about today. Now, our guest has spent many years in tech. He's been a software developer, a data architect at AWS. He's led data and AI teams at Microsoft, been a VP of data and AI at Capgemini Inven, and that's only scratching the surface. So please welcome to the show.
Pratt & Das.
Pratim Das (01:03.553)
Thank you Ben, thanks for having me. Really excited for our conversation. It's a very, very relevant one and I'm sure our audience will really love some of the insights we're going to explore in this conversation.
Ben Pearce (01:14.646)
Yeah, no, I think you're right. Well, but before we dive into it proper, could you tell us a bit about your background?
Pratim Das (01:24.621)
Well, you did a fantastic job. Just the way I see it, my career is across sort of four pillars. So I've been a client myself in Adele, IFPI, I spent significant amount of time there. I work for product companies, AWS, Microsoft, where we work together. And I've done consulting as a VP in CAP.
and I also meant a startup. So that's the sort of four areas which kind of gives me a very rounded perspective when I'm working with clients or solving problems with tech, AI, et cetera.
Ben Pearce (01:59.726)
Brilliant. Well, I wonder if the first question we could start to think about is, when we're talking about this leadership in the age of AI, what do you mean by leadership?
Pratim Das (02:14.83)
So leadership, particularly as soon as you attach the word AI to it, people may focus straight into the tech. But realistically, you need much more from leadership in today's world, And AI is continuously going to evolve. is a new innovation out every hour, in fact. And unless you drive clarity,
Ben Pearce (02:37.397)
You
Pratim Das (02:45.037)
true leadership, all you're going to end up with chaos, right? And that's where you need a well-rounded leader with lots of experience to drive that clarity. And even though AI will evolve, the very heart of leadership will still be humans. And I think the key is to embrace it with curiosity and humility and allow that meaningful experimentation and align to business value.
So just, it's not just the tech, it's the people, the process, the tech that aligns the business outcomes and is so much more important than it was ever before.
Ben Pearce (03:28.206)
And so just to build on that bit there you say importance. Why do you think for people listening, know, listening to the podcast that are out there in the tech world, why is it important to build that leadership muscle, do you think?
Pratim Das (03:42.455)
Well, look, I think I'm going to go through six different themes, maybe five themes that will really go into deep. Because if you're really not a leader and working with your teams and driving that clarity, you can very easily be lost in that noise and spend hours driving something that doesn't yield any outcome for you, your team or for your clients.
So very important to be grounded, very important to do the experimentation, but how do you find that balance between a commercial vision and teams vision and a tech vision? That alignment is critical, I think.
Ben Pearce (04:29.9)
Yeah, it's getting stuff done, isn't it? Like, you know, you can just do the tech, but that doesn't land it anywhere. It doesn't make people use it. It doesn't mean that it drives value for people. It's just some interesting tech that sits there. So, you know, if some.
taking on some of this, building this leadership muscle that I referred to, is how you get stuff done, be successful, have impact, I think. So I think it's a really important topic. Well, you mentioned that you've got a number of themes that we're gonna step through today as to how to be this leader in an AI world. So, should we get cracking? So what would be your first bit of advice, your first theme for people on how to be a great leader in the AI world?
Pratim Das (05:16.588)
Well, just in case I forget, I think there's five things that I have in mind is one, to be very open-minded. The second one is to embrace change. Continuous learning is critical. And then the focus and purpose. And finally, the responsibility as a leader to use AI responsibly and build AI applications responsibly. Those are the five things.
Let's start one at a time, Ben? So being open minded, as a leader who may have done things in the past, and this huge eruption of AI tools and techs, you can always feel a little bit defensive and say, I've seen this, it's too much noise out there. And it's not
Ben Pearce (05:46.999)
Okay?
Pratim Das (06:14.732)
As time is not ready, their products are not enterprise ready. It's quite easy to say that. And in fact, for example, I, when I was in cap, we go into doing vibe coding, which is now a phenomenon, right? So AI assisted coding. And you know, I'm a little bit hands on, I like to get my hands dirty. So that my initial reaction is, it's just making scaffolding. It's not really building real applications.
But then I reflected back and then and well in the last six months has evolved some of the tools are phenomenal. And you really look at the value that's right. So from an idea, from a vision to value and in an accelerated pace is very important. You really need human engineers, developers on top to make sure is enterprise ready.
it's got the security right, it's got scalability, all these things are essential but at least what it does, it does really well from that idea to a prototype, very very very important. And so I think teams and leaders should be non-judgmental and really be curious and I think we should also encourage the environment of experimentation.
And some experimentations are going to fail, right? This is where leadership comes into play and say, encourage experimentation and don't judge. Sometimes things are going to go wrong, but the ones that are going to get right are essential.
Ben Pearce (07:56.43)
Okay. how do you, right, because there's a million startups out there telling you the thing that they're doing is gonna rock your world, change your life, right? There's a lot of hype out there. So how do you get the balance of being open-minded to the things that are gonna be of benefit versus chasing the shiny thing because it's all over
Twitter x, wherever it might be. Everybody's talking about... So how do you balance open-mindedness versus being a magpie and constantly chasing the shiny thing?
Pratim Das (08:41.193)
You're going to enjoy my four letter and five letter frameworks very soon. So as I can introduce my first framework open, we're talking about open minded, it's called open. So the first open O stands for observe without judgment. P is pragmatically adopt something and E is envision new opportunities.
Ben Pearce (08:46.849)
Okay, okay.
Ben Pearce (08:52.855)
Okay.
Pratim Das (09:10.245)
and N is nurture, human connections. So all of this should be formed on foundation pillars of business outcome. Because as you say, you could have this tendency of thinking, let's just experiment this, this and all these things are very cool and let's just try this and that. What is that you're trying to solve?
I think that's the question to ask. What is the business outcome you're going to try and deliver? Is this going to increase your revenue? Is this going to improve your team's productivity? Is this going to reduce errors? Is going to make customers delighted by your products? So those are the sort of critical business outcome questions to ask and then use my open framework to choose the right tool and give everything a time bound window.
I'm going to try and experiment on this and if it doesn't succeed, we try this. So it's also important to carve out the people in that as well because the majority of your team is busy building stuff that's already business critical. So where do you find time for experimentation? So it's also that culture of experimentation is to baked into the team's operating model. So it's a combination of all those.
Ben Pearce (10:29.966)
Okay, so open-mindedness, try new things. Don't think you've always got the answer. There's a lovely phrase that I've heard over the years. What got us here won't get us there.
Pratim Das (10:44.924)
and listen.
Ben Pearce (10:45.642)
And there can be a, particularly as you get more seasoned in your career, you can start to think, well, you know, this won't work, it's a fad, it's a hype, you know, but constantly reminding yourself, what got me to here will not get me to there. And I need to be open-minded about it. So love that. First theme. What's your second theme, Pratton?
Pratim Das (11:04.867)
And the second one, I would say embrace change. And you can't hide away from it. And while you're embracing change as a leader, and I think this is the focus of our discussion today, you really ought to think of simplicity. And throughout my career, one thing I have realized, you ought to make
thing simple. Simplicity is directly proportional to adoption. Well, let me give you a good example of embracing change in leadership. So when we were at Microsoft and one of my favorite sports cricket as ECB and Microsoft signed a partnership, Ed Smith, English cricket board, English cricket board, signed a partnership and Ed Smith was the then
Ben Pearce (11:49.794)
So that's the ECB is the English cricket board, okay.
Pratim Das (11:59.002)
selector of the English cricket team. So Ed came with an amazing open mind and saying, look, we've been doing this with intuition and we were doing a very good job of selecting teams, planning the game and everything. Prathim and team help us. So how do do it more scientifically with AI? How do we
Ed was never talking about replacing anything with AI. He's saying, how can we augment AI into our decision making so it is always backed by science? And that humility and just like curiosity that he showed is exactly what we need leaders to do now. Doesn't matter you're in health tech or consulting or finance. You ought to be
embracing that change, coming with that question as to how do we do things better with AI so that things are engineered for success. And yeah, does that make sense?
Ben Pearce (13:07.358)
It does and I'm really intrigued. So what did you do? So the English cricket board are saying we want to be more scientific and use AI in our selection process. What did you do?
Pratim Das (13:19.004)
Well, we looked at the various aspects of cricket, like team selection and on the day. There's a lot of stuff we can't talk about in this. yeah, well, because it's international cricket, every team has their own strategy. If you look at Australia, India, they're fantastic in sort of using AI already in cricket matches.
Ben Pearce (13:30.572)
Okay, okay.
Pratim Das (13:48.288)
And so, don't go into details, but we kind of looked at all aspects of cricket and how data is augmented, how much data is actually stored. Every ball that you ball is like a four meg of information stored for every ball. So there's a lot of information out there that could be used to help teams or help captains or leaders within them, any sports to make the right decision. at American baseball.
100 % data and AI driven pretty much from team selection to the actual day of running of the day. It's fantastic. So yeah.
Ben Pearce (14:25.346)
So your point, guess, therefore is, but to look for, in this case, the competitive advantage through cricket and embrace that change. Again, it's building on that. You've got to be open-minded that there could be new ways to do something and then now embrace that change and really try and adopt that change and drive it forward.
Pratim Das (14:41.008)
Correct. 100%.
Pratim Das (14:49.666)
the right outcome. Absolutely.
Ben Pearce (14:51.67)
Yeah, okay. Love it. Third theme. What's your third theme, Preston?
Pratim Das (14:58.791)
And you love this and we kind of practice some of this when we're in Microsoft is continuous learning. And and and particularly in the world that we are living with AI and AI is here to say what I call it the flipped pyramid model. And again, I'll give you an example. Paul Hudson, who used to be the CEO of Novertis, I think he's now the CEO of Sanofi.
Ben Pearce (15:01.526)
Yeah
Ben Pearce (15:05.774)
Okay.
Pratim Das (15:28.967)
And he did a fantastic Ted talk and I'll get your audience to listen in as well. And he was saying that Paul got to the role of CEO because he did loads of stuff. He ran Japan, he ran global marketing, he has done this and that. So that allowed him to be the CEO because he could be in every decision.
Pratim Das (15:57.37)
When it comes to AI, the graduate who just two years of world of experience probably has seen more of that evolution of AI than Paul has. So he purposefully made decision in a way that those voices are hard. And that's what I call it, the flipped pyramid. You ought to be mindful.
of there will be, even though you may be a leader, between 500 years of experience doing various things, the adopters are different generation. people who are end users have often different motivations, different ways of doing things. So you ought to be mindful and bring that inclusive mindset.
you know, have that continuous learning mindset to be able to learn how this is going to be used. And so, yeah, so does that make sense? And I do have a small framework as well.
Ben Pearce (17:04.254)
Well, you've teased me now Pratim. So firstly, I love this this flipped pyramid the idea actually that people some of the perhaps people earliest in their career actually can have some of the most valuable voices and so if you're a leader thinking about how you purposefully
Pratim Das (17:18.629)
Absolutely.
Ben Pearce (17:23.89)
hear those voices, what are the forums, the ways, the approaches that you can use to bring those voices into your decision making. So I really like that from the flipped pyramid thing. But you teased us that you've got a framework around this. So what's the framework you've got, Pratik?
Pratim Das (17:39.274)
So the framework is learn, we're talking about learning, so L-E-A-R-N, right? So L for listen actively, and E for encourage mentoring, and you need to have that reverse mentoring as well. Be mentored, be okay, be comfortable to be mentored by, you know, the youngest member in the team, for example. And A stands for adopt the bigness mindset.
As in like, I don't know anything. Let me just go in and be the master of this, but learn from scratch. Regularly, R for regularly update knowledge. Because AI is evolving so fast, what you learn today, tomorrow could be static. So you need to be able to update it. And then the most important is the N in learn. Normalize sharing. You ought to be able to reward sharing, whether it's a
Ben Pearce (18:23.182)
Yeah.
Pratim Das (18:37.935)
client project which has been successful by using AI within your team or using a new tool that's improved your productivity. So yes, I think that's the framework, but there are things that you can actually do like structure reversed mentoring practice within the organization, put KPIs for learning, essential for your team in a time you spend.
outcomes you drive. from the time Microsoft used to always say activity is not always proportional to impact. Obviously focus on impact. But text and tools, right? So there are tools and I use LinkedIn learning all the time and to learn new things. But there is so much content out there. I attended the Google Next, that was last week.
amazing sort of innovation coming up. And NVIDIA GTC, was the week before. I'm looking forward to AWS Summit end of this month. And there is also Databricks, Data and AI Summit coming up. So you just have to learn and not just the tech. How customers, how people are adopting, how teams are embracing AI is also the critical thing to learn in this.
Ben Pearce (20:05.002)
And how do you practically do that? I'm a massive fan of taking time to learn as well. But when you've got business challenge X, customer A, boss B, all of these people, family, all of these people trying to get a piece of your time, have you got any thoughts on?
Pratim Das (20:25.706)
Yeah? Yeah.
Ben Pearce (20:34.552)
how much time you should be learning and how you ring-fence and protect that time to do the learning.
Pratim Das (20:42.596)
But this is where leadership is critical and the role it plays. And I think you answered the question in your question. How do you protect that time? And so as a leader, I put a good chunk of my Friday in learning new things. And throughout the week, I will encounter new things and new terms for my team would say, I probably don't know. And I would block that Friday afternoon to do that.
Ben Pearce (20:51.008)
Okay. Okay.
Pratim Das (21:11.329)
And I encourage, when I was in Microsoft, I used to send the blocker to my team on Friday afternoon. I can't remember, learning or nurturing a growth mindset, something like that. So as a leader, was letting my team know that I am doing it, you should also do it. And we should also have a discussion circle and say, in the next team meeting, I learned this. And it's not always about tech, as I said, it could be about how.
Ben Pearce (21:40.28)
Yeah.
Pratim Das (21:41.143)
someone else do something. So you have to lead as a leader, have to lead this and lead this and let your team adopt that mindset as well. So absolutely you have to protect that time.
Ben Pearce (21:52.397)
here and the other thing I think that I've sort of from my experience has worked out is having a bit of focus because or at least a bit of balance so it's great to know everything at the top at a high level look at shiny thing shiny thing shiny thing shiny thing shiny thing shiny shiny thing I know a little bit about all of these shiny things but actually picking a thing
Pratim Das (22:11.265)
Yeah, yeah. Yeah.
Ben Pearce (22:16.46)
and then going, I'm gonna learn about that thing and how I use that thing and then learning about it, understanding the theory, then trying it, breaking it, getting it wrong, doing that over a couple of weeks so that at the end of it you've got a new skill. I just found, like I used to be a fan of, look, here's this book, I'm gonna read that book, that book, that book, that book. And actually, at the end of the year, none of it had stayed in.
I'd learn maybe a few little bits. But actually, if I just picked two things that were things that were important to me this year, and I learnt that thing, at the end of it, I really know that thing. And that learning was productive and it's useful and it's stayed with me, as opposed to being a shiny flash in the pan. Do know what I mean?
Pratim Das (22:48.983)
Yeah.
Pratim Das (23:05.046)
I don't know what you mean. The only thing I would add to that is as a leader, you kind of need both. You need the breadth and the depth. And so you kind of need to stay on top of what's happening. let your passion guide you where you want to deep. And I think where passion meets the business objective, that's where magic happens.
Ben Pearce (23:15.702)
Yeah. Yeah. Yeah.
Ben Pearce (23:35.126)
Yeah, yeah.
Pratim Das (23:35.574)
So now I totally agree with you, but you need both.
Ben Pearce (23:40.14)
Lovely. Right, what's the next theme?
Pratim Das (23:43.969)
Well, this is one of my favorites and kind of something that's echoed with me, I would say, in the last few years in my career. And that's something that I got from one of my cousins, who is a senior chap in the healthcare NHS, with speed and purpose, he calls it. And so really that purpose.
Yes, AI is a productivity booster and building efficiency, but most important is to be able to drive things with purpose. And while you're doing this, there may be experiments that may not yield a purpose, but you should always be guided towards a purpose. So I'll give you an example like Google
ex moonshots like learning projects like they did Waymo and Project Lume. All of these were just experimental, but they had a bigger purpose to solve, right? Which was successful, but there has been many other projects that wasn't successful. So I think that's something as a leader needs to do definitely in their teams, instill that
sense of urgency and create a safe space for experimentation, always ensures you're laser focused on purpose. And I think in a world of AI, nothing is as important as purpose when it comes to retention, because people can change jobs and skills are very much in demand. But once you're
passionate about the purpose of your team, your organization, that's where you do your best.
Ben Pearce (25:43.862)
Yeah, no, it's just reminded me. I was chatting to somebody the other day and they were saying that their CEO of the company had come to them and said, you need to do AI and you need to tell me how are we doing AI because I need to tell my investors. So basically it was AI is the answer, right? And
And of course, right, there's politics, right? Because AI is the buzzword, AI is how you get funding, AI is how you move your stock price. I get it, I get it, all that. But it was just such an example of, the answers AI now find a problem, which is the complete opposite to what you're saying, you know, whereas, you know, in my eyes, the right approach would be to say, right, we feel that we are...
Pratim Das (26:12.811)
Mm.
Pratim Das (26:24.735)
opposite.
Ben Pearce (26:32.894)
Let's take some really obvious examples. We are wasting time writing up meeting minutes and we are missing actions, which is making us less effective for customers. Therefore, we are going to turn on transcription on our meetings and summarise and auto. So there you go. There was a problem, you know, where and it saved us 10 minutes on every meeting or it's meant that we've captured an extra three actions, is, you know, there's a purpose, there's a measure or there's something about it as opposed to the answer.
as AI.
find a purpose? So that purpose is key, you're saying.
Pratim Das (27:07.745)
Yeah.
Absolutely. That's everything should always and why are you doing this? That purpose could easily be lost because you're just in a momentum of doing something and you almost forget why you're doing this. So as a leader is very important to go and reattach the purpose in every iteration. And I think that's key. Yeah.
Ben Pearce (27:32.0)
Yeah. Yeah. Yeah. We're doing this because we want to fix problem A. Yeah. There's opportunity B. Right. Got it. Wow. Last last last theme. What's your what's your last theme Pratom?
Pratim Das (27:44.928)
Last one. The last one is the responsibility of leaders in AI. I think it's a bit of a mouthful. So like, how leaders must take on ownership and leadership to be able to do AI in a responsible manner, in a safe, secure and responsible manner. Because
Let's take social media for example. Social media for the last 20 years had an unregulated space. It's evolved, it's innovated, and probably there are some good things about it, but it has caused societal harms. There has been damages. And if you think of social media, it uses AI, parts of AI. But AI is
Ben Pearce (28:32.622)
Okay.
Pratim Das (28:43.039)
much more powerful. So how do we pragmatically have the balance of agility and innovation and AI, but also be very mindful of the power of AI that if it's not done in the right, with the right purpose and the right framework, it could have a long term consequential implication, right?
So I think, yes, I think that's the most important thing. And there are people, process, technologies and framework, we'll probably dive a little bit into that. That is key, then that will help leaders.
Ben Pearce (29:28.342)
So when you say the word responsible AI, maybe you've got a framework, but how do you break that up? What are the things that people need to do to be confident that they are doing this responsibly?
Pratim Das (29:43.89)
Yeah, so look, think Microsoft had a fantastic framework and I love it because it was very simple. So they had three core principles of fairness, reliability and safety and inclusiveness underpinned by two foundational principles of transparency and accountability. Very simple, those five things, right? So you need to embed them across people.
Ben Pearce (29:49.879)
Okay.
Pratim Das (30:11.839)
processes and tools to be able to do AI responsibly. So very interesting. Your team ought to, if you're building AI products, you ought to have a diverse and inclusive team because I'm afraid the data, particularly the data that these LLMs are generating, they're all biased. They're biased on one side or the other. I'm not going to into the depth of it.
Unless you have this lived experience in your team, you just inherit the bias and put it in your product. And then suddenly a billion users are using it and it's got bias and it's just going to create that flywheel effect. So it's essential for leaders to have that inclusive voice, inclusive team to be able to do that. Processes.
the ethical frameworks like the Microsoft one. think there's about over hundred frameworks out there, Capgemini had one as well, but really create a simple framework that's easy to understand, embedded in tools and practices every day that you produce. And I'll name some very simple tech tools like Anthropic has done some amazing work in responsible AI. I use a product called Liza, but AI has got the guardrails built.
by default and Calm for example doesn't matter how complicated API is Applications you're building if you're using API's they have a layer of guardrails built in that stops that And there are boutique consultancies Like it's not often a consulting gig because it's a journey. It's not a TNM or a fixed price Initiative that you can go to a client is I'm gonna make sure you're
you have responsible AI built into your team. It's a journey. for example, Lotus AI does a fantastic work in sort of taking clients into that journey. So, yes, I think there's really have to look at holistically with that people process and to an open mindset to ensure this is done with some sort of rigor across your team and your products.
Ben Pearce (32:32.728)
Love it. Well, do know what? think we've run through those themes quickly, but we've run out of time as well. should we just start to wrap up, Pratim? What would be your closing message and your key takeaways for everybody that's been listening?
Pratim Das (32:52.241)
Well, look, I think leadership is more important than it was ever before. And it's not just about the shiny tech. It's about your lived experience, your experience that you have acquired over the years. The battle scars are critical and the differentiator and that world needs it. And in a world where automation is everywhere with AI and what it doesn't have is those experience. So as a leader, you should be very comfortable.
and be willing to, you know, share that knowledge with your teams and guiding the team with clarity, particularly when there is so much ambiguity. I personally selectively advise and mentor some startups, so, you know, feel free for your audience to reach out on LinkedIn. And, you know, I'm more than happy to help some of them. But look,
The last one I would say Ben is simplicity. Simplicity is directly proportional to adoption. I keep telling everyone and you see simple things are one that's successful. If you make things too complex without that you're not going to see that option. So yeah, you may maybe think of some of those frameworks I've said in the chat before and try and use one next week. You don't have to do all in one go.
Ben Pearce (34:14.466)
Yeah, love it. And I'm just gonna run through, you key takeaways. There was five themes. I'm just gonna run through those again. So you had open-mindedness, which is really good. So that's theme one, open-mindedness, then embracing change. Then it was about always learning. Then purpose beyond productivity. And then finally we talked about responsible AI. So.
five themes to think about as you build your leadership muscle in this AI world that we're in. of course, I'll put in the show notes links to your LinkedIn. And I think you said there was a TED Talk link. If you can give me that, Bratton, I'll add that in the show notes as well so people can get the links there. So the final thing for me to say is, Bratton, thank you so much. It's been a really interesting and fun conversation. So thank you for taking the time to come on the podcast.
Pratim Das (34:54.352)
Yeah, Paul Harson, also in the air.
Pratim Das (35:09.87)
Indeed, I totally enjoyed it. Thanks Ben. Thank you.
Cheers!
