Beyond the Algorithm – Human Insights in Data & AI

00:00:01:15 – 00:00:14:08

Speaker 1

Two interviews. I know I’m nervous. I mean, I’m nervous. Don’t think that I’m gonna visit the food bank. So, But I think over the next, I think after five minutes, it’s very chill. Yeah.

00:00:14:08 – 00:00:15:09

Speaker 2

Because you have a thing.

00:00:15:12 – 00:00:18:07

Speaker 1

You’re thinking like that?

00:00:18:09 – 00:00:20:00

Speaker 2

Yeah. Sure thing.

00:00:20:02 – 00:00:25:00

Speaker 1

But when you’re doing only one for one customer, you know, for one amplifier, and there is only one.

00:00:25:02 – 00:00:27:05

Speaker 2

This will be bad than this will be bad.

00:00:27:06 – 00:00:52:13

Speaker 1

Just one more. There’ll be no one and there’s only one. And then example. Right. So it’s exclusive, right? Then that’s how it should be. Okay. So, hi. And welcome to my talks, Business Insights Unplugged. My name is I’m a deep. I am head of Europe at McQuaid. And I’ll be your host today. I’m very excited to introduce you to do that before we got.

00:00:52:14 – 00:01:20:03

Speaker 1

Is, technology you need, group data and AI officer and amplify. And it brings a wealth of experience and data strategy and transformation. Giuseppe is an expert in helping businesses rethink their processes, decision making through the power of data and how I can, be leveraged to improve small and complex, challenges. And that’s driving innovation.

00:01:20:03 – 00:01:29:13

Speaker 1

So is that be welcome once again, to the post podcast. And I’m it’s an absolute pleasure to have you on the show.

00:01:29:15 – 00:02:08:15

Speaker 2

Oh thank you, thank you. It’s my my pleasure really my pleasure. And thank you for the great, presentation and introduction. Well, let’s say I can give you a little bit of context of what is my, my experience now, what are the key? Less and less to start talking about. These are great content that I get that this data data and I, you know, well before joining amplify and in my current position as a group data and AI officer, I spent more or less 15 years in that in the data and AI space and all primarily, let’s say, shaping strategy in leading consulting firms like Deloitte, and and Accenture.

00:02:09:01 – 00:02:34:00

Speaker 2

And actually, these speakers gave me the opportunity to work across different markets, industries and geographies gaining. I say I can say I breadth perspective on our organization. Big has more on our approach in data there than desk formation. Well, let me say that one of the biggest, challenges I’ve seen in adopting data and AI is that people really struggle to change how they work.

00:02:34:00 – 00:03:13:05

Speaker 2

And, companies investing in cutting edge, tools like Nology is by, you know, that trust formation happens all when employees are willing to experiment. Let’s say that, at a they approach also if they consider we have time, I want to give you something that I used to say to my, to my the, yeah, I used to say to my clients and all and I used to say to my, to my peers and I, my colleagues that, that we share a fascinating, I think, experiment and that now conducted at Stanford, the university in the 70s and all from a professor.

00:03:13:05 – 00:03:42:02

Speaker 2

What does micro it’s called, maybe, you know, it’s it’s called that, marshmallow challenge. You know, it’s quite, quite fascinating because they’re all, very simple. Now teams get, 20 sticks of spaghetti, some tape, and I’m an Italian. So when I refers to spaghetti, always playing some tape, a piece of string and a marshmallow. And the goal of this challenge is actually to build the tallest possible, freestanding, tower.

00:03:42:03 – 00:04:08:05

Speaker 2

What, with a marshmallow on top. Well, now involved the the teams are made up, by MDA graduates. Top engineer is a senior executive and a group of, really young player kindergarten. And so, so, you know, surprise. You know who who always won, one and win this, Lanza the kindergarten every time. Every time.

00:04:08:08 – 00:04:36:06

Speaker 2

But you know why? Why? This is very interesting. Because, what? The profession are all the thing all the time, all strategise, plan, etc., etc.. They keep just start building. They test, fail a just try again. And so without fear of making any mistakes. So meanwhile, the MBAs and senior executives spend so much time discussing the perfect plan that they finally place their marshmallow on top and and stature collapses.

00:04:36:08 – 00:04:58:03

Speaker 2

Now, this I think this very minute, this pediment is a perfect metaphor on how many companies approach AI and data and audience formation. The employees who have been doing their job in the same way for years, for years now tend to analyze and resist and wait for the perfect use case rather than experimenting and iterating. And so no.

00:04:58:03 – 00:05:33:05

Speaker 2

So, you know, the on me and at the amplifier, naturally, we know that the successful AI adoption isn’t just about having the best technology in place now. It’s about helping people to go back, let’s say to the kindergarten that, you know, so we create an environment where people and employees feel comfortable to test, fail fast, to learn quickly, just like those gates, on the marshmallow challenge, because at the end of the day, not just to just to just to conclude my my, my my answer, AI and data are not just about technology alone now.

00:05:33:05 – 00:05:49:05

Speaker 2

They are about changing how people work now and it requires rediscovering the ability to experiment and embrace a new way of thinking. So I think this is my my first lesson on my 15 years in data.

00:05:49:05 – 00:06:18:10

Speaker 1

And I thank, you know, I, I actually couldn’t agree more. I think fail fast and adapt and retry is very crucial. I think it comes to all innovation, all new tech, new new technology trends. It’s it’s without a doubt, I think key to success. So you know, while, you know, you mentioned this is one of your key lesson that you learned, you know, in the data in the AI space as the, you know, we create more and more data and we hear about more and more AI applications.

00:06:18:10 – 00:06:45:04

Speaker 1

And obviously there are a lot of use cases now with the lessons that you’ve learned, what are the biggest challenges that you see when you actually are implementing complex programs? You know what are the challenges you see? And with those complexities, do you see, navigation around data governance, regulatory or is just all about technology adoption? So how do you see them and then what do you do, which is that big?

00:06:45:05 – 00:07:04:12

Speaker 2

One half a lot of challenges. Otherwise there would been there would be not an all day that may I hope is there around that. But I think, except for the, the adoption part and all that we already discussed before. And now there’s, I think three main topics that you already mentioned. A couple of them. The first one is about data governance now.

00:07:04:13 – 00:07:33:10

Speaker 2

So, you know, there’s a lot of technology around the we used to talk a lot about AI, generative AI. And I’ve been robo. Now I mentioned that will, that will do our job. But at the end of the day, what is important is our knowledge about our processes. And so the, our data now, our data is, I think, still, still then, you know, some one, or ten years ago, I would say that there is then you are in a.

00:07:33:10 – 00:07:54:08

Speaker 2

Well, I think that is the same now. And AI is a very big, game changer. But data is still is still then you are in because we the consistent the AI quality accessible data across different regions and business unit. You know you can gain. And what is the the the realities that you want to you want to achieve.

00:07:54:08 – 00:08:38:05

Speaker 2

And I added on the phone, for example, we are adopting that data is product approach. You know, where business, business domains take the ownership of the data, making it more accessible, high quality and reusable. So I think first the challenges but also first opportunity is how to best govern the data. So that I think a second I think is what you mean and all the regulatory and it’s not a sexy topic and not the very fancy one, but I think it’s, something that we need that we need to be really, really taking care of now because the different regions have different, topics about privacy and regulation.

00:08:38:05 – 00:09:04:13

Speaker 2

You can think about the GDPR in Europe and all, or the emerging AI, those in the US, they. Yeah. Yeah. That just that. No. Right. The Europe in February you know that we the first regulation in place so basically addressing this kind of, regulatory framework, having the technology to monitor it, I think it’s, batty, batty, mandatory.

00:09:04:13 – 00:09:27:07

Speaker 2

And AI is a big challenge in our company, a nine, in a multi-country company, you know, like, like amplify, like the other companies that the managing the business in different countries. I think the third one, the third one is that, is, always on a challenge for every for every technology leader. Is that technology fragmentation?

00:09:27:09 – 00:09:51:03

Speaker 2

So there’s a lot of a lot of technology around the nowadays. And, but in the previous. Yeah, there’s a be these, arrays, to journey in the journey to the, to the cloud and to migrate all the things or the cloud and, and it’s, let’s say duplicate the there or duplicate or duplicate, the number of, system that we have to manage.

00:09:51:03 – 00:10:15:15

Speaker 2

And now, because we have several options with the cloud instead of the, of the, the legacy and I think easier these are the complexities to build the, scalable on the data and AI context of scalable data and AI architecture that enables seamless access of data and the AI solution across different geographies. And platform. Now, simple to say complex, complex, complex to do.

00:10:16:02 – 00:10:45:06

Speaker 2

But I think at the end of the day, what I learned during my experience, I what I’m trying to do in my, in my job is to leverage on a federated data governance model, now ensuring that the local markets have the flexibility to adopt and adopt while maintaining a global consistency in our data. And I, I use the across regions counties, and processes.

00:10:45:07 – 00:11:05:10

Speaker 1

I think this is really important. I think the having sovereignty in terms of standardization centrally and giving regions the flexibility to adopt and adapt to the change. I think this is brilliant. I think I really resonate, I think we this is really resonating point, which is.

00:11:05:10 – 00:11:36:13

Speaker 2

That, yes, I think I think on this point, there’s a lot of value and in different angle, nine different point of view and the localization and the peculiarity of each, of each county of each, of each, which people not. But it is very important to empower. And as these value, you know, and valorize this, opportunity but there the in mind that, we need to maintain standards and our regulation policies, and, and governments.

00:11:36:13 – 00:11:52:13

Speaker 2

So this is the challenge. This is the challenge. I think that is a regulatory that is technology, that is data. And about the guaranteed, the flexibility by maintaining your standard that monitoring is, is the key challenge.

00:11:52:15 – 00:12:12:07

Speaker 1

Well, I agree, I think I think that will continue to evolve. Now while the as you said, you know, one year ago versus what we see today in terms of AI and the number of applications, we heard about something coming out in China as well. And, you know, data and AI data is evolving and data science is being created every day.

00:12:12:08 – 00:12:43:01

Speaker 1

AI is evolving every hour. I would say every day you see a new application which is being which is coming out. Now in terms of trends in how to manage data. So how do you see that is being enabled by the the advancements, advancements in the AI space and how the analytics so data, the analytics and the advancements in AI you believe will help us as a as a as you know, this generation to move forward.

00:12:43:04 – 00:13:06:10

Speaker 1

How do you think the businesses will adapt to it? And if more so, how does that help? The health tech, organizations, you know, to improve their businesses and, and and possibly, you know, how does this help the society at large? It’s a very long question. Is everybody learning has made a difference to it. But you can it can be done to 20.

00:13:06:12 – 00:13:10:14

Speaker 1

Yeah. Can you help society finally move forward. You know.

00:13:11:00 – 00:13:42:05

Speaker 2

Yes, yes. Actually now this is a really, really good question. I think it’s, it’s quite I think I really feel lucky now to be in this, in this market, benign in this industry during this time now, because we are experiencing very, we are witnessing, in historical moment and now on, fundamental shift, let’s say, where AI is more being for being something very technical, a very focused on, predictive tool, forecasting tool.

00:13:42:06 – 00:14:22:14

Speaker 2

Now to becoming a sort of, let’s call it copilot for decision making. Now, in general, in general, oh, you are failing. So what are the key trends or the key benefits to complex to summarize it, but I think I have this I desired, you know, the first the first very crucial point is that, I and Jen, I would support us, we support our business productivity, our personal, let’s say, personal productivity, because everyone know in our daily, daily, daily tasks, Dahlia, it is that we we start using AI and Jen I, GPT Gemini and or whatever.

00:14:22:14 – 00:14:46:10

Speaker 2

Now I am a very frequent traveler. Now. I used to I used to travel a lot for, this is my passion on, on and before I used to do research is on Google, like said, planet. Doing a lot of, sort of, you know, numbers. I have to spend this time to go there from there today, I don’t know, I have to do the passport.

00:14:46:11 – 00:15:05:14

Speaker 2

And, the visa for this, for this county. I have to spend money for this and that, and and now, before, you know, more than before, planning gets rather. And I used to ask to Gemini or, shall I. I want to go there now what are the, the main things that I had to plan. What is the, the most, the most important, places to visit.

00:15:06:00 – 00:15:33:05

Speaker 2

Can you, can you build the plan for me? And then I, you know, for for this traveling and this is happening. You know what I am day to day, day to day activities. And if you can think about it from an enterprise perspective or not, this is a great, boost in our productivity. Now, I see, AI powered copilot and enhancing efficiency across functional from the customer support and marketing to the R&D.

00:15:33:06 – 00:15:59:05

Speaker 2

A lot of colleagues are asking me, okay, can I have, can I have tools, knowledge like generative AI to to start brainstorming now to add some challenges. So to, to to to have a benchmark of my ideas and all that is fantastic. Fantastic. But we we really need to take it seriously on, on, on how we use these kind of, this kind of tool with the right, policies, with AI guidance.

00:15:59:05 – 00:16:28:13

Speaker 2

Now. So first, I think, the first point is that personal productivity is not in our life, in our in our in our in our business. Second talking, I refer me to enterprise. And I think there’s a lot of room for optimizing, processes. So of course the cost, cost optimization to enable to enable our, our colleagues and not and not our, to enable, to enable to free up our space, our time to do things with a much value.

00:16:29:00 – 00:17:03:13

Speaker 2

No, optimizing the automate izing routine. Really routine. Any job. And then I see a lot of opportunity for personalization. Now, you see, marketing is very impacted. And on these, on these, on these kind of, on this kind of solution I saw during my past, my past year knowing consulting a lot of a lot of, clients, industry and companies working on this, on this personalization, because this is something that, they us a lot of time right now before the journey, to, to, to build, copy creatives.

00:17:03:13 – 00:17:48:07

Speaker 2

I see this. So there now now we, we, we had the opportunity to push our imagination now to boost our imagination because we have a lot of, you know, someone that that was doing the, the, the very practical, the very practical, the very practical job. And I think also for the educational, there’s, there’s a huge, huge potential now because, you see, and there’s a, there’s an opportunity for us, for example, to support, our, our clients and to, to also also at least, to inform the self, now about what is, what is an irrigates and what, what are the benefits and not where to to buy any

00:17:48:07 – 00:18:08:06

Speaker 2

and and gates and to personalize the experience in the shop and all to personalized experience in everything that needed gates and nine and living better now enjoying that the sounds of life now like we used to say, you know, and we used to it, we used to, we used to work on every day, every day.

00:18:08:07 – 00:18:30:14

Speaker 2

And then I think there’s, there’s, there’s a beef by and the you being responsible and explainable. I know, because we can do a lot of a lot of things, both in personalization and everything we said about that. We need to be very careful to have the human in the loop. Now, at the end of the day, who is in charge of taking decisions, building products, offering new services.

00:18:30:14 – 00:19:00:14

Speaker 2

At the end of the day, it’s always the human. And so we need to have that tool and technologies that support the human to do is work in a better, faster way. Not to substitute how people and employee work. So I the end of the day, personalization, efficiency, no. And new new services are the key, the key benefit that this kind of technology will, will bring us.

00:19:00:15 – 00:19:18:03

Speaker 1

So I think I, I completely agree with you. I think, I think just, just what you mentioned at the end, you know, summarizing it, the personalization being one of the key points as well. I think I completely, agree with you. You know, and what you said is, is very touching to that. You you said the hear the sound.

00:19:18:03 – 00:19:35:13

Speaker 1

You know, I think it’s it’s it’s what a great moment. Somebody who has it was hearing it or is he going to hear for the first time, you know, and walking them through the whole journey, I think it it’s just fantastic. I think it’s a, it’s it’s really it really. You know, they give you an experience.

00:19:35:14 – 00:20:04:02

Speaker 2

One of the key reason why I joined, before and is that, because I can be part, all of us started that support, and make the life of, millions of, of, person that that now I, I joined that couple of, couple of, store and all doing, doing their job. It is a really amazing see what happened, what happened when that were people, start dating.

00:20:04:05 – 00:20:24:08

Speaker 2

And I’ll start dating by then. It’s, the completely different life. And also, this is very, very emotional. Very emotional to me. Instead of just walking on the AI, that is very, very machine and very cold, very cold topics about I think this is very emotional apply and yeah, I that in on the phone.

00:20:24:09 – 00:20:43:07

Speaker 1

I think to I, I completely agree. So you know while we spoke about the, the, the how the AI is being applied and you see personalization at the center of it. Right. And I think there was a great example used by, by you for the, the emotional element of AI. Right. And making, making sure it is all responsible.

00:20:43:08 – 00:21:02:07

Speaker 1

You know, organizations are going to this massive change. So, you know, obviously, the, the, the, the, the fellow chief data and AI officer is, you know, what would you like them to know, you know, for defining the strategy when they are going to go after the AI in their businesses? It could be it could be genetic to any industry.

00:21:02:07 – 00:21:12:15

Speaker 1

But you know, what would you recommend? As part of, their strategy, they have, you know, a couple of things that are quite important to, to consider while defining this.

00:21:13:00 – 00:21:40:08

Speaker 2

Good, good question. It’s always challenging to answer this question because, as I used to be a consultant, now, the answer should be able to see all the ways that it depends, not just, but the I think that, considering the time we are living now, I always say we talk about the very great, innovation every, every day, you know, every every month, there’s a new AI annual new best of breed in the market and all that.

00:21:40:09 – 00:22:11:13

Speaker 2

I think that we as a technology leader, and I know we used to always says that not the latest one, not the most innovative one, that really used to focus on the technology instead of the the business side of this story. Now, I think the first that now the first, focus, I think should be always think about the business impact that now think always about how this kind of technology can support the can support to do things better, faster or in more cost efficient way.

00:22:11:13 – 00:22:39:06

Speaker 2

So having the ROI of the initiative in mind, instead of having the the identification of the best technology on the, on the market and all things seems easy now to to understand the budget is very complex. And when you love, your job as a they then they are your technology technology leader. I think the second point so the first is, sort of business alignment and all the first, the first, principle.

00:22:39:10 – 00:23:19:14

Speaker 2

Now the second one, I think it is, we use we already talk about it and all about these, the data and AI governance that is of organization, not be the, the, the only one, the only one player nor the main character of this story, but, build up a team, not involving all the all the all the players in the company and, for example, the security guy and, the, the innovation guys, the business, the business, the marketing and the marketing guy, Avi, boda now and why the team?

00:23:19:15 – 00:23:42:02

Speaker 2

Because is AI is not about only one function and not it’s not about as not only about technology, it’s about having a broader impact in the company. So this is a matter of not having only one deciding what is the best AI or which is the best use case to, to, to, to develop, to design, to play. Now in the in the company.

00:23:42:02 – 00:24:06:08

Speaker 2

Right. It’s about having teamwork now on prioritizing and doing the, the the right investment and the right. We are in position in the use case and third, third, I think, I think we, we already talk about it very fast, now, but that’s the, that’s the everything, make it, make it scalable. No. And improve it.

00:24:06:10 – 00:24:32:06

Speaker 2

Prove it with, strong adoption plan. I think as we as we said that now, the adoption and and the possibility to fail that in this moment, very and out of that, you know, because the technology is very great, but it’s very new. So how to integrate it, in that in processes, they use the door in the same way now, for years now, it’s a big change.

00:24:32:07 – 00:24:57:02

Speaker 2

And the most difficult one is not the technology change and all the technologies shift. That is the human, change management. So I think this is, this is, the scalability adoption is the third one. So business alignment, the data and the AI algorithm model and organization and scalability adoption are the three focus that I would suggest to any to any data in the I.T.

00:24:57:02 – 00:24:58:14

Speaker 2

There.

00:24:58:15 – 00:25:17:11

Speaker 1

Thank you know, notice I think I agree I think keeping auto in mind not focusing on the best technology in the world, focusing on the on the fail fast, adapting to the change. And I think, scalability adoption of the I, I think it’s key to its success. I think more people adopted the auto I this becomes much easier.

00:25:17:11 – 00:25:39:13

Speaker 1

It’s I, I, I think I think this is a great feedback to the fellow, investigator that, you know, what should they consider when they are implementing AI? Now? You know, I think I want to it away from the technology part. I want to ask you something, you know, in, in in terms of, you know, personally, it’ll be mentioned, we talked about, you know, that joining amplify and and doing the larger good.

00:25:39:13 – 00:25:55:05

Speaker 1

You know and AI being at the core of it, I think it’s it’s interesting. So, you know, while you, you are passionate about what you do, do you what are your other hobbies outside of this passion that you have? And, you know, how do you how do you maintain balance with it? You know.

00:25:55:07 – 00:26:23:13

Speaker 2

Interesting, interesting, interesting question. The balance is always, is always a problem in our, in our life, but I think, I think I, I really love that just said and I really love exploring the world. I used to do is, with my, with my girlfriend and wife now, and that is, to do it also with my little daughter now, I used to travel around the world because traveling gives me new perspective now.

00:26:23:13 – 00:26:44:03

Speaker 2

And continuous learning. I up for opportunities now. I am a backpacker together. And also I used to do it like like this I, I visited more than 60 counties, I think in the, in the, in all over the, all over the continents in the last 15 years. And, honestly, I really miss India are not just the referring by the I will call.

00:26:44:04 – 00:27:08:01

Speaker 2

I would call if, I even call it that soon. The sooner the sooner the better. So for sure, now, one of the best moment for me is, when I travel with my family. Because I completely stop thinking on about, thinking about work, and I really focus on my on my, on my family. This is, I think, the best, the best moment when you recharge your battery.

00:27:08:03 – 00:27:38:07

Speaker 2

Now, you can be you can be smart that night. You can be energized when you, when you come back, when you come back to work. Obviously not as every day then. I’m also really passionate, about soccer. And I’m big, a big fan of Inter Milan and the way they possibility. I’m always interested to see it, supporting, supporting the team and, the, you know, for an Italian, it’s quite easy to say that.

00:27:38:08 – 00:28:04:05

Speaker 2

And then I think that the third, the third one is I, I enjoy driving my motorbike and visiting the most beautiful places in Italy. And, and there’s another, another, another way to, stop, thinking on everything else and joining and joining the ride, and, feeling, feeling the, the freedom of, of going on about the bike.

00:28:04:05 – 00:28:21:02

Speaker 2

I think this is something really, really powerful for me. And I having this moment to completely stop thinking as, they, go over the, security or whatever and, and start, start thinking and focusing on complete something completely, completely different.

00:28:21:03 – 00:28:38:04

Speaker 1

And saying, no, I fantastic. You are invited to India. Do that be you know, we have facility in Chennai. So you know yes, I have to you have to be and we will invite you to see our bigger center, the track. You know, we have we I that’s in India. So we’ll be more than happy to invite.

00:28:38:05 – 00:28:41:05

Speaker 2

There will be there will be chance for sure. Well we’ll we’ll.

00:28:41:06 – 00:29:02:00

Speaker 1

We’ll make some plans around it. So, you know, as we wrap up for now, I think, I think, you know, what we talked about, you know, I, we talked about, you know, personalization. We also talked about the strategy and what should be, you know, what are the things we should look after. Finally, you know, what about you?

00:29:02:00 – 00:29:15:11

Speaker 1

What is it? Is there any key takeaways from from a life perspective factory? So our listeners, you know, perhaps one a professional one and one can be personal if you have some two key takeaways for our listeners that be great. Does that mean.

00:29:15:12 – 00:29:47:08

Speaker 2

Yes. Yes. I you know, I’m not, I’m not a big fan of, giving other, takeaways. I give you another suggestion because every everyone as it’s so on and I’ll take it. But if I had to say, you know, for for for professional takeaway, I think that we discuss a lot about, I think there are and I think, yeah, if you ask permission is like, we talk about the marshmallow challenge, and I think marshmallow is like the marshmallow challenge.

00:29:47:08 – 00:30:12:05

Speaker 2

It’s not about the planning for perfection. No, it’s about just preventing, adapting and deteriorating, quickly. You know, it’s it’s about the AI, and it is about, technology in general. Now, this is the profession that they can worry about is simple, but but it’s, it’s, it’s a it’s a real life area. Work life. And for the personal, for the participant to take away.

00:30:12:05 – 00:30:36:07

Speaker 2

I think the point is there’s, there’s a very, a very big fan was want to say stay, stay curious. And I’ll say, Angus curious. And I think this is, this is something that I, they, they used to think about every time now, whether in business or in life, and all continuous learning got will always lead you to, to do something special.

00:30:36:09 – 00:30:53:00

Speaker 2

Now having always the curiosity to do something different and not, living in the status quo and, not living in a comfort zone, I think is the is the most important, is the most important takeaway that I always follow in my in my, in my life.

00:30:53:02 – 00:31:15:02

Speaker 1

I couldn’t agree more. I couldn’t imagine, but I think, stay good. Curious is very important. I think it it opens a lot of possibilities. You see things sometimes actually to the point of view. So I couldn’t agree more. I think, well, you know, Giuseppe, thank you so very much for, for the key takeaways and taking out the time, we and sharing your thoughts, you know, and being part of our podcast.

00:31:15:02 – 00:31:33:14

Speaker 1

I really appreciate this. And I’m sure that, you know, the, the the listeners would have gained a lot from the, from the AI, the strategy that you mentioned and the common pitfalls, etc. and, I’m sure there’ll be some learnings for all of us, but thank you. Thank you so much. She had a good experience.

00:31:33:15 – 00:31:36:12

Speaker 2

Thank you. It was a really a pleasure.

00:31:36:13 – 00:31:37:13

Speaker 1

Thank you. Directing.

00:31:37:14 – 00:31:39:05

Speaker 2

Thank you.

00:31:39:07 – 00:31:48:00

Speaker 1

Okay, good. Maybe I think it was okay because none of us from my side. But. Is that me? Was that you were great.

00:31:48:01 – 00:31:50:08

Speaker 2

I do it for job.

00:31:50:09 – 00:31:52:01

Speaker 1

You do? Yeah.