How Agentforce is Transforming Businesses in ASEAN with Sujith Abraham
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what's the point if it's a fast platform but i still have to go somewhere else and the last thing is speed right now especially in our region it's a land grab right when we think about some of the fastest growing economies in the world indonesia vietnam the philippines you have hundreds of millions of people here and every customer i speak to is interested in how they use our platform to be able to move faster

to be able to deploy AI. They don't want to have to build a foundation level of AI, build all those elements in. They want to be able to deploy it faster. And when you think about our history, we have 250 petabytes of data being accessed by 150,000 customers every single day. We had to get this right. We had to make it because we have thousands of engineers focusing on building these platforms so our customers don't have to.

so they can deploy innovation, they can deploy really unique and differentiated customer journeys.

Welcome to Analyze Asia, the premier podcast dedicated to dissecting the powers of business technology and media in Asia. I'm Bernard Leung, and agentic AI is about to sweep the globe. What is the future of AI agents? With me today, Sujith Abraham, Senior Vice President and General Manager, ASEAN. Salesforce, to tell us about AgentForce 2.0 and what it means for the enterprise customers.

Welcome to the show. Thank you for having me, Berg. So it's very interesting because I saw Mark's keynote on agent force last year, and I think it would be great for you to tell me what is this context specifically to the Southeast Asia customers here. But of course,

Every time when we have a guest here, we want to hear their origin stories. So how did you start your career and eventually end up in Salesforce? Oh, thank you for the question. Look, I didn't actually start off in tech. I went to an engineering school that was very tech-based, but I actually started off in the automotive industry. And if you can believe it, I was designing seatbelts and airbags.

Yeah. The only thing is I ended up in Michigan. I didn't really like the cold weather. I didn't really like engineering and I was away from any sort of ocean. Other than that, it was great. So I honestly, I got on a plane. I still remember it was 96, I think it was 96, 97, 97.

And decided to take a chance and went out to California. I mean, it was growing like crazy and they were looking for people from the industry. And I ended up at Oracle when they were getting into their foray with enterprise applications. And it was just an incredible start. And they brought me to Singapore in 2004. I saw Salesforce from its humble beginnings back then.

And, you know, I admired them and we had been talking, but there was never really quite the right role. And then strangely enough in 2020, I was on a trip home to visit my parents from Singapore. I've been in Singapore for almost 20 years now, but I was, I was home. It's been a while. And, um, I got a call from them and it was a role that I wanted and they gave me the opportunity to run Southeast Asia and then the rest is history. And so I've been here for five years.

I see. So I think interesting thing as a senior executive, what are the lessons from your career journey that you can share with my audience? Oh, interesting question. Look, I think for me, what I can say is it was just as important to figure out what I didn't want to do as much as it was figuring out what I did want to do. And

That process of elimination was really deciding that engineering really, as much as I valued the study and the background, it wasn't something that I was excited about as much as I was excited about high tech. And I took a chance, right? So I knew I didn't want to do this thing. And I wasn't totally sure about tech. And I did that. And I encourage everyone to take that risk. And I think that has served me well. There are other instances in my life that taking those risks has served me well.

The other thing is, I would highly suggest that you follow your passion and not follow the money. I've seen a lot of people pursue things. And again, each person is different. But I know that if I don't enjoy what I'm doing, if I'm not passionate about what I'm doing, no amount of money can make up for it. And so for me, if you love what you do, everything else will fall into place. That's great. It's like the privilege of a lifetime is to be yourself.

Yes, that's right. It's a gift if you get a chance to do that. So I want to get to the main subject of the day. I want to talk about Asian Force 2.0 and Salesforce in Southeast Asia. So maybe to start, can you introduce Salesforce, its global mission and vision, and its current footprint in Southeast Asia or what we call ASEAN region? Yeah, I can definitely do that. So Salesforce, that's hard. What we want to do is help our customers understand

connect with their customers in a whole new way, right? So whether that's across digital or messaging or the web or email or even coming to a physical event, we want to be able to help our customers bring all their signals together and drive a 360 view of that customer. And then we want to democratize all that access across your sales departments, your service departments, your marketing departments,

all underpin by AI plus data plus CRM, right? All of that helps drive customer centricity. What's really exciting today, and you've been touching on it,

is this third evolution that we're in, this third phase of AI, which we're leading with agentic services, so autonomous AI agents, or what we call agent force. So it's a super exciting time because you have this always on, basically autonomous being helping and assisting customers and employees drive customer centricity. Now you asked about

Southeast Asia. So we, we started in Singapore in 2004 and I was, I was an admirer from afar at a competitor. And in 2020, that's really after I was able to come, we opened up our second entity in Thailand. And then we opened up a third entity in 2023 in Indonesia and

Soon after that, we also opened up Hyperforce, which is the cloud or the public cloud version of Salesforce. We first in Singapore and then in Indonesia as well. And so that opened up our ability to service regulated industries, bring data more close to home. We work, we have our public cloud infrastructure on AWS. But beyond that, Bernard, our mission really is we see business as the greatest platform for change. Right. And so we're very values led.

Trust being our number one value, customer success, innovation, sustainability, equality. These are all very important. If you ask any Salesforce employee, they'll be able to quote all those as the things that are very close to their heart and what brings us all together. The other thing I would tell you is we're a family in Southeast Asia of 1,000 employees. So a great, vibrant community.

We are very lucky to have customers like Siam Commercial Bank, we have Singapore Airlines, we have Converge, Techcom Bank in Vietnam, Indosat. So really great span of customers ranging from different industries and different sizes. And we're really excited and getting into a lot of conversations around the future of digital labor.

So let us first, I think, baseline the following to help my audience to understand the key concepts, right? How do you define generative AI and AI agents? And how does this intersect with enterprises specifically for applications? Sure. Maybe if I can, I'll even draw back to some of the other forms of AI, right? So you have predictive AI, right? Where you're looking at historical data to predict patterns or infer patterns, right? And that's where...

We started with our own AI in 2014. Generative AI is taking data to create new things. So it could be new images using prompts. It could be answers. We're all familiar with ChatGPT, right? And how that essentially surfaces an answer based on connecting vast streams of data, right? Mid-journey, you may be familiar with creating images, right?

That all enabled, that was all enabled through co-pilots, right? So co-pilots, you could go in, ask questions in natural language and come back with an answer or an image often referred to as prompting, right? Now, that was a good start and it helped move us forward. But what was lacking was the ability to drive action, right? So it's great that I can get an answer, but what if I want to actually follow through to do the upgrade of my plane ticket, right?

I want to be able to get through to a referral at my healthcare provider, right? I want to actually realize that loan without necessarily having to wait for the human to come back online. That's where agents and our agent force platform are powerful because they drive action. Oh,

So it's actually invoking the action coming from the sort of the prompt from the getting the knowledge base from the large language model. That's how he actually pushes the action into the real world. Correct. So like if you look at, you know, Remarkable, you know, the new notepad company, they stood up agent force in three weeks and could suddenly serve as

thousands of conversations any time of the day and night, basically. We have Heathrow Airport that is shepherding passengers along, connecting with flight information, allowing them to get to different vendors and merchants in the airport. We have Wiley Books, for example, who has...

driven case resolution and improved it by 40% productivity. So lots of great stories. Saks, Fifth Avenue, luxury retailer driving hyper-personalization at scale. So lots of great stories, lots of great customers doing amazing things with this platform and driving action. So Mark Benioff, the global CEO of Salesforce and also founder as well, has touted the importance of agent force in your recent Dreamforce Conference 2024. I'm curious

currently teaching a class to both government business leaders and also to the engineers on how to use, build their own large language models. The question of agent force actually came up.

Because I think there's a lot of thinking about how to think about bringing AI agents to the real world. So can you share the key ideas behind Asian Force and how does it work for businesses on the Salesforce platform? Sure, I can do that. Can I ask you a question? How excited are you when you talk to a bot?

Well, I think I'm okay talking to a bot, but I think to a certain point, if the bot cannot resolve my queries, it better be routed to a human being. That's exactly it, right? Because it can't answer the question, right? There's only a point. And, you know, the background to that, I'm sure you know, I know being an expert in this area yourself,

is that we're talking about a decision tree. So hopefully the answer to the question you have in mind is there, but most of the time it's not, right? It's been a terrible experience and we're all pounding the agent, please, agent, please button on there, right? So the difference with agent force is that it's a natural language conversation, right? So all these years we've had these application platforms that have been storing information

data about our customers in them. But the reality is we also, as Salesforce realized, not all your customer data

is in Salesforce. It can be in your other systems. So if you're a bank, it could be in your core banking system. It could be in your ERP. If you're an airline, it could be in your passenger booking systems. And so if I draw the analogy to working with a doctor, for example, senior doctor, that doctor, there's a lot of similarities because that doctor brings something to the table that you just can't get with somebody who's not that informed or a practitioner. First of all,

They have all of your information, all of your medical records, right? So in the same way, agent force brings all of your data together. Now, the important thing is that the way we bring your data together, so you may have, for example, a data warehouse. You might have your data sitting in Amazon. We don't copy all your data together. We unify it and reference it. That's what allows our co-pilot to go in and surface the answer. So like the doctor looking at your records are bringing that information together, right?

We bring it with zero copy, right? The other thing is, like a doctor and different from a bot, is we need to use powerful reasoning. So we have an Atlas reasoning engine that allows us to discern, is this about a ticket upgrade? Is this about a loan? Is this a question we should be answering or shouldn't be answering? So that power to reason and use all the information we have available about you.

about our products about our guidelines are you eligible for that upgrade or make this very powerful then the then the other the third element is trust right can you trust this answer how do we make sure that the answer we're getting back is a hallucination it's not false information how do we also make sure that when we go out to a to the external llm to construct the answer

that your data, your IP is not getting out there. That's the third element. Fourth element really comes down to putting these actions in the flow of work. So if I'm an internal person, I'm an employee, I'm working with a customer and I have this agent supporting me, I don't want to go somewhere else.

I want it to be right in the flow of work so I remain efficient and get back to the customer very quickly. I mean, what's the point if it's a fast platform but I still have to go somewhere else? And the last thing is speed, okay? Right now, especially in our region, it's a land grab, right? When we think about some of the fastest growing economies in the world, Indonesia, for example, right? Vietnam, the Philippines, you have hundreds of millions of people here.

And what we see in every customer I speak to is interested in how they use our platform to be able to move faster, to be able to deploy AI. They don't want to have to build a foundation level of AI, build all those elements in. They want to be able to deploy it faster. And when you think about our history, we have 250 petabytes of data being accessed by 150,000 customers every single day.

When you take that set in, we had to get this right. We had to make it because we have thousands of engineers focusing on building these platforms. So our customers don't have to.

So they can deploy innovation. They can deploy really unique and differentiated customer journeys. So I would understand that maybe agent force also works for Salesforce suite of products. Let's say, for example, Slack. Correct. Yes. That's exactly right. So we have our AI in all of our products, whether it's Pulse in Tableau, it's iCompatible,

Einstein in Slack. It's our sales, service, marketing agency. We have what we call SDR coaching agents. We have sales agents. We have service agents. We have marketing and commerce agents. So it's AI anywhere you want it in Salesforce. So if I were to think about it, how does AgentForce actually operate as an AI assistance? I think

One of the questions is there are certain components, right? Say, for example, a customer service agent, you have a certain requirements of getting the customer FAQ situations and how to resolve giving the sentiment analysis. And then in the sales agent course, the SDR course is a totally different thing. You're trying to qualify a sales lead.

or maybe even for marketing as well how you get able to configure these different agents under the agent force right so the key thing the starting point is to make sure you've brought all your data together so we have a very powerful platform and this is where all of our organic development came in we started with something called data cloud data cloud is our data platform that connects all your sources of information right because we're going to have good ai

You need to have good data, complete data. So data cloud is at the heart of this whole thing. It connects whether it's Salesforce or AWS or Databricks or Snowflake, your ERP systems, anywhere Bernard lives. We connect that into a unified platform of who you are. Plus, we also bring in all your product information.

you know, your do's and don'ts, right? What your guidelines are on who can be upgraded. So if you're calling into an airline, we bring all of that together. Okay. Then, you know, we of course have our co-pilot layer and then we have our agent layer on top of that. The agent layer understands through the reasoning engine, which we call our Atlas engine. So think agent force, Atlas, data cloud,

All those pieces come together to make sure that the answer that comes back is contextual to you, where you are as a customer in our customer's sort of matrix and what you're eligible for. And that's important because that's what drives speed and our ability to answer quickly. I think, Suju, you made a very, very good point about the data cloud. I think a lot of businesses or CEOs, business leaders thinking about AI, I think they

usually overlook the importance of integration of data source to allow themselves or even set up the infrastructure. I think McKinsey had a report say somewhere around 20 to 30% of companies actually data ready for AI applications. So is that how I think about when agent force being having this data layer plus the agentic layer that differentiates itself from the rest of the other enterprise AI applications similar to this

in the ai era that's exactly right because you know a lot of you know a lot of organizations try go down the diy path right and it's a bit like we could start an insurance business but that's on us we're better off working with an insurance provider who really knows this space well so a lot of organizations their core competency might be could be an industrial it could be a transportation business

When they get into this area, just to get to a standardized level of security and trust takes a lot of work, right? So getting to unify all your data sources, making sure it's accurate, that's why we've focused on taking the work out of that so that you know when you're running on the Salesforce platform, you can connect all your data sources in a trusted way and get a reliable answer faster, right?

Otherwise, you're going to be building that and the idea of trying to deliver innovation is going to be something you're chasing for a long, long time before you ever realize it. I used to be a user of Salesforce when I'm in my corporate career in one of the tech companies. But, you know, I think now with AgentForce, probably half my work is actually automated. Yes, we'd love to. I mean, look, we want to, our goal is to have it work with you and help you drive more and more productivity. Yeah. So I think one

One question that comes to me is a lot of businesses are currently in experimentation, but they have to get to some point to full-scale AI adoption. How does AgentForce actually help them to overcome some common challenge? I think the question, I think scalability, integration workflows, but I think there's also a specific area that you alluded to, which is the trust part.

the ability of less hallucination, making sure the information that is given correct. I definitely know what happened to Air Canada recently on that. Yes. Well, let me, that's a great point. When you're talking about enterprise AI, right, actually, the assumption is that the answer is within your four walls, right? It's within your data. So,

When we think about maybe consumer AI, chat GPT, the way that works is it's essentially consumed the web up to a certain point, right? All the data is out there. When you look at enterprise AI, there is an entire AI stack that's supporting the surfacing of that information that you have to build. We talked about the Atlas engine. We talked about data cloud. We talked about the agentic layer. The actual external LLMs that you hear about

Those are used to construct the answer, but we don't actually let your data go into those LLMs, right? They're just there to formulate and articulate the answer back. And so we take all of that work away. So you're not having to constantly test, is your agent doing the right thing? Is my trust layer really reliable? Is it keeping up with the changes, right? Is my data platform really bringing in all those sources of information accurately? And am I coding it?

Or can I do that through low code? So we take away all of that complexity with no less sophistication

and enable you to focus really on building your customer journeys out in a unique way. I think it's like think solution rather than think of the components so that the customer has the ease of just getting into what they need to do rather than trying to think about what they need to build to do that. That's exactly right. Think deployment rather than think building. Would you go build your house yourself? No. Right? I'd probably have to hire a contractor. Yeah, same. Same. I wouldn't trust myself. Yeah. But I know what I want.

So one interesting thing, and I think I'm very excited with AgentForce when it first came out, was actually the business model. It's very interesting because usually SaaS is a subscription based on user. But I think the way how AgentForce is charged, I think is actually do the work we do, pay as you go for the work we do. Can you talk, explain a little bit about the business

business model, the way how customers are actually thinking about this new way of pricing with agenting. You're exactly right. So what we are shifting to is a consumption model, right? So as opposed to, you know, a per month fee, that's just a blanket fee, you pay for what you use, right? So in our case with AgentForge, it's based on conversations, right? So think of each session, each 24-hour session as a conversation, right? Ask all the questions you want within that session. And so...

That's what drives a consumption. So you essentially can pay for what you consume. Do you find that the customers in this region, because I'm going to be asking you what are the interesting case studies, are they actually much more open to this kind of new business model? They are. I mean, look, it's not the first time. We know Amazon, for example, has been operating on a consumption model, right? And I think it gives them a new way to think about things, a new way to engage with us.

and understand exactly, pay for what they're using. And so they like that as opposed to saying, we're just going to keep paying a fee over and over again. I do the same for my customers now even as well. The pay-as-you-go model is actually a very big step, I think, for Salesforce to actually come into this domain.

I'm pretty curious, like what are the really interesting use cases in that Salesforce has done for industries in this region, for example, say logistics, finance and retail within the Southeast Asian market? Yeah. So let me, let me talk about that a little bit in the sense that we are having a number of POCs underway as we speak, and we're excited to be able to share those soon, but to give you a sense,

We have banks looking at how they completely reimagine wealth management and a wealth advisor's role. So sometimes these banks are, a wealth advisor can only handle so much. They're trying to handle multiple customers. And same thing on the institutional side. How do you manage the onboarding process? Look, there's only so many hours in the day. Imagine if I had an always honest agent supporting me and engaging with a customer that I've established a relationship with.

We think about the airlines. Think about several months ago when we had that massive outage. People are trying to call in and trying to get service. They couldn't. Imagine if you could spin up an unlimited amount of digital labor to personalize their responses to every single person who needed help. Imagine what the customer satisfaction rates would have been like if you're the airline out there being able to service your customers uniquely. So we've got banks,

We've got telcos looking to, we've got really interesting use cases for the telcos. We've got, we've got healthcare providers. We've got the government. We've got educational institutions all looking at how they service your customers and constituents all the time.

with natural language conversation. So we're seeing a lot of that. Broadband companies all looking at how they basically grab market by servicing their customers better. And in our region, it's really important. So I think...

I think you talk a little bit about the governance and the trust part. Let me dive a little bit deeper. What kind of safeguards are in place within Salesforce? Because sometimes the agents would make the decision, right? So how does it ensure that there's some kind of transparency or accountability to, say, audit the decisions that are made by the autonomous agents that's actually doing the work for you?

Yes. So first and foremost, you asked me about this earlier and I wanted to reemphasize this. Trust is our number one value, right? So that means we put a lot of focus on making sure trust and call it the trust there. I think we're probably one of the most vocal talking about it. So we are very careful when we do anything with language or translation and making sure your data doesn't end up

in the public corpus. So we are constantly, our engineers are very, very focused on making sure the information that goes in and out

is trusted. We'll be testing that with synthetic data. We also have an office of ethical and humane AI that governs what we do. We speak about it. We publish on it. We have an AI research team, by the way. The first AI research team sitting outside of California sits here in Singapore. We have a ton of effort and investment. We're working with our customers constantly to monitor it. We go through our POCs. We're looking at accuracy and looking at how we increase the accuracy. Then we're

fine-tuning our technology to ensure that accuracy only increases. And that's what's really interesting. Some of our customers are looking at 95 plus percent accuracy in their answers. I believe with Heathrow Airport, the accuracy rates are really, really good. So I advise a lot of CEO business leaders on adoption of generative AI. And this question always comes to me. And when we introduce a full solution,

With the LLM in the background, they will usually ask me, you know, which large language model they use. So I guess, how does AgentForce actually decide which foundational large language model they use? Yeah. So there are a number of different models that we use for different purposes, right? So if you think about the external models, which we're all familiar with, OpenAI, Google, whoever it is, first and foremost, we allow you to bring your own model.

But I have to tell you, that's only a fraction of where the work gets done. The majority of the work is actually through our own internal models. So we use XSlam for reasoning. So our Atlas reasoning engine uses XSlam models. We also have small models that we use for different purposes. And so we have a range of different models that we use across. And the ones that you hear about are...

or what we use when we reference an external model. But again, we're open. I will probably have to say this because I do know Salesforce was one of the earlier pioneers in the large language models. I think that was based on Einstein. I think that was the earlier iteration of that specific model itself before that. So what would be your advice to your customers when it comes to generative AI? What would you tell the CEOs, the leaders, maybe government leaders, what to do and what not to do? That's a great question. Look,

I think first and foremost, think about what use case you're trying to solve. What are you trying to do? You mentioned McKinsey at one point, and they came up with an interesting study that I believe 75% of the value is actually in the front office, right? So it kind of behooves us to say, what can we do more of for our customer? So first and foremost, think about what use case. Is it how you're going to service? How are you going to sell? How are you going to market, right?

Second thing I would really think about, and this is fundamental if you want to do good AI, is how do you unify your customer data? And it's not just about the data sitting in your CRM system. Do you have a mechanism to quickly connect your other systems, right? Third thing is, have you built trust? Have you got a platform built around speed? That's where I see a lot of customers are now coming to the realization of this DIY effort, right?

is really not panning out. It's expensive. There are certain reasons to do it, for sure, and certain areas where there isn't something like Salesforce's platform available. But if you're really looking to garner value, because right now it's about speed. And if you're going to spend all your time, and we've been out there with customers where we're benchmarking ourselves against them, spending a lot of time trying to get it right, trying to get it accurate, trying to source your customers,

They're going to continue to spend that time when we've already built it. They can leverage the capability we have, connect their other systems, and deploy this capability so much faster. Frankly, it's a land grab. It's a land grab. I can tell you from the number of conversations I'm having and the number of PRCs we're doing,

it is top of mind for them to focus on deployment speed more than building it. So what's the one thing you know about Salesforce and agent force in ASEAN that very few people do that? Oh, well, you know, one thing we're really proud of, particularly given where you and I are sitting, is that our first research AI research center ever was here in Singapore. And it actually files more patents than

than our other departments. It's at an incredible rate. They're working on helping us build our product out, the use cases. They're doing some really, really great work. And I'm very lucky to have them sitting here in this building. Wow.

Henry Suryawirawan: Wow. So actually I wanted to follow up with this then. How do you envision that AsianForce and maybe even your innovation center here actually go with say broader AI initiatives that are shaping the ASEAN ecosystem then? David Pérez: Yeah. So one of the things that's been true to us is our community, right? So we have our trailblazers who you may be familiar with. These are, these can be individuals, these can be our heroes within organizations and

They're taking our platform and doing amazing things with this stuff you couldn't even imagine. And that's why I often say it's a platform, right? Then we have our developer community who's building IP on it and making new customer journeys that they can either commercialize or make available. And similarly, our customers themselves, right?

We will be delivering them out of the box capability, but they can then build on top of that and say, we want to build capability specific to an airline, specific to a logistics company, specific to a bank that differentiate that. So we're really proud and excited about the idea that, or governments, for example, how do I drive maybe even a new journey into the CPF here, right? Or how do I make that even possible in other parts of the world? And, you know, we've got, we're very lucky because we have an incredibly advanced, uh,

a forward-thinking government. We're excited to power enable that group as well to serve citizens even better. So what is the one question that you wish more people would ask you about Salesforce or AgentForce? You know, I wish they would ask me why Salesforce. I could just ask you that now, right? Yeah, you can, right? And it's a fair question. I alluded to some of this before, but first and foremost, it comes down to

The fact that we've thought through a lot of this because we've had to. I mentioned we had 250 petabytes of data and we had to get this right, 150,000 customers. So the ability to bring the data together and be able to leverage the good work that our customers have done standing up other data warehouses or the ERP, right? Being able to build in some of those things that you think about when you see your doctor, a very strong and intelligent reasoning system like our Atlas reasoning system, right?

the ability to have trust built into the platform. So you can trust the information that's coming out of it and also wherever it's going and making sure that your information, your IP is not ending up in the public domain. It also comes down to being in the flow of work. So your employees are not so nurturing, but they're really being able to get supercharged and actually operate faster and be able to get the information, not be subject to frustration. In fact, I was just talking to another customer the other day

who are sharing the amount of attrition they have because their new employees can't get on board fast enough. And so having an agent to support them would take down a lot of the anxiety they have when they get tough questions.

And then the last and probably the most important thing is speed. I mentioned this before. We can offer incredible speed because we've developed this thoughtfully and with all the components you need. So again, you focus on the deployment, right? Because as I said, it's a land grab. Yes. Right? And we have some massive populations and some high growth economies. And we got...

we've got big and small customers coming to us because they recognize it too and they want to focus on deployment, not on development. I see. So my traditional closing question, what does great look like for Salesforce or agent force from your perspective? Well,

Look, for me, for us, for all of our organization, when we go and see our products enabling incredible new journeys for citizens, you know, whether it be connected to government services or let's say patients or passengers.

or customers of a bank, and we can see that we've enabled capabilities that are making everyone's lives better, more efficient, giving them the support that they need, democratizing that access. I mean, you know, I'm sure like me, you're busy during the day. You can't always get back in time to have that call after hours, right? If we can make our customers' customers' lives better,

it makes us feel really, really good. And then that helps us drive change. Yeah, I'm looking forward to that. So Sujit, many thanks for coming on the show and thank you for having me in your studio to have this conversation. But I always have two very quick closing questions. My first one, any recommendations which have inspired you recently? Okay, I'm going to give you...

A non-technical one. Or is it a non-sales question? Go for it. So I encourage everybody to experiment with AI, no matter what it is. I have been playing with Midjourney and with Runway. You know, my team, we've been thinking about how do we tell the story fast enough, right?

So we've been building stories using Midjourney, which, you know, is an image creation platform. And what you do is you start off with an idea and Midjourney will develop that image. That's right. And then we animate that with Runway. I see. And we show...

We show our solutions in context for that. Imagine years ago, you'd had to go out and hire a big studio, actors. You can actually now create that prototype. And then you go to the professionals and say, I want this. Can you help me to refine it? 100%. And it's really democratizing access. So I think once people see the tools that are out there and play with it,

It's amazing how much easier you can make your life. I know some of us don't necessarily like to write, right? Or some of us, you might want to get something out there in a different language. How do you do that? Now you can do that. And so my advice is go out and experiment. Yeah, I would add to what I call the Chachupiti Blast.

combination where you try to use whatever to generate the outline of a presentation, put it into Gamma and then it generates this beautiful presentation for you. Which a lot of my students loved it now. And it's actually easier to do business school classes now. Yes. With them because they actually use the tool to do it for me. So how do my audience find you? LinkedIn. Okay. They can find me on LinkedIn. Very easy to find me. Sarah, if you need to get in touch, please find me on LinkedIn. And you definitely can find me

us in anywhere from YouTube, Spotify. By the way, Spotify is now on video too. So share us with your comments on the episode and most important, let us know who you are. And Sudhir, many thanks for coming on the show and we should probably talk again at some point. Absolutely, Bernard. Thank you for the time. Really appreciate it.