 Fortunately, we do have a positive time, which is why we're not going to set the stage and get started with our panel discussion. Now, while we're doing that, I'm going to keep urging our members of the audience to keep those tweets coming using hashtag screenage. And we'll also take a minute to also thank our partners for the fantastic support. Our presenting partner for the screenage is Sony Live. We live to entertain. Associate partner, share it. AI and big data partner, MoMagic. Data-driven intelligence and badge and Lanyard partner, times now, action begins here. So on that note, we're about to get started with our first panel discussion for the conference over here. And this is where the theme of the panel discussion will be about how AI is going to unleash a new wave of marketing revolution and how enterprises need to adapt in order to be competitive. I'm going to urge our members of the audience to please be seated because it's time to get started our next panel discussion and we have some very esteemed panelists joining us in a short while. Well, that's right, please do note, it's not a break. It's slightly a minute break on the stage, giving it a quick makeover, but I'm going to urge our members of the audience to please be seated. In fact, this interesting session will be chaired by Mr. Sanjay Trehan, digital and new media consultant who in fact will be responsible in extracting perspectives from the fellow esteemed panelists. So we're going to be inviting him along with the panelists on the stage to come together and deliberate on this very important topic on how AI is going to unleash a new wave of marketing revolution. All right, so well on that note, as we get the session started, firstly I'd like to invite our session chair, Mr. Sanjay Trehan, to please come on the stage. So ladies and gentlemen, let's have a round of applause to welcome him on the stage as well. And joining him, let me also invite our esteemed panelists as well. May I please invite Jason Buu, Chief Strategy Officer, Mo Magic. Jyoti Kumar Bansal, CEO with PhD India. Varag Murudkar, Executive Vice President, Head Digital Marketing with Yes Bank. Mr. Ravi Shaube, Head Digital Marketing with Bajaj Auto. Vanita Keswani, CEO, sorry, CEO, Madison Media Sigma, Madison World. And Premjeet Sodhi, Senior Vice President, Mindshare Falkram, South Asia. Ladies and gentlemen, let's have a huge, huge round of applause to welcome our super upset of panelists over here. And I request Mr. Trehan to take it over from here for the next 45 minutes. Over to you, sir. Good afternoon, everybody. This is such a fascinating subject, the one which is at the cutting edge of what we are currently doing. And hopefully the one which is going to catapult us into the next generation of consumer experiences. Now, I've been doing some reading and recently read a fascinating study and if you haven't come across that, please look for it. The Cap Gemini study on AI and what it showed us was that as large as 84% of marketing organizations in the US are implementing AI. So it is not a buzzword in the most developed economy of the world, it's already happening. Interestingly, out of these 84% that are implementing, 75% of these enterprises that have actually implemented AI have seen a consumer satisfaction scores go up by more than 10%. So from a marketer's perspective, it is something which is of tangible value. So this afternoon we have a very illustrious panel and I'm going to be focusing on talking about the challenges that the companies in the Indian perspective are facing in terms of implementing AI. We're going to talk specifically from a consumer perspective about the deconstruction or demystification of AI because this is a buzzword and a lot of people perhaps may not be aware about what all it entails. So we will talk about that. We will also talk about how from the complete gamut of predicting consumer behavior to looking at price predictability, price elasticity, and ultimately price enhancement in terms of upping the profitability, how AI is playing a critical role. But most importantly is from an organization's perspective, price optimization or optimization of marketing efficiencies is the core objective or ultimately the core objective is enhancing consumer satisfaction. We will talk about that. We will also talk about technology at the core of AI versus human ingenuity. Can it only be, will it be 100% table stakes for technology or there is a play for human ingenuity in that? So we will talk about this. The way I'm going to structure this panel discussion is that we have six very smart people and I would like to take some of these specific questions. I had to address maybe a specific question to maybe two panelists so that I can take in around six or seven different aspects of AI and we would talk about this for around 40 minutes and in the last five to 10 minutes I'd like to open it to the audience and take in their questions. So after this preamble and a little bit of rambling, let me now begin the conversation. The first question that I have in mind to the panelists and I think what Vinita would you like to take that which is, how do you demystify the strange animal of AI, machine learning, big data? How do you demystify it from a consumer perspective? What does it entail in your day-to-day working? How does it translate into the benefit for the organization and the consumer? Yeah, thanks Anjai. Good afternoon to everyone. First of all, AI, which is artificial intelligence, simply put would be, I would say, like I said, demystifying would be simply put the ability of machines to exhibit intelligence like human beings. Very, very simply put, ability of machines to exhibit human-like intelligence. Basically technology is at the root of AI which is what again, Anjai just mentioned. So AI technologies can be classified in various different ways, whether it is based as the functionality in terms of like say it's text, speech, image recognition that we've seen all around us, or based as the business types that it helps in, suppose e-commerce, auto, et cetera. The way I'd like to really propose what I think about AI in the sense of the vastness and the space of AI in general, is that almost like the four P's of marketing, we have the four P's of AI, which is the way it touches across the value chain for all of us. So the first P would be a project, which would be nothing but R&D forecasting, using data and using it for data analytics, which is the project type. The second would be the produce type, which is where automation is there for automated cars. So you produce stuff, like you make products which allow you to use AI technology. Third, which we as agencies and members in the panel would use the most, is the P of promotion, which is to target the end consumer in digital media and targeted better media, which is the P of promote. And lastly, as consumers, which is the P of provide, which is all of us get a better user enhanced experience. So that's the way AI can be put. So some examples that will make this come alive would be like I said, project would be R&D. So in advertising and media also, each of these P's could be done. So not only promote, which is the predominant part of AI, but also provide. So customer experiences provide, we've done many, many innovations, which I think when we speak more, we'll talk about. I hope this kind of just demystifies it a bit. Interesting, in fact, Kotla will be very proud of you, four P's of AI, interesting. Jyoti, would you like to amplify on any other aspect that she may have left out? So I think Vanita has covered the basic of what AI is about quite well. I think the way I would like to add a layer to it is in terms of what we can do with it in terms of our day to day work lives as marketeers, as advertisers, as media companies, because there is so, so much data that is getting generated every day. And I think that's why it's becoming so much more important for us to understand this whole piece. Today there are maybe some 6 billion or 8 billion connected devices or objects in the world. In another less than 10 years, there'll be 27 billion. So I think from that perspective, everything is generating data. And for us to be able to harness that data to make intelligent decisions is going to be super, super critical. So it will have an impact on everything that we do, whether it is new kinds of job roles that will emerge, whether it is the way we connect with our consumers to enhance their experiences, which is the fourth P as Vanita mentioned. Or it is in terms of preparing ourselves for a future when AI will literally be the X factor and almost like the electricity around us. It will be so ubiquitous and omnipresent. Fantastic. We will not now shift gears to the Indian domain and look at currently, you know, the receptivity of the Indian organizations in terms of adapting to the challenges of AI is there. We are seeing early and very aggressive movements in the banking and the e-commerce space, but we are also looking at a few challenges there. So let me shift gears and talk to Parag about what are the specific challenges the companies who are looking at fast adaptation of the AI currently facing? Yeah, so in my point of view, the biggest challenge that today any organization has is the right type of data. Now let's say that because you cited example of banking, if I have to implement artificial intelligence for banking, I'm doing certain KYC width of the consumers and there is no right source of data available to me. How am I supposed to do that? Right? There are certain fraudulent protection, preventions, things that we want to carry out, but there is no right source of information which is available there. So if you ask me in order of priority, data is number one, the biggest challenge that we have today and data is the backbone of AI. AI is nothing if the data is not right. Secondly, you talk about, we've heard about this whole NLP and everything and right. But if the banks have to cater with NLP to the mass audience, right? They have to do a huge progress today because today NLP is available in only few forms. It's only the main languages that are available today. So that I think is the second challenge that we face. Third challenge is the resources. Like let's assume that we have these fantastic tools, there are some amazing solutions which are available in the market, but there is a huge shortage of resources. We don't have people who can manage these tools. The right people, what we call as data scientists, data engineers, data analysts, who can do this. So that's the third challenge, what I feel. Again, there are other challenges like the whole infra cost, the time to market. These are again challenges which organization faces today and these are practical challenges. By the time you implement something and things are live, you start feeling outdated. So how do you stay outdated? What is the whole scalability of this entire thing? Like if you're investing in infrastructure, how long can we sustain with that kind of infrastructure? That's always a challenge because the whole space is moving in such a rapid pace that it is very difficult for you to kind of cope up and plan for the next. If you say that I'm doing futuristic planning on AI, that futuristic planning will be not more than two years. So that's the challenge that typically organizations face. Fantastic, in fact, data is the new key buzzword for AI, but when I look at data, data is just binary quotes for me. My question to Ravish, you is, how do you derive insights in a meaningful way from this data? And when you look at predictive modeling, do you only look at price elasticity in terms of upping the profitability or do you also look at a tangible benefit to the consumer? So share with us some examples of what you and your current, currently your company is doing. Sure. So basically when we think of AI or even consumer experience, and I will start with the consumer experience and move more to the data and the insights. But what is the epitome of good consumer experience? So in my opinion, it's when you walk into a restaurant and actually there is a chef there who says, Mr. Ravish, please come. And here is the dish which you'll usually love and here are the variations. And before you even saying anything, you feel as if the organization or the restaurant actually knows you and gives you that kind of experience. Now this experience is today available to some of, of course, to some of the well-known personalities or to the regular customers. What AI will enable us to do is to basically democratize this whole process. And it is easier to do when we are talking about online challenges and when the person is online interactions and when the person is online through an app or through a website. So that is one of the bits where AI will actually enable all the organizations to serve that kind of experience to everyone. Now in terms of, in order to extract these insights, one of the biggest barriers which we are facing as you rightly pointed out is data. And before even moving to outside data, most of the organizations are not ready in terms of integrating their inside data to extract those kinds of insights. Let's say the first touch point today for the customer usually is the website. Then he comes to the app, maybe registers. Then he purchases. And then there is a post-purchase kind of behavior which he elicits. Now you call most of the call centers today. They will have absolutely no clue about what you have purchased or what was your order number unless and until they ask it. And I'm not saying none of the companies have implemented it, but for most of the companies, it is a long way. And when you actually start looking at those behaviors and then build the models on top of it, that's where you are able to extract those insights and start and gather. Then that's when magic happens. You have the ability to actually predict what the customer is going to buy or what can you cross-sell, where can you upsell, et cetera. So that is the second challenge is actually taking all your data and basically evangelizing AI through the organization. First I'm building a charter where you actually define those objectives for the organization. This is different factors like the tech readiness or the amount of data the organization have. And then evangelizing it across the organization and then integrating all the sources of data into one central DMP. And that's where you start extracting it. Third, big challenge for a company like, let's say, Bajaj Auto or any company where most of the touch points are offline is how do you push those insights? Because a lot of purchase is not going to be online. It is the person who is sitting in the showroom and actually selling the bike or actually selling the car who is going to be interacting with the user. So how do I first, how do you align him to start using these insights? And second, how do you then build an infrastructure which will push those insights to him when he's actually interacting with the customer? So once you integrate all this into one seamless thread is when you'll be able to extract insights and use them for actually pushing up conversion, sale or profitability. As I see, this is work in progress, right? We haven't arrived yet, go ahead. In fact, you know, we are kind of not forgetting here but the whole data security in the privacy. We don't have a GDPR for India today, right? But we are kind of, you know, following everything that is happening in the European markets. If there is a GDPR equivalent which comes to Indian market and it says that this kind of data will not be passed on to anything for any sort of analysis and that's a huge challenge. Like, you know, that's the biggest challenge. I think that will be my number one challenge when it comes to using AI for any organizations. Okay, as an aside, while GDPR is not there in India, I think the government of India is playing the role of a more restrictive kind of a regime. Okay, my Jason, you know, people have, you know, other panelists have very succinctly articulated the challenges that the organizations are currently facing. In your experience, share with us how, you know, companies are overcoming these challenges. What is the way to take on these challenges and to move on? Okay, before answering this question, I also want to add for some challenging as I know, according to MoMagic's research we did, we found out for few challenging is very common, exists for the company they want to adopt AI. One very fundamental question is, what is the AI's meaning? AI, this terminology, we are known everywhere, but what does that mean? If you wanna look at from the consumer or audience perspective, it's very simple. We emphasize highly relevant to consumer. Highly relevant is the key, means every message we give to the consumer. Is it highly relevant? Means is it useful to their life? Make them really feel convenient or not? If negativity, no, it's not a true value of AI. Okay, if we from the marketer perspective to look at, what is the AI means? Actually AI is to make machine or say computer, imitate human's intelligence to achieve the mission in a better way. So the key word here is in a better way. What does that mean in a better way? Actually the AI, I try to break down into few concepts. AI is to help us automated by intelligently. What does that mean automated? Means we can leverage machine to minimize the manual arrow and minimize the manual effort. So if we look at the very positive side of the AI, it's beautiful to help human being to minimize our effort on repeated work, right? Our value as a human being, we should create the innovation to make our life better. Then repeated job handle by machine. Okay, so secondly, very key element is actually AI is try to provide the deep insight about consumer. So here deep insight, if we can make it better, it become almost like true insight to the consumer. When we make the true insight means it's highly relevant to the consumer. Again, here it's very meaningful. And the third from the advertiser or from the company wise. AI have to achieve a better result in terms of ROI and can be manageable by number. It can achieve for all of those three factor. Actually it's the real meaning of the AI. However, I think many company is very struggling with what's the meaning of the AI. And secondly, also very struggling with how to adopt AI in daily workflow. Okay, AI only two words. But daily work is so intensive. It's how to integrate. Okay, another question is since not easy. So it's very ambiguous idea about how the budget, how to manage the ROI. So my answer or from more major perspective, we believe actually the solution to manage all those problem is firstly, we need to build up a correct concept about data. Although we know data is important just like all year. But how did we deal with the data? We might not really respect the data value. For example, we might have a lot of valuable data but we might have them sleep and idle in any way in the company. Actually just like garbage in and garbage out. So respect data we have is the first principle. And to be followed by all mindset, very important. No fear for the AI because as I said, AI is something like a tool for us. So now it's AI with marketing. We use AI to maximize AI, to maximize marketing effectiveness. So that's why I think if we can have this good concept, I think very easy to be followed. And then we think if we can have very specific objective, how we wanna implement AI based on our company mission and create our use case. And then we need to identify our metric to evaluate what's the good ROI on the investment. We can proceed a POC to minimize our risk. And surely very important. Based on all those concepts, we should revamp our daily workflow to be really data-driven. Not to make garbage in and garbage out. And surely less input. Jason, I think you have touched on very many points and I think I'm glad you've shifted the discussion to the moral question. Because that is something which I was itching to sort of get into. Which is that if you look at the consumer experience as a funnel, at the beginning of this funnel is data. But from an organization's perspective at the end of this funnel is higher profitability. My question is, and I think I would like, you know, before Vanita comes in and looks at that, bring it to share with us his experience on when you're looking at planning, are you only looking at meeting the client's end objective is to get the bank for the buck which is a marketer's essential wet dream? Or are you looking at creating tangible value creation which will ultimately enhance consumer experience, hence up consumer satisfaction and hence as a part of the overall process leads to maximizing marketing reach and ultimately follow the objective of higher profitability? Yeah, ultimately I think all of us are serving the consumers, right? So that is always going to be the core objective. AI is a tool which enables us to do that in a much better fashion and at scale, right? So the DNA of any organization and wanting to serve the consumer, I think that doesn't change. What AI adds is the capability to do it at scale, yeah? So I got introduced to AI and now I regret I did not take it that seriously earlier. When you remember engineering, we used to write programs in C plus for recognizing shapes and for taking some decisions on certain games that were to be done. Yeah, so since then, which is sorry to reveal my age, somewhere in the 90s, that's when we got introduced to the subject and it's very good that it is now out there interacting with all our lives. Yeah, so for the consumer, very, very simply speaking, it's for the consumer, it is an advanced kind of automation, right? The consumer will not know what is automation and what is AI, yeah? So for the consumer, it is automation and one of the, or rather the three aspects that automation lands with the consumer through AI. One is natural interaction, right? The consumer is able to speak his language. The consumer doesn't need to use different keyboards or different kind of formats to speak to the machines or to the brands. Second is delegation of tasks. What happens is all the, like you said, the routine tasks, they get delegated, right? You don't need an answering machine. There are virtual assistants that are there. But the third most important aspect which affects marketing and the core domain which I work in the media is the ability to deliver personalization, right? And that personalization is whether it is in terms of are we targeting the right people? Are we delivering the right message to the people? Are we co-creating or curating the content which gets delivered to those people? But these are all the things which marketing needs to deliver to these consumers, yeah? So in all these aspects, each company has a different architecture, needs to operate differently. For some companies like banking or e-commerce, data comes naturally to them. They have the data, they have consumer information. But for example, the current client which I work with, Hindustan Unilever, data is very difficult to get because it is, the trade is 90% in moment pop stores across, you know, Kirana stores in India and how do you get data on the consumer? So from the data point of it, it's very important that we look at the overall architecture of our marketing delivery system, right? What we call agile marketing or adaptive marketing framework which we at Mindshare use. It's about looking at how we construct our delivery. How do we capture the data? There's a beautiful example where Disney at their amusement parks just created this product called a magic band which was in the wrist of all the people who came to the center and it captured each and every data about the consumer. Where is he going? How much time he's spending? Which rides they are having to wait for in the queue? What are their preferences? So that was a innovative way of capturing data. So I think what all organizations need to look at is how do we capture data? Is all of them rightly said? We said that data is at the center of it but data is not gonna happen on its own. We have to figure out how we capture data. Second is that once we have the data, are we ready to deploy using that? I may know that this particular section of the audience is somebody who I need to address but then do I have a system where my voice can only go to them? Right now it's getting broadcast to all of you, the same message across everybody. So do we have those delivery systems in place? And ultimately that when enabled that is capturing data, deriving insights and deploying what we very, very broadly used from programmatically which is through automation, targeted, what we call precision marketing at times, we call real-time marketing at times. So all of these need to come together as one to ultimately give us the beautiful consumer experience. And once there is a good consumer experience, there is ROI and that's what delights our clients and therefore us. Thank you for amplifying that. In fact, personalization is really at the core of the consumer benefit. But Vanita, I have seen the way, you know, smart, eliquid Indian companies are using AI is perhaps not the best way to do it because at the core of their attempt is to maximize profit. I have seen it personally as a consumer and I'm sure many in the audience would have seen the way travel, online travel industry sort of hijacks the price or ups the price when you show a particular interest. And recently I've also seen in the e-commerce industry that your repeated interest in a product leads to an upping of price by them which I believe is not only the best use of AI but it's counterproductive because it assumes that consumer is not smart enough to get that. In fact, consumer is smarter than most of these companies put together and consumer sees through that. So my question is to Vanita, you now. And Jason did allude to it about in his, you know, a long sort of illustration. At the core of this whole exercise, ideally in an ideal world, should be the benefit to the consumer in terms of not only the enhancement of consumer experience through the complete value chain, not only providing customer support in a jiffy, not only looking at creating personalized experiences, custom experiences, bespoke content, everything put together. Ultimately, it should be the value creation for the consumer because a happy consumer, ultimately, you know, works for the benefit of the brand. Somehow, I have seen in the early stages of AI in India, the AI is being used for price optimization. What has been your experience? Yes, you're right. I think, and I totally agree with this whole price. Elasticity, this whole, you know, AI technology, you go, you use your ID and you use your computer, you'll get a different price. You get it in a different price. It obviously feels cheated. But yes, we are already using AI for a couple of different things and I'd like to touch upon both of them who just spoke about how, and you asked that question of how efficiency and ROI versus user experience. You know, that's the whole piece I wanted to talk about, was that, yes, so efficiency and ROI is, in plain terms, in media agencies, programmatic is the most easy way to do that and all of us in media planning have started using programmatic. So just to give you an idea, maybe two years ago, programmatic was say 10% of our media plans. Today, it's as high as 60, 70 or plus. Some cases, some clients put 100% of the money on programmatic. We're very, very ROI oriented. Just only a small interruption and I would like you to carry your argument. Programmatic is, I would not really qualify programmatic as AI because in programmatic, the parameters are defined and maybe from an enterprise point of view, you can really say that programmatic is making the use of artificial intelligence but when you tightly control parameters, then it is simulated AI. Actually, if you just use cookies and do that, that probably is, but you also do personal and that is AI, you know? I mean, that is the way we are trying to do it. So for example, a very simple one on Mariko that we had done was on bio oil versus say a hair fall oil, anti hair fall. Now, bio oil was an anti stretch for pregnant women and there was a hypothesis that those women would also be keen to, you know, use an anti hair fall because hair fall is also a problem noticed more amongst them. Things like this, you know, when you dynamically use that, that's what I meant. So these kind of things are being done much, much more than earlier and that also answers your point and you know, consumer also benefits in all of this because you're reaching out to the consumer because that consumer needs you. The other bit that I wanted to touch upon which I think Jason said that, you know, effectively saying that, you know, it's actually benefiting us as human beings and you know, look at it in a positive aspect and also look at it as a driving ROI and it frees up, you know, frees us up for innovation. I'd like to take the flip side of it. That actually it's allowing us to do innovation, you know, so that was a key piece. So this last past year for our client, YCOM for MTV, we did this lovely AI technology backed piece which you all can go back and see if you've not seen that which is called dare2stair.com, you know, so the whole technology was like, you know, they wanted a wild card entry for people and you know, when you log into the site, you could just, it was a challenge thrown right there to you to stare and basis that we took. So that's image recognition, that's AI technology. So that was something I wanted to speak of. Fantastic. I'm glad you got provoked and you challenged my hypothesis which is, and you did present us some compelling examples. My next question is to Jyoti. You know, if you look at AI and we did talk about it in our earlier conversation, some of the pressing problems that a country like India specifically is facing are in the realms of education, health, agriculture. We have seen companies like ITC doing pretty well in terms of using the internet technology but it's currently a one-way traffic and generating tangible benefits for the farmers. In your view, what do you think would be the full potential of using AI to look at value creation for India, which is Bharat? So the potential is actually, I think, as vast as we could think because there are multiple organizations already working in this space, whether it's agriculture, whether it's healthcare, whether it is education. And recently, the Niti Aayog has, I think a lot of us already know that they're working on an AI charter for India as a country. The very simple and I think easy to understand examples would be things like harnessing our monsoon data to find the right time for sewing, impact of various kinds of parameters on crop yield from a pure agriculture perspective. And I think that's critical because with 50% of our population engaged in agriculture and agriculture contributing barely 18 to 20% to our GDP, technology could actually hugely, hugely enhance. And the impact of that on our economy will be probably much more than what all private enterprise put together could conjure up in the next few years. The other big advancement is in the healthcare space and while in India we are still a little slow on it, but across the world, various kinds of advancements have already happened in terms of bringing down the cost of healthcare, you know, things like cancer screening. I think it's democratizing a lot of the healthcare availability. The other thing, I think, which is a little bit into the future but will hopefully come as soon as it is there in other countries to India also is things like variables and injectables, which actually talk about how little nanobots into our body could very precisely target certain cells which carry disease. So I think what Premjit said about precision marketing to the consumer, this is literally precision delivery of medication to patients. And those are things which from a future perspective, you know, there is the whole commercial aspect of how commercial organizations are using technology and harnessing the power of intelligence and machine learning. There is a whole social transformation angle and there are enough and more companies in India today which are working in this space. Large partners like Microsoft, Google, Facebook are all enabling it and I think it's going to be fairly soon that we'll really see those results coming and that will probably be a much, much bigger economic impact than anything else today. Let me get some grounded examples in the Indian context from Avish and Parag both, very quickly. One of the biggest ways in which I would say AI has opened up education to the masses is through voice search. Now if you look at and let's all accept the one of the biggest sources of learning for us is either YouTube or consuming online videos. And now when I go to villages and I see, actually see people who don't know English and just saying that how to repair a mobile phone or how to learn programming in the YouTube app and that reads it and throws the results and they can watch the video, that's an enabler. In terms of healthcare, there is one very recent example which was in an article which I was reading is Apple Watch actually saved a life. So there was someone who fell down and I think he met a heart attack or it fell down due to some reason. And Apple Watch was able to detect that fall and since he was inactive for certain number of seconds, actually alerted the authorities. So this shows what is possible in adult healthcare and democratizing the kind of VIP care which people go to get to the masses. So I see a lot of such applications coming up in future. Let's say I come from the biking industry and what such a smart helmet can do for someone who is riding a bike. If he meets an accident, immediately the local and through local search immediately the local hospitals are alerted. So we are going to see more and more of these innovations coming and solving problems. Great, Parag very quickly because I want to definitely touch about the next generation. So if I have to give you out of banking examples, there are lots, like there's been a huge, yeah, there's been a huge AI disruption from a consumer point of view. We start our day with Google Maps. We filter our Gmail or whatever emails with Spams and all that, it's all AI, right? We have bots which are available on all the service websites like travel, shopping and everything. So all that has been there. So there's already a huge exposure which people are kind of getting sucked into. Maybe they are not realizing it but it's kind of they are into that stuff. But coming to banking very quickly, if I have to say, we are at a very rudimentary level right now where we've started with, say, chatbots. Again, chatbots are of two types. One is rule-based and one is a self-learned. So we've started with rule-based right now. So if I have to give an example of the chatbot which is there on the website, there's a lot of information which is available on the website which is typically given out by the bot if you're asking him questions. For example, what's the savings accounts rate and all that kind of things, right? Other than that, we've seen a huge use of AI when it comes to our marketing campaigns. We have subscribed to Cloud Era which is like a tool for us for campaigning and it creates segmentations and on its own it will send out subject lines which are much more understood by consumers which get more click rates and open rates. We have also kind of used bots for acquisition and we've seen a huge increment when it comes to those numbers. We've seen close to about 30% increase in our acquisition rates when we have used bots for acquisition. On Facebook as a platform or even some of the display banners and that's been some of the case studies that we've been used for. Okay, Premji, you wanted to. Not bother you. Yeah, so when you're talking of health and hygiene and medicine use, so the case which comes to my mind is of LifeBoy which from the social aspect and driving health and hygiene in rural India, what was done was that the disease incidence data for the past few years at a village level was collected. And that data comes streaming in at a regular interval and that data is then used to programmatically or to predict what is the incidence of disease which is likely to be there at any village or district level and when is that time likely to happen. So taking data, collating data, predicting with that and then media messaging is deployed specifically to the concerned target groups in those geographies. And since precaution is better than cure just by driving the incidence of hand washing which is a social objective that LifeBoy drives just by driving that millions of lives are saved in rural India today using in some form this AI as a technology. So that's a very successful case on how it is being done. We've did it in two states and now it's being scaled to another six states more all over India. So that's a power of data and targeting with that. I think he's made a very, very interesting point because most marketers today in my view are looking at talking about four piece let me inject another perspective of three piece plus one more piece just come to my mind. Marketers today I believe are using artificial intelligence for precision and profitability in pricing. Essentially if you look at it, it just occurred to me and I think what our friend Premjit has alluded to is the fourth P which is missing is people. Ultimately everything that we do at the heart of any corporate's objective has to be people. Okay now shifting gears and I would definitely like to take in some questions before this last query is to Jason. What next? While this is still work in progress for a country like India, the rules of the game are being written, organizations are re-skilling themselves, technology is shaping up. What do you think is going to, how the landscape is going to pan out in the next couple of years in terms of the gamut of AI? Actually as I shared previously, now I think it's AI with marketing. We utilize AI to help us on marketing but in the near future I believe it's become AI in marketing. It means AI is going into everything. When going into everything I believe it's something like not just chasing for pure ROI because let's say if we use AI now to maximize our profit. Human being also not stupid. They will find out oh you are playing the trick. So then what's the best ROI? It's the long term we can fulfill certified consumer experience they know is highly relevant as I said. So for the next generation I would say the AI very critical is start to integrate online and offline data as a whole. Because nowadays when we are talking about AI I would say it's almost about online data only. And offline data can we imagine? Even for the shop visitor we can also calculate their conversion. We can compare the online conversion versus offline conversion and in between different timeline we can know this specific consumer. What's their preference? So once we can integrate online offline means we can really see the true lifestyle picture of this user. And at this moment we can see the true inside. So for the marketer we are really sincere to deliver the message because it's very complicated. I show you at this moment if as a human being we want to manage the right message sent to the right consumer at the right timing, at the right place through the right channel for consumer to read at least the five right. As a human being how can we manage so many different factor? So only AI. But AI how can we make it as I said? Once we achieve online offline data integration we can make it. So I think with the IoT more and more mature. Surely it's already very close to us. We are on this journey. Although many uncertainty we are facing. But as I said, always when new technology enter into this world, always we are scrolling with privacy, law, cause, what to do. But normally I would say always we keep exploring and approaching for the destination we will know the picture how we wanna manage. All right, the clock says my time is up but we're going to exceed our brief and give you five minutes or more if you'd like. I would like the audience to jump in and if you have any questions please feel free to ask. Identify yourself and address your question to the specific panelists. Hello everyone, I'm Avinash Janyani. I'm actually the CEO of Play2Transform. We are a design thinking and innovation consulting firm. Just be closer to the mic. Okay, so I mean I have a quick question. How are you guys realigning or restructuring your organization internally in order to stay relevant in this new AI, digital or data-driven age? And this is addressed to the banking industry, Bajaj Auto, all the media planners. All of the above whoever wants to. Thank you. Grab the mic first. No, no, it can be ladies first too. Yeah, so yes, we're all in a state of evolution. The fundamental thing which have come across by all the panelists that they've talked of is getting our head around how do we gather data? How do we get the data about our consumers and put it into certain buckets which are practically usable, right? They can be reams and reams of data lying in say paper and nobody will be able to do with it. So there is specific focus on as the industry is evolving for us as a media agency also to build it into our architecture or whole specialization on data and technology, right? Which was unheard of with agencies maybe five years or a decade ago. But now there are specialists in the agency who understand data, know how to have data. There are legal aspects of data, the GDPR angle which is coming in and how do we look at that? So I think the key to the way we are evolving on that is how to get data and how to manage data and how to then deploy using that data for the benefit of the consumer. That's a key aspect. Add on to what Premjit said. The way we are looking at it, there are three key things, acceptance, competence and capability. And all of these have to be built into the organization for us to move forward on this journey. One of the big things that we at PhD globally and in India do from an acceptance perspective is we have a very large thought leadership program which within the organization democratizes the knowledge and understanding of this. So it is not just restricted to people who are sort of seen as the tech experts within the organization. Of course there'll always be people who understand all of this a little more than the others. But the idea is to have everyone understand and accept it because that then removes a lot of the roadblocks to spreading it far and wide within and also offering these kind of solutions to our clients. And then of course it has to be backed with a huge capability building program. So we identify skills, we identify programs that are needed to be done by our people. And that's I think the root which a lot of other organizations are also taking. From a marketing perspective what we are seeing with a lot of our clients is that they're all cognizant of this need to move in this direction because with the way data is spiraling we all know that we have to accept it and see how we can make the best use of it. So they're evolving roles. So if you look at it from a marketing perspective the chief marketing officer's role itself is evolving. I would say it almost will become like a chief marketing technologist because they function at the cusp of marketing and technology and that's very, very critical for them because a lot of their road jobs are already being taken over by intelligent machines and by processes and systems. So their job really evolves to then how do we best make use of this to provide meaningful consumer experiences which is what a lot of us at the panel have spoken about today. And I think that's really the way things will definitely move as we go forward. All right, are there any more questions? We can see your hand there. Sir, unfortunately we are completely run out of time. Is it okay if they can connect with you offline during lunch, sir? I would like to take one last question as a respect to the gentleman there. Sure, sir. And post that we break for lunch. Hi, so I work at Haptic and I work with advertisers and publishers to deploy AI, NLP for marketing outcomes. My question is, this is a problem that I face personally where the publishers and advertisers don't really understand NLP technologies and a lot of time is spent in educating them, creating awareness and then basically when they don't see ROI, they go back to their conventional marketing channels. So do you also foresee that as a challenge today or do you see that things are changing for the better? I think we talked about risk-killing and at least two of the panelists I remember specifically talked about this challenge but still, would you like to elaborate? So basically, and from what I understand about the question is, I think there are two challenges there. First of all, AI and the getting results through AI takes time because you have to train the model and also you need to ensure that the right data is fed and there will be a lot of tinkering required before it can actually deliver the efficiency at a scale which has been promised. So first is that, aligning them in the beginning itself to say that, yeah, it will take some time and you have to be patient. That's the first part of this. And second is, you need to talk with, I mean, this has to align with the objectives which they are driving. So for example, while evangelizing AI within our own organization and especially for the services team, we got very good results when we could actually display the increase in profitability and reduction in cost which will come if a lot of informational calls can be directed through this channel. So basically what happens is that then you are not wasting manpower, you are not wasting money through a telecollar or deploying them and it's basically taken care of by an automated system. So I think if this kind of alignment of objectives and alignment of expectations happen, I think that should pretty much solve such a problem. One small thing to add. See, it's ultimately about the focus of what the organization wants to deliver. If you look at the case of Netflix, many years ago and in the book on business or success with analytics, what Netflix figured out that the most profitable accounts with them were the ones who joined but did not then really use their service and they opted out after one or two trials, right? So if they just went after a ROI perspective at that point of time, at a short-term perspective, they would have really wanted a lot of people to join but don't use their service, right? So if there is a clarity at the top that it is not short-term ROI but overall consumer experience enhancement that we're looking at, I think what you're saying would also be only a short-term problem. Great, there's more to life than ROI and definitely lunch is one of them but thank you panelists for your enriching insights and thank you audience for being such a patient audience. Thanks everybody. Thank you very much indeed. We're gonna request our panelists to please remain on the stage. I'd like to invite Mr. Kunal Deer, co-founder Mo Magic and Ms. R. K. Lakshman, head of digital business with ABP Live to please come on stage and present a token of gratitude to all of our panelists as well. Well, meanwhile, ladies and gentlemen, for those who are breaking for lunch, please note that our next session is about to begin at 2.30. That is if everyone's in the hall, but 2.30 p.m. Well, let's request our panelists and our presenters to come together for a group photograph. And once again, for those who are breaking for lunch, please note that our next session will commence at 2.30 p.m. Thank you.