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upGrad Enterprise aims to build the world’s largest GenAI learning initiative to enable high-growth companies to embrace technology’s transformative business impact. Hosted by Srikanth Iyengar, CEO, upGrad Enterprise, the GenAIrous Podcast, will curate an exciting roster of global experts and guests, who are at the cutting-edge of Generative AI, and its varied applications in the world of business.
Srikanth Iyengar (CEO upGrad Enterprise) in conversation with Asavari Moon (Founder, Future Female Marketers; Global Marketing & Al Leader)
[00:00:00] Srikanth Iyengar: Welcome to the GenAIrous Podcast, where we unravel the fascinating world of generative AI and its transformative impact on businesses globally. I'm your host, Srikanth Iyengar, CEO of upGrad Enterprise. At upGrad Enterprise, we're building the world's largest gen AI learning initiative, and we're empowering high growth companies to leverage cutting edge technology. Each week, join me and a roster of global experts as we explore innovations shaping the world of work as we know it. Are you ready? Let's get GenAIrous.
[00:00:39] Welcome to The GenAIrous Show. It's an absolute pleasure to have Asavari Moon with us today. Moon, as she prefers to be called, has had a fantastic career spanning multiple continents. I believe Australia, North America, other parts of Americas and now the UK again. Been with some you know, global leaders, Infosys early in her career, L'Oreal, now with Google, but I think the most important part of Moon's role today is that she's founder of Future Female Marketers and she's also at the forefront of AI and the you know the revolution that is causing the market. So moon such a pleasure to have you with us today.
[00:01:16] Asavari Moon: Hello everyone I'm so excited to be here and thank you for that wonderful introduction and thanks for having me Srikanth. It's an absolute pleasure.
Srikanth Iyengar: So look, I know you're a marketer. I know you use a lot of technology and you also are connected with a lot of thought leaders who are at the cusp of technology and marketing.
[00:01:34] There's a lot of talk about the fact that marketing is going to get completely disaggregated by Gen AI. So why don't you give me some initial thoughts on what you're seeing out there in the marketplace?
Asavari Moon: Absolutely. Maybe I'll start with a very controversial answer saying that AI in marketing is not new.
[00:01:52] And I say that because of course I started my marketing journey after being an engineer and doing my MBA in a very traditional marketing set up. You know, think of newspapers and out of home ads and radio and all of that. That was what I call as “broadcast era”, where you had one too many messages. And then came digital marketing, you know, with the likes of social media and emails, et cetera.
[00:02:19] And that's why you could have one-to-one direct sort of messaging. You could have one-to-one sort of reach as well and targeting, which is what I call like “precision era”, because that's why we also had programmatic marketing as well. So you could sort of like design your marketing for that specific person.
[00:02:36] But now I feel like AI is playing something that's going to be at the forefront of the change again. And it's going to be almost like a linear growth, exponential growth. In fact with the advancement that's happening in the gen AI space. And this is what I'm going to call it as “predictive era”, which is not likely going to stop just at AI, but will also have integration of AI, blockchain and web3 and really change the way the marketing is done now. And to my point earlier, I know I said that, you know, AI is not new in marketing because whether we've seen it or not, AI had been, you know, embedded in our daily lives and often in ways that we don't necessarily recognize. And one simple example, would be like an Amazon.
[00:03:21] You know, when you buy something, you get recommendations that you may like this, or you may, you know, people like you have also bought these. Similarly, like Spotify also uses AI to curate a playlist. You know, based on what your listening habits have been and, you know, suggest songs that you're most likely to enjoy.
[00:03:40] The way I see AI will sort of like transform this whole space and I say that because the way marketing was six months ago it's not what it is right now and I don't say I'll be wrong if I say this, but in six months, it's most likely to change again because AI is going to help us, you know, provide those insights for understanding your consumers deeply or enabling those really highly personalized marketing for them, which will allow marketers to be more focused on strategic decision making.
[00:04:13] And I read this stat somewhere which literally blows my mind that the market for artificial intelligence right now is estimated to be 20 billion. But just in five years, in 2028, it's going to be 107. 5 billion dollars. Wow. You can see the scale.
Srikanth Iyengar: Wow. So lots and lots of action. So, but I love the insights, right? The broadcast era, which is pray and pray. The precision era, which is n equal to one. And now you've got the predictive era where you're probably doing personalization at scale. So let's dive a bit more into detail, right? In a typical marketing value chain, you know, you've got content generation, you've got understanding consumer behavior and on the back of that predictive analytics.
[00:04:57] You talked a bit about how Amazon personalizes you talked about Spotify curating playlists, et cetera. But just if we can get into a little more detail on how one could use, let's say, a chatbot for consumer behavior as an example, any, any thoughts, any examples you've seen out there?
[00:05:14] Asavari Moon: I'll also try to get us back to the basics and differentiate between different types of AI, because I feel like that is so important for any marketer who's trying to understand how AI plays into any workflow.
[00:05:29] Exactly as you mentioned as chatbots. I see AIs into three different categories. You know, giving example of say, machine learning. This is something where you're trying to model with one single input and sort of model them for a singular output. An example probably would be what a post office does with handwriting detection.
[00:05:50] Then we have deep learning, which in a typical FMCG organization. I'm going to use a lot of FMCG because that's been my background. As you mentioned, I've worked with the likes of Nivea, L'Oreal, Estée Lauder. So it's an industry that's been my favorite. But yeah, something that we use in that industry would be demand forecasting.
[00:06:10] Now with the advancement of LLM, we have something called a generative AI, which in a way generates. So it generates content, it generates output, such as images, music, or text. And it has ability to learn from existing data, which is really exciting. And this is the landscape that has literally exploded in the last few months or a year, I'll say.
[00:06:37] And then, you know, you have farm two and Gemini and Lama and so much around it. And I feel like with all of that, AI will touch lots of different aspects of marketing and, and, and, and, and, and, and, will not just stay at personalized experiences, but will also help in content generation and educating your consumer and creating demo tools or creating conversion rates and helping you, you know, like hone your analysis and insights.
[00:07:07] But chatbot is another area that I see will rise really high. So according to Statistica, the chatbot is forecast to grow at significant space. So expected to pay 1. 2 billion just by 2025, which is next year. And yeah, I've already seen some really amazing examples of you know, brands utilizing it into their workflows.
[00:07:32] For example TGIF has also included Chatbot into their work system where, you know, it's making it easier for our people to book restaurants and book tables, but also in a very inclusive way, but also very immersive way, I'll say, because, you know, it's like a chat, you're chatting to somebody, but it is an automated voice and you can see how people react to it and how they're doing that is that they are making the, the system or the AI to learn from its previous conversations or data that they had from their customer experience.
[00:08:05] So chatbots definitely with the rise of the whole LLM and voice search will be a big thing for marketers to have an eye on.
Srikanth Iyengar: No, a hundred percent. And you know, I recently saw Reid Hoffman's post, which I'm sure you've seen as well, how, when he creates almost a virtual identity of Reid Hoffman using generative AI, it feels almost like the real person.
[00:08:27] So I can only imagine how that consumer experience gets better and better and almost real, like without all the irritations that covered talking to a real human. So I can, I can, I can see the benefits there, but let me, let me switch tracks a bit, right. Marketing, I dare say has always been a bit of an art. creative, you know, it's about thinking about the art of the possible.
[00:08:50] And now you're talking about content generation, which can be done at scale using generative AI. So what does that mean for digital marketers who pride their skill to be creative and think outside the box? Is this something that sort of marginalizes them or is it something that just makes them even better at what they do? What do you think?
[00:09:07] Asavari Moon: You've raised a very interesting point and I'd love to say that again to our listeners as well, that, you know, a lot of time people see marketing just as a creative field. But it is a combination of art and science. And yeah, I do believe that, you know, AI will impact the whole content generation space as well.
[00:09:28] But I like to see it as something that's enabling you rather than disabling you, taking away from you or risking your output or your capabilities. It's an enabler. So I really want people to not have the fear of AI as something that's doom, you know, you're gonna take away your job. See it as something that, that's, it's here to stay.
[00:09:51] It's already here, but how do you implement in your life to ensure that, you know, it increases your output? But the reason I say that it's an enabler, but not gonna replace your role is because it's gonna be so generic. So all these AI tools, you know, create their output based on lots of generic data that they have.
[00:10:10] So. You know, if everyone's using that, then everything's going to be so generic that people will tune off. So this is where as a digital marketer or a content creator, your role comes into play where you use what the output that you get from these AI tools. And then you add your flavor, you add your brand guidelines to it, you add your niche to it and use that as a base and then explore on it or expand on it.
[00:10:35] This is how I see that playing. As a marketer, particularly in digital marketing, what it gives you an edge is that now it brings your content fast to the market, like initially what probably would have taken three months to create with photography studios and graphic designers and, you know, just like this whole process of brainstorming is now available to you in three minutes.
[00:11:00] So obviously that really helps. And with that speed to market, it also gives you opportunity to test and learn. So now instead of creating just five assets that you think will speak to all your market, all your consumers, now you have an opportunity to create 100 different creatives for 100 different personas.
[00:11:17] So that's another way to look at it in terms of how it's enabling your role. No, fantastic. So, you know, the days of giving an agency a brief and disappearing to the beach for a week or two while they do the, like the heavy lifting is gone away.
[00:11:31] Srikanth Iyengar: So no, completely. So look, if I'm a, let's say I'm a young digital marketer at the start of my career, clearly, this is something that's going to be an integral part of my career for the next few decades. So how would you say I should learn the tools that are out there? How do you think I could bring this into my daily life?
[00:11:50] Asavari Moon: That's a really nice question. And I'll probably share my experience, how I went about it. I think it's just having two main skills. One would be curiosity. It's just being open to learn what's out there and then adaptability.
[00:12:04] So if you find something, how do you include that in your work? And the best way to do that would be when you are beginning any task, just any task, think about are there any tasks in your current role that could be enhanced or automated using AI? The way I see it is that when I'm starting any task, say I'm writing a blog, I start to think to myself, can I do this manually?
[00:12:27] Or can I automate it to AI or could it be a combination of them? So that would be a really nice way to sort of get that starting point and then keep refining on it. It could be as simple as when you're writing an email, see if you can use Grammarly or, you know, even like a chat GPT to you know, help you with some recommendations or check your grammar, or if you are in a meeting, you know, as marketers, you are in a lot of meetings ask AI to transcribe, you know, the ca;; for you or summarize the meeting for you.
[00:13:00] If you're writing an ad copy, why don't you test it with a ChatGPT or, you know, any available tools like Anyword, et cetera. Or if you are in the process of creating you know, your content brief why don't you create like a mood board with that? The other one way would be to subscribe to newsletters and subscribe to, you know, industry conferences where you have all these industry leaders and thought leaders sharing the trends in it and sharing the tools in there.
[00:13:27] So that would be really a nice way to keep yourself informed, but also help that or enhance that with your curiosity. So there's a tool that's mentioned. Add 15 minutes in your calendar slot every week to try and test that tool or see what other, you know, adjustment tools are around it or how that's benefited your work or hasn't, and make a note of that.
[00:13:48] And that's how you develop that learning and adaptable mindset. Some of the tools that I absolutely love and would be a good start would be our favorite, Chat GPT. You know, ask certain questions and learn from there. You know, there's a lot of information around prompt engineering as well. So the way you ask your question or the way you refine your query.
[00:14:08] So play around. I think that would be really nice way. If you are a marketer in digital sector and if you're looking at customer segmentation use Jasper. ai to see what that output comes to look like. You know, just for fun of it, you know, for your passion projects or side project, use Adobe Firefly.
[00:14:26] They have some amazing tools for content generation. The other way would be to utilize already integrated tools. Like, you know, if you are advertising on Meta platforms, they have something called a Sandbox already in it. Similarly, you'll have Google Studio. And if you're really curious, one of my other favorite platform is called Ad Creative Studio.ai and the way they position themselves is almost like Chat GPT marries Canva, which I absolutely love the proposition and again, a really great way for marketers to, yeah, test and learn and incorporate into their daily lives and their already existing work streams.
Srikanth Iyengar: No, amazing. I think Moon really good overview of the landscape.
[00:15:09] You know, obviously you've got Chat GPT, you've got tools from Meta from Google, from you know, Adobe. So clearly an exciting space. And I think from what you say, what I take away is each of these addresses a different need and coming to that and talking about the 15 minutes, I know you mentioned that you spend 15 minutes a week just playing around with these tools you know, just to get yourself acquainted with them. So how do you do that?
[00:15:32] Asavari Moon: I think I've also been very fortunate of course, my background's been in engineering and I also worked at, you know, big tech companies. So, I have been at the forefront of this whole technological innovation and I had seen the impact of AI in my previous life as well where, you know, we were using AI for demand forecasting.
[00:15:54] I remember there was this time when pandemic happened and all retail stores closed and I was in the business of selling lipsticks and, you know, cosmetics, which people need to try on. So I remember I had used a lot of virtual try on into my workflows there and also use a lot of chatbots into my workflows then when we didn't have beauty advisors.
[00:16:14] So fortunately, I had been at the forefront. And I had also learned how the whole marketing landscape changed with digital marketing, as I said, from traditional marketing you know, when digital marketing was sort of like booming back in the days of 2014 and 2016. I was working at Uber Eats in the digital marketing forefront, and I realized how fortunate I was to be at the forefront of that.
[00:16:38] So when I started, saw this whole AI thing coming, and I knew how impactful it's going to be for marketing. I decided that I wanted to learn, and I wanted to understand what's happening around it. And that curiosity led me to know more about the tools, know more about the trends. But it was that ad block in my calendar that really helps my stay up to date.
[00:17:00] Srikanth Iyengar: Well, thank you. I actually took your advice. So I've started playing around a lot more myself. So thank you for that. So look, clearly for a digital marketer, one has to get hands on an experiment. There's no other way. But the other question we often get from people I talk to is, if I'm a digital marketer today, how do I prioritize a digital marketing approach or roadmap? What should be short term? What should be long term as Gen AI comes into the fold? Any recommendations, any advice from you?
[00:17:29] Asavari Moon: That is such a great question. And for that, I sort of have created this three golden rules of Gen AI, not just in digital marketing, but marketing in general. And the first one and the most important one would be to start and end with the customer.
[00:17:48] So sort of looking at You know, is that going to be something that's going to enhance my customer experience or my employee efficiency and go from that way? So sort of looking at as a enabler rather than something that's gonna be quick and short in your economic goals. The second one would be to sort of have exactly as you said, short term and long term goals.
[00:18:08] So focus on quick wins, but also complex projects, and they must run in parallel. Like some teams are now that are already deploying generative AI in their, you know, manageable pilots, such as like, you know, as I said, Sephora is using it in their tech bots and employee facing context, etc. Or, you know, situations where employees can review AI generated content. So look at the short term gains where you look at ways to implement a tool in your existing workflows, but then also have this long term vision of building your work streams around these AI tools. And then another would be also to have a sense of ethical way of looking at AI as well.
[00:18:52] You know, even now, when you have all these tools. tools and you get the short term, really cool projects that you could work on. Still try to be that brand guardian and be very responsible and carefully review the output that's coming through you. And then in the long term, as I said, you create AI models that learns to be your business. And then, you know, creates and rolls out output that's more relevant for you. So just kind of balancing that short term to immediate pain points that AI can address, such as automating and improving customer service. But then at the long term, develop this vision of integrating AI in to enhance your customer experience, but also to drive innovation, like, you know, even for the, the white space marketing innovation, AI could be really great because, you know, as marketers we, we tend to think in terms of what our existing products are and where we can develop it.
[00:19:45] It's a sort of an incremental way, but with LLM. Because they give very generic answers you might come up with some really great product ideas that you wouldn't have thought of because it's so generic. And yeah, it just gives you an outsider's perspective on it. So having that balance is really critical.
[00:20:04] Srikanth Iyengar: That's super. Very, very important rules. Start and end with the customer. I think have a two track process. Low, you know, low hanging fruit, but at the same time, strategic complex initiatives. And thirdly, the responsible and ethical nature of AI is critical. So just touching on that third topic. I mean, that's obviously a very important point in marketing. You know, there are legal aspects around who you market to and how you do it. But there are also ethical aspects to ensure that one doesn't, let's say, upset any particular ethnicities or genders or certain, you know, parts of the world. You know, and so with AI, obviously the model learns from past data and therefore biases that exist in past data get amplified. And that's a big challenge for marketers. So how do you see that panning out? Because On one side, we have the super powerful tool, but on the other side, you know, we have the ability to, let's say, offend at scale, if I use that phrase. So how do you see that balancing out?
[00:21:07] Asavari Moon: I think it's a learning, gradual process. I feel like with every single technology, you know, we first learn the scale of it, and then we learned how to monitor it or how to balance it. And one example, I use this metaphor a lot, which is fire you know, when, when, humankind invented fire. They first learned that the scope of it, like what they could do, they could use it for steam engines, they could use it to keep themselves warm, they could use it to, you know, create yeah, fire and all of that.
[00:21:35] And then slowly they also realized the destructive power of it, or they also realized the harm it could bring. And then slowly they started building fire extinguishers. They started building, you know, fire alarms and they started building fire safety protocols and all of that. I like to say AI is in a very similar phase.
[00:21:54] Like, of course, AI has been around, but it's now expanding rapidly. Let's understand how it can really help us and in what scope and what would be the dangers of it. And then how do we build around protecting those dangers and misuse of AI. And I foresee that in a couple of years we will have you know, our policy makers, our government, and our, you know, tech innovators and marketers sort of working together to create this ethical guidelines that you could use similar to what we have with ASCII now or we have with advertising associations, etc.
[00:22:31] However, we are not there yet, because just with the nature of the whole, you know, your government and your business and, you know, your policymakers and all the demands of the world It is taking time and they're also learning as they grow. So I think this is where as a marketer, the whole essence of this ethical and unbiased AI lies with you.
[00:22:54] You know, there are certain ways that you could take that conscious approach and review the output of AI and the use of AI, you know, starting from us being as mindful of as not using any customer's personal data when you're putting in anything into AI. As you would be careful of GDPR in your normal life, just be careful when you're asking that questions to, you know, any Chat GPTs or AI tools.
[00:23:18] But at the same time, be very, very transparent. Like if you're using AI, no matter where, tell your customers that you are. Clearly communicate that how AI has been used in that marketing effort. If it's AI generated, a content that's been generated by AI, label it. You know, Meta allows you to label it on their Facebook platform and even Instagram platform.
[00:23:38] TikTok makes it mandatory to label it. So just being that transparency really helps. Again, as I said, be very mindful of privacy, ensure that, you know, your data is protected and your privacies are all AI driven activities. And then exactly as you said, you know, that bias mitigation is so important. And it exists, you know, it exists in real life.
[00:24:01] And because all these generative AI and LLMs are taking data from, you know, what's in the society, it gets reflected in their output as well. And one great example would be when you ask them, can you create an image of a CEO? And you would get definitely a white man with blue eyes and tall six foot eight in a blue suit.
[00:24:22] And we know that's not ideal. We know that's not very inclusive. And we are seeing women working from home who are also CEOs with two babies. So, how do you review that to ensure that it's more realistic and it's more you know up to what we see in the market now? And how do you remove that human bias?
[00:24:40] Tools not going to do that job. It's as a marketer that you need to do it. And then just taking the accountability as well. So if you, if you even have a slightest question about it, speak to your legal team, like speak to your brand and rep team to say whether this is something that could be used or not.
[00:24:57] Again, be very mindful of commercial usage of certain things as well. You know, there are certain AI tools that gives you music rights or certain AI tools that helps you, exactly as you said, like create a virtual avatars or virtual identities or you know, of different personalities to say if you have you know sort of like a go ahead from those particular people that you're trying to utilize.
[00:25:21] And again, if AI is generating a content which looks very similar to an existing personality, defer from using it. Yeah. So just being mindful, using your common sense for now until you have this ethical set of guidelines to use would be my approach.
[00:25:44] Srikanth Iyengar: Completely. And I think look, the regulation always catches up with technology. We've seen that in the past as well. It starts, but then it takes time. I think while one has to follow the letter of the law, a lot of this comes down to self policing to a certain extent as well. Thank you for those insights, Moon. Just one other question on the market, and then I have something else to cover with you. Obviously, digital marketing is a huge area of spend for marketing companies and you've been with CPG companies for quite a while.
[00:26:09] So what does this mean for traditional large spenders on marketing? Does this shrink their budgets? Does this expand it, reallocate it to a different place? What does it mean for the industry as a whole?
Asavari Moon: That's a very good question. And I hate to say this, but the answer depends. It depends on where, you know, what your business vision is, what your business goals are for the next few years.
[00:26:35] And again, what is it for your short term and long term? I feel like, Unlike many other industries, say, like banking or technology or healthcare, there has been a lot of data that's been available since, you know, many, many years and decades. FMCG and large vendors in that case haven't been up to that scale to have data with them. And this is where I'll encourage all of the, these you know, these businesses would be to be a little bit more data driven approach towards it, to optimize their marketing budgets and strategies. And it may, As you exactly said involve reallocating funds towards AI tools and, you know, also like upskilling and training and expertise to maintain that competitive edge you know, you could look at in the long term, building your own custom GPTs, as I mentioned, or creating this whole AI models that's based for FMCG but how I see this, that's not as shrinking your budgets, but sort of leveraging AI tools to best optimize your budget.
[00:27:39] But yeah, sort of look at it as not a money saving thing, but more of a way to drive efficiencies at scale.
[00:27:48] Srikanth Iyengar: I think going back Moon, there are many examples of how technology when it's come in has you know, really acted as an accelerator to humankind. And I know you use a very good example about farmers. Why don't you tell us more about that?
[00:28:01] Asavari Moon: Yes, absolutely. I've still stolen this with pride from Gary Vaynerchuk. And he mentions this as you know, when tractors came into life there was this whole talks about how it's gonna, you know, take away from the farmers. They're going to be jobless. There's no room for them.
[00:28:17] And we've seen how tractors has actually helped farmers be better at their jobs. It's the same thing with marketing as well, particularly with this whole advancement of AI. AI is going to enable you to do your job better. And the whole fear that you will lose your job or AI will take your job is not right.
[00:28:37] So AI will not take your job, but a marketer who knows how to use AI tools efficiently might. So I think it's that way of looking at it with not a fearful approach, but sort of a way that it's going to enable me and how I upskill for it.
[00:28:53] Srikanth Iyengar: Super. So Moon, with that, I want to shift to another topic that I know is very close to your heart. You're a very passionate marketer. You're also a big, big proponent of DEI in the workplace. And that's why you founded this organization called Future Female Marketers. So tell me a bit about that.
[00:29:11] Asavari Moon: Sure. I'll first tell you about Future Female Marketers. It's a global platform where women who are in marketing industry or keen to understand the new era of marketing can enter and learn about technologies such as AI, AR, VR, Web3, Metaverse, gaming, you name it. And the reason I created this was exactly as I mentioned before, when I moved to digital marketing, I was very fortunate to play at the forefront of it. And I did see how later, you know, the skill set was exploded and there was so much demand for this skill set.
[00:29:48] However, the first movers advantage still was with men who were the first ones to upskill and women were sort of left behind in an industry which predominantly is female oriented. Same thing is happening with AI. I feel like this skill is going to be so important in the future. However you know, women are still ones who have been left behind because they don't know where the resources are.
[00:30:10] They don't know where to find that mentorship to upskill themselves. And that's the gap I'm trying to bridge with future female marketers. But even as women, you know I feel like that bias still exists. And even when you look at AI entrepreneurs right now and the funding that goes to AI companies, the women led businesses just gets 2 percent or 3 percent of it.
[00:30:31] And it's just mind boggling to know that if we are not in the rooms where the decisions are made, if we are not making the tools that are going to be unbiased and representing us, then we're not going to make a world that's truly representative of what we are living in. And that's the reason I'm really trying to push a voice for women in the whole AI development and push a voice for get seat at the table for women to add to those discussions, add to those changes so that yeah, we are building a more inclusive AI that represents all of us in the best way possible.
[00:31:06] Srikanth Iyengar: No Moon, thank you for that very, very inspiring initiative. More power to you because we do need more of that in this world. So thank you.
Asavari Moon: Thank you for having me and thank you for organizing this. This is such a relevant topic for all the marketers. I'm sure a lot of them will benefit from this.
[00:31:29] Srikanth Iyengar: And that concludes another episode of the GenAIrous Podcast.
We're very grateful to our guests for their time and their expertise. A big thank you to our producer Shantha Shankar in Delhi and our audio engineer, Nithin Shams in Berlin, for making the magic happen behind the scenes. Join us next time and don't forget to subscribe to GenAIrous wherever you listen to your podcasts.
[00:31:52] See you next time.