The Estée Lauder Companies’ Kalindi Mehta on Applying AI to Beauty and Beyond

MOLLY WOOD: That was Kalindi Mehta, Global Vice President for Consumer Foresight Strategy and Predictive Analytics at the Estée Lauder Companies, or ELC for short. The multinational cosmetics powerhouse is home to more than 20 prestigious and beloved beauty brands—from MAC to Clinique, The Ordinary to La Mer, Aveda to Bobbi Brown. And Mehta herself is frequently cited as one of the world’s top experts in data-driven insights. I talked to her about how ELC has used AI to supercharge its market knowledge with the latest customer insights, and how other leaders, especially those at legacy companies, can use the technology to tap the value of their data. And now, my conversation with Kalindi. Kalindi, thank you so much for coming on WorkLab.  

KALINDI MEHTA: Very excited to be here.  

MOLLY WOOD: Let’s start by having you tell me more about your role at ELC.  

KALINDI MEHTA: I lead the global consumer insights, trends, foresight, predictive analytics capabilities at the Estée Lauder Companies. My role is to help the organization to react to trends today and react immediately with speed, but also to anticipate future needs. Now what I really focus on is building these future-forward capabilities that integrate deep consumer, human, cultural understanding across markets, data science, predictive analytics. But most importantly, on the foundation of a thorough understanding of the business strategy, brands, and some of our regional challenges. You know, ultimately, my goal is to empower our business, our brands, our regions to make consumer-centric decisions and uncover those growth opportunities that can drive business today in the short term, but also in the long term. Most importantly, to do it at scale and with the speed at which the beauty industry operates. 

MOLLY WOOD: Give us a sense of how competitive it is and how you do need every advantage.  

KALINDI MEHTA: The beauty industry has 20,000 brands worldwide. US itself, there are 2,800 brands actively marketing themselves. You know, the current leading social commerce platform, one beauty brand is sold every two seconds. Consumers here are so involved in beauty. Beauty enthusiasts discuss their needs with other people. They ask people about brands and products. They’re constantly searching. They’re on multiple platforms, and they’re also in real stores. And so, it’s complex and they’re in so many different touchpoints where you have to constantly engage with them. 

MOLLY WOOD: Can you give us some examples that sort of highlight how fast you need to move in this industry?  

KALINDI MEHTA: A beauty microtrend can spread in days to weeks and even hours via social media platforms, influencers, user-generated content, hashtags, viral content. And what’s also interesting, with increased global connectivity, it means trends originating in one region can spread to others in months rather than years. In March 2024, an Indonesian makeup artist, influencer, Sita Suwarnadwipa, posted a social media video lip syncing to a song from a Bollywood movie called Asoka while applying traditional Indian bridal makeup. This is in Indonesia. This video garnered 7 million likes, so it was starting in an emerging market like Indonesia, but it gained such rapid global interest. It of course got adopted in India, but also in Brazil and Mexico, which is at the other side of the world, and the US by just April 2024, in a few weeks. There’s just so much cross-cultural pollination happening in such a short time.  

MOLLY WOOD: Where do you see the biggest opportunities for AI in beauty and retail right now? 

KALINDI MEHTA: We are hardwiring AI into our company in so many ways across the business. First, from a meeting the needs of the consumer’s perspective, this virtual try-on technology. It’s kind of spreading across the beauty world. It allows consumers to see how you can apply makeup or skincare products, and how they would look on your actual faces or bodies. Beauty is all about me. I want something for my lifestyle, for my life stage. I want something for my skin type, for my weather, for my time of day. And getting that right is critical. And so AI has tremendous potential in the beauty industry to offer those personalized recommendations, those customized solutions for something that you need for yourself.  

MOLLY WOOD: That feels like such a specific challenge, in terms of breaking down all of that data into individual needs so that people feel met exactly where they are and where their skin is. Like, how could you, how do you do that?  

KALINDI MEHTA: There’s just vast amounts of data you need in terms of understanding the consumer and the consumer needs. And bringing that together in a simple way is something that we’ve been leveraging AI for. This can work in so many different ways, right, just from a personalization perspective. Yes, it’s about consumer experience and consumer engagement. It’s also about product development and making sure we are building products that meet a variety of different needs, and bringing that consumer data together with your product data. There was a couple of ingredients that were really trending, and people wanted it for a specific season, for a certain type of profile, and we took those insights and we matched it against our rich database of products. We have hundreds and thousands of different products and SKUs, and we found a product that matches that very consumer insight or need or trend and created a whole campaign and content around it. And that was extremely successful and helped, for that specific brand, take the sales up by 10 to 15% immediately.  

MOLLY WOOD: So then you have all of that information. You have to really approach customers with empathy and with awareness of these contradictions. And yet, you have to do that at scale. And is there a version of your job where technology actually helps you inject that sense of care and empathy and understanding?  

KALINDI MEHTA: Yes. And at scale and at speed. So, you know, just— 

MOLLY WOOD: No pressure. No pressure, Kalindi. [laughter] 

KALINDI MEHTA: We built this end-to-end trend studio, which allows us 1) to sense trends across multiple markets around the world. Second, you can match products to those trends within our vast portfolio. Like, what’s the right product versus the right trend? Or if you have a product, it can recommend the right trend or consumer need that you can go after for that product. And so once it does this matching of the portfolio with the trend or the insight, it can help then create the content, it can help create a concept, create a brief, it can help create messaging. It can help write copy super quickly, bringing the product information, product insights, together with the consumer insights. You’ve got the insight, you’ve got the trend, you’ve got the product, the product details, and you’ve got messaging copy. And so you can go to market really quickly. This would’ve taken us three to four weeks in the past, but now it’s taking us a few hours, if not like a day, max.  

MOLLY WOOD: It’s my understanding that ELC is also incorporating AI agents, right? Specifically, you’re about to launch an AI agent initiative called Consumer IQ. What can you tell me about that?  

KALINDI MEHTA: So one of the challenges that we have is we have so much insight—consumer insights, market insights, social listening insights, insights through product reviews, through search, and it’s real time and it’s ongoing. In order to make a good decision, we need to use these insights, we need to use this data. But if you have to do it at speed and still make good decisions, it’s really difficult. This is where consumer IQ, this agent, comes in, which helps us leverage this enormous database and quickly synthesize insights across multiple different sources and give you the what and even the so what, give you some strategic insights just at the point where the decision has to be made. You don’t have to wait for weeks for someone to go and synthesize all the learning, figure out where it is. That really improves the speed of decision making, but also, you make better decisions.  

MOLLY WOOD: Now of course, the ELC is a legacy company with nearly 80 years of history and experience, and like a lot of established companies it finds itself in this moment of needing to transform. What advice do you have for business leaders at other such companies? What are the added challenges of transformation and what are the opportunities?  

KALINDI MEHTA: Legacy companies are super rich in terms of insights. Whether it’s market research, it’s social listening, it’s just proprietary insights about consumers, about their products. And so now with AI, there’s tremendous power in leveraging all those insights into treasure, into action, into things that businesses can really use and drive those business results. As these large legacy companies are competing with small, agile, indie companies, this will become a real strength, because you own this proprietary information, insights, facts, data, and you can now use it, you are actually harnessing it. And AI allows you to bring all of that together and to drive that business action and get those business results from all the insights. And so this will help any consumer insights function or team be super successful if they embrace AI as a copilot, as their partner. But as you do it, I think the important thing is, don’t just do it because of FOMO, because everybody’s doing it. Take a measured approach, identify the right use cases that are low-risk to brand trust but deliver high value. You know, you can see it in your business results and you can get good ROI. Make sure you do it in a very responsible, ethical way. And then most importantly, do it around problems that you’re trying to solve. It’s not about cool tools; it’s about, start with what is the problem. Don’t start with the solution.  

MOLLY WOOD: I want to come back to this idea of personalization and empathy at speed and scale. Can you give me an example of how using the data to understand a trend or a need translates into a more personalized approach or product or marketing campaign? 

KALINDI MEHTA: You know, it might seem like a contradiction that AI and empathy are two different things, but in fact, AI actually enables us to drive that deeper understanding around consumers’ needs with more precision and depth. It helps us to serve our consumers better. It’s never AI for the sake of AI. There’s always a human in the loop. But the human now understands the consumer a little bit better, so it builds his or her own empathy. So as the human drives the creativity and the decision making, AI is helping drive that empathy into action.  

MOLLY WOOD: And then, of course, this must extend to influencers. I mean, influencers are a huge part of your world, and that sort of personal sharing—how does understanding the data that you have help you interact with that community?  

KALINDI MEHTA: We use AI to kind of synthesize some of the insights around the trends, around the products. And as we brief the influencers, we share some of these insights with them now in a simpler way, in an easier way, in a quicker way, so that they know more about the consumer that they’re talking to. 

MOLLY WOOD: I mean, every brand is trying to figure out how to engineer virality. So I wonder, does data give you valuable insights? Maybe a better sense of what is going to work and what isn’t?  

KALINDI MEHTA: There’s a lot of noise in the system, right? When you see the data, there are lots of trends that are going up and down. Not every trend may be meaningful for you to action, so I think what you need is deeper understanding of society and culture, and a deeper understanding of beauty so that you can pick trends that are actually meaningful and that are worth acting upon. And AI can help you make that connection between what is meaningful and what’s just noise. Second, is there are still no certainties. And so you don’t know what’s going to be big and what’s not, so it’s this always-on learning approach that you try something, you get some learning early on, and then you scale or not. 

MOLLY WOOD: As you have been incorporating AI and building this into your workflow, what kind of skill sets are required, or are people having to learn, to do this right?   

KALINDI MEHTA: The fundamental technical skill sets are important, but a lot of people get intimidated thinking that you need to be highly technically savvy to leverage AI, which I don’t think you need to be. What’s more important when it comes to AI, and the skill sets you need to build across the wider organization beyond your IT team is the softer skills. The softer skills are really the power skills. It’s, again, going back to that humanity, which is building that ability to solve problems, and creative problem solving is a curiosity to ask the right questions and more questions so that you can get better out of your AI. Building that adaptability skill set as workflows change with technology is going to be more critical than any technical skill set. And so really elevating the soft skills and the humanness of the organization, and getting people to leverage their strengths around that, is going to be critical. But then I think beyond that also. It’s about constant learning, because AI is evolving so constantly and you have to evolve with it. It’s not about taking one fancy single course; it’s about creating this mindset that you’re learning all the time. And I have to say that at ELC, while we’ve set up this training for 15,000 employees globally on Copilot, educating teams on GenAI tools, I think what’s really helped is building this inspiration motivation to self-learn this AI culture that the leadership team is trying to build here, which is not just about training tools. AI has become an integral part of strategy plans that start right from the top. Leadership is walking the talk, is setting the tone. It’s kind of showing the organization that AI is hardwired into everything that we are doing. It’s at the heart of everything we do, and it’s not the future, it’s the present. That spreads then across the entire organization, it kind of sparks this culture of learning and curiosity, which is what you need, because you need to be learning every day, otherwise you will become irrelevant.  

MOLLY WOOD: I mean, it sounds to me like you’re saying that legacy organizations have kind of a potential superpower, even if they don’t realize it. Yes, legacy corporations might form silos, it might take them longer to course correct. But also they’ve amassed all this data and that could really put them ahead of the game if they can figure out what to do with it.  

KALINDI MEHTA: Exactly, exactly. And this can be a strength against all the smaller, newer, digitally born competitors. 

MOLLY WOOD: Decision making is a huge part of your job. Like, you can gather all the data you want, but at the end of the day, you have to have an insight that leads to an action. What is something you wish people understood about the process of making the decision after you’ve looked at all the data?  

KALINDI MEHTA: There’s no such thing as—I really believe there’s no such thing as certainty. You know, even if you look at all the data, you’re not going to get a hundred percent certainty. What, as you make a decision, you should aim at is clarity. Having all the facts, all the data, very simply and clearly laid out, and having those insights so that you have clarity of all the pros and cons and what’s behind it, and what’s right and wrong in making that decision. 

MOLLY WOOD: Do you have any other actionable insights from your work that might help other business leaders?  

KALINDI MEHTA: Don’t view AI as a tool for isolated tasks, that you’re going to do this one task, you’re going to do the second task. We’ve learned that AI really helps us transform entire workflows. From sensing trends to matching products to creating content to measuring impact. And that’s when you really see the efficiency, and you see the business results and the ROI. This helps bring everybody on the same page and work in a seamless, collaborative way.  

MOLLY WOOD: How do you use AI in your work life every day, or even in your personal life?  

KALINDI MEHTA: I cannot imagine working without AI now, in such a short time. It’s become this indispensable tool in my daily routine, both at work and personally. I use it to synthesize multiple reports, analyze consumer transcripts. I’ll give you an example. I’ve done this significantly large project in China where we did like 50 to 75 in-person interviews. We had transcripts with 75 hours of consumer conversations, and in one hour I was able to synthesize all that for a leadership discussion. That made me and my team so powerful in terms of what we could deliver and extract from everything that we’ve done. It also helps me craft complex emails—sometimes they’re difficult to write—develop new product concepts as we work with the R&D and product development teams. Potentially when you are making presentations, it helps you come up with engaging headlines to bring to make things more interesting. So, in so many different ways, it’s just become my partner and helps me do things faster and hopefully better.  

MOLLY WOOD: Fast-forward three to five years for us. What do you think will be the most profound change in the way we work? Or the way you work?  

KALINDI MEHTA: AI will not just be a mere tool, right? It’ll be a true collaborator in our workflows, as I spoke about, where AI will be handling all the heavy lifting—data crunching, complex forecasting, optimization—but allowing humans to focus on what we do best; allowing humans to be human and do strategy and creativity and emotional intelligence, and lead with intuition and connection. This is where our unique human abilities will shine, because the machine is taking care of the grind. We will still drive the vision. So we won’t just be more efficient using AI, but it really frees us to be more human and be more creative and more impactful.  

MOLLY WOOD: Thank you again to Kalindi Mehta, Global Vice President for Consumer Foresight, Strategy, and Predictive Analytics at the Estée Lauder Companies. Thank you so much for the time.  

KALINDI MEHTA: Thank you. I enjoyed this conversation, Molly. 

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