AI at Scale

Ilda Metani: Time for the year of AI practice

In this episode we bring questions that customers across market segments are asking today. Ilda Metani, Head of Industry AI Consulting at Schneider Electric, shares insightful stories about creating value from AI. Gosia Gorska, host of the show, asks Ilda how businesses can become more agile and digital driven, how to democratize data and AI internally, and tackle issues like sustainability at the same time. In the second part of the show, Ilda unveils what’s the focus area and starting point for businesses that want to use AI at scale. She also gives practical examples from her experience in advising the customers.

Duration:: 17m
Broadcast on:: 05 Aug 2024
Audio Format:: mp3

I think AI today really extends the capabilities of electricity and internet, because it does offer advanced data processing, it does offer intelligent automation and it does offer decision making capacities, and these are really impacting and having implications across tons of sectors. Welcome to the AI and Scale podcast. This is a show that invites AI practitioners and AI experts to share their experiences, challenges and AI success stories. These conversations will provide answers to your questions. How do I implement AI successfully and sustainably? How do I make a real impact with AI? Our podcast features real AI solutions and innovations. All of them ready for you to harness and offer a sneak peek into the future. Hi, I'm Gosh Agorska and I'm the host of the Schneider Electric AI at Scale podcast. Today, I'm pleased to introduce my guest, Il Dhammatani. Il Dham is the head of industry AI consulting at Schneider Electric. She's a customer centric executive with strong international sales leadership experience. She focuses on creating business value from data and AI. Also, she's an active supporter of women in AI and women in tech. So welcome, Il Dham. Thanks for joining the show. Thank you so much, Gosh, for inviting me. I'm delighted to be with you today. I was really surprised to discover from your biography that you can speak six different languages. Is it true? Yeah, it is a little bit. It is true, I would say, and it's hopefully not making me blush right now, but it's a hard work that I really started when I was only eight years old. So since eight years old, I've shared this passion for languages becoming a polyglot and willing to become a doctor, which I'm not today, actually. Yeah, that's impressive. I think it's very helpful when you're speaking with clients from around the world, which I have the impression is your superpower. You've been advising them for most of your career. Could you please tell us a bit more about your background? Yes. And so I started my career, actually, within Schneider Electric after some internship on another company, but Schneider Electric has been the company which has crafted me as an executive, so I'm very much grateful for that. And using the different languages has been a key asset, a great tool, I would say, because we would like to delight our customers, and when you're connecting with them at the level of their mother tongue languages is a great way to create customer intimacy and talking technology in Italian or in Russian or in Spanish, it's also a great asset, so they love it. Yeah. I am very happy to hear that you have this intimacy because I invited you today to discover how companies can create value from AI, and I would be really interested to hear some of the stories. But before we dive into that, I need to ask you, what is artificial intelligence to you and how do you perceive it? I just see it not just as a technological revolution, but really as a paradigm shift in how we solve problems and really make decisions. So I'm fascinated by how algorithms can really mimic, and sometimes they do surpass human intelligence, but for me, literally, it's like having a kind of a colleague, one that is really tireless, exceptionally analytical, and it is constantly evolving. And in other ways, to see it as an extension of the human capabilities, being like an extended arm of ourselves and a way to say it's not really replacing human intelligence, but it's rather enhancing it. It's really making us better, more productive, and definitely more equipped to handle complex challenges. Yeah, that's right. I think the way that I experience AI in terms of different applications, I also see it as a great assistant to daily tasks that is helping me to save some of my precious time. And last year was all about AI already. We've heard about responsible, trustworthy, ethical considerations, a lot of conversation about gen AI, and we could debate on this for hours. And then at the beginning of this year, especially at Davos, everyone started to talk, "Okay, this year will be the year of AI practice." And I wanted to know from your perspective, do you think, is it still a hype or a real trend? Will this year be really a year of AI practice? But a few of us are asking that question, but I definitely don't see it at all as a hype, but I see AI today as a real trend. Otherwise, I wouldn't be sitting today in front of you having this virtual coffee and sharing about this specific topic. And I'd like to make the parallel as and the comparison with the invention of electricity or the invention of internet. Electricity was introduced in the late 19th century. But what it did is that it really revolutionized industries, homes and societies by providing what we know, a powerful energy source that gave us so many inventions and conveniences. But at the same time, internet emerging in the late 20th century, it fundamentally altered the way we access information today and the information is communicated, and it did actually connect the world in different ways that were completely not possible before. So I think AI today is kind of following the footsteps of these fundamental innovations. And when you look at it, it really extends the capabilities of electricity and internet because it does offer advanced data processing. It does offer intelligent automation, and it does offer decision making capacities. And these are really impacting and having implications across tons of sectors. So I think it's really sad to enhance and to optimize these technological ecosystems and bringing us really unprecedented efficiencies and innovations which are yet to come. Yeah, and I think exactly like electricity and internet, everybody was very afraid of them at the beginning. And after as people started to use them, they saw the benefits and they got more comfortable and more open to experiment with them. So I guess the customers that you are meeting, they are no longer afraid. What they are asking about, what kind of AI solutions they are seeking. The customers today will continue to ask the same questions and will continue to want ways that ask as a company can continue to delight them. So today, businesses are really seeking ways to harness AI, to enhance efficiency. They'd like to reduce costs on definitely gain a competitive edge. So how can they become much more agile and digital driven by democratizing data and AI internally, tackling issues like sustainability, how to become much more sustainable. These are typical areas that they are asking today, but in particular, they are interested in how can we do or repetitive task in a more automotive way, how can we gain predictive insights for decision-making in their own areas of industry, personalizing their customer experiences, et cetera, et cetera. Yes, you're done. I'm very curious to know, when you discuss about drivers behind applying AI, like you mentioned cost efficiency also sustainability. What is the awareness among customers of different capabilities, benefits that AI brings? Like, are they really treating sustainability as an objective itself, or is it rather a byproduct of the efficiency that they will gain thanks to AI application? I think customers are pretty smart today. They would fall in both categories, I would say, because first they recognize, actually, you know, the power of AI and how the AI can really support them in bringing the transformative potential internally. They also have their own sustainability KPIs internally, which they really need to meet, because that's really critical for their own interests and for their own results. These two are the categories, I would say, for the typology of the customers. They would then both recognize, first, it's great because I can use machine learning algorithms and AI applications to reduce my costs, and also I can gain in, I can get my return on investment, but then at the same time, I'm also meeting the KPIs, because I'm becoming much more energy efficient and I'm reducing waste. For example, if we take the energy consumption of a building, you know, we've been using and playing or let's say, implementing our technology as always to reduce energy consumption in different types of buildings. But we're saying that we can even go further or beyond that by using AI models to become much more efficient in terms of, you know, the consumption of the buildings. So that's a way also to meet the customer's demands in both hitting the sustainability assets, but also having them optimize and reduce their costs. Yeah, and I heard about one application, there's been a research paper about some methods about how we can apply deep learning for buildings from the get go. So usually you need a lot of data to feed AI, so you can achieve this outcome. But interestingly, there are already some methods to also have this optimization enabled even without this data, so we can kind of overcome this. Exactly. That's a great asset. Actually, it's a member of my team who I would have enjoyed to have him sit with us, you know, during the coffee today, but he has been providing a building a pay ton, I would say, and that's called start. It's precisely exactly what you're mentioning, so it's very difficult to have historical data for some of the buildings, yet we've been able to coordinate and to build models of AI with very small amount of data to be able to show patterns and predict energy consumption of the buildings. These are things that were not possible to do before, which we're typically using today and showcasing. Yeah, that's great. So it sounds like I have already an idea for the next episode, thanks you for that. Coming back to our conversation, and I hope that you still have some coffee left and we keep our listeners energized, yeah, there is some left for sure, that's great. So the first part of the conversation was more about customers and trends, and for the second part, I wanted to focus a bit more on AI solutions. What's the holy grail for our customers? What are they looking for really? So customers today are looking for different AI solutions, and these solutions are varying really between one industry to another, and they vary a lot, of course, because some AI solutions are tailored for specific challenges and opportunities, typically in manufacturing AI is used for the optimization of production lines and predictive maintenance. In supply chain, again, you can go beyond lean six sigma methodology by itself using AI algorithms. In healthcare, these applications do focus on personalized medicine, patient care management or and focus on diagnostics in finance and so on. So really, different sectors are using the AI solutions differently. So if you had to ask me the question of who is really adopting them the most aggressively, I would say, well, the industry is with high volume data, because there is no data, there is no AI, data is really at the core of what we do in terms of AI models. So finance, healthcare and retail are continuously adopting AI. Some other tech service sectors are also using them because they're dearly want to enhance their user experience, and also they would like to streamline their operations. And typically, for giants like our company Schneider Electric, well, the adoption of AI is really critical, and it does make a lot of sense in reason because it does not only boost our internal processes through its implementation, but we're really trying to embed it in our technology. And when saying technology is really embedding it in our hardware, because we want to bring innovative offers to our customers globally. So these are for me core accesses in the applications and the solutions of AI. Yeah, I appreciate this, Ilga, but let me push you a bit more here and ask a question, because I'm really hungry for this customer story. So could you give us one example from your daily life? You are working in a consulting team, advising customers about AI applications. So how do you do that, and what's the value that they can obtain thanks to AI? So there are lots of examples that we can deliver. I like to share about the energy efficiency side 10 years ago. In the energy efficiency domain, we had a much more traditional approach via our customers and the solutions that we were able to provide to them. Today, we're taking the same story to another level, because we're talking energy efficiency through AI driven technology. So the capacities to tell our customers, a typical customer, it would be a pharmaceutical customer that is having several buildings. These buildings have different features in terms of energy consumption and personalized data. We would be able to take the energy consumption to the next level in terms of energy efficiency, because we're going to have the introduction of how to learn from historical data, how we can bring AI driven HVSS systems to analyze historical data by including past usage patterns such as temperature setting energy consumption, understanding these trends, the system can really predict future needs more accurately, which was not possible to do before. And at the same time, we're introducing a way to self-regulate and to detect anomalies. So the intelligence system, HVSS system can not only self-regulate, but in a particular zone, if the zone is not reaching the desired temperature, the system can flag this for maintenance by indicating, in a way, a possible issue with vents or ducts. So these are really typical features which we were not able to come, or let's say to provide to this extent, and AI is bringing them to our customers. So the integration with the other buildings, the self-regulation, occupancy-based adjustments, and the facts that we can learn from historical data are new ways to push our energy efficiency value proposition to the next level. Yeah, and it's quite amazing to also see the variety of values and benefits that we can have from that. Like you mentioned about the cost, about efficiency, also the lower carbon emissions, right? Because the more efficient we are, the less carbon is emitted. And last but not least, also safety, right? We talk about predictive maintenance and detection of different failures. So this is really a variety of different outcomes that can be achieved with one technology. Okay, so for the last question, I wanted to know if the audience had to remember three things from this conversation, what would be your message to them? Definitely, I would say first, the AI is not a hype, but it's a real trend, and I think it's really important that we embrace it. The second is really there is real growing demand in AI applications, and our customers are demonstrating, and that's why they are asking us to support them, and that's also the goal of my team. It's really to support our customers in tailoring new solutions through the usage of AI to enhance their processes and to help them in their energy consumption reductions. And number three is that tech companies like Schneider Electric, they have, they can gain a competitive advantage by becoming more innovative, not just by gaining an agility internally, but also by innovating and bringing innovation capabilities to our customers today. Yeah, that's a great message. Thank you, Ilda. It was really a pleasure to hosting you today. And thank you, Gorsha. It's my pleasure to you. So I hope we speak again next time. Thank you. Thanks for joining us today on AI at scale podcast. Be sure to visit our sc.com/ai website and learn more about our AI-scale solutions. Head over to our Schneider blog platform to read more. Don't forget to subscribe to the show on your preferred platform and share it with your network. Thank you for listening and stay tuned for the next episode. [MUSIC] (upbeat music)