India's AI Growth Explained by Dr. Peter Koerte - Siemens AG’s CTO

Thank you. Thank you for having me.

Yeah, this event is about how we can help the Indian economy to achieve its goals with regards to the growth of 7.5% on GDP and how to build a manufacturing base, increasing the share from 15% to 25%. And as you know, at Siemens we provide all the technology to make sustainable infrastructure, to build state-of-the-art digital native factories. So very, very excited about discussing with customers what it takes to get to that next level.

Yes, we first off we focus on two different things. Number one is on larger companies where we obviously work very much hand in hand in a direct sales motion. But then also with regards to the MSMEs that you mentioned, India has 60 million small to medium-sized enterprises. We need to find a good way of how to interact with them. That's why we launched two years ago at the Innovation Day in India the Siemens Accelerator, which is a curated portfolio that connects very easily between hardware and software, that brings in an ecosystem of many different partners on the marketplace that everybody can go to and find the elements that they like to see. Now you're right that every business in India has somewhat a different need, they produce different things, they have a different setup, tools, methods, knowledge, all of that sort. However, what we find is there are use cases that are there over and over again. Let me give you three. One is about machines, it's about predictive maintenance and making sure that the machines are having their uptime. Irrespective if you are a producer of contact lenses or food and beverage, it's always the same problem that we try to solve. So we provide the basic tools to them in order to solve uptime. The second one is about energy and energy efficiency, about sustainability and reducing your CO2 footprint. So we see that use case over and over again. And the last one right now is how can we lower the hurdle in terms of technology adoption, which is really low code environments where people very flexibly can put things together because sometimes the skill level is not there. We have a low code platform which we can provide to anyone and they can switch it on and then start coding and develop their applications.

Yes, it is both actually. It is an ecosystem, however that's on the supply side. So the demand side comes really on the marketplace. So you go there, usually you are a manufacturer of a certain industry, let's say again the example of food and beverage. So you may, of course doing your search engine, you say, 'I have an issue with regards to energy efficiency in dairy production processes,' and then you Google it or you search, whatever search engine you use, you end up on the marketplace at Siemens. You find it already tailored to your needs for food and beverage where you find seven to eight major common use cases and challenges where then Siemens and its partners provide an easy-to-use application to make that work.

Yeah sure. First off, what's the difference between consumer AI as you picked it and industrial AI? The number one difference is that if your AI in assisting writing you an email gets the tone wrong, there's a little bit of harm done but you can figure it out and correct it easily. If the AI gets it wrong when you produce dairy or cars or whatever, the harm can be outright detrimental. So the level of precision required in the industrial world is much higher. For us, industrial AI has three components: it needs to be safe, reliable, and trustworthy. And that's what industrial customers usually ask you to do and that's what we provide. In industrial AI, to give you an example, there are a lot of repetitive tasks that you can teach the machine to do on behalf of us humans. There's one particular operation called pick and place. If you in packaging have to take many different elements, assemble them, put them into a box, wrap the box, and ship the box, and do this the whole day, it's very hard on your mental health. A machine can do this much better. So we brought what we call a pick AI, which is pre-trained, and the cobot can take this and already sort and place it. That frees up our creativity as humans to solve other problems.

Yeah, so India has tremendous potential, as you know, a population of 1.4 billion people that has a demographic clearly in your favor because you have so many young energetic people, clearly educated with regards to being able to communicate through the world in plain language, meaning English. That is an outstanding advantage that you have as a society and is very exciting to see. On top of that, you can build almost anything because after all, it's humans that build things. So on your path to 2047, what we already see happening is the first stage is building out all the infrastructure required: railways, transportation, energy sector with renewable energy, buildings that are more energy efficient. Building an intelligent infrastructure from the get-go is a unique opportunity in India. Then as you build that infrastructure, usually it happens in parallel: you attract a lot of industry because ports, airports, logistics are simple to get things around. That's happening as we speak with electronics investment, semiconductors, batteries. Then you build your ecosystem around certain industries, and on top of that, your final products like cars, planes, alongside digital capabilities and software. All of that is happening in India and you have everything in your own hands because you got the population that is eager and willing to learn and contribute. I was very shocked to see that so many of these solutions were actually being built by Indian engineers in your Bangalore office, and the solutions they are making are revolutionizing three very big industries: manufacturing, mobility, and infrastructure.