Emily Glaze: For how AI will improve the supply chain, you talked about both short – and long-term considerations, how will it improve Flextronics’ efficiency and productivity? And how can data be used to ease some of the obstacles in global supply chains? In the longer term, what is your vision for the future? If you can fix the supply chain and use AI proficiently and properly, what does the future look like?

CI532V01 Revathi Advaithi: I’m going to talk about it in two parts. Part of it is based on the situation on the production floor. The other part is from the perspective of macro planning. For the past 30 years, I have been working in factories all over the world. I’m looking forward to the next 20 years. The reason is that if you consider the productivity of the factory, it hasn’t improved significantly. Just like in the early 2000s, in the late 1990s, when labor arbitrage took off, you saw a lot of emerging economies benefit. And AI can be an equalizer in a way. I’m not talking about large manufacturing plants that are fully automated or large plants that we operate. But if you think about AI in small, mid-sized manufacturing, if implementation costs are low, then hardware machines may play an equalizing role in increasing productivity.

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They might have 25, 30 different discrete software systems, not talking to each other, trying to run production schedules in the factory. In order to make up for the low utilization of equipment, you can only add more equipment, capital will no longer be cheap, so what do you do? So I feel that AI can help by considering a combination of: How is your working capital deployed? Can equipment utilization be improved? Putting all of this together, I think AI can help increase the productivity of factories. So I’m very much looking forward to this because it will give small and medium-sized manufacturing an advantage.

CI532V01 Revathi Advaithi: But let’s go back to the macro level of AI and planning. We just went through a supply chain crisis. It strikes me that in this day and age, despite all the data and information, we still don’t know how much supply or demand the world needs to function. The world shouldn’t be like this anymore, should it? Therefore, I am looking forward to seeing large-scale multi-modal LLM model planning, and even chip planning, take place. This will drive true intelligence to ensure that you don’t get stuck with supply and demand. Also, you won’t get stuck again with too much inventory. This should not be happening in this day and age. But this will require varying degrees of engagement from all industries and sectors of the world. What I’m looking forward to is in the future, can we effectively prevent the next supply chain crisis caused by a global lack of a certain component?