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  AI For ESG! Discover new green opportunities through data exploration   Xie Zongzhen took the manufacturing field as an example. Through data collection, the future production simulation of the factory can be carried out. Based on these data and simulation, the three elements of ESG can be satisfied. The first is energy saving and carbon reduction for "Environment", that is, through data and AI algorithms, to simulate the most energy-saving and carbon-reducing operation mode under qualified production. The second is "Social". There are many industrial safety risks in the factory environment, including sudden equipment failure and downtime, resulting in personal injury or environmental pollution. At the same time, downtime also means stoppage of work, inability to produce, and even affect employees' right to work. . Therefore, AI can be used to tell the fortune of the factory, make the factory run smoothly, and predict which equipment may fail in the future. This is an advanced deployment of "prevention is better than cure". The last is "Governance". From the perspective of supply chain management, if you can predict how many orders customers will purchase in the future, you can effectively control inventory. If too many parts are produced and stored for too long, they may rust and cannot be delivered. Therefore, through the AI ​​algorithm, it is possible to analyze the international trade situation, determine the required order quantity, and where to produce and export, so as to reduce the additional costs caused by tariffs. Therefore, when relevant personnel in factories and manufacturing can effectively use data-driven AI algorithms to practice these application scenarios, it means that he is empowered by AI, can cooperate with AI more intelligently, and has stronger working ability, and even one person can be used by ten people. . Xie Zongzhen believes that in terms of Taiwan's population structure, declining birthrate, aging population, and insufficient labor force are already foreseeable scenarios in the future. Empowering manpower through AI to do more things is also a very important ESG issue. Six steps to promote AI For ESG   How should companies think about their own ESG strategies? Xie Zongzhen compiled six steps to promote AI For ESG for reference by enterprises. First of all, it is necessary to clarify and define what problems the company currently needs to solve? What kind of problems are suitable to be solved by AI? Then, after determining the topic, you need to have data. How complete is the data collection? "The first two steps are often confused," Xie Zongzhen emphasized. Many companies think that they should first look at what information they have before deciding what problem to solve, but the opposite is true. It is possible to solve the problem only if the infrastructure construction is done well. Once you have the topic and information, you can start to create a typical case of the company and implement a new AI For ESG project. After completing the typical case, it is necessary to think about how to effectively replicate and spread it, so that the enterprise can implement the data-driven DNA, and finally support the sustainable operation of the enterprise with sustainable AI.  

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