61 NOTICIAS I NEWS the models are cloud-based, which means connecting to send data and subsequently receiving a response. In the industry, there are processes that are traditionally not connected to the outside world, so the incorporation of these technologies must be done considering potential security contingencies. “We cannot ignore these considerations because we could also create significant security problems”, he warns. At the same time, he points out that there is also”a human element, ” since the transformation involves modifying processes and ways of working. Training emerges as another challenge. There is currently a high demand for AIrelated professionals. Therefore, in addition to incorporating new profiles, it is important to train and retrain existing talent. Díaz emphasizes the importance of “training, education, and retraining.” This training, he explains, must be adapted to the different areas of application: “Sometimes very specific training is needed for each area.” Alongside cloud solutions, there are also technologies like machine learning, deep learning, and edge computing, which can be applied to machines and processes disconnected from the cloud. Brossa points out that the difficulty in finding personnel in the industry was already driving automation. Given the rapid adoption of AI, he agrees that it is necessary to train and educate people. For Vila, the speed of technological evolution makes adaptability especially important, “finding those who will learn and those who will be professionals who can adapt quickly.” Traceability and sustainability Traceability is another area where AI can be applied. Brossa defines it as “one of the key topics, “since it allows us to know”where the raw materials come from, their composition, where they have been, and, once my product is released, which commercial channels it follows.” The main challenge lies in sharing information: “It’s one thing to do it internally, another to do it with other companies in the group, and yet another to share it with clients or suppliers.” At this point, security issues arise. In terms of sustainability, Vila highlights AI applications for calculating carbon footprints and comparing different options, automating processes that previously required specific studies. It can also help optimize logistics and palletization, allowing for the simulation of different possibilities and the selection of the most suitable one. These applications can contribute to reducing the number of trucks needed. Díaz adds other possibilities: “There are research groups working on finding natural alternatives to petroleum-derived polymers, as well as other types of more sustainable packaging materials.” He also emphasizes that, through AI combined with imaging, vision, inspection, and quality control techniques, manufacturing or sealing defects can be detected early, reducing waste. Data exchange can also advance through data spaces. Díaz explains that they allow “establishing an architecture for data exchange between different stakeholders in the supply chain, but without losing data sovereignty.” He also points to the digital product passport as an opportunity “to improve traceability and tracking of packaging and packaged materials.” A progressive transformation In conclusion, Díaz believes that AI opens a perspective of collaboration between technology and people. “I think we are heading towards the fifth wave of the industrial revolution, in which artificial intelligence will not replace people, but rather seek collaboration.” To achieve this, investment, training, and finding good partners are necessary. Brossa encourages companies to work “on optimizing their current processes” and also to “try to think a little further ahead, about what opportunities this technology can generate for them.” Vila, for his part, summarizes his position by stating: “This is not optional; this is a wave that affects us, whether we like it or not.” Companies should try to leverage this resource and make the most of it to face change in the best possible way.
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