With fewer than two weeks to go to the opening of the 2024 CIBJO Congress in Shanghai, China, on November 2, 2024, the tenth and final of the pre-congress Special Reports has been released. Prepared by the CIBJO Technology Committee, headed by Stéphane Fischler, the report reviews a momentous period in the introduction of new technologies into the jewellery industry, noting that artificial intelligence (AI) may soon be driving the most efficient ways of using data to optimize the various processes in our industry.
“Yes, many challenges remain, and there is a lot of hype for sure,” Fischler writes. “Those are well known caveats that it’s important we appreciate, especially when incorporating or investing in any new technological strategy or use. But we should focus on the positive, because we undoubtedly work in an industry that has been progressively and constructively impacted by the adoption of new technology-driven production and management systems.”
Unlike most of the CIBJO Commissions and other committees and working groups, which largely are concerned with the development of standards, working principles and nomenclature in the areas in which they are concerned, the CIBJO Technology Committee is more of think tank, which considers how the various sectors of the jewellery industry are likely to be impacted and changed by technologies coming down the pipeline. Its other members are Thomas Baillod, David Block, Mahiar Borhanjoo, Elle Hill, Daniel Nyfeler and Emmanuel Piat.
While jewellery industry technology development traditionally focused on the development of automated systems that improved efficiencies in the mining, rough processing and manufacturing sector, a much greater focus today on the downstream section of the distribution chain.
“What had changed dramatically in recent years,” Fischler writes, “is how we study and understand the marketplace, and then how we develop, package and position our products, and pinpoint and communicate with the consumers we seek to supply. Digital data collection, analysis and delivery systems enabled the introduction of a highly effective golden bullet approach, as opposed to the hit, miss and adjust coordinates model that had been used beforehand.”
“The good news is that improvements in software using AI and ‘machine learning’ will hopefully generate greater gains,” the Chair of the Technology Committee continued. “But we to need to introduce such technology carefully, and step by step. The intelligence may be artificial but to optimize its introduction we need to nurture the right human resources. Finding the necessary expertise to manage these technologies is not only essential, but is becoming a serious challenge.”
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