Stifled Opportunity Gen-AI Can Boost Manufacturing

Source: Peter Königsreuther| Translated by AI 2 min Reading Time

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A study by NTT Data has found that while the introduction of Gen-AI (generative artificial intelligence) offers many advantages, it is often not embraced...

NTT Data has inquired worldwide about the use of generative artificial intelligence (generative AI or Gen-AI) in manufacturing. The experts have compiled the following results...(Image: © panuwat - stock.adobe.com)
NTT Data has inquired worldwide about the use of generative artificial intelligence (generative AI or Gen-AI) in manufacturing. The experts have compiled the following results...
(Image: © panuwat - stock.adobe.com)

NTT Data, a leading provider of digital business and technology services, presents the findings of its latest study. The data reveals that manufacturing companies face challenges in implementing Gen-AI (generative artificial intelligence), yet the technology as a whole has the potential to elevate the industry to a new level of efficiency and innovation. The focus was on hurdles related to personnel, infrastructure, and ethical frameworks. Over 500 executives and decision-makers from the manufacturing sector in 34 countries were surveyed. Respondents indicated that Gen-AI is already being used for process automation, supply chain and warehouse management, and monitoring and maintenance of their infrastructure. However, artificial intelligence not only optimizes processes but also redefines possibilities along the entire value chain in manufacturing, ranging from supply chain predictions to quality control.

This is the Global State of Gen-AI Use in Manufacturing

  • 95 percent of respondents stated that generative AI is already accelerating processes and improving production results;

  • 94 percent indicate that edge and IoT data can make AI results even more accurate and useful when integrated into generative artificial intelligence models;

  • 91 percent expect that digital twins, in combination with Gen-AI, will both improve the performance of physical assets and make supply chains more robust;

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