The architect named the reasons for the companies' failures in implementing AI
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- The architect named the reasons for the companies' failures in implementing AI
Automation and implementation of artificial intelligence (AI) in many companies are conducted as a set of disparate initiatives without a single strategy. Expert Alexander Suleikin, founder of DUKE Technologies, associate professor, Ph.D., architect of Big Data systems, on September 17, in an interview with Izvestia, named the reasons for failures in using neural networks in business.
"The failures are mainly caused by the fact that the solution turned out to be expensive and can take decades to pay off, or it doesn't pay off at all: automation turned out to be unnecessary, poorly functioning, or of poor quality. Each such problem deserves a separate dive and study, the reasons here are quite different," said the expert.
Suleikin also said that when implementing AI, it is necessary to determine its role in the company's IT landscape in advance, predict the payback period and adapt internal processes to new technologies.
In addition, according to him, the lack of a comprehensive IT and AI strategy is one of the most common problems. Disparate and uncoordinated initiatives lead to integration difficulties, system migration, and significant future costs.
"Automation and implementation of AI solutions is a complex task that requires consideration at different levels, from strategy to calculating payback and changes in relevant business processes," the architect concluded.
On July 29, Russian President Vladimir Putin noted the development of artificial intelligence in the country. In turn, German Gref, Chairman of the Management Board of Sberbank of Russia, said that a new domestic AI model, GigaChat, had been made publicly available since April 1. According to him, the model is actively used by both citizens and legal entities. The head of Sberbank also stressed that Russia has implemented unique payment technologies that have no analogues in the world.
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