Economic prospects of using artificial intelligence and neural network algorithms in research of generation Z biotechnologists

the article discusses the use of artificial intelligence-based platforms and services in various fields of modern biotechnology using real-world case studies from recent decades. The issues of practical expediency, economic and commercial risks, as well as possible prospects and ways of further development of artificial intelligence (AI) in educational research of biotechnologists for generation Z. The authors present a theoretical overview of the use of artificial intelligence in modern biotechnology and the results of a survey of a specialized audience on the use of AI in biotechnology as an applied aspect of research. The purpose of the study: based on the analysis of scientific papers and a survey conducted, professional perception of the community and possible ethical and social risks and consequences. Research methods: the authors used decomposition, analysis, and synthesis as methods in the study. Surveys, questionnaires, and an analysis of innovation ideas were also conducted using artificial intelligence tools proposed by undergraduates while completing the Economics and Innovation discipline. Results: in the presented review, the authors repeatedly refer to real-world cases of developing and using programs and algorithms to solve a wide range of problems in modern biotechnology, and many others. The analysis of the survey data also demonstrates a predominantly positive trend in the introduction of AI algorithms for generation Z biotechnologists. Conclusions: a theoretical review of scientific papers on the study of the introduction of artificial intelligence in the biotechnology industry, a survey of the relevant audience on the integration of AI in the professional field (biotechnology). The conclusion is made about the prospects, taking into account its role in breakthrough innovations and multidisciplinary educational research.

artificial intelligence, neural network, biotechnology, biotechnology manufacturing, biotechnological innovation, maths algorithm