This paper discusses the perception of artificial intelligence (AI) in the scientific community and the main factors determining differences in its use. The research underlying this article focused on three key aspects: 1) the level of AI penetration in scientific practice, 2) the self-assessment of scientists' digital competencies, and 3) institutional differences in the organisation of introduction of AI between the scientific and business environments. Comparing academic and corporate experiences allows us to more clearly demonstrate the specific characteristics of the scientific environment and identify the unique drivers and barriers in the field of AI technologies for the science institution.

A complex picture of technological adaptation of Russian scientists to the implementation of innovative technologies is demonstrated. Despite a formally high level of AI penetration, its rather shallow application is observed. Few scientists report advanced levels of AI proficiency, and scientists' self-assessment of their digital competencies is low, indicating a significant gap between formal use and actual adoption of these technologies.

A comparative analysis of AI development practices in academic and business environments revealed fundamental differences in organisational models associated with the prevalence of different value-based and ethical principles. The corporate sector uses a centralised approach with top-down initiatives supported by systemic investments and regulations. In the scientific community, individual initiatives prevail that is explained by the predominance of sociocultural barriers over technological ones. Scientists recognise the benefits of using AI, such as increased data processing efficiency and automation of routine operations, but simultaneously express serious concerns about ethic risks, the loss of author´s originality, and the need to constantly master new skills.

The authors attribute these differences to the specific value-based and ethical principles underlying research and corporate activities. In the business environment, where utilitarian logic prevails, the AI serves as a tool for increasing efficiency. In a scientific environment where deontological ethics and virtue ethics are more pronounced, organisations face socio-cultural barriers connected with the need to avoid violation of ethical principles in academic work, as well as with the same risks from the use of AI.

artificial intelligence, scientific activity, technological development, digital transformation, technology perception, academic environment, business environment

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