ORGANIZATIONAL PREREQUISITES FOR TRANSITION TO IFRS IN THE ARTIFICIAL INTELLIGENCE CONTEXT

Аннотация

In this paper, the author’s position is explained on how an entity should prepare its IFRS financial
statements and what challenges entities in Russia face due to the transition to IFRS. It focuses on the theoretical,
methodological, practical issues of IFRS reporting. Its objective is to theoretically substantiate the IFRS regulations
on the preparation of financial statements and the inclusion of analytical financial information in the IFRS reporting
process. This objective is met by solving the following tasks: justify the benefits of IFRS reporting for an entity;
define the reasons why Russian companies should prepare their financial statements in accordance with IFRS. By
summarizing the opinions of various authors, an integrated organizational and methodological approach for the
transition to IFRS has been developed to enhance the company’s efficiency and reduce its costs. The quality of
reporting is the same in both systems of standards (RAS and IFRS). However, there are differences in the purpose of
reporting and the basic principles enshrined in the normative. Thus, IFRS reporting is more focused on investors and
their interests, it objectively reflects information on the financial condition of the company and plays a significant
role in making economic decisions, while RAS reporting is more focused on regulatory authorities and plays a
supporting role in making decisions by owners and investors. This leads to further differences in the reporting
structure, content and format of accounting standards.
In addition to the above, it is necessary to identify any problems that may impede the project, any dysfunctions
and inconsistencies, the reasons for the insufficiently fast transfer of information, and all previous information should
be used to identify priority processes [6,18].
Any revealed contradictions and inconsistencies form the basis for finding the ways for their effective
resolution on a company-wide basis. It is necessary to determine the efficient time frame for the implementation of
the transition plan, which should be spread over the relevant stages of work.
At the next stage, i.e. the organizational design stage, the technology, standards, procedures, systems, and types
of control to be used in the transition process should be defined. The purpose of this stage is to determine the
technical characteristics of the transition process.
In parallel to the social design stage, models for the interaction of social and technical elements are developed,
preliminary plans for development systems and procedures, software and services are drawn up.
Character references for the company’s employees should be compiled in order to assess their qualifications,
the degree of interest in the changes and their role in the new company structure.
Professional knowledge and skills of employees should be assessed and verified for compliance with the basic
requirements set for each position and level. Information on any retraining necessary to meet such requirements can
be used to develop a training program and topic-specific advanced training in special courses.
Most managers are well aware that artificial intelligence (AI) can change almost all aspects of doing business.
Thanks to this technology, by 2030 the world economy can grow by 15.7 trillion US dollars. However, many
company executives do not know how to implement AI, and not just as part of individual pilot projects, but
throughout the organization, where this can give the maximum effect.
The question of “how?” Causes difficulties in introducing any new technology, and artificial intelligence is no
exception. How do you develop an AI strategy? How do you find specialists in this field or train your current
employees? What do you do with data so that it can be used for AI tasks? How do you ensure the reliability and
security of AI?

The matter is complicated by the fact that different companies often answer these questions in different ways,
and the surrounding conditions are constantly changing. But you can’t wait until everything settles down. The
introduction of artificial intelligence, which so far has been jerky, will accelerate in 2019.