Problem of Assessing the Investment Attractiveness of Risk Projects for Developing Artificial Intelligence
Irina Reshetnikova1, Olga Yanina2, Larisa Semenova3, Lesya Bozhko4, Oleg Veselitsky5

1Irina Reshetnikova, Tyumen Industrial University, Tyumen, Russian Federation.
2Olga Yanina, Russian State Social University, Balashikha, Russian Federation.
3Larisa Semenova, Bashkir State Medical University of the Ministry of Health of the Russian Federation, Ufa, Russian Federation.
4Lesya Bozhko, Emperor Alexander I St. Petersburg State Transport University, Saint Petersburg, Russian Federation.
5Oleg Veselitsky, Moscow City Government University of Management Moscow, Moscow, Russian Federation.
Manuscript received on 18 September 2019 | Revised Manuscript received on 05 October 2019 | Manuscript Published on 11 October 2019 | PP: 238-243 | Volume-8 Issue-2S10 September 2019 | Retrieval Number: B10410982S1019/2019©BEIESP | DOI: 10.35940/ijrte.B1041.0982S1019
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Abstract: The article discusses the problem of assessing the investment attractiveness of risk projects for developing artificial intelligence, the methods of such assessment and their features. It is shown that due to the lack of relevant statistical, financial, operational information, the models and methods of investment valuation are, for the most part, subjective. The use of only one model or method of assessing investment attractiveness in the field of the development of artificial intelligence projects is insufficient, while the complex use without taking into account systemic aspects is likewise not sufficiently substantiated. To solve the existing problem, it is proposed to comprehensively use the available capabilities of the method of functional cost analysis (FSA), the essence of which is that the development project is decomposed into separate functions, and the necessary resources are measured and fixed for each function. Analysis of the functions of the object and the costs of the implementation of the functions makes it possible to identify the most acceptable variant of the object from the position of its functional content. At the same time, the article considers the possibility of using the functional-cost analysis method in the evaluation, the essence of which is that the development project is decomposed into separate functions, and for each function, all necessary resources are measured and fixed. An analysis of the object’s functions and their costs will help to identify the most economical version of a risky investment project from its functional content. It is reasonably noted that the main resources to support and promote the development of innovative projects are venture companies that invest considerable funds both at the initial stages and at the stages of development and expansion of projects. The amount of financial resources coming from business angels, crowdfunding and business accelerators is much smaller and goes mainly to the initial stages of project implementation.
Keywords: Artificial Intelligence Development Project, Investment Attractiveness, Valuation Methods, Functional-Cost Analysis, Venture Financing, Business-Angels, Crowdfunding.
Scope of the Article: Artificial Intelligent Methods, Models, Techniques