The business assistant service as one of the promising areas for the adoption of AI technologies in the enterprise
In modern conditions, entrepreneurs are faced with the acute problem of analysing of numerous information, quickly responding to a constantly changing economic situation, and making the most optimal decisions. In this regard, the development of a Business Assistant service (BAS) is a very relevant since it is a modern solution that can significantly simplify and improve the work of enterprises. The main goal of the research is on the basis of AI technologies to elaborate the Business Assistant service, that would speed up, optimize and simplify the decision-making process for the entrepreneur and can be used by many enterprises both when starting a business and when operating it. The main tasks for implementing the goal are: to analyze the scientific literature regarding the possibilities of using AI technologies in business, to identify the factors that mainly influence the entrepreneur’s choice regarding the sphere of activity, as well as the types of information most useful for doing business, to analyze and collect data for the model design, to develop a prototype of the BAS and test its functionality in practice. The research methods are: the theoretical – analysis and synthesis, abstraction method, the empirical – modelling (clustering, classification, logistic regression) and experimental method.The investigation results are: a prototype of the BAS was created, its effectiveness – ability of delivering useful recommendations and improving the business decision-making process for the entrepreneur has been proven experimentally using actual market data. The service can be effectively used by small and medium-sized enterprises in various industries and regions, provided that there is an access to the necessary data. The main risks associated with its implementation and possible ways of their reduction were considered.
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Bawack, R. E., Wamba, S. F., & Carillo, K. D. A. (2019). Artificial intelligence in practice: implications for information systems research. 26th Americas Conference on Information Systems. Cancun. https://www.researchgate.net/publication/333853703
Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108–116. https://hbr.org/2018/01/artificial-intelligence-for-the-real-world
Etrade. (2020). Stocks. https://us.etrade.com/what-we-offer/investment-choices/stocks
Fortune 500. (2019). Top US companies by total revenues for their respective fiscal years. https://fortune.com/fortune500/2019
Finlay, S. (2018). Using a predictive model to make decisions. In S. Finlay, Artificial intelligence and machine learning for business (3rd ed.) (pp. 42–46). Relavistic.
Hanlon, K. (2015). 6 Factors to consider when choosing a business entity. http://www.lucerelegal.com/6-factors-when-choosing-a-business-entity/
Inc. (2019). 5000 the most successful companies in America. https://www.inc.com/inc5000/2019/top-private-companies-2019-inc5000.html
Investing.com. (2020). US wheat futures historical data. https://www.investing.com/commodities/us-wheat-historical-data
Ivankin, A. (2018). Public financial statements: is it possible to get it. https://nv.ua/biz/experts/publichnaya-finansovaya-otchet-nost-mozhno-li-ee-poluchit-2471351.html
Kashyap, P. (2018). Industrial applications of machine learning. In P. Kashyap, Machine learning for decision makers (pp. 189–234). Apress. https://doi.org/10.1007/978-1-4842-2988-0_5
Kenton, W. (2019). Small business administration (SBA). https://www.investopedia.com/terms/s/small-business-administration.asp
Kopanakis, J. (2019, May 9). How artificial intelligence positively influences business decision making. https://www.mention-lytics.com/blog/how-artificial-intelligence-positively-influences-business-decision-making/
Liberto, D. (2019). Small and Mid-size Enterprises (SME). https://www.investopedia.com/terms/s/smallandmidsizeenterprises.asp
Law of Ukraine. (2017). “About Amending the Law of Ukraine “About Accounting and Financial Reporting in Ukraine” regarding the improvement of certain provisions” dated 05.10.2017 No. 2164-VIII.
Michalewicz, Z., Schmidt, M., Michalewicz, M., & Chiriac, C. (2006). Adaptive business intelligence. Springer. https://doi.org/10.1007/978-3-540-49774-5_8
Neortaite, J. & Bulteris, R. (2009). Improving business rules management through the application of adaptive business intelligence technique. Information Technology and Control, 38(1), 21–28.
Our World in data. (2020). Food prices refer to the average price of particular food commodities globally and across countries. https://ourworldindata.org/food-prices
OANDA. (2020). Solutions for business, historical exchange rate. https://www1.oanda.com/fx-for-business/historical-rates
OECD. (2017). Technology and innovation in the insurance sector. OECD Publishing, Paris. https://www.oecd.org/finance/Technology-and-innovation-in-the-insurance-sector.pdf
OECD. (2019). Artificial intelligence in society. OECD Publishing, Paris. http://doi.org/10.1787/eedfee77-en
Paliukas, V., & Savaneviciene, A. (2018). Harmonization of rational and creative decisions in quality management using AI technologies. Economics and Business, 2018, 32, 195–208. https://doi.org/10.2478/eb-2018-0016
Phillips-Wren, G., & Jain, L. (2006). Artificial intelligence for decision making. In Knowledge-based and intelligent information and engineering systems (pp. 531–536). Springer. https://doi.org/10.1007/11893004_69
Ransbotham, S., Kiron, D., & Gerbert, P., & Reeves, M. (2017). Reshaping business with artificial intelligence: closing the gap between ambition and action. MIT Sloan Management Review, 59(1). http://image-src.bcg.com/Images/Reshaping%20Business%20with%20Artificial%20Intelligence_tcm9-177882.pdf
Schatsky, D., Muraskin, C., & Gurumurthy, R. (2014). Demystifying artificial intelligence: what business leaders need to know about cognitive technologies. A Deloitte Series on Cognitive Technologies. Deloitte University Press. https://www2.deloitte.com/content/dam/insights/us/articles/what-is-cognitive-technology/DUP_1030-Cognitive-Technologies_MASTER.pdf
Schatsky, D., Muraskin, C., & Gurumurthy, R. (2015). Cognitive technologies: the real opportunities for business. Deloitte Review, 16, 115–129. https://www2.deloitte.com/us/en/insights/deloitte-review/issue-16/cognitive-technologies-business-applications.html
Shefford, A., & Holland, P. (2018). Trust in artificial intelligence. Transform Your Business with Confidence. https://assets.kpmg/content/dam/kpmg/ph/pdf/services/TrustInArtificialIntelligence.pdf
Soumya, S. (2019). What are the factors that affect the choice for the form of organisation? http://www.preservearticles.com/economics/what-are-the-factors-that-affect-the-choice-for-the-form-of-organisation/21247
The Billion Prices Project. (2019). Daily price indices, monthly, and annual inflation rates for Argentina and the US. http://www.thebillionpricesproject.com/datasets/
The Open Data of 500 US companies. (2020). http://www.opendata500.com/us/list/
US government. (2020). https://www.usa.gov
US Stocks. (2020). https://money.cnn.com/data/us_markets/
Voitenko, T. (2019). Graduation of enterprises according to the Ministry of Finance. Accounting Week. 1. https://i.factor.ua/journals/bn/2019/january/issue-1/article-41682.html
Weller, C. (2017). Swedes can find out each other’s salaries with just one phone call – but there’s a catch. https://www.businessinsider.com/sweden-salaries-freely-available-2017-4