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Artificial Intelligence in Business Management

Motivation

The application of assistive instruments and technologies for effective business management is a practice that is increasingly being adopted in many organisations. One of the most innovative and modern approaches is the use of artificial intelligence (AI) aimed to help in solving several control tasks. Bringing digital tools into the management process is not a unique solution, but the use of AI is a little-studied procedure due to the recent introduction of such technologies. According to Haenlein and Kaplan (2019), the first mentions of AI were in the 1940s, but most of them were assumptions about the possible development of computer technology and its potential applications in various industries. In the field of business management, utilising AI is a technique that may contribute to improving the quality of control activities, simplifying the decision-making process, and eliminating errors caused by the human factor. Therefore, the assessment of this technology from the perspectives of its benefits, applications and subsequent improvement is essential.

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Introduction

The increased use of digital advances in business is a natural result of the computerisation of various processes, including those in the management sphere. As Haenlein et al. (2019) argue, combining AI with other relevant practices is a solution that allows maximising the outcomes of control over all operational processes. In other words, this technology serves as an auxiliary tool for decision-making and helps assess the prospects and risks of specific decisions based on programmed algorithms. Business owners and executives are increasingly paying attention to AI as a convenient technology that operates on large-scale data, analyses incoming information and develops adaptive solutions based on it.

Due to the wide programming possibilities of AI algorithms, the use of this digital technology in business management is applied as often as in other areas where large volumes of data need to be processed. The application of modern developments in this field can help determine how broad AI capabilities are with control over various operational processes within companies. Benefit analysis is an approach that allows identifying the positive differences of this technology from other digital tools used in the business environment to simplify management. Finally, considering the prospects for the development and spread of AI in the business environment may help predict weighty reasons for introducing this technology and successful solutions to facilitate the implementation process. The technology under consideration can be an irreplaceable tool as one of the key components of the decision-making process and contribute to strengthening management positions in companies of different profiles.

Applications of Artificial Intelligence in Business Management

As the volumes of information and data that need to be controlled to maintain business resilience grow, artificial intelligence technologies are a convenient solution. Moreover, according to Obschonka and Audretsch (2019), this technology is widely utilised due to the various functions they are capable of performing. As an example, the authors note a large amount of data that AI engines can process by using specially designed analytical algorithms, which, in turn, match or exceed human capabilities (Obschonka and Audretsch, 2019). Kolbjørnsrud, Amico and Thomas (2016) also analyse the applications of AI in business management and classify activities based on their importance. The use of these high-precision algorithms is relevant to administrative coordination and control maintenance. The performance assessment of subordinates, current results analyses and other areas of management activities can be simplified due to the introduction of AI mechanisms.

Another area of work in business management is problem-solving that is closely related to maintaining productive collaboration. As Kolbjørnsrud, Amico and Thomas (2016) state, predictive systems allow determining which solutions are optimal to overcome specific barriers. The area of ​​strategic planning is one of the most frequent applications of AI due to an opportunity to evaluate the perspectives of a particular business and compare these results. These objectives, as Kolbjørnsrud, Amico and Thomas (2016) note, has value for any manager. Finally, establishing interaction with all stakeholders and implementing engagement practices can be realised due to an AI ​​system designed to distribute roles by interpreting specific indicators, for instance, key performance indicators. All of these areas of business management are significant aspects that shape the overall picture of executives’ tasks, and the introduction of unique artificial intelligence programs is an effective and sought-after approach to avoiding errors.

Benefits of Artificial Intelligence in Business Management

AI systems are complex programs with many functions that not only simplify the work of business managers but also have significant advantages over traditional practices of maintaining control. Hirsch (2018) argues that one of the benefits of advancing AI technology is to provide more reliable cybersecurity compared to obsolete firewalls. An algorithm with the ability to not only recognise but also classify and prevent threats is objectively in demand. As Duan, Edwards and Dwivedi (2019) note, in the aforementioned field of decision-making, one of the main strengths of AI is finding beneficial solutions in multi-level structures. Something that causes challenges for an average manager, for instance, the need to assess the impact of an intervention on different organisational departments, can be performed by machine algorithms successfully.

Another valuable advantage of AI over other primitive programs designed to simplify business management is its breadth of application. According to Quan and Sanderson (2018), the use of these high-precision technologies is acceptable not only internally, for instance, within companies, but also externally to analyse different aspects of entrepreneurial activities on a broader scale. The authors cite the example of Google, one of the world’s largest corporations that invests heavily in the development of innovative AI solutions (Quan and Sanderson, 2018). Such a benefit is a crucial advantage and allows determining the technology under consideration as the main tool for business administration and control.

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Finally, as an essential benefit, one can mention an opportunity to test the performance of AI systems and draw objective conclusions regarding their productivity and relevance to a specific business environment. Duan, Edwards and Dwivedi (2019) take this perspective and note that compared to traditional decision-making tools that are auxiliary instruments, AI algorithms are designed to be highly accurate mechanisms with reporting functions. The head of any structural unit of a particular company can test the operation of such a system and obtain a detailed analysis of the work done. In such conditions, the security of business management increases, which, in turn, has a beneficial effect on the financial outcomes of work.

Future Perspectives of Artificial Intelligence in Business Management

While considering the prospects for the development and implementation of AI algorithms in business management, one should take into account the specifics of their service. According to Haenlein and Kaplan (2019), the continuous application of this technology will provide an opportunity to find optimal mechanisms for its regulation. In other words, the introduction of AI will become more rational from the standpoint of the compliance of a specific system with the stated goals. This perspective is critical in the context of the lack of sufficient research data on the possibilities and limitations of this technology.

The expansion of AI is inevitable since more managers are using corresponding tools as a supporting resource base. In this regard, Lichtenthaler (2018, p. 13) notes that strengthening the links between executives and machine algorithms is a logical and obvious perspective when “human and artificial intelligence work together”. The digitalisation of various industries, including business, is inevitable, and the sooner appropriate ways to effectively apply AI are found, the higher is the likelihood of more productive management activities. Thus, when assessing the prospects for the development of this technology, one can assume that its use will become more rational and, at the same time, wider given the aforementioned benefits and convenience.

Conclusion

The use of artificial intelligence in business management is a sound practice due to many benefits that this technology offers and an opportunity to secure operational controls. The scopes of these algorithms are diverse and include decision-making, strategic planning and other fields. Among the undeniable advantages, one can pay attention to the width of AI use, its ease of utilisation in multi-structured tasks, as well as chances to test the current performance. In the future, the application of this technology will become widespread due to the constantly evolving mechanisms for regulating AI systems and the possibility of combining human efforts with machine operations.

Reference List

Duan, Y., Edwards, J. S. and Dwivedi, Y. K. (2019) ‘Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda’, International Journal of Information Management, 48, pp. 63-71.

Haenlein, M. et al. (2019) ‘Artificial intelligence (AI) and management analytics’, Journal of Management Analytics, 6(4), pp. 341-343.

Haenlein, M. and Kaplan, A. (2019) ‘A brief history of artificial intelligence: on the past, present, and future of artificial intelligence’, California Management Review, 61(4), pp. 5-14.

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Hirsch, P. B. (2018) ‘Tie me to the mast: artificial intelligence & reputation risk management’, Journal of Business Strategy, 39(1), pp. 61-64.

Kolbjørnsrud, V., Amico, R. and Thomas, R. J. (2016) ‘How artificial intelligence will redefine management’, Harvard Business Review, 2, pp. 1-6.

Lichtenthaler, U. (2018) ‘Substitute or synthesis: the interplay between human and artificial intelligence’, Research-Technology Management, 61(5), pp. 12-14.

Obschonka, M. and Audretsch, D. B. (2019) ‘Artificial intelligence and big data in entrepreneurship: a new era has begun’, Small Business Economics, 55, pp. 1-11.

Quan, X. I. and Sanderson, J. (2018) ‘Understanding the artificial intelligence business ecosystem’, IEEE Engineering Management Review, 46(4), pp. 22-25.

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