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Can an artificial neural network replace the CEO in the management of corporate legal entities?

27 Jun 2022 Europe

Artificial neural networks (hereinafter referred to as ANN or neural networks) can be used for almost anything due to their versatility. The rapid development of ai technologies results in the increasing number of employees being replaced by computer algorithms, raises the question, which professions are safe from this trend? Today, we can easily replace a cashier or a driver. However, will artificial intelligence be able to replace the CEO?

The CEO is the "core" of the entire legal entity. He carries out the current management of the company's activities, makes the most important decisions on concluding and evaluating contracts or agreements with counterparties of the legal entity, and organizes effective interaction of all structural divisions of the legal entity.

 Assigning functions of this kind to a neural network would take a lot of preliminary technical work and collecting a huge amount of statistical data. So, today, it would not be possible to create an algorithm capable of doing something like this for several reasons:

• First of all, neural networks are algorithms that perform one specific task that they are trained to perform. At the same time, corporate management is a process that requires a quick shift of attention between different unrelated tasks. The algorithm can certainly not deal with such variable shifting focus of attention at is time.

• Secondly, the technical process of presenting and formulating a business problem to the neural network is unclear: in what form should we pack the relevant data so that it can provide a solution?

• Third, the neural network doesn't have emotions or the abilities to motivate and inspire the team. It is difficult to imagine an artificial intelligence that could motivate or inspire. An ANN cannot understand and factor in a particular problem's social, political or emotional context to provide the most beneficial solution for the corporation.

Therefore, we can confidently say that today's artificial neural networks wouldn't be able to manage a business corporation.

However, what if we do not try to make the ANN a full-fledged participant in corporate relationships but will make it an assistant to corporate management bodies? The main task of business management has always been to find the method of carrying out the corporation's activities in the most optimal way (producing more goods or providing more services to create more profit while using fewer resources and time). Undoubtedly, the introduction of a neural network into the life of a corporation greatly optimizes the process of managing it, and that's why:

• An artificial neural network can perfectly cope with a specific task. For example, an ANN can be trained to predict decisions on the management of a legal entity not in the interests of any of the participants (shareholders) but the interests of the corporation as a whole. When predicting the decisions of the corporation's management bodies, a neural network can act as a kind of "alternative scenario". We are talking about the fact that when making a final decision, the governing bodies can analyze the solution proposed by the neural network. It seems to us that considering such an "alternative" would allow management to approach the choice of a particular solution more objectively.

• The ANN can also simplify a complex structure of corporate bodies. The ANN can replace, for example, control bodies of a corporate legal entity or assume some control functions, for example, by tracking the actions of the CEO that the board of directors or the general meeting of participants/shareholders entrusted to him. With regard to the structure of management and control bodies, we believe that the neural network would easily replace the control bodies. As for the control and auditing body, the neural network can easily replace it quite soon. The audit commission (auditor), which, as a rule, is elected to conduct inspections of the financial and economic activities of the corporation, is more a kind of procedural fiction. In practice, the utility coefficient of such a body is too low. Such technical work suits a neural network like no other. We just need to identify the basic and particular features of financial documentation that the neural network must pay attention to, as well as flag up changes in such documentation that are not standard for its corporation. And thus, the neural network would be able to identify unfair transactions concluded by the executive body. The neural network would be able to control the activities of accountable persons. We believe that such innovation in corporate affairs would make them stable in investors' eyes and allow them to make investments less fearfully than is happening today.

• The third significant argument in favour of introducing a neural network in some corporate affairs is that doing so would make corporations using such products more attractive and "open" to investors. For example, in case of an economically negative outcome of events, it would be possible to review the solution proposed by the neural network and compare the final decision made by the corporate bodies. A neural network is an effective way to make a corporation transparent and make safer investments.

As a result, with the help of a neural network, it is possible to reduce the possibility of corporate conflicts. The business would become much more “transparent” than it is today. Financial reporting would also be an excellent tool for using neural networks. Thanks to machine learning and large data samples, a company's management and accounting departments could get comprehensive reports indicating the likelihood of an increase or decrease in costs, quantitative and qualitative factors affecting this development, seasonality in demand for products and much more. Neural networks could be used to plan advertising budgets effectively. The neural network could conduct a thorough analysis of past campaigns, make forecasts and allocate costs, so business owners spend less and [1].

Using neural networks in business management would allow forecasting demand, optimizing logistics, increasing transparency and security of supplies, ensuring warehouse control, and planning human resources[2].


Summing up, we can draw the following conclusion. At this point, an artificial neural network is unable to replace the executive body in the management of corporate legal entities completely. However, we can consider it as an "assistant" capable of increasing and controlling the corporation's significant economic and reputational indicators, improving daily operations' speed. A neural network can perform complex business tasks more efficiently and cheaply than a human. When dealing with large amounts of data, the probability of error remains at a relatively low level. Unlike a human, a neural network is more stable and unemotional. It means that the neural network does not decrease the efficiency of solving tasks in the case of long-lasting high loads.


[1]create more profits



Kirill Cherevko, Associate, Intellect