Artificial Intelligence in Established of Industry 4.0

KATERYNA KRAUS

Department of Management,

Borys Grinchenko Kyiv University,

Kyiv, 18/2 Bulvarno-Kudriavska St., Kyiv,

UKRAINE

NATALIIA KRAUS

Department of Finance and Economics,

Borys Grinchenko Kyiv University,

Kyiv, 18/2 Bulvarno-Kudriavska St., Kyiv,

UKRAINE

MARIIA HRYHORKIV

Department of Business Informatics and Economic Modelling,

Yuriy Fedkovych Chernivtsi National University,

Chernivtsi, 2 Kocyubynskogo St., Kyiv,

UKRAINE

IHOR KUZMUK

Department of Economic Theory, Management and Administration,

Yuriy Fedkovych Chernivtsi National University,

Chernivtsi, 2 Kocyubynskogo St., Kyiv,

UKRAINE

OLENA SHTEPA

Department of Management,

Borys Grinchenko Kyiv University,

Kyiv, 18/2 Bulvarno-Kudriavska St., Kyiv,

UKRAINE

Abstract: The purpose of scientific research is to present the features of digitization of business processes using

artificial intelligence at enterprises as a foundation on which the gradual formation of Industry 4.0 is built and

the search for reserves of socio-economic growth in the conditions of the development of digital ecosystem and

digital entrepreneurship. Presentation of a number of positive and negative consequences of the influence of

artificial intelligence on the operation of digital infrastructure, as well as to indicate possible approaches in the

practical application of artificial intelligence based on the substantive characteristics of its construction. The

results and forecasts of four waves of modern development of artificial intelligence are presented, including:

increasing the profits of Internet companies, monetization of creative Internet applications; reducing the

number of cases of non-repayment of loans, establishing objective diagnoses, court decisions, etc.; protection of

phones and digital wallets; payment by face scan. It was determined that the expected high-quality product of

the fourth wave of modern development of artificial intelligence will be computer intelligence that understands

and changes the world, a direct economic benefit first of highly structured environments, and then of other

spheres of human activity. The peculiarities of the application of artificial intelligence in the course of the

formation of digital enterprises of Industry 4.0 are revealed. The possibilities and advantages of the application

of technical capabilities on which the development of artificial intelligence technology is based are analyzed.

Approaches to the practical use of artificial intelligence are indicated, including: the synthesis of a human

likeness with an independent thinking platform; predictive analytics; methods of control, planning and

dispatching; storage, processing and presentation of knowledge. Having conducted a thorough analysis in parts

of the acceleration of deep digitalization of business processes with the help of artificial intelligence, authors

determined the impact of digitalization process and the operation of digital platforms on the transformational

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Mariia Hryhorkiv, Ihor Kuzmuk, Olena Shtepa

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changes of enterprises. It has been found that digitalization lowers the barriers to market entry for small

businesses, which have significantly expanded their niche and limited the monopoly of large companies, and

the development of digital platforms determines the so-called network effects, when a large number of platform

users creates conditions for the emergence of even more consumers. The directions for the development of

artificial intelligence technologies are proposed, among which are named: creation of tools for users that allow

to simplify the configuration of AI components of systems and to perform some actions without the

involvement of developers. A step-by-step algorithm for setting up AI models is defined, namely: definition of

the goal; tool selection; configuration and training of the model; hypothesis testing and model optimization;

analysis of results.

Key-Words: artificial intelligence, Industry 4.0, digitization of business processes, cloud technologies,

intelligent solutions, digital transformation, Fourth Industrial Revolution.

Received: June 3, 2022. Revised: October 9, 2022. Accepted: November 4, 2022. Published: November 28, 2022.

1 Introduction

Digital transformation of large enterprises is a

complex and multi-stage process. However, this

transformation is extremely necessary today, as

drones and artificial intelligence are already helping

industry save significant resources. Of course,

changing processes that have been established for

years or even decades, moreover, on the scale of

huge productions, is a serious challenge. Despite

frequent discussions of the benefits of digitalization,

the practical result of innovation efforts is far from

always obvious.

In industry, digitization has its own

characteristics. When a large industrial enterprise

unites many structural units, it is possible to

effectively manage a large-scale IT infrastructure

only with the help of a single center of expertise.

Previously, each enterprise had its own IT

department, but over time, as a result of the scaling

of IT projects, the IT function is being centralized.

Artificial intelligence is increasingly penetrating

our lives today, artificial intelligence technologies

are already with us. Yes, in modern smartphones, a

large number of applications use artificial

intelligence, and these aren’t only the well-known

voice assistants, but also many other applications:

keyboards, image processing programs, etc.

However, artificial intelligence is in demand not

only in the world of mobile devices. The advantages

of machine intelligence technologies attract the

attention of business as well – SME implementation,

practice in the enterprise segment. And if for the

most progressive companies’ artificial intelligence

has already become a working tool, the

implementation and development of which are

actively being worked on by business users and IT

experts, then for many Ukrainian organizations

smart technologies are still something unattainable.

The development of Industry 4.0 caused the need

to find new approaches to managing business

processes at enterprises, offering a significant range

of the latest digital technologies for the high-quality

functioning of various sectors of the economy. Each

industry, each company, by means of a preliminary

analysis of opportunities and evaluation of the

effectiveness of implementation and improvement,

makes a choice in favor of one or another tool of

Industry 4.0, including artificial intelligence. In

harmony with these processes, digital

transformation of the economy is being

implemented, as its role in the deployment of smart

industry and the use of artificial intelligence is

constantly growing. The issue of studying practical

experience of working with artificial intelligence

requires further in-depth research.

Experts in the field of IT technologies claim that

artificial intelligence technologies ensure the quality

of decision-making, increase the efficiency of

internal and external processes of the organization,

and also improve the customer experience. But these

are not all the advantages of using artificial

intelligence, because today artificial intelligence

makes it possible to significantly speed up

processes, and speed nowadays is the main

competitive advantage for most business structures.

2 Problem Formulation

2.1 Literature Review

The question of the conditions for the formation and

development of Industry 4.0 based on artificial

intelligence is only beginning to attract the attention

of foreign and domestic researchers [1], including

Kai-fu Li [13], Raymond Kurzweil [18], [19].

According to Kurzweil, in the future humanity will

achieve almost unlimited material wealth, and

people can become immortal. He also provided a

scientific rationale for the technological singularity

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– phenomenally rapid scientific and technological

progress based on powerful artificial intelligence

(superior to human intelligence) and the

cyborgization of humans.

Scientists see the ultimate goal of their research

on “artificial intelligence” in uncovering the secrets

of thinking and creating a model of the brain. The

fundamental possibility of modeling intellectual

processes follows from main epistemological result

of cybernetics, which is that any function of the

brain, any mental activity, described in a language

with strictly unambiguous semantics using a finite

number of words, can in principle be transferred to

an electronic digital computing machine. Modern

scientific ideas about the nature of the brain give

reason to believe that, at least in the purely

informational aspect, the most essential regularities

of the brain are determined by a finite (although

perhaps extremely large) system of rules.

Based on the analysis of the experience of

working with artificial intelligence, scientists have

concluded that this is a technology that is the basis

of our future, as it intersects with all aspects of

human life: health, medicine, housing, agriculture,

transportation, sports, even love, sex and death.

Artificial intelligence is no longer a technological

trend, a buzzword or a temporary pastime, but the

third computer era. In the midst of fundamental

changes, not similar to those experienced by the

generation of the first industrial revolution [31].

In the scientific article “Artificial Intelligence:

Learning and Limitations” [39] the authors A.P. De

Oliveira, H.F.T. Braga analyzed main technologies

used in artificial intelligence, the history of their

development, presented their considerations

regarding artificial neural networks and failures that

arise as a result of the learning processes and the

equipment used. The researchers presented their

understanding of three types of errors: adversarial

examples, soft errors, and errors due to lack of

appropriate training. The researchers managed to

carry out a practical study related to the third type of

error and propose actions based on the basis of

experiments. Goal pursued by scientists was to

change the way artificial intelligence models are

trained, add some rare conditions and improve their

ability to predict with greater accuracy in any

situation, soft errors and errors due to lack of proper

training.

Artificial intelligence is able to ensure the correct

and prompt solution of various socio-economic

tasks, which will contribute to increasing the

efficiency of state regulation. At the same time, the

rapid development of the latest technologies, in

particular artificial intelligence systems, the Internet

of Things, cloud technologies, necessitates the

introduction of institutional changes. These results

are presented in scientific papers and articles by

S.J. Russell, P. Norvig [26], A. Bundy, R. Burstall

[5], N.J. Nilsson [23]. Some other relevant studies

can be found in [6], [7], [8], [9], [10], [14], [16],

[25].

A galaxy of well-known researchers in the

scientific world, such as V. Ifantis, K. Ntalianis,

P. Ntalianis, are dealing with the issues of studying

the possibilities of the introduction of artificial

intelligence in the public sector and in the field of

education [38]. Scientists have succeeded in

presenting the concept of public offices without

employees, where the concept of public

administration is applied through the synergy of

artificial intelligence and other technologies aimed

at improving the service of citizens even in extreme

conditions such as pandemics and physical disasters.

The proposed design complements the out-of-office

Amazon Go store and the latest cutting-edge e-

government technologies.

Scientists S. Russell and P. Norvig in their book

entitled “Artificial Intelligence: a Modern

Approach” [26] made an attempt to present the

stimulus for development of artificial intelligence as

a science of designing rational agents. “Life 3.0.

The Age of Artificial Intelligence” is a book by the

Swedish-American astrophysicist, one of the most

authoritative researchers of artificial intelligence,

Professor M. Tegmark of the Massachusetts

Institute of Technology [29], in which the author

considers possible scenarios of the development of

events in the event of the appearance of super

intelligent artificial intelligence on Earth, analyzes

the prospects for the development of high

technologies, their opportunities and risks.

M. Tegmark calls on experts to join forces in the

fight for cyber security and “friendly” artificial

intelligence. M. Tegmark points out that humanity

perceives the mind as something extremely

mysterious from a biological point of view. At the

same time, he claims: such ideas have no basis. The

author insists that for the generation of machines,

intelligence (which will be better than human) is not

an obstacle. Organic matter has no effect on the

mind. Physicists admits that artificial intelligence

has high risks: it will either radically change

everyone’s life for the better, or it will become the

most dangerous phenomenon in the history of

mankind. And in order to eliminate these risks,

humanity should conduct discussions on this issue

more often.

Scientists K.R. El Helou, A.-B. M. Salem [36] in

their research raised the issue of the role and

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effective combination of artificial intelligence and

machine learning in helping humanity cope with the

coronavirus pandemic. Thus, researchers believe

that machine learning can help make the right

decision in time, save lives and reduce health care

costs. The mediating effect of artificial intelligence

is researched by scholars Y. Suleiman,

M.A. Rahman, N.K.N. Mat in their work “A

Conceptual paper on Re-Patronage Model for

Syariah Compliance E-lodging Industry: The

Mediating Effect of Artificial Intelligence” [37].

This study aims to analyze the predictors of Muslim

tourists’ online repeat patronage intentions towards

Shariah compliance in the e-accommodation

industry in Malaysia. The AI wave in the business

landscape is said to combat human error and

increase customer satisfaction through their

efficiency and ability to meet human needs.

Therefore, this study also aims to cover the

implementation of AI in the hotel industry and

specifically the Syariah compliance of hotels.

Despite the fact that the problem of “artificial

intelligence” is closely related to the needs of

practice, there is no single general practical task that

would clearly determine the development of theory

and methodology, but there are many tasks that are

partial and narrow. Therefore, the problem of

“artificial intelligence” is, in fact, a whole complex

of problems characterized by varying degrees of

generality, abstractness, complexity, and

sophistication, each of which has its own

fundamental and practical difficulties. These are

such problems as pattern recognition, learning and

self-learning, heuristic programming, creating a

general theory of self-organizing systems, building a

physical model of a neuron, many of which have

great independent significance. Important results,

both of a practical and theoretical nature, have been

obtained for all these directions, and intensive

research continues. Since, apart from a small

number of optimists, almost no one is trying to

“produce” intelligence similar to humans, then we

are talking about creating a system that will be able

to implement certain models of intelligence.

Among the cohort of researchers engaged in

revealing the content of methods and systems of

artificial intelligence in the era of digital economy

can be named N. Andrusyak [31], V. Gitis,

K. Hudkov [8], M. Hlybovets, O. Oletskyi [9],

N. Shakhovska, R. Kaminskyi, O. Vovk [],

N. Kraus, K. Kraus [17-19], D. Pchelyanskyi,

S. Voinova [24], O. Manzhura [20-21],

O. Yershova, L. Bazhan [35], O. Marchenko [22],

O. Shtepa [28], N. Yasynska [34]. The analysis of

the noted recent studies proved the need for a

comprehensive approach to finding ways to

implement the directions of artificial intelligence

development, namely in solving problems related to

the approximation of specialized artificial

intelligence systems to human capabilities and their

integration, which is realized by human nature, and

in the creation of Artificial Intelligence, which

represents the integration of already created

artificial intelligence systems into a single system

capable of solving humanity’s problems.

2.2 Purpose of the Article

The purpose of the publication is to present the

characteristic features of the application of artificial

intelligence as the foundation on which the gradual

formation of Industry 4.0 is built and the search for

reserves of socio-economic improvement in the

conditions of innovation and digitalization, which

has every chance of becoming a decisive step in the

formation of a virtual space with augmented reality

in a harmonious combination with the real, the

physical world.

2.3 Tasks of the Article

Among the tasks set in the article are:

argumentatively reveal the peculiarities of the

implementation of artificial intelligence in business

processes by enterprises using the example of

progressive companies; to determine and reveal the

content of the possibilities of practical application of

artificial intelligence in the course of digitizing the

business processes of Industry 4.0 enterprises in the

conditions of digitization; to present the results and

forecasts of four waves of modern artificial

intelligence development in parts of the formation

of Industry 4.0; to reveal the step-by-step algorithm

for setting up AI models; to analyze the effects of

the digitization process and the operation of digital

platforms on the transformational changes of

companies; to present the possible directions of

changes aimed at accelerating Industry 4.0 and

implemented by managers of modern progressive

enterprises as a result of the involvement of artificial

intelligence; to indicate technologies on which the

development of artificial intelligence technologies is

determine directions of their development.

2.4 Methodology

On the basis of dialectical, systemic and matrix

methods, the use of artificial intelligence

capabilities by digital enterprises of the Industry 4.0

ecosystem, which determine socio-economic effects

and virtual format of business work, was

investigated. The research used general scientific

methods, such as methods of analysis and synthesis,

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induction and deduction, in order to find out the

positive and negative consequences of the impact of

artificial intelligence technology as the newest tool

for the development of Industry 4.0. The method of

scientific description made it possible to outline the

main characteristic features of the use of artificial

intelligence and to indicate correct and incorrect

actions during its application. A comparative

analysis was used in the part of revealing the step-

by-step algorithm for setting up AI models; features

of using artificial intelligence in business;

elucidation of the influence of the digitization

process and the operation of digital platforms on the

transformational changes of companies; features of

the application of technologies on which the

development of artificial intelligence is based and to

determine the directions of their development.

3 Problem Solution

3.1 The Essence of Artificial Intelligence and

the Scope of Its Penetration

Cyber-physical systems and other breakthrough

achievements of “Industry 4.0” radically change the

world of people themselves and begin to compete

with the latter. The activities of business entities,

both new organizational forms and traditional ones

that adopt digital technologies, are increasingly

connected with virtual reality, as it includes the use

of online services, cloud services, social networks,

e-commerce and artificial intelligence. Digital

initiatives using elements of artificial intelligence

technologies have helped businesses adapt to the

conditions of Covid-19 pandemic. It was digital

initiatives that minimized the involvement of people

in day-to-day operations and contributed to the

optimization of business processes.

The use of AI is the ability of a digital computer

or a computer-controlled robot to perform tasks

usually associated with human activities. This term

is often applied to the project of developing systems

endowed with human-characteristic intellectual

processes, such as the ability to reason, discover

meaning, generalize, or learn from past experience

[2]. Today, the concept of “artificial intelligence” is

gaining more and more direct meaning. It is

understood that developments correspond to the

essence of the term, that is, systems are created that

can process the information that comes to them,

connect it with the knowledge they already have and

form their own idea about the objects of knowledge.

But at the beginning of the formation of such a

phenomenon as artificial intelligence, the term had a

different form of interpretation in accordance with

the content and essence of the inventions of that

time. Artificial intelligence could be defined as “a

device for enhancing mental abilities”.

An early example of artificial intelligence is

Wilhelm Schickard’s mechanical digital calculating

machine (a device functionally similar to a

calculator that could add and subtract six-digit

numbers with a bell ringing when it overflowed),

which dates back to 1623. At the end of the 18th

century Austrian inventor Friedrich von Knaus

designed a series of machines that could write rather

long texts with a pen. The next person who achieved

success in creating artificial intelligence at that time

was the English mathematician Charles Babbage,

who came up with the concept of a complex digital

calculator – an analytical machine that could

calculate moves for a game of chess [24].

In today’s conditions of innovative development,

artificial intelligence can be understood as a field of

computer science that deals with the modeling of

intellectual behavior in computers – Merriam-

Webster Dictionary [4]. According to the

interpretation of the Cambridge Dictionary, artificial

intelligence is considered as “the ability to produce

machines that have certain qualities of the human

mind, such as the ability to understand language,

recognize images, solve problems and learn” [3].

Examples of such AI include robot manufacturing,

intelligent assistants, proactive healthcare

management, automated financial investing, virtual

travel booking agent, social media monitoring,

cross-team chat tool, conversational marketing bot,

and natural language processing (NLP) tools.

It would not be a mistake to interpret artificial

intelligence as a new technology with a huge

potential to forever change the world as we know it.

Artificial intelligence finds application in many

areas of human activity, including services,

industry, education, social networks, transport.

However, scientific publications rarely discuss the

accuracy and reliability of such technology, which

has found application in situations where a person’s

life depends on his decision-making process, which

is the result of his training, one of the stages of

development. It is known that the learning process

of artificial intelligence, which can use the

technology of artificial neural networks, presents an

error of the predicted value in relation to the real

value, which can compromise its application, being

more critical in situations where the safety of the

user is the main concern [39, p. 80].

Artificial intelligence can be considered as a

complex of technological solutions that imitate the

cognitive functions of a person and allow to achieve

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results comparable to the results of human

intellectual activity when performing tasks [15]. The

scientific point of view is also interesting: artificial

intelligence is the simulation of the processes of

human intelligence by machines, especially

computer systems. These processes include learning

(acquiring information and rules for using

information), reasoning (using rules to reach

approximate or definite conclusions), and self-

correction. Special applications of artificial

intelligence include expert systems, speech

recognition, and machine vision [32].

Artificial intelligence is present in all areas of

digital transformation, as the growing amount of

data exceeds the human capacity to process it. At

the beginning of the development of computing

technology, AI was considered as technologies that

can reproduce human intelligence and even surpass

it using electronic computing technology. Such

technologies were used to develop theoretical and

methodological foundations of forecasting, planning

and optimization of procedures and parameters of

technical and economic systems [35, p. 53].

3.2 Practical Application of Artificial

Intelligence in Today’s Conditions

Despite the fact that artificial intelligence is still far

from perfect, its impact on the global economy has

been felt since the beginning of 2018. Technologies

such as computer vision, intelligent decision-

making, and machine learning have already

radically changed various sectors of the economy

around the world, but this is only a small part of the

overall capabilities of artificial intelligence.

Covid-19 pandemic accelerated the adoption of

AI, changing the attitude of international business to

new technologies, and in many ways served as a

driver for the development of the market for AI

solutions. In the future, business will show even

more demand for more complex solutions that

integrate AI with other digital technologies,

including the Internet of Things, new generations of

communication, and distributed ledger systems. In

the near future, this will allow the transition from

fragmented to systematic development of AI

technologies throughout the value chain. In the

future, AI solutions deployed in the cloud

infrastructure will become widespread, showing that

companies find the deployment of smart

technologies in the cloud to be a more efficient and

flexible process. Approaches in practical application

of AI, based on the content characteristics of its

construction, we tried to present in Figure 1. The

results and forecasts of the four waves of the

modern development of artificial intelligence are

presented in Table 1.

Fig. 1: Approaches in the practical application of AI based on the content characteristics of its construction

Source: composed by authors

Artificial intelligence has a human likeness and develops through interaction with others and accumulates

knowledge and skills in the course of experience. In a real enterprise, we are talking about the use of robots and

robotic machines that can be used in production, in the process of customer service, in warehouse logistics.

AI has the appearance of an independent thinking platform. It is inside the servers and doesn't have a “corporeal”

shell. Such AI will receive information via the Internet. Similar systems based on AI are already widespread

today for the analysis of a large array of information in the companies Google, Facebook, and Amazon.

Synthesis of the human likeness with an independent thinking platform. A “scanned” human consciousness is

superimposed on the machine code. Such solutions do not necessarily have a physical implementation, they are

often visualized using virtual reality.

AI has the following functional capabilities: predictive analytics; methods of control, planning and dispatching;

storage, processing and presentation of knowledge; speech recognition and computer vision; biometrics, image

and video segmentation, character recognition, object tracking, general vision); natural language processing

(including extraction of new knowledge, machine translation, dialogue). These functions can be used

independently or in combination.

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Table 1. Results and forecasts of four waves of modern artificial intelligence development

Time period

Products

Practical

application

Expected results

The first wave is Internet

AI (status – implemented).

The peak of success –

2012, the preparatory

stage – 1997-2011

Recommender algorithms based

on personal preferences, fake

news recognition algorithms,

targeted digital advertising,

personalized Internet user

content

Clicks and

likes of

Internet users

Increasing profits of Internet companies,

monetization of creative Internet

applications

The second wave is

business AI (status –

implemented, at the stage

of completion). Peak of

success – 2019-2022,

preparatory stage – 2003-

2018

Recommendation algorithms of

banks’ credit policy, algorithms

for recognizing diagnoses based

on patient analysis indicators,

structuring of big data, speech

recognition tools and natural

voice processing during legal

proceedings

The number

of requests for

technology

use

Fewer loan defaults, establishing objective

diagnoses, court decisions, etc.,

autonomous cyber-physical production,

unmanned transportation, localization of

production, ludic community practices,

lifelong learning, LegalTech, FinTech,

InsurTech. Artificial intelligence has

caused the emergence of new jobs in terms

of their functional content

The third wave is AI of

perception (it affects

people) (status is in the

implementation stage).

The year of

implementation is 2020,

the preparatory stage is

2003-2019

Algorithms for recognizing

faces, sounds, city traffic flows,

individual educational

programs, digital models of

human behavior (including

financial)

The speed of

proliferation

of sensors and

intelligent

devices

The physical world is transformed into

digital data, which will later become part

of deep learning algorithms; protection of

phones and digital wallets; payment by

face scan, new learning system.

Manufacturers of artificial intelligence and

endowments try to make its application

“transparent” and understandable for

people (due to misunderstanding, fears

arise among main mass of the population

about products that act on the basis of

artificial intelligence)

The fourth wave is

autonomous AI (status –

planned)

Computer intelligence, which

understands and changes the

world, is a direct economic

benefit first of highly structured

environments, and then of other

spheres of human activity

There are no

data yet

Artificial intelligence will perform tasks

that meet two criteria: they can be

optimized based on data analysis and do

not require social interaction. Artificial

intelligence will deepen its penetration

into business. Artificial intelligence will

increasingly become the subject of

international politics (in particular, the

issue of competition and struggle between

states)

Source: compiled by authors based on sources 34; 13; 25

The development of hardware and software tools

is necessary for the implementation of artificial

intelligence technologies, namely:

- Hardware and software platforms for

implementing methods and algorithms of artificial

intelligence;

- Conclusion machines and their operating

systems;

- Data repositories for machine learning.

The spheres of application of artificial

intelligence technologies in various sectors of the

digital economy are business processes in industrial

production, agriculture, transport systems, logistics,

construction, energy, the banking sector, trade,

medicine, national security, education, urban

infrastructure, public administration. The

development of artificial intelligence is associated

with the development of standards that should take

into account both universal work on standardization

of information systems and technologies, and areas

specific to intelligent data processing systems. At

the same time, for the development of products and

services based on artificial intelligence, an

unambiguous interpretation of the concepts used by

all participants in the digital transformation of the

economy is necessary [35, p. 53].

The development of basic artificial intelligence

technologies is based on a number of technologies

presented in Figure 2.

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Fig. 2: Technologies on which the development of

artificial intelligence technologies is based

Source: composed by authors

AI technologies are developing very quickly and

in different directions. The tools of predictive

analytics, natural language processing, etc. have

already shown their effectiveness. So, with the use

of machine learning models, the Creatio system can

predict the values of various fields, carry out

categorization, calculate the probability of given

events, rank data and much more.

As part of the problem of the article, it should be

noted that according to the Country-level digital

competitiveness rankings worldwide 2020 [33],

Ukraine received 48.81 points out of 100 possible.

USA, which is recognized as the most competitive

country in the world (100 points), has the best

result, Singapore is in second place with 98.05

points. Digital competitiveness rating is aimed at

analyzing the country’s ability to apply digital

technologies and implement these technologies at

enterprises and government organizations.

The ranking showed that many Scandinavian

countries took high positions in the list and are

among the top ten: Denmark – 96.01 points, Sweden

– 95.15 points, Norway – 92.17 points and Finland –

91.13 points. According to another study published

by the company IoT Analytics Industry 4.0 & Smart

Manufacturing, in 2020 the most common digital

technologies used in the world are: 3D printing, 5G

Internet, artificial intelligence (Artificial

Intelligence), augmented reality, automated guided

vehicles (Automated Guided Vehicles – AGV),

blockchain technologies (Blockchain), cloud

technologies, cobots (Cobot), cyber security, Digital

Twin, drones, IoT and IoT platforms, quantum

computing and virtual reality [11].

According to leading experts [40] in the field of

cyber security, over the past few years there has

been a transition from the stage of cybercrime to the

stage of cyberwar. In order to adequately respond to

new challenges, the expert environment has two

main approaches: to adopt the philosophy and

methods of military intelligence and to use artificial

intelligence methods to counter cyber-attacks.

3.3 Use of Artificial Intelligence: Experience

and Benefits

Already in 2020, about 30% of all B2B companies

used AI in at least one of their main sales processes.

Instead, according to experts’ forecasts, by 2030

already 70% of these companies will use at least one

AI tool. One of the first tasks that artificial

intelligence developers were given was

communication with real people in companies

working in the B2C segment.

So, modern CRM systems – systems that manage

relationships with customers – no longer provide for

personal communication, but actively use bots,

automatic responses and AI. Undoubtedly, this

affects the management of communication with

consumers. Such communication differs from

communication with a real consultant, which affects

the level of consumer loyalty and can lead to

negative consequences [6, p. 5].

With AI, machines can perform human-like

tasks, adapting to new data and continuously

learning from experience. It is learning from

experience that is the main driver of the

development and application of technologies based

on the use of a large amount of accumulated data.

You can teach the system to make decisions the way

a person would, and sometimes even find patterns

and regularities that are difficult for a person to find,

thus increasing the effectiveness of the decisions

made. Moreover, receiving new, more relevant

experience, systems are able to relearn or relearn,

which makes it possible to always maintain the

knowledge and skills of machines in an up-to-date

state.

In addition to the undeniable advantages that AI

technologies provide, there are also a number of

difficulties that companies face in the process of

their configuration and implementation. Research

data on the use of artificial intelligence indicates

that only 23% of organizations have implemented

AI in their business processes, while 36% of

companies do not use artificial intelligence

technologies. The reasons for such indicators are, in

particular, that these companies are not very

knowledgeable about the use of such tools.

Technologies

on which the

development

of basic AI

technologies

is based

Extracting

knowledge

from various

sources Forecasting

and decision

support

Cognitive

data

analysis

Multi-agent

management and

dispatching of

resources in

distributed systems

Planning and

management of goal-

directed behavior in

unstructured

environments

Machine

learning

Pattern

recognition

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On the one hand, the development of most

software for business is quite simple – there are

many ready-made tools, and over the years of their

design, best practices have been formed that can be

easily applied. And things are going well with

internal development – it is not difficult to find a

specialist on the market who can design a system,

develop or adapt it to business needs. After all,

recently, leading software providers, in particular

Terrasoft, have been offering clients so-called low-

code and no-code tools that make it possible to

create and adapt software products without

knowledge of programming languages – only by the

efforts of business analysts.

On the other hand, the implementation of AI

technologies is accompanied by a number of

difficulties. First, there is a lack of knowledge,

because there are a large number of artificial

intelligence algorithms that are quite complex, both

mathematically and technically, and require specific

skills and knowledge.

Secondly, the complexity of the design, since the

stage of designing the model is difficult and very

important. It is necessary to choose the right data for

training the model; determine the parameters on the

basis of which the system will operate; select the

used algorithms. The presence of an error or

inaccuracy at this stage can lead to a low accuracy

of the system, which is unacceptable. In order to

avoid errors and inaccuracies, it is worth practically

using the possibilities of automatic and automated

management. It is automatic control systems (ACS)

that are a technical analogue of human intelligence.

Modern automated control systems are built on the

basis of digital devices – computers and

microprocessors.

The basis of such systems is complex software

that uses both simple calculation algorithms and

algorithms based on artificial intelligence – neural

networks and fuzzy logic. ACS is used to manage

any modern processes and productions. A modern

enterprise functions almost without human

intervention. Intervention in the work of the

enterprise is necessary only in the event of an

emergency – an accident or equipment breakdown.

Many enterprises have introduced remote control

via the Internet or via mobile applications.

Thirdly, the complexity of the implementation,

given that the modeling of AI systems is carried out

iteratively and is based on the selection of a number

of hypotheses, due to which the process becomes

longer and more resource-intensive.

However, despite the apparent difficulties, there

are prospects that the situation will change for the

better, because artificial intelligence technologies

are constantly evolving and developing (Figure 3).

Nevertheless, one of the most important stages –

model design, which includes data preparation, their

preliminary processing, selection of features on the

basis of which system training and forecasting will

be carried out – remains the field of activity of

narrowly specialized specialists in data analysis and

processing (data scientists). But even here, thanks to

the expansion of knowledge about artificial

intelligence, as well as the development of

technologies themselves, the situation is changing

for the better. Consequently, more and more

companies are successfully innovating in the field of

AI and getting good results.

Developers of computer games are forced to use

AI of one degree or another. Standard tasks of AI in

games are finding a path in two-dimensional or

three-dimensional space, simulating the behavior of

a combat unit, calculating correct economic

strategy, and so on. In 2018, a portrait of a fictional

person drawn by AI was sold for $432,000. Before

drawing Edmond Bellamy, the algorithm examined

15,000 portraits dating from the 14th to 20th

centuries.

Fig. 3: Directions for the development of artificial

intelligence technologies

Source: composed by authors

Companies using AI in sales have already been

able to generate 50% more leads, 60-70% shorter

call times and 40-60% lower costs. That is why 84%

of modern companies implementing AI believe that

it will provide them with a competitive advantage in

the future. The use of AI technologies enables many

advanced companies to focus their attention on

achieving the result, leaving the system to analyze

data and search for patterns. Therefore, the goal of

the teams of these companies is to work on the

development of AI technologies – to create tools

that make it possible to use information from IT

systems as efficiently as possible, to improve the

quality of decisions made on the basis of historical

Tools are created for users, which

allow to simplify the configuration

of AI components of systems and to

perform some actions without the

involvement of developers

Vendors offer

customers AI

models that

require a

minimum of

steps to run

Libraries are being

developed in which the

most popular

algorithms for learning

AI systems are

implemented

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data, as well as to optimize processes.

Today, companies are trying in every possible

way to set up AI tools in the simplest and fastest

way possible, to minimize the need to involve

expensive specialists to design models and explain

the factors that affect one or another forecasting

result. This makes it possible to increase trust in

artificial intelligence, and also helps analysts of the

Creatio system to quickly understand the logic of

the model and its settings. Creatio’s AI tools allow

you to solve business tasks of various levels of

complexity. But the practice of using artificial

intelligence has shown that a solution does not have

to be complex in order to be effective.

AI is a technical (in all modern cases of attempts

at practical implementation – a computer) system

that has certain signs of intelligence, i.e. is able to:

recognize and understand; find a way to achieve

results and make decisions; to learn in practical

terms, the presence of only incomplete knowledge

about the brain and its functioning doesn’t prevent

us from building approximate information models of

it, simulating the most complex thinking processes,

including creative ones, on digital computers.

3.4 Algorithm for Setting up AI Models

To implement a small and simple, but quite

effective solution using Creatio AI tools, it is no

longer necessary to involve developers and data

specialists. The step-by-step algorithm for setting up

AI models is not complicated (Table 2).

Table 2. Step-by-step algorithm for setting up AI models

Stage of setting up

AI models

Procedure for achieving results

Stage 1 –

Formation of the

team

Finding a business expert who has a deep understanding of how the division works and can articulate the tasks that need

to be solved. Thanks to working with such an expert, it is not necessary to involve narrow-profile specialists, because

most of the answers are received from business representatives. They are the ones who can tell you what data is used in

decision-making and what can potentially affect the performance of tasks.

Stage 2 –

Defining the goal

Analysis of business unit goals and KPIs. So, for example, involved specialists are engaged in communications with

potential clients (leads), and their task is to interest the interlocutor and arrange a meeting with him. Accordingly, the

more scheduled meetings, the more efficient the unit’s work.

Stage 3 – Tool

selection

Creatio implements a platform for training models and solving tasks of classification (for example, to determine the

category of sale, priority of the request), regression (for example, for predicting the amount of the order, processing

time of the request) and scoring (for example, for calculating the probability of concluding a deal, the readiness of the

lead to purchase). The most acceptable solution for the task is the use of scoring to predict the probability of the

occurrence of a given event – successful communication with the client and the appointment of a meeting.

Stage 4 –

Determination of

model parameters

Consideration of the reasons for the expected result. The answer can be given by business experts. It is not at all

necessary to engage a data scientist to analyze large arrays of historical data and search for correlations and patterns.

Based on their experience, experts can show what will potentially affect the result, and based on this, you can choose

the necessary parameters of the model. For example, the success of planning a meeting can potentially be influenced by:

the presence of a contact’s corporate e-mail; the number of other leads generated for the same client; number of

newsletters read; ice source etc. Only about 10 parameters – and the hypothetical model is ready.

Stage 5 – Tuning

and training the

model

Machine Learning Models section of Creatio makes it possible to perform most of the settings by means of the user,

using the basic capabilities of the system. It took 2-3 hours to set up all the necessary model parameters. After building

the model, the process of learning it on a small amount of data is started. As a result, information is obtained about

predictive accuracy and the degree of influence of each parameter on final result. This is a great opportunity to perform

an initial analysis of the hypothesis, find parameters that do not affect the result and need to be excluded, or consider

adding new factors and re-examine the model. After several iterations, a model of sufficient accuracy is obtained and a

pilot project can be launched to evaluate the quality of the model on real data.

Stage 6 –

Hypothesis testing

and model

optimization

To implement the model in the department’s processes, it is worth setting up several queues with leads that are

processed by employees. The first list includes leads with a probability of appointment (scoring score) from 75% to

100%, the second – with a probability from 0% to 75%. Within a few weeks after the launch of the pilot project, the

conversion rate of the first stage was 32%, and the second stage was 12%, which proves the effectiveness of the

adjusted model.

Stage 7 – Analysis

of the results

Employees have changed the course of the process and now focus on a higher value of the scoring point when selecting

leads. So, in a short period of time, with minimal costs, it is possible to increase the efficiency of the unit. It is based on

three entities: historical data, intelligent self-learning algorithms and employee expertise. Work on process optimization

does not end there. You can continue to iteratively experiment with parameters to improve the quality of the model, and

add new intelligent features to further improve the results of the process.

Source: author’s development

Revealing the content of the algorithm for setting

up artificial intelligence models, it is worth noting that at Stage 5, a strategy for the development of

cyber security education should be chosen based on:

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international standardization documents; the

conceptual model developed by the Joint Working

Group on Cybersecurity Education; good practices

of modular structure and dynamic building

principles that allow for rapid content changes.

Based on the principles of “domains of

knowledge” and “domains of application”, each

training course should be designed as a workflow

for a specific application domain, consisting of

modules that represent the relevant domains of

knowledge. We share the opinion of scientists

R. Trifonov, G. Tsochev, O. Nakov, G. Pavlova,

S. Manolov regarding the need for decisive

improvement of education through the introduction

of dynamic principles and personalization in

educational programs, which can be implemented

with the help of so-called adaptive learning systems

[41].

Nowadays, it is not the volume of collected data

that matters, but how this information is organized,

structured and how it is then used. The

transformation of primary data into useful

conclusions and specific actions is a complex and

time-consuming task that a person faces every day

and which machine intelligence technologies can

quite successfully cope with. AI technologies are

becoming more popular and in demand, and now the

main thing is not to miss the right moment and start

implementing smart algorithms into business

processes in order to benefit from this in the future.

Several main conclusions can be drawn from the

experience of using Creatio artificial intelligence

technologies and general trends in the development

of artificial intelligence systems.

First of all, building intelligent solutions does not

always require the involvement of specialized

specialists and large investments. Instead, you can

use the knowledge of internal experts and low-code

tools, which make it possible to make settings in a

simple and understandable interface for users.

Secondly, even the implementation of small and

simple solutions based on artificial intelligence

provides an opportunity to increase the effectiveness

of internal and external processes and help

businesses become more efficient.

But it is also worth noting that since the creation

of the first information management systems,

scientists have been constantly talking about the

need to organize a secure information environment.

The use of artificial intelligence was not an

exception. Issues of cyber security come to the fore,

so the more powerful the technology of artificial

intelligence, the more resources will need to be

spent on organizing the security of its use. However,

the question of concern is: what will happen if

artificial intelligence turns against us?

We are not talking about apocalyptic scientific

scenarios. Rather, it is about the management of

artificial intelligence technology in terms of the

fulfillment of the tasks set before it, which can lead

to unpredictable consequences. AI is a technology

that is capable of self-development and self-

learning, that is, it is able to propose and implement

an innovative solution that can radically affect

business processes, communication with customers,

or technological processes. At the same time, it is

important to remember that AI does not have

feelings and does not understand where the limits of

the implementation of tasks are, so it can become a

real challenge for managers [5], [6].

3.5 Artificial Intelligence in Industry and

Digital Transformation

Therefore, based on the above features of the work

of artificial intelligence, there is a need to create a

single digitalization control center – this is a global

trend for large B2B companies and a market

necessity. When the company is ready to embark on

the path of digital transformation, the effectiveness

of the introduction of new technologies will, first of

all, depend on a comprehensive approach and the

preparation of a digitalization strategy within the

framework of all business processes.

For example, in metallurgy, the Indian Tata

Group and the Korean Posco created their Digital

companies. In Ukraine, there are few companies that

have only centralized their IT departments, and even

fewer that have separated the divisions into a

separate company. Yes, Metinvest Digital is the first

such IT company in the country [7].

Consolidation of IT functions helps to rebuild

management processes, unify all service units,

establish quality control, change management,

monitoring and infrastructure development. If you

need to automate not a single function, but the entire

value chain, then advanced technologies can

significantly help in this. Automating the work of

specific nodes and technological processes, as well

as combining aggregates, workshops and enterprises

into single information systems allows to reduce the

cost of products and increase quality, making the

working conditions of employees more secure,

intelligent and comfortable.

One of the steps in this direction is the use of

drones for measuring bulk substances at the GZK.

Drones make measurements, all received

information is centrally entered into the ERP

system. Up-to-date data is received throughout the

entire product production chain, and it is possible to

timely control resource stocks and promptly manage

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logistics. Today, in order to remain competitive in

the market, industrial enterprises cannot do without

digital modernization of production. Given that

there is regulation of gas consumption at the state

level, and industrial enterprises need a lot of this

resource, work is underway to minimize the cost

due to accurate forecasting. To do this, a significant

amount of historical data on about 20 parameters is

loaded (steel grade specification, melting

characteristics, actual volume of previous

consumption, etc.) and artificial intelligence

independently builds a correlation model of

parameters, analyzes the dependence between data

and predicts numerical trends. At the output, the

predicted value of gas consumption for the next

calculation day is obtained with an accuracy of more

than 97% [7].

With the aim of digital transformation of the

field of document management, there is an

opportunity at industrial enterprises to use the

innovative SAP Fiori technology. This is a

convenient web interface to main functions and

business operations in SAP systems, as well as a set

of applications that can be used on any device. This

step greatly facilitates the process of agreement of

contractual documents.

Industrial enterprises cooperate with a number of

large B2B companies, which also face the task of

digital transformation. By providing complex

solutions for business, end-2-end IT solutions,

which include IT infrastructure, automated systems

in production, accounting and information systems,

systems for supporting key business processes and

ensuring company’s activities, the industrial

company thereby implements a comprehensive

approach – full cycle of IT solutions:

implementation, monitoring, integration, support

and further development.

Digital transformation is supported by

innovations and technological solutions, but

primarily the drivers of such changes are leaders

who are open to change and able to quickly adapt to

changing market and industry conditions. Some

innovations of a transformative variable nature are

presented in Figure 4.

Fig. 4: The influence of the digitization process and

the operation of digital platforms on the

transformational changes of enterprises

Source: compiled by author based on source 14, p.

For example, the Ukrainian company Nova

Poshta actively uses robots at its sorting terminals.

In 2021, cargo and small shipment areas at 20

sorting centers were robotized. Depending on the

weight of the parcel, the company uses different

types of robots. A robot train consisting of two

sections is used in the sorting areas of small

shipments (up to 2 kg). This is an in-house

development of Nova Poshta and the Ukrainian

manufacturer SBR, which has no analogues in

Ukraine.

The worker places the package on the robot,

which takes it to the scanner and moves it to the

box, which is responsible for a certain geographical

direction. Robots work on a special platform with a

monorail, which simultaneously serves as their

charger. The use of such robots made it possible to

increase the productivity of sorting small parcels by

2 times. Currently, 272 such robots are working

[30]. Pirouette robots of Ukrainian company Deus

Robots are used to sort shipments up to 30 kg. They

got this name because they can rotate around their

axis. From the unloading belt, the package falls on

the robot. Next, he drives up to scan the parcel and

then puts it on a roller conveyor, from which the

shipment goes directly into a special bag for

delivery. Due to their dexterity, such robots can

work in different sorting areas.

The Nova Poshta company continues to improve

the robotization of cargo terminals. In November

2021, a terminal with a fully robotic cargo shipment

area opened in Dnipro. 50 robot trucks

manufactured by SBR move goods inside the

Digitization connects

supply and demand

through digital platforms

and does not require

intermediary structures

Digitization lowers

barriers to market entry

for small businesses that

have significantly

expanded their niche and

limited the monopoly of

large companies

Digital platforms are, as

a rule, multi-purpose and

open up unprecedented

opportunities to provide

services quickly,

qualitatively, at

relatively lower costs

and without most of the

previously existing

geographical barriers

Digitization, the

development of digital

platforms lead to so-called

network effects, when a

large number of platform

users create conditions for

the emergence of an even

greater number of

consumers

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terminal from the unloading area to the loading area.

They move on a magnetic tape and can

simultaneously carry up to 300 kg and pull another

1000 kg behind them. Such robotic trucks can

transport up to 5,000 loads per day, which increases

the productivity of the terminal by 30%. In total, the

company already uses 180 robot trucks at various

cargo terminals [30].

With the increase in the volume of shipments,

the company aims to remain the fastest delivery in

Ukraine and to create a flexible system for

increasing sorting capacity using robots.

Robotization of sorting terminals allows to increase

productivity without additional burdens on

employees. In addition, by automating processes, it

is possible to achieve greater accuracy in sorting

parcels, because reducing the influence of the

human factor allows avoiding possible errors.

Robots are already working at depots in Kyiv,

Kharkiv, Dnipro, Odesa, Boryspil, Melitopol,

Pokrovsk, Novomoskovsk, Korosten, Strya, Sambir,

Kovel and Stoyanka. The Nova Poshta company

plans to create a fully robotic sorting center.

The directions of changes intended to be carried

out by the managers of modern progressive

enterprises:

- Introduction of artificial intelligence creation

system. It involves not only programming, but also a

training phase, during which they learn to identify

the correct patterns of actions and act on them, and a

testing phase, where the artificial intelligence

receives many examples that it can deal with in real

life, allowing us to follow his work. However, in life

there are non-standard situations that occur rarely,

but artificial intelligence must also react to them.

So, if we rely on this technology, which should

theoretically create a world of efficiency and safety

for us, we must first verify that the artificial

intelligence works according to the plan and code

[6, p. 5];

- Automation of your enterprise as soon as

possible – in some cases, this is a more effective

method than trying to retain workers. Unfortunately,

the economic situation in the country will not

change dramatically in the next 3-5 years;

- Maximum outsourcing of everything that does

not relate to key production business processes and

competencies;

- Formation of a targeted policy for the growth of

personal incomes. The salary of an automation

engineer (designer) should not be 2 times lower than

a programmer of the same or even lower

qualification;

- Formation of system policies of recruiting and

personnel management. In particular, plan the

number of new jobs to be created, review and

standardize qualification requirements, and inform

training centers that train specialists about this;

- Consolidation in its field – as well as with other

high-tech industries – for the growth of the image of

the engineering profession, their qualifications and

working conditions. Use IT-like tools to: change the

educational landscape – invest in schools and

courses to improve skills and knowledge; implement

new technical standards; adjust system work with

media; together to lobby the interests of

industrialists, first of all, in terms of improving the

economic situation, attracting investments and

creating new jobs in industries with high added

value [12]. There are no secrets in what the IT

industry has done. It is only about systematic

approaches and consolidation of efforts.

In addition, it is important to exercise control

over artificial intelligence. Given that this

management function is the easiest to automate, it is

advisable to come to the realization that complete

automation of related business processes is

impractical. It may be an impossible situation that

we simply “unplug” artificial intelligence, because

this technology can predict it and protect itself.

Also, a modern manager must not only control the

development of artificial intelligence, but also

predict the vector of its development [6, p. 5].

3.6 Challenges in the Development of

Artificial Intelligence

Among the challenges that, according to the

expectations of experts, should be addressed by

developing countries should be attributed:

1. Technology penetration, effective deployment

and “capability threshold”. Digital technologies

have raised the “capability threshold” that

companies need in order for new technologies to be

truly effective.

This is explained by the fact that 4PR is about

the “alloy” of existing and new technologies into

new integrated technological systems. Accordingly,

the management of complex, integrated

technologies, such as fully automated production,

the combination of robots with IoT technologies,

requires appropriate expertise, knowledge and

qualified personnel, which are often not available in

developing countries.

2. Integration and modernization of existing

production systems. One of the definitions of

industrialization says that it is about the

mobilization of resources in conditions of

uncertainty. Most of such obligations require the

involvement of physical capital, which is built into

certain (production) technologies and cannot be

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quickly transformed into other technologies. Such

investments also require the use of specific, narrow

expertise and skills. And all this becomes critical,

because in the conditions of a specific industry and

production technology, further change or use of

such technologies for other purposes is unlikely.

For developing countries, such investments are

risky. Existing companies have already invested in

certain technologies and are currently considering

how to modernize them, how to integrate digital

technologies into production. And the construction

of new plants requires developed access to capital

and long-term investments, which is not possible

everywhere.

3. Basic and digital infrastructure. Digital

technologies are very demanding in terms of the

infrastructure that enables them to function at full

scale. Many developing countries still have

significant challenges even in electrification, let

alone reliable Internet communications. In certain

cases, the infrastructure is a real bottleneck, but one

that can be bypassed with new possibilities – for

example, using new sources of electricity or

wireless communication.

On the other hand, these new capabilities also

require corresponding quality and reliability. Either

way, improving the productivity and quality of

digital manufacturing requires overcoming these

infrastructural limitations. Otherwise, investments in

digital technologies can take a very long time to pay

off.

4. Technology diffusion, hubs of the Fourth

Industrial Revolution and the digital divide. Despite

the fact that most developing countries have their

own hubs of the Fourth Industrial Revolution – that

is, where there are individual advanced companies

that have mastered digital manufacturing, most such

examples are isolated. Often, such local

breakthroughs are associated with the activities of

suppliers in individual, large projects.

At the same time, most companies and sectors

are still operating at the previous level of

technology. This means that it is extremely difficult

for new solution providers such as OEMs and

Engineering companies to build equally sustainable

manufacturing links in value chains at home. Digital

divide between customer islands and advanced

providers is significant and costly to bridge, limiting

the diffusion of Fourth Industrial Revolution

technologies.

5. Asymmetry in access to technologies. Digital

technologies are complex and controlled by a

limited number of leading firms from developed

countries. Firms in developing country value chains

rely on these technologies and in some cases, even

as they mobilize their resources, are ultimately

dependent on these technologies from advanced

countries. In global corporations operating around

the world and in global value chains, the type and

use of standards and equipment is often determined

by corporate and international standards. The value

of the latter is increasing. The use of these

technologies and standards means the growing

weight of global corporations in global networks

and access to their technologies is not the same for

different countries.

The usefulness of modern research in the

practical applicability of artificial intelligence lies in

the fact that it has become an important trend in the

creation of promising battlefield management

systems and weapons. Banks use artificial

intelligence systems (AI) in insurance activities

(actuarial mathematics) when playing on the stock

exchange and property management. In August

2001, robots beat humans in an impromptu trading

competition (BBC News, 2001). Pattern recognition

methods (including both more complex and

specialized ones and neural networks) are widely

used in optical and acoustic recognition (including

text and voice), medical diagnostics, spam filters, in

air defense systems (identification of targets), and

also to ensure a number of other tasks of national

security.

With the help of AI, it is possible to ensure an

optimal and threat-adaptive selection of a

combination of sensors and means of destruction, to

coordinate their joint functioning, to detect and

identify threats; assess the enemy’s intentions. AI

plays a significant role in the implementation of

augmented reality tactical systems. For example, AI

allows for classification and semantic segmentation

of images, localization and identification of mobile

objects in order to schematically reproduce the

contours of objects as symbols of augmented reality

for effective targeting. There are high hopes for the

use of artificial intelligence to manage 6G cellular

networks.

4 Conclusion

In conclusion, it should be noted that the importance

of new technologies of the Fourth Industrial

Revolution is growing everywhere. Many of them

are not only a component and driver of innovation

for classic industrial sectors, but also become self-

sufficient economic sectors over time. What makes

these technologies revolutionary is the effect they

provide – we are talking about the “alloy”,

combining the physical and digital worlds,

ubiquitous data processing and much greater

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Mariia Hryhorkiv, Ihor Kuzmuk, Olena Shtepa

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integration with science. This has already given

significant improvements in economic indicators,

for example, in automation or predictive (predictive)

maintenance [10].

Digital transformation is a process of qualitative

restructuring of the way of doing business or

changing business model in order to obtain a

significant optimization of resources or a

competitive advantage due to the introduction of

new technologies, including algorithms using

artificial intelligence and machine learning.

Many countries in these sectors are on the

threshold of mass use of artificial intelligence

algorithms – this 4.0 technology is the most

breakthrough. At the same time, the level of

countries and the level of penetration of new 4.0

technologies in them are different – there are

pioneers and those that are increasing their pace,

and there are lagging countries.

Only 50 of the world’s economies are considered

to be truly engaged in digital technologies today.

Yes, the Fourth Industrial Revolution is not the

same asset for different countries. The effective

application of these new technologies assumes that

enterprises have passed the classic stages of

industrialization, have the appropriate capabilities,

standards and infrastructure. These conditions are

still lacking in many developing countries.

In recent years, many countries are trying to

embark on the path of the Fourth Industrial

Revolution and are considering the presence of the

necessary parameters and conditions in the

industries on which success depends. Many of these

are critical success factors, but some appeal to

challenges those developing countries themselves

must address. As the experience of different

countries shows, mastering the industrial

requirements for Fourth Industrial Revolution takes

time and requires basic capabilities to accept the

digital world.

Based on the results of our research, we came to

the conclusion that artificial intelligence is a product

of the development of Fourth Industrial Revolution.

However, according to its content, Fourth Industrial

Revolution itself should cover the automation of all

stages and processes, and when products are not yet

things, but exist in the virtual world in the form of

information models.

On the eve of the future Industry 5.0, it is

necessary to consider two worlds together: the

virtual world, implemented with the application of

artificial intelligence, and the real world,

implemented by artificial intelligence. It is

expedient to build the Internet of knowledge on the

ontological methodology, which is based on the

world of virtual agents representing object-functions

capable of generating new data taking into account

the available information.

Digital transformation of business based on the

application of artificial intelligence changes the

forms of activity, rebuilds organizations, lays the

foundations for the possibility of using new business

models, new sources and forms of income

generation, attracting more consumers, and brings

customer service to a new level. As a result of new

opportunities provided by artificial intelligence for

Industry 4.0, spheres of functioning are being mixed

in new formats, including in the form of digital

platforms. The practical application of various

digital technologies provides maximum energy

efficiency and sustainable development; smart,

productive and profitable operations; optimal

availability of resources and efficiency of their use;

mobile intelligence gathering and proactive risk

mitigation.

References:

[1] Andrusiak N.O., Kraus N.M., Kraus K.M.

(2020). Digital Cubic Space as a New

Economic Augmented Reality. Sci. innov.,

Vol. 16, no. 3. 92–105.

[2] Artificial intelligence (2022). Britannica.

URL:

https://www.britannica.com/technology/artific

ial-intelligence (assessed 25 June 2022).

[3] Artificial Intelligence (2022). Dictionary.

URL:

https://dictionary.cambridge.org/dictionary/en

glish/artificial-intelligence (assessed 12 June

2022).

[4] Artificial Intelligence. Essential Meaning

(2022). Merriam Webster. URL:

https://www.merriamwebster.com/dictionary/

artificial%20intelligence (assessed 08 June

2022).

[5] Bundy A., Burstall R. (1984). Artificial

Intelligence: an Introductory Course.

Edinburgh: Revised. Edinburgh University

Press. 200 p.

[6] Doroshkevych D.V., Lytvynenko I.S. (2022).

Analysis of challenges for management due to

the activation of the use of artificial

intelligence in the digital society. Efficient

economy, no. 1. 1–6. (in Ukrainian).

[7] Drones and artificial intelligence are already

helping industry save resources (2019).

Metinvest Digital. Company news from May

24, 2019. URL:

https://metinvest.digital/page/drony-

WSEAS TRANSACTIONS on BUSINESS and ECONOMICS

DOI: 10.37394/23207.2022.19.170

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Volume 19, 2022

iskusstvennyj-intellekt-pomogayut-

promyshlennosti-ekonomit-resursy (assessed

15 June 2022). (in Ukrainian).

[8] Gitis V.B., Gudkova K.Yu. (2018). Methods

of artificial intelligence. Kramatorsk: DDMA.

136 p. (in Ukrainian).

[9] Glybovets M.M., Oletskyi O.V. (2002).

Artificial Intelligence. Kyiv: Kyiv-Mogyla

Academy. 364 p. (in Ukrainian).

[10] Industrial policy tools for 4PR – the example

of MedTech from Costa Rica (2020).

INDUSTRY4UKRAINE. URL:

https://www.industry4ukraine.net/publications

/instrumenty-promyslovoyi-polityky-dlya-4pr-

pryklad-medtech-z-kosta-riky/ (assessed 29

June 2022). (in Ukrainian).

[11] Iot-analytics. URL: https://iot-

analytics.com/industry-4-0-adoption-2020-

who-is-ahead/ (assessed 18 June 2022).

[12] Industry 4.0 in mechanical engineering, the

state in Ukraine and prospects for

development (2021). Analytical report of

APAU, Vol. 1. (in Ukrainian).

[13] Kai Fu L. (2019). The superpowers of

artificial intelligence. China, Silicon Valley

and the New World Order. 233 p.

[14] Kolot A., Herasymenko O. (2020). Digital

transformation and new business models as

determinants of formation of the economy of

nontypical employment. Social and labour

relations: theory and practice, no. 10(1). 33–

54.

[15] Kraus K., Kraus N., Nikiforov P., Pochenchuk

G., Babukh I. (2021). Information and Digital

Development of Higher Education in the

Conditions of Innovatyzation Economy of

Ukraine. WSEAS Transactions on

Environment and Development, Vol. 17, Art.

#64. 659–671. URL:

https://wseas.com/journals/ead/2021/b305115

-652.pdf (assessed 15 July 2022).

[16] Kraus K., Kraus N., Shtepa, O. (2021).

Synergetic effects of network interconnections

in the conditions of virtual reality. Journal of

Entrepreneurship, Management and

Innovation, no. 17(3). 149–188. URL:

https://jemi.edu.pl/uploadedFiles/file/all-

issues/vol17/issue3/JEMI_Vol17_Issue3_202

1_Article5.pdf (assessed 20 July 2022).

[17] Kraus K.M., Kraus N.M., Manzhura O.V.

(2021). E-commerce and Internet commerce:

a textbook. Kyiv: Agrar Media Group. 454 p.

(in Ukrainian).

[18] Kurzweil R. (1992). The era of intelligent

machines. Massachusetts: MIT Press. 580 p.

[19] Kurzweil R. (2005). The Singularity is Near:

When Humans Transcend Biology. New

York: Viking Adult. 602 p.

[20] Manzhura O., Kraus K., Kraus N. (2021).

Digitalization of Business Processes of

Enterprises of the Ecosystem of Industry 4.0:

Virtual-Real Aspect of Economic Growth.

WSEAS Transactions on Business and

Economics, Vol. 18, Art. #57. 569–580. URL:

https://www.wseas.org/multimedia/journals/ec

onomics/2021/b165107-021(2021).pdf

(assessed 5 January 2022).

[21] Manzhura O., Kraus K., Kraus N. (2021).

Digitalization of Business Processes of

Enterprises of the Ecosystem of Industry 4.0:

Virtual-Real Aspect of Economic Growth

Reserves. WSEAS Transactions on Business

and Economics, Vol. 18, Art. #57. 569–580.

URL:

https://www.wseas.org/multimedia/journals/

economics/2021/b165107-021(2021).pdf

(assessed 11 July 2022).

[22] Marchenko O., Kraus N. (2021). Innovative-

digital entrepreneurship as key link of

Industry X.0 formation in the conditions of

virtual reality. Baltic Journal of Economic

Studies, no. 7(1). 47–56.

[23] Nilsson, N.J. (2009). The Quest for Artificial

Intelligence. London: Cambridge University

Press. 578 p.

[24] Pchelianskyi D.P., Voinova S.A. (2019).

Artificial intelligence: prospects and

development trends. Automation of

technological and business processes, no. 3.

59–64. (in Ukrainian).

[25] Pyshchylina O. (2020). Digital economy:

trends, risks and social determinants. Kyiv:

Razumkov Center. 274 p. (in Ukrainian).

[26] Russell S., Norvig P. (2006). Artificial

Intelligence: a Modern Approach. USA:

Prentice Hall. 960 p.

[27] Shakhovska N.B., Kaminskyi R.M., Vovk

O.B. (2018). Artificial intelligence systems.

Lviv: Lviv Polytechnic. 392 p. (in Ukrainian).

[28] Shtepa O., Kraus K., Kraus N. (2021).

Teaching Guidelines for Digital

Entrepreneurship. Cracow University of

Economics, Kiev-Cracow. 71 p. URL:

https://ted.uek.krakow.pl/output-1-teaching-

guidelines/ (assessed 18 January 2022).

[29] Tagmark M. (2019). Life 3.0. The age of

artificial intelligence. Kyiv: Our format. 432

p. (in Ukrainian).

[30] The new post office introduces robots to sort

parcels (2021). GSMinfo. Hardnews from

WSEAS TRANSACTIONS on BUSINESS and ECONOMICS

DOI: 10.37394/23207.2022.19.170

Kateryna Kraus, Nataliia Kraus,

Mariia Hryhorkiv, Ihor Kuzmuk, Olena Shtepa

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Volume 19, 2022

November 29, 2021. URL:

https://gsminfo.com.ua/68352-nova-poshta-

vprovadzhuye-robotiv-dlya-sortuvannya-

posylok.html?fbclid=IwAR0nWJiysw35PvYv

QTWbZU5x00ESyOpBNOtOL6PiLDSBE6ty

YLdEi8SsflY (assessed 11 June 2022). (in

Ukrainian).

[31] Vebb, E. (2020). The big nine: how the tech

titans and their thinking machines could warp

humanity. Kharkiv: Vivat. 352 p. (in

Ukrainian).

[32] What is Artificial Intelligence? (2022).

TechTarget. URL:

http://searchcio.techtarget.com/definition/AI

(assessed 21 June 2022).

[33] Worldwide digital competitiveness (2022).

Statista. URL:

https://www.statista.com/statistics/1042743/w

orldwide-digital-competitiveness-

rankingsbycountry/ (assessed 14 June 2022).

[34] Yasynska N.A. (2022). Exism-challenges of

personal finance in the cognitive capacity of

trust, structure of employment and

knowledge. Efficient economy, no. 1. 1–10.

(in Ukrainian).

[35] Yershova O.L., Bazan L.I. (2021). Artificial

intelligence is the technological basis of the

digital transformation of the economy.

Statistics of Ukraine. New information

technologies, no. 3. 47–59. (in Ukrainian).

[36] Helow K.R., Salem A.M. (2020). Are

artificial intelligence (AI) and machine

learning (ML) having an effective role in

helping humanity address the new coronavirus

pandemic? WSEAS Transactions on Biology

and Biomedicine, Vol. 17, pp. 119-124.

[37] Sulaiman Y., Rahman M.A., Mat N.K. (2020).

A conceptual paper on re-patronage model for

syariah compliance e-lodging industry: the

mediating effect of artificial intelligence.

WSEAS Transactions on Business and

Economics, Vol. 17, pp. 153-163.

[38] Yfantis V., Ntalianis K., Ntalianis F. (2020).

Exploring the implementation of artificial

intelligence in the public sector: welcome to

the clerkless public offices. applications in

education. WSEAS Transactions on Advances

in Engineering Education, Vol. 17, pp. 76-79.

[39] Oliveira A.P., Braga H.F.T. (2020). Artificial

intelligence: learning and limitations. WSEAS

Transactions on Advances in Engineering

Education, Vol. 17, pp. 80-86.

[40] Trifonov R., Manolov S., Tsochev G.,

Pavlova G. (2019). Automation of cyber

security incident handling through artificial

intelligence methods. WSEAS Transactions on

Computers, Vol. 18, pp. 274-280.

[41] Trifonov R., Tsochev G., Nakov O., Pavlova

G., Manolov S. (2020). Possibilities for

improving the quality of cyber security

education through application of artificial

intelligence methods. Engineering World,

Vol. 2, pp. 145-149.

Contribution of Individual Authors to the

Creation of a Scientific Article (Ghostwriting

Policy)

Kateryna Kraus, research the essence of artificial

intelligence and the scope of its penetration,

visualization of the presented material, writing

conclusion, drawing up a list of references.

Nataliia Kraus, formulation of the purpose and tasks

of research, research the practical application of

artificial intelligence in today’s conditions and

challenges in the development of artificial

intelligence selection of literature and its analysis.

Mariia Hryhorkiv, research the use of artificial

intelligence: experience and benefits.

Ihor Kuzmuk, write an annotation of scientific

research and highlighting the essence of the

algorithm for setting up AI models.

Olena Shtepa, describe the artificial intelligence in

industry and digital transformation.

Creative Commons Attribution License 4.0

(Attribution 4.0 International, CC BY 4.0)

This article is published under the terms of the

Creative Commons Attribution License 4.0

https://creativecommons.org/licenses/by/4.0/deed.en

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DOI: 10.37394/23207.2022.19.170

Kateryna Kraus, Nataliia Kraus,

Mariia Hryhorkiv, Ihor Kuzmuk, Olena Shtepa

E-ISSN: 2224-2899

1900

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