Communication in entrepreneurship: using artificial Intelligence
BUSINESS INTELLECT
Kaplan Jaroslav
Kaplan Research Company
Founder of the Business IQ project
Kaplan Jaroslav
Kaplan Research Company
Founder of the Business IQ project
PDF scan of the article: https://drive.google.com/file/d/1kRVDnehxHS1Vfjz3iobT85Q7aP5ZnVx_/view?usp=sharing
Abstract
Modern digital technologies and, in particular, artificial Intelligence technologies are changing the way we think about the modes and means of entrepreneurial activity. The penetration of artificial Intelligence into business processes is inevitable. In the near future, the degree of participation in entrepreneurship of humans and programs that determine consumer behavior using digital algorithms will shift towards the latter. To achieve high business results, an entrepreneur needs to understand both the essence of communication systems and AI’s "way of thinking" as well as the general context of interaction with consumers. This article analyzes the process of communication in the system of entrepreneurial activity, as well as the use of AI in it. The author systematizes his own experience in the field of consulting entrepreneurs, reveals some characteristics of communication systems of entrepreneurial activity and possibilities of application of artificial Intelligence technologies in it, and defines the role of context in the management of business processes.
Keywords:
business, business communications, artificial Intelligence, business Intellect, context of interaction
For Citation:
Kaplan J. Communication in business activities: The use of artificial Intellect // Communicology. 2023. Vol. 11. no. 2. C. 139-149. DOI:10.21453/2311-3065-2023-11-2-139-149 .
Modern digital technologies and, in particular, artificial Intelligence technologies are changing the way we think about the modes and means of entrepreneurial activity. The penetration of artificial Intelligence into business processes is inevitable. In the near future, the degree of participation in entrepreneurship of humans and programs that determine consumer behavior using digital algorithms will shift towards the latter. To achieve high business results, an entrepreneur needs to understand both the essence of communication systems and AI’s "way of thinking" as well as the general context of interaction with consumers. This article analyzes the process of communication in the system of entrepreneurial activity, as well as the use of AI in it. The author systematizes his own experience in the field of consulting entrepreneurs, reveals some characteristics of communication systems of entrepreneurial activity and possibilities of application of artificial Intelligence technologies in it, and defines the role of context in the management of business processes.
Keywords:
business, business communications, artificial Intelligence, business Intellect, context of interaction
For Citation:
Kaplan J. Communication in business activities: The use of artificial Intellect // Communicology. 2023. Vol. 11. no. 2. C. 139-149. DOI:10.21453/2311-3065-2023-11-2-139-149 .
Introduction
Today, the field of application of intelligent algorithmic systems capable of self-learning, which are commonly referred to by the generalized term "artificial Intelligence,” has significantly expanded. In Russia, the development of artificial Intelligence technology is regulated within the framework of the program "Digital Economy of the Russian Federation."1 According to this state strategy, within the next ten years, technologies, in one way or another related to artificial Intelligence, are planned to be introduced at every fifth enterprise in the country. In this article we will try to reveal the prospects for applying this technology in the sphere of entrepreneurial activity.
At the very beginning, let us define what "artificial Intelligence" is and what role this technology is playing in modern entrepreneurship. Currently, the term "artificial Intelligence" is actively used in the media, discussed in scientific publications and applied in various spheres of activity [see, for example: Kai-Fu; Barkovich; Ha et al.; Hasan et al.]. A. Kaplan and M. Haenlein define artificial Intelligence as "the ability of a system to correctly interpret external data, learn from this data, and use this knowledge to achieve specific goals and objectives through flexible adaptation" [Kaplan, Haenlein] [Kaplan, Haenlein]. AI technologies are increasingly integrated into our daily life in the form of specific intelligent agents - voice assistants or chatbots, which are increasingly used not only for communication, but also in education, business and other areas of human activity [Osipov].
The application of AI technologies is associated with many risks. For example, today it is well enough investigated that in certain situations people tend to rely too much on automated decision making. This is called "automation bias," which can lead to a potential inability to recognize errors in the "black box" that artificial Intelligence still is for us. For example, there is evidence that a significant proportion of healthcare professionals tend to ignore their own diagnoses, often correct, when their diagnosis has not been recommended by an AI system [Goddardet al.]. Research on the risks of implementing chatbots that mimic communication situations is also of interest [Gorwa et al].
From the point of view of technology, artificial Intelligence is the whole range of programs and algorithms that imitate human cognitive functions to a greater or lesser extent. A recent paper "Artificial Intelligence: a modern approach" is devoted to the study of artificial Intelligence [Russel, Norvig], in which the authors summarized all the key studies on artificial Intelligence in recent years and proposed a universal approach to understanding the system of interaction between humans and computers. Both cited works actualize the central problem of application of artificial Intelligence in practice. It actualizes a number of questions of communication theory [Miller]: what it means to "correctly interpret data"; what are the criteria of this "correctness" and under what internal or external conditions this or that interpretation will be "correct" and under what conditions it will not be.
Entrepreneurship as a system
It is not a secret that companies today have a lot of data, but entrepreneurs often lack the time, experience or methodology to transform it into actionable ideas and tangible results.
Any entrepreneurial activity does not happen by itself, but within a specific space in which it is "unfolding". If within that space there exist such favorable conditions where an action can potentially be performed, then there is a probability that a particular action can be performed. If, on the other hand, the conditions existing within that space do not allow such an action to occur, then the zero result of such an action is obvious. For example, you will not be able to sled on water or float on them in the air, the conditions of the physical universe will not allow you to do it. Such limiting conditions exist in every area of the entrepreneur's activity, whether he or she knows about them or not. For an activity in an area to become possible and predictable, some degree of coherence between that activity and the environment is required.
Thus, the most important task of data analysis is to understand the boundaries within which certain events or phenomena may exist. Then, once these boundaries are known, it is possible to structure the data within these boundaries, establish their relationships, and build a data system. The systems approach in this case assumes that instead of fragmented knowledge about a business system, there is a system of characteristics describing that business system, and the problem of correctly interpreting the data lies in the context.
Here is a very illustrative example of a study of employee compensation programs for training [Johns]. At first glance, compensation should create in employees a desire for learning, competence growth and eventually lead to a decrease in employee turnover. However, the main influence on employees' promotion prospects in the company was the existence of another program, a career management program. If such a program existed, it helped to reduce employee turnover; if not, then compensating employees for training, on the contrary, helped to increase employee turnover. It turns out that the same factor (tuition reimbursement program) leads to completely opposite outcomes depending on the presence or absence of another component (career management program). This is a clear example that for some organizations the assumption that turnover reduction programs are effective will be true for some organizations and false for others. The answer to the question, "Do tuition reimbursement programs help employees manage turnover?" should be, "It depends...". Here we have a context-dependent approach. In the case of the example described, the primary context would be the career management program. Without identifying this context, much of the data will be impossible to put into practice. On the other hand, identifying this context makes communication about the effectiveness of tuition reimbursement programs simple and clear. In today's entrepreneurial world, the influence of context on a field of work cannot be overemphasized. For our research topic, it is important that the influence of context on the entrepreneur's activity is an upper bound, the application of artificial Intelligence tools. In each specific case, this "ceiling" will be the degree of understanding of the context of activity. In order to get an answer to a question "in context" and be able to "correctly interpret the data", it is first necessary to place the question in a particular context, or in other words, to formulate it in a certain way. Formulating a problem or a question is always about "placing" it in a particular "meaning space". At the same time, the context of interaction can radically change the whole meaning of communication [Gurov, Kaplan].
According to Rousseau and Fried, the choice of context leads to linking observations to a set of relevant facts, events, or points of view that make the research possible [Rousseau, Fried]. In other words, context selection of consumer interactions is the anchoring of a product to the specific locale in which consumers live, work, and interact, including the language they use to describe the products and these interactions. In doing so, different contexts can be interrelated or nested within each other.
For much of the twentieth century, entrepreneurship has been dominated by a steady tendency to ignore the elements associated with an understanding of human behavior. This understanding of human behavior has been replaced by technology, automation, social networks, standardization of production and globalization of the entire world economy. Milton Friedman in his famous essay "The Methodology of Positive Economic Science" [Friedman] and in his other works of the 1950s, based on the data available at the time, insisted that economists could ignore human factors in their forecasts of market performance without any fear. In our view, this is a big misconception, because customer relations - a fundamental element of any business - cannot be built by "ignoring human factors," just as it is impossible to build a successful family by ignoring all your housemates.
For this reason, in the book Business Incognita: How to Push the Boundaries of Entrepreneurial Thinking, the author formulated a type of task (which often remains overlooked in entrepreneurial practice) that was labeled the concept of "entrepreneurial task" [Kaplan]. At the center of such an entrepreneurial task is the perceived value of the entrepreneur's products and services by customers. This value (perceived value of customers) is always relative and depends on external conditions, because each person has his or her own needs and tastes [Woodruff]. An entrepreneurial task finds its solution (and often, its meaning) only in a specific context of interaction with consumers.
By context we mean a set of any factors that can influence the perception (measurement, testing of data, including value or usefulness) of something. A success factor in one context may be a failure factor in another. Thus, the meaning of an action, phenomenon or event is always related to the observer's chosen point of view, which tells us that strategy is closely related to the entrepreneur's choice of perspective on his or her development.
According to McKinsey, an international consulting agency, only 7% of respondents in the study (April, 2023) reported using artificial Intelligence in strategic planning, while in the areas of marketing, supply chain and operations maintenance - AI technologies are engaged by 25-30% of respondents2. One of the reasons for the lag in the adoption of AI in strategic planning is that strategy itself is the most context-dependent area of activity. Entrepreneurs often find themselves unable to choose a particular perspective on their development, that is, to choose a particular context of interaction with their customers3.
In turn, the value of products cannot be perceived by consumers in the abstract, disconnected from their real life conditions, worldview and experience, but can only be perceived within a specific communication system, within which all these factors exist, as well as the interaction between the entrepreneur, the product and the consumers.
The context of interaction
So, the interaction between the entrepreneur and consumers does not take place by itself, in some abstract vacuum, it takes place in a certain context of such interaction, including language, culture, and society [Kaplan]. When we talk about the context of interaction between entrepreneur, product, and consumer, we are also talking about the fact that any product must be embedded in some specific existing structure of activity. Further development of this product will take place in this particular structure. Thus, predicting the development of a product, it is necessary to take into account the prospects of development of infrastructure in which the product is "embedded", while the consumer understands the meaning of a particular product not directly, but through the objects surrounding this product, including the very interaction between the entrepreneur and the consumer. "No phenomenon is explained in and of itself." [Goethe: 334].
Any business system generates its own unique context of interaction between the entrepreneur, the product and the consumer. It is the context that defines all possible actions available to the participants of such interaction, as well as all the states in the environment that existed at the moment of interaction. In each such context there is a limited set of alternatives, so the choice of this or that business system (or, what is the same, the choice of this or that context of interaction) is also tantamount to the choice of the boundary between the business system and the environment.
Thus, since the meaning of an action, phenomenon or event is always related to the observer's chosen point of view, we can conclude that the semantic boundary of the field of activity precedes any other boundaries, including physical boundaries, logical boundaries and so on. Therefore, an entrepreneur's products and services can only be "relevant" to the consumer within a particular communication system. To illustrate this reasoning, we can give such an example. Often consumer surveys in different social networks show completely different results, even if the demographic and psychographic parameters remain approximately the same. Different communication systems generate different meanings and, consequently, different conclusions and results.
At the same time, the meaning given to the entrepreneur-consumer interaction is a pre-contextual concept. This means that the meaning of the interaction is "generated" before the entrepreneur-product-consumer business system itself is formed. Among other things, it also means that such meaning emerges not only before the interaction, but also before the emergence of both the consumer and the product. In turn, the presence of such meaning further shapes the business system, its structure, boundaries and constraints. In the book "Business Incognita: How to Expand the Boundaries of Entrepreneurial Thinking" we described the coordinate grid of entrepreneurial thinking with an initial point of reference for this coordinate system, which was labeled as the "value reference point" [Kaplan]. From a semantic point of view, a value reference point is a minimal, limiting unit of content. Continuing this analogy of the coordinate grid of the entrepreneur's thinking, we could say that such a "value reference point" is the very meaning that is invested in the interaction with the consumer. Then this central meaning with the emergence of the business system expands in abstract dimensions to the whole "category of meaning" in the very activity within the business system new meanings appear, somehow related to the central meaning and being in the same semantic space with it [Vasiliev]. In the most general sense, one can establish an unambiguous correspondence between the perception of value and the communication system (business system) that generates it. This also means that a change in the communication system ("entrepreneur - product - consumer") will lead to a change in the perception of value.
To summarize, let us repeat one of the most important theses that the meaning of any element in any system of activity is determined not by itself, but by its "neighbor in the system". Thus, integrity is formed for the whole system - any element becomes significant and contributes to the meaning of existence of any other element. This becomes a fundamental point for studying the development of any business systems, because the integrity of a business system is the main thing that determines the possibility of its algorithmic description. You will not be able to create a working algorithmic model for a fragmented, non-integrated business system. This approach will create countless errors, distortions, and false assumptions. In turn, the integrity of any business system begins with its "central" meaning - the point of reference for the value that this system creates. It is this direction - working with new meanings of interaction with consumers, in our opinion, is the most promising direction for artificial Intellect in the field of solving entrepreneurial problems. Thus, the task of discovering the "central meaning" in the interaction with consumers becomes the starting point for building the entire communication business system.
According to US scholars published in the article "Scaling Artificial Intelligence", companies perform best by applying the basic principles or methods of design thinking and working backwards from a key goal or objective [Fountain et al.]. For example, firms can envision what a five-star customer experience would look like and then explore in detail how they can achieve it. Following this logic, with which the author of this article fully agrees, the entrepreneur's primary task is to discover such meaning not only (and not so much) for any particular process (e.g., such as customer service), but a "central" meaning for the entrepreneur's interaction with customers in general, across the entire customer communication system.
Most entrepreneurs admit that artificial Intelligence has the potential to completely change the way organizations operate. They can visualize a future where, for example, retailers deliver customized products before customers even ask for them - perhaps on the same day those products are made. This scenario may sound like science fiction, but the AI that makes it possible already exists. What is preventing this future from being possible is that companies haven't figured out how to change themselves and organize their system processes in a way that optimally integrates AI4. After all, making a product before the customer asks for it requires a very good understanding of your field of activity in general and your customers in particular. This understanding of complex activities is only possible within a certain framework (activity boundary). Such a basic boundary (demarcation point) in entrepreneurial activity is set precisely by the "central" sense of interaction between the entrepreneur and his consumers.
In this context, when discussing any technologies, including artificial Intelligence, we should consider them not by themselves, but as tools that can or cannot strengthen each individual entrepreneur.
What was once beyond the reach of many can now be solved at virtually no cost thanks to artificial Intellect. This technological shift is without a doubt raising the level of competition to a level never seen before. All of this together requires the entrepreneur to have a solid foundation of knowledge, which can be labeled by the concept of "business Intellect". Earlier we have defined that the concept of business Intellect is closest to the concept of critical thinking, because in entrepreneurial activity a person faces situations for which there are no rules, and to make decisions it is necessary to be able to think effectively, i.e. to analyze, ask questions, propose and reject hypotheses, evaluate their own and others' theses and arguments, understand that the truth of a statement is almost always limited by certain conditions of truth, implicit assumptions, etc. [Gurov, Kaplan]. Without individual business Intellect, all processes of its "strengthening" with the help of technology are doomed to failure. Observing the activities of entrepreneurs, we managed to derive an empirical formula for the total potential of an entrepreneur as a multiplication of his individual business Intellect by the power of artificial Intelligence.
Obviously, it is impossible to "boost" the strength of a grasshopper to the energy of a tiger in a decisive jumping fight. Thus, artificial Intelligence will bring significantly more benefits to those who have already developed a sufficiently high individual business Intellect, and will give very little benefit to those who lack individual business Intellect. The key capability of high business Intellect is the entrepreneur's ability to search for and discover new valuable meanings of interaction with their customers.
Conclusions
Artificial Intelligence technologies are actively used in entrepreneurial activities. Intelligent algorithms are being integrated into everyday human life, including entrepreneurial activities. However, these technologies are not capable of critical evaluation of information, contextual analysis and strategy building. Despite the perceived advantages, developments based on AI technologies today are not flawless, and their use is associated with many risks. For any entrepreneurial activity, the starting point of activity is the context of interaction in a particular business system "entrepreneur-product-consumer", as well as the formation of relationships and the establishment of strong ties for the long-term reproduction of such interaction. Achieving success in many ways depends on the entrepreneur's ability to analyze the context of interaction of all participants of entrepreneurial activity.
Today, the field of application of intelligent algorithmic systems capable of self-learning, which are commonly referred to by the generalized term "artificial Intelligence,” has significantly expanded. In Russia, the development of artificial Intelligence technology is regulated within the framework of the program "Digital Economy of the Russian Federation."1 According to this state strategy, within the next ten years, technologies, in one way or another related to artificial Intelligence, are planned to be introduced at every fifth enterprise in the country. In this article we will try to reveal the prospects for applying this technology in the sphere of entrepreneurial activity.
At the very beginning, let us define what "artificial Intelligence" is and what role this technology is playing in modern entrepreneurship. Currently, the term "artificial Intelligence" is actively used in the media, discussed in scientific publications and applied in various spheres of activity [see, for example: Kai-Fu; Barkovich; Ha et al.; Hasan et al.]. A. Kaplan and M. Haenlein define artificial Intelligence as "the ability of a system to correctly interpret external data, learn from this data, and use this knowledge to achieve specific goals and objectives through flexible adaptation" [Kaplan, Haenlein] [Kaplan, Haenlein]. AI technologies are increasingly integrated into our daily life in the form of specific intelligent agents - voice assistants or chatbots, which are increasingly used not only for communication, but also in education, business and other areas of human activity [Osipov].
The application of AI technologies is associated with many risks. For example, today it is well enough investigated that in certain situations people tend to rely too much on automated decision making. This is called "automation bias," which can lead to a potential inability to recognize errors in the "black box" that artificial Intelligence still is for us. For example, there is evidence that a significant proportion of healthcare professionals tend to ignore their own diagnoses, often correct, when their diagnosis has not been recommended by an AI system [Goddardet al.]. Research on the risks of implementing chatbots that mimic communication situations is also of interest [Gorwa et al].
From the point of view of technology, artificial Intelligence is the whole range of programs and algorithms that imitate human cognitive functions to a greater or lesser extent. A recent paper "Artificial Intelligence: a modern approach" is devoted to the study of artificial Intelligence [Russel, Norvig], in which the authors summarized all the key studies on artificial Intelligence in recent years and proposed a universal approach to understanding the system of interaction between humans and computers. Both cited works actualize the central problem of application of artificial Intelligence in practice. It actualizes a number of questions of communication theory [Miller]: what it means to "correctly interpret data"; what are the criteria of this "correctness" and under what internal or external conditions this or that interpretation will be "correct" and under what conditions it will not be.
Entrepreneurship as a system
It is not a secret that companies today have a lot of data, but entrepreneurs often lack the time, experience or methodology to transform it into actionable ideas and tangible results.
Any entrepreneurial activity does not happen by itself, but within a specific space in which it is "unfolding". If within that space there exist such favorable conditions where an action can potentially be performed, then there is a probability that a particular action can be performed. If, on the other hand, the conditions existing within that space do not allow such an action to occur, then the zero result of such an action is obvious. For example, you will not be able to sled on water or float on them in the air, the conditions of the physical universe will not allow you to do it. Such limiting conditions exist in every area of the entrepreneur's activity, whether he or she knows about them or not. For an activity in an area to become possible and predictable, some degree of coherence between that activity and the environment is required.
Thus, the most important task of data analysis is to understand the boundaries within which certain events or phenomena may exist. Then, once these boundaries are known, it is possible to structure the data within these boundaries, establish their relationships, and build a data system. The systems approach in this case assumes that instead of fragmented knowledge about a business system, there is a system of characteristics describing that business system, and the problem of correctly interpreting the data lies in the context.
Here is a very illustrative example of a study of employee compensation programs for training [Johns]. At first glance, compensation should create in employees a desire for learning, competence growth and eventually lead to a decrease in employee turnover. However, the main influence on employees' promotion prospects in the company was the existence of another program, a career management program. If such a program existed, it helped to reduce employee turnover; if not, then compensating employees for training, on the contrary, helped to increase employee turnover. It turns out that the same factor (tuition reimbursement program) leads to completely opposite outcomes depending on the presence or absence of another component (career management program). This is a clear example that for some organizations the assumption that turnover reduction programs are effective will be true for some organizations and false for others. The answer to the question, "Do tuition reimbursement programs help employees manage turnover?" should be, "It depends...". Here we have a context-dependent approach. In the case of the example described, the primary context would be the career management program. Without identifying this context, much of the data will be impossible to put into practice. On the other hand, identifying this context makes communication about the effectiveness of tuition reimbursement programs simple and clear. In today's entrepreneurial world, the influence of context on a field of work cannot be overemphasized. For our research topic, it is important that the influence of context on the entrepreneur's activity is an upper bound, the application of artificial Intelligence tools. In each specific case, this "ceiling" will be the degree of understanding of the context of activity. In order to get an answer to a question "in context" and be able to "correctly interpret the data", it is first necessary to place the question in a particular context, or in other words, to formulate it in a certain way. Formulating a problem or a question is always about "placing" it in a particular "meaning space". At the same time, the context of interaction can radically change the whole meaning of communication [Gurov, Kaplan].
According to Rousseau and Fried, the choice of context leads to linking observations to a set of relevant facts, events, or points of view that make the research possible [Rousseau, Fried]. In other words, context selection of consumer interactions is the anchoring of a product to the specific locale in which consumers live, work, and interact, including the language they use to describe the products and these interactions. In doing so, different contexts can be interrelated or nested within each other.
For much of the twentieth century, entrepreneurship has been dominated by a steady tendency to ignore the elements associated with an understanding of human behavior. This understanding of human behavior has been replaced by technology, automation, social networks, standardization of production and globalization of the entire world economy. Milton Friedman in his famous essay "The Methodology of Positive Economic Science" [Friedman] and in his other works of the 1950s, based on the data available at the time, insisted that economists could ignore human factors in their forecasts of market performance without any fear. In our view, this is a big misconception, because customer relations - a fundamental element of any business - cannot be built by "ignoring human factors," just as it is impossible to build a successful family by ignoring all your housemates.
For this reason, in the book Business Incognita: How to Push the Boundaries of Entrepreneurial Thinking, the author formulated a type of task (which often remains overlooked in entrepreneurial practice) that was labeled the concept of "entrepreneurial task" [Kaplan]. At the center of such an entrepreneurial task is the perceived value of the entrepreneur's products and services by customers. This value (perceived value of customers) is always relative and depends on external conditions, because each person has his or her own needs and tastes [Woodruff]. An entrepreneurial task finds its solution (and often, its meaning) only in a specific context of interaction with consumers.
By context we mean a set of any factors that can influence the perception (measurement, testing of data, including value or usefulness) of something. A success factor in one context may be a failure factor in another. Thus, the meaning of an action, phenomenon or event is always related to the observer's chosen point of view, which tells us that strategy is closely related to the entrepreneur's choice of perspective on his or her development.
According to McKinsey, an international consulting agency, only 7% of respondents in the study (April, 2023) reported using artificial Intelligence in strategic planning, while in the areas of marketing, supply chain and operations maintenance - AI technologies are engaged by 25-30% of respondents2. One of the reasons for the lag in the adoption of AI in strategic planning is that strategy itself is the most context-dependent area of activity. Entrepreneurs often find themselves unable to choose a particular perspective on their development, that is, to choose a particular context of interaction with their customers3.
In turn, the value of products cannot be perceived by consumers in the abstract, disconnected from their real life conditions, worldview and experience, but can only be perceived within a specific communication system, within which all these factors exist, as well as the interaction between the entrepreneur, the product and the consumers.
The context of interaction
So, the interaction between the entrepreneur and consumers does not take place by itself, in some abstract vacuum, it takes place in a certain context of such interaction, including language, culture, and society [Kaplan]. When we talk about the context of interaction between entrepreneur, product, and consumer, we are also talking about the fact that any product must be embedded in some specific existing structure of activity. Further development of this product will take place in this particular structure. Thus, predicting the development of a product, it is necessary to take into account the prospects of development of infrastructure in which the product is "embedded", while the consumer understands the meaning of a particular product not directly, but through the objects surrounding this product, including the very interaction between the entrepreneur and the consumer. "No phenomenon is explained in and of itself." [Goethe: 334].
Any business system generates its own unique context of interaction between the entrepreneur, the product and the consumer. It is the context that defines all possible actions available to the participants of such interaction, as well as all the states in the environment that existed at the moment of interaction. In each such context there is a limited set of alternatives, so the choice of this or that business system (or, what is the same, the choice of this or that context of interaction) is also tantamount to the choice of the boundary between the business system and the environment.
Thus, since the meaning of an action, phenomenon or event is always related to the observer's chosen point of view, we can conclude that the semantic boundary of the field of activity precedes any other boundaries, including physical boundaries, logical boundaries and so on. Therefore, an entrepreneur's products and services can only be "relevant" to the consumer within a particular communication system. To illustrate this reasoning, we can give such an example. Often consumer surveys in different social networks show completely different results, even if the demographic and psychographic parameters remain approximately the same. Different communication systems generate different meanings and, consequently, different conclusions and results.
At the same time, the meaning given to the entrepreneur-consumer interaction is a pre-contextual concept. This means that the meaning of the interaction is "generated" before the entrepreneur-product-consumer business system itself is formed. Among other things, it also means that such meaning emerges not only before the interaction, but also before the emergence of both the consumer and the product. In turn, the presence of such meaning further shapes the business system, its structure, boundaries and constraints. In the book "Business Incognita: How to Expand the Boundaries of Entrepreneurial Thinking" we described the coordinate grid of entrepreneurial thinking with an initial point of reference for this coordinate system, which was labeled as the "value reference point" [Kaplan]. From a semantic point of view, a value reference point is a minimal, limiting unit of content. Continuing this analogy of the coordinate grid of the entrepreneur's thinking, we could say that such a "value reference point" is the very meaning that is invested in the interaction with the consumer. Then this central meaning with the emergence of the business system expands in abstract dimensions to the whole "category of meaning" in the very activity within the business system new meanings appear, somehow related to the central meaning and being in the same semantic space with it [Vasiliev]. In the most general sense, one can establish an unambiguous correspondence between the perception of value and the communication system (business system) that generates it. This also means that a change in the communication system ("entrepreneur - product - consumer") will lead to a change in the perception of value.
To summarize, let us repeat one of the most important theses that the meaning of any element in any system of activity is determined not by itself, but by its "neighbor in the system". Thus, integrity is formed for the whole system - any element becomes significant and contributes to the meaning of existence of any other element. This becomes a fundamental point for studying the development of any business systems, because the integrity of a business system is the main thing that determines the possibility of its algorithmic description. You will not be able to create a working algorithmic model for a fragmented, non-integrated business system. This approach will create countless errors, distortions, and false assumptions. In turn, the integrity of any business system begins with its "central" meaning - the point of reference for the value that this system creates. It is this direction - working with new meanings of interaction with consumers, in our opinion, is the most promising direction for artificial Intellect in the field of solving entrepreneurial problems. Thus, the task of discovering the "central meaning" in the interaction with consumers becomes the starting point for building the entire communication business system.
According to US scholars published in the article "Scaling Artificial Intelligence", companies perform best by applying the basic principles or methods of design thinking and working backwards from a key goal or objective [Fountain et al.]. For example, firms can envision what a five-star customer experience would look like and then explore in detail how they can achieve it. Following this logic, with which the author of this article fully agrees, the entrepreneur's primary task is to discover such meaning not only (and not so much) for any particular process (e.g., such as customer service), but a "central" meaning for the entrepreneur's interaction with customers in general, across the entire customer communication system.
Most entrepreneurs admit that artificial Intelligence has the potential to completely change the way organizations operate. They can visualize a future where, for example, retailers deliver customized products before customers even ask for them - perhaps on the same day those products are made. This scenario may sound like science fiction, but the AI that makes it possible already exists. What is preventing this future from being possible is that companies haven't figured out how to change themselves and organize their system processes in a way that optimally integrates AI4. After all, making a product before the customer asks for it requires a very good understanding of your field of activity in general and your customers in particular. This understanding of complex activities is only possible within a certain framework (activity boundary). Such a basic boundary (demarcation point) in entrepreneurial activity is set precisely by the "central" sense of interaction between the entrepreneur and his consumers.
In this context, when discussing any technologies, including artificial Intelligence, we should consider them not by themselves, but as tools that can or cannot strengthen each individual entrepreneur.
What was once beyond the reach of many can now be solved at virtually no cost thanks to artificial Intellect. This technological shift is without a doubt raising the level of competition to a level never seen before. All of this together requires the entrepreneur to have a solid foundation of knowledge, which can be labeled by the concept of "business Intellect". Earlier we have defined that the concept of business Intellect is closest to the concept of critical thinking, because in entrepreneurial activity a person faces situations for which there are no rules, and to make decisions it is necessary to be able to think effectively, i.e. to analyze, ask questions, propose and reject hypotheses, evaluate their own and others' theses and arguments, understand that the truth of a statement is almost always limited by certain conditions of truth, implicit assumptions, etc. [Gurov, Kaplan]. Without individual business Intellect, all processes of its "strengthening" with the help of technology are doomed to failure. Observing the activities of entrepreneurs, we managed to derive an empirical formula for the total potential of an entrepreneur as a multiplication of his individual business Intellect by the power of artificial Intelligence.
Obviously, it is impossible to "boost" the strength of a grasshopper to the energy of a tiger in a decisive jumping fight. Thus, artificial Intelligence will bring significantly more benefits to those who have already developed a sufficiently high individual business Intellect, and will give very little benefit to those who lack individual business Intellect. The key capability of high business Intellect is the entrepreneur's ability to search for and discover new valuable meanings of interaction with their customers.
Conclusions
Artificial Intelligence technologies are actively used in entrepreneurial activities. Intelligent algorithms are being integrated into everyday human life, including entrepreneurial activities. However, these technologies are not capable of critical evaluation of information, contextual analysis and strategy building. Despite the perceived advantages, developments based on AI technologies today are not flawless, and their use is associated with many risks. For any entrepreneurial activity, the starting point of activity is the context of interaction in a particular business system "entrepreneur-product-consumer", as well as the formation of relationships and the establishment of strong ties for the long-term reproduction of such interaction. Achieving success in many ways depends on the entrepreneur's ability to analyze the context of interaction of all participants of entrepreneurial activity.
Jaroslav Kaplan
Author of the book "Business Incognita. How to push the boundaries of entrepreneurial thinking". Expert in the field of sustainable development of organizations and discovering new sources of growth. Developer of the methodology of contextual market research. Member of the International Association of Strategic and Competitive Intellect Professionals SCIP (USA).
Blog: https://www.kaplanresearch.pro/eng
In this light (yet profound) business fable a very magical and sincerely nice goldfish, Goshio, navigates her aquarium and the seas of the Paraquarian world beyond. The heroine's journey is an allegory of the entrepreneurial world (and of life) – based on the author's own research journey to circumnavigate the fascinating World of Entrepreneurship. www.goshio.com
Contact:
E-mail: work@kaplan4research.com
Linkedin: www.linkedin.com/in/jaroslavs-kaplans-11255b
Author of the book "Business Incognita. How to push the boundaries of entrepreneurial thinking". Expert in the field of sustainable development of organizations and discovering new sources of growth. Developer of the methodology of contextual market research. Member of the International Association of Strategic and Competitive Intellect Professionals SCIP (USA).
Blog: https://www.kaplanresearch.pro/eng
In this light (yet profound) business fable a very magical and sincerely nice goldfish, Goshio, navigates her aquarium and the seas of the Paraquarian world beyond. The heroine's journey is an allegory of the entrepreneurial world (and of life) – based on the author's own research journey to circumnavigate the fascinating World of Entrepreneurship. www.goshio.com
Contact:
E-mail: work@kaplan4research.com
Linkedin: www.linkedin.com/in/jaroslavs-kaplans-11255b
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