ARTIFICIAL INTELLIGENCE
AND DEVELOPMENT STRATEGY
AND DEVELOPMENT STRATEGY
The entrepreneurial task finds its solution (and often, meaning) only in the specific context of interaction with consumers.
The choice of a solution to a consumer's problem is largely determined by the context in which the problem arises, not by the problem "itself", detached from the environment.
The meaning of an action, phenomenon or event is ALWAYS connected to the chosen point of view of the observer, which tells us that strategy is closely related to the entrepreneur's point of view on his development.
The choice of a solution to a consumer's problem is largely determined by the context in which the problem arises, not by the problem "itself", detached from the environment.
The meaning of an action, phenomenon or event is ALWAYS connected to the chosen point of view of the observer, which tells us that strategy is closely related to the entrepreneur's point of view on his development.
One of the key findings of our study
can be stated roughly as follows:
can be stated roughly as follows:
THE SEMANTIC BOUNDARY OF AN AREA OF ACTIVITY PRECEDES ANY OTHER BOUNDARIES, INCLUDING PHYSICAL, LOGICAL, ETC.
It is the meaning that defines the context outside of which individual words, actions, phenomena and objects have no meaning and have "zero value" for consumers.
This context of interaction does not arise on its own, but is formed within a specific communication system, which we often also call a business system. Thus, an entrepreneur's products and services can only be "relevant" to consumers within a known communication system. Outside of such a known communication system, the entrepreneur's products will most likely not be relevant to consumers.
In the most general sense, it was possible to establish an exact correlation between consumers' perception of the value of a product and the communication system (business system) that generates that value.
This context of interaction does not arise on its own, but is formed within a specific communication system, which we often also call a business system. Thus, an entrepreneur's products and services can only be "relevant" to consumers within a known communication system. Outside of such a known communication system, the entrepreneur's products will most likely not be relevant to consumers.
In the most general sense, it was possible to establish an exact correlation between consumers' perception of the value of a product and the communication system (business system) that generates that value.
It also means that
A CHANGE IN THE COMMUNICATION SYSTEM WILL LEAD TO A CHANGE IN CONSUMERS' PERCEPTION OF THE VALUE OF PRODUCTS
In this way, building and managing changes in such a communication system become the entrepreneur's strategic task number 1.
This becomes a matter of principle also because the wholeness of such communication systems (business systems) is the main thing that determines the ability to describe it algorithmically or as it is now called "digitization".
You cannot create a working digital business model for a fragmented (siloed) business system lacking wholeness... This fragmented approach will create countless errors, distortions and false assumptions.
In turn, the wholeness of any business system begins with its "central" meaning – the value point reference that this system creates.
This direction – working with new meanings of interaction with consumers – is, in our opinion, the most promising area for artificial intelligence in solving entrepreneurial problems.
Today, artificial intelligence has already been successfully adopted by many business functions, but business development strategy seems to remain largely immune to the use of artificial intelligence and has very limited implementation.
This direction – working with new meanings of interaction with consumers – is, in our opinion, the most promising area for artificial intelligence in solving entrepreneurial problems.
Today, artificial intelligence has already been successfully adopted by many business functions, but business development strategy seems to remain largely immune to the use of artificial intelligence and has very limited implementation.
Just 7% of people surveyed in the McKinsey study (April, 2023) say they use artificial intelligence in strategy, compared to 25 or 30% in the areas of marketing, supply chain, and operations maintenance. [1]
One reason for the lag in implementing AI in strategy is that development strategy is the most context-dependent area of the entrepreneur's activity.
[1] https://www.mckinsey.com/capabilities/strategy-and-corporate-finance/our-insights/artificial-intelligence-in-strategy#/
One reason for the lag in implementing AI in strategy is that development strategy is the most context-dependent area of the entrepreneur's activity.
[1] https://www.mckinsey.com/capabilities/strategy-and-corporate-finance/our-insights/artificial-intelligence-in-strategy#/
USE OF AI SYSTEMS
7% — strategy and planning
35% — marketing
The ability to recognize new opportunities and "points of growth" depends largely on understanding the context of the business. And in this case, it is difficult for artificial intelligence to know everything that an entrepreneur knows, because this knowledge about business is not "digitized" and at best is available to the entrepreneur at the level of his experience and intuition. Consequently, artificial intelligence can't do much to help the entrepreneur in solving his strategic tasks.
However, if in one way or another we solve this problem of "digitizing" the context of the activity and put it into the results in artificial intelligence algorithms, we expect a significant increase in the entrepreneur's productivity in the following areas:
However, if in one way or another we solve this problem of "digitizing" the context of the activity and put it into the results in artificial intelligence algorithms, we expect a significant increase in the entrepreneur's productivity in the following areas:
- Improvement in the quality and quantity of automatically updated analytics that are used for competitive analysis or performance studies in different parts of the business.
- The ability to predict the dynamics of perceived product value based on the analysis of past and present data.
- Improve diagnosis of existing business problems. Chronic problems in business tend to exist at different "levels" or "layers" of activity, making them often "invisible" to the entrepreneur. With artificial intelligence, these problems can be successfully diagnosed and "brought into the light" for solving.
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