Artificial Management
ChatGPT has opened the AI Pandora's box. YOU must now drive forward the Digital Transformation and utilise Artificial Intelligence as a key enabler for real and Digital Business models and processes. This requires an adjustment to the organisation of a company, as the associated management will also become Artificial Management via Digital Management. It is still up to YOU to decide what the future will look like with IT, not ChatGPT and its competitors. But not for long…
The Evolution for Corporate Management
When an AI becomes a Colleague!
Suppose Amazon uses an AI to proactively send you parcels with goods that you have not ordered, but which you can still use and therefore do not return. In that case, this is Artificial Management (here: Artificial Analytics). If NetDragon Websoft appoints an AI as the head of the company, which controls all processes within the company and also provides relevant instructions to employees, then this is Artificial Management (here: Artificial Leadership). When Booking.com utilises AI in individual customer dialogues to consistently identify the maximum willingness to pay in dynamic pricing, this is Artificial Management (here: Artificial Business). As a result, management in this area will quickly develop into Artificial Management via Digital Management and change how the organisation, management, and implementation of strategic and operational tasks for companies, especially in the context of Digital Transformation, will be implemented in the future. Against this backdrop, Artificial Management can be defined as follows:
Artificial Management describes the use of Artificial Intelligence (AI) by Humans (Managers), but also the replacement of these same Humans (Managers) by this Artificial Intelligence (AI) for functional tasks in procurement, production, sales, financing, human resources and administration as well as for the operational tasks of analysis, goal setting, planning, decision-making, organisation, delegation, coordination, employee management and control.
Accordingly, the aim of this book is to highlight the tension between deployment and replacement and thus the areas of application and interaction between man and machine in management. In this context, the various theoretical and practical influences will also be discussed in order to identify the associated need for research and action. This is exemplified in a subject area that - as already indicated above - is directly affected because data already plays a significant role here today and is already available: The "Digital Transformation" for existing and "Digital Innovation" for new business models and processes. The evolution here will be immediate and rapid, and, accordingly, will essentially turn Digital Business with the associated Digital Leadership into Artificial Business with Artificial Leadership. We aim to present an initial approach to this topic, incorporating conceptual considerations by outlining the various developments and potential applications of Artificial Intelligence (AI) in operational and strategic management.
Note: The book draws on various previous works, such as Kollmann, T. (2025): What is Artificial Entrepreneurship?; Kollmann, T./Kollmann, K./Kollmann, N. (2023): Artificial Leadership; Kollmann, T. (2022): Digital Business and Kollmann, T. (2022): Digital Leadership. However, the relevant content has explicitly been expanded to include the influences of AI, and current references have also been added in order to expand on the previous findings.
The Evolution of AI will essentially turn Digital Business with the associated Digital Leadership into Artificial Business with Artificial Leadership.
Artificial
Management
Tobias Kollmann • Kilian Kollmann
Full Titel
Artificial Management: The Evolution for Corporate Management
​
​Publication Date
26.11.2025
The Book/eBook can be orderd here:
Introduction
Regardless of which form (Weak/Strong/Super) of Artificial Intelligence (AI) will be used now or in the future, the fundamental pre-requisite is the digitization of information, communication, and transactions (Kollmann 2022a). From an economic perspective, this includes the digitization of products and processes as well as the associated organizations (Kollmann, 2022b). Why? On the one hand, competition that has already digitized forces you to do so, and on the other hand, customers who now want to take advantage of digital offerings in addition to real ones expect it. In addition, only through fundamental digitization and thus the conversion of real content into binary 0/1 data can the actual basis for AI-Systems be created, as they need the resulting 0/1 data in order to function at all. This means that there is no point in thinking about AI, its use, and the associated "Artificial Transformation" if the homework of digitization and the associated "Digital Transformation" has not been done first. So anyone who thinks they can skip the homework and jump straight to the fun part will quickly learn otherwise. The rule is: first Digitalization, then Digital Transformation, and only then Artificial Transformation!
"Digital Transformation" (also referred to as "digital change") is an ongoing and far-reaching process of change in society, economic and politics based on digital technologies that has a fundamental impact on information, communication and transactions between the players involved and leads to a new understanding and behaviour in the social, economic and political spheres of life.
Development
Against this backdrop, companies are subject to constant digital change and must deal with both new opportunities and threats to their operational business (Nambisan 2017). An essential part of this digital change is the possibilities enabled by new AI technologies, which have given rise to new market players.
The market for Artificial Intelligence (AI) has grown rapidly in recent years and is expected to continue to grow strongly as more and more companies and organizations use AI technologies to automate their business processes, achieve efficiency gains, and develop new products and services (Kollmann et al. 2023). Overall, the AI market is distributed globally, with the US, Asia, and Europe being key players (Kollmann et al. 2023): "The US has traditionally been a leader in AI, but Asia is catching up fast, especially China. Europe also has some strong AI companies and startups, but is not as strong in this area as the US and Asia. The relative strength of the US can also be seen in the AI companies already listed on the stock exchange, which have once again managed to transform technology into marketable products and go public with this added value.
"Artificial Transformation" refers to an ongoing and far-reaching process of change in society, economic and politics based on Artificial Intelligence (AI), that has a fundamental impact on information, communication and transactions between the players involved and, in the tension between humans and machines, leads to a new understanding and behavior in the social, economic, and political spheres of life.
Artificial Transformation
After presented the fundamentals of Artificial Intelligence (AI) for the transformation of business processes and models, and even entire companies, and discussed the associated forms of AI use, from Artificial Intelligence Exploitation to Artificial Intelligence Exploration to Artificial Intelligence Disruption, we can now present the Artificial Transformation Matrix (see Figure), which visualizes these relationships. The characteristics of the various forms of AI Transformation for overarching "Artificial Management" are characterized on the basis of the axes "Business Relevance" and "Level of Creativity" (Kollmann 2025 and Kollmann/Kollmann 2025):
Artificial-Intelligence-Exploitation
In the area of Exploitation, AI is primarily used to improve existing systems and processes, use resources more efficiently, and maximize short-term profits, rather than to search for new innovations or markets. The point of reference here is therefore the existing business, for which most of the data is already available internally. AI, such as machine learning, data analysis, and automation, offer enormous potential in this area to specifically exploit the already known information/data (provided it is actually available or has been digitized) and associated strategies, and to maximize the economic benefits for the company.
Artificial-Intelligence-Exploration
In the field of Exploration, AI is primarily used to discover new opportunities, tap into unknown markets or technologies, develop new business models, and gain groundbreaking insights in various scientific disciplines. The point of reference is therefore the as-yet non-existent innovation business, for which not all data is yet available. AI then helps to analyze the more or less available internal data, enrich it with further external data, generate hypotheses, recognize unknown patterns, and drive innovation, which brings long-term benefits for companies, researchers, and creative fields.
Artificial-Intelligence-Disruption
While Exploitation and Exploration still have clear links to a company's previous activities, either in improving its existing business or developing an innovative one, disruption involves completely new approaches with no such links. In the area of Disruption, AI will be used to manage entire companies and organize their future development at all levels. With their ability to automate processes, analyze huge amounts of data, develop new business models, and drive innovative technologies, AI-Systems could replace traditional working methods and human management.
Artificial Business
Now that the basic possibilities for using Artificial Intelligence (AI) for the three central platforms of Digital Business (Digital Procurement, Digital Shop, Digital Marketplace) have been outlined, we can present the Artificial-Business-Matrix (see Figure), which visualizes these relationships. The influences of AI on the three platforms that also make a Digital Business an Artificial Business are characterized for overarching "Artificial Management" using the axes "Decision/Support" and "Standardization/Individualization" (Kollmann/Kollmann 2025):
Artificial-Intelligence-Purchase
The integration of Artificial Intelligence (AI) into Digital Procurement is fundamentally changing the way companies in the business-to-business (B2B) sector purchase (or will purchase). AI technologies enable the automation and optimization of purchasing processes, improve the decision-making basis for purchasers through data-driven analyses, and increase efficiency in the supply and logistics chain. The focus is particularly on the areas of supplier search, supplier selection, negotiation, order processing & logistics, and warehouse and process organization. Numerous practical examples already demonstrate the potential of AI in these areas.
Artificial-Intelligence-Sales
The integration of Artificial Intelligence (AI) into a Digital Shop fundamentally changes the way companies sell (or will sell) in the business-to-consumer (B2C) sector. AI technologies enable a personalized customer approach, optimize processes along the customer journey, and improve the management of a Digital Shop in terms of control and design. The focus here is particularly on product analysis, demand analysis, sales and payment processes, customer acquisition and reten-
tion, and dynamic pricing. Numerous practical examples already demonstrate the potential of AI in these areas.
Artificial-Intelligence-Trading
The integration of Artificial Intelligence (AI) into a Digital Marketplace fundamentally changes the way marketplace operators, as well as suppliers and consumers in B2C, B2B, and C2C sectors, operate (and will operate in the future). The use of AI on these platforms improves both the operational processes and the strategic management of the marketplace operator with regard to its coordination tasks. The focus is particularly on the areas of optimized marketplace design, in-depth process and product analysis for bringing together suppliers and consumers, precise analysis of marketplace participants and their needs, an efficient matching process between supply and demand, and associated dynamic price coordination between of both sides of the market.
Artificial Leadership
In summary, Artificial Leadership will play an essential role for companies and organizations in these areas in the foreseeable future in order to remain successful in the future. However, this requires continuous adaptation and development of the necessary digital algorithms of a machine leadership authority (AI) in order to meet the requirements and changes of the digital world. And one point should be reiterated at this point: without a digital or data strategy, there can be no AI strategy in leadership. The first step must come before the second because AI is dependent on data. With regard to the illustration (3 cases with Artificial-Autocratic-Leadership), a distinction can now be made—as already indicated above—with the help of the axes "Authority" and "Leadership Tasks" (see Figure):
For further information on the topic of Artificial Leadership, please visit our website: www.artificial-leadership.com
Human-Digital-Leadership
Digital Leadership describes a management style in which a person not only wants the Digital Transformation (Digital Mindset), but also has the necessary knowledge for this Digital Transformation (Digital Skills) and can finally also consistently implement the resulting measures within the framework of the Digital Transformation (Digital Execution).
Artificial-Intelligence-Leadership
Artificial Leadership describes a style of leadership in which a machine (in the best case as an AI) not only obtains the required data via a Big Data approach (Digital Source), but can also evaluate it independently with the associated algorithms via a Deep Learning approach (Digital Analysis) and finally the resulting results are also accepted as an order for action by humans via a Data-Driven approach (Digital Decision).
Artificial-Autocratic-Leadership
In this case, there could also be "Artificial-Autocratic-Leadership" in the future, where AI simply decides everything in the company independently (up to and including Artificial Intelligence Disruption)! This would then apply not only to the development of a (real/digital) existing and/or innovative business, but also to the entire corporate structure and strategy, as well as the entire organization and the people who work in it.
Accordingly, the aim of this book is to highlight the tension between deployment and replacement and thus the areas of application and interaction between man and machine in management. In this context, the various theoretical and practical influences will also be discussed in order to identify the associated need for research and action. This is exemplified in a subject area that - as already indicated above - is directly affected because data already plays a significant role here today and is already available: The "Digital Transformation" for existing and "Digital Innovation" for new business models and processes. The evolution here will be immediate and rapid, and, accordingly, will essentially turn Digital Business with the associated Digital Leadership into Artificial Business with Artificial Leadership. We aim to present an initial approach to this topic, incorporating conceptual considerations by outlining the various developments and potential applications of Artificial Intelligence (AI) in operational and strategic management.
Note: The book draws on various previous works, such as Kollmann, T. (2025): What is Artificial Entrepreneurship?; Kollmann, T./Kollmann, K./Kollmann, N. (2023): Artificial Leadership; Kollmann, T. (2022): Digital Business and Kollmann, T. (2022): Digital Leadership. However, the relevant content has explicitly been expanded to include the influences of AI, and current references have also been added in order to expand on the previous findings.