Artificial Management—The Influence of Artificial Intelligence on Digital Business and Digital Entrepreneurship

Dear Colleagues,

The rapid advancement of algorithmic performance and the exponential growth of data availability—both within and beyond corporate boundaries—are fundamentally redefining the role of Artificial Intelligence (AI) in organizations. AI is no longer confined to being a supportive analytical tool; it is increasingly evolving into an autonomous decision-making authority within managerial contexts. These developments are particularly visible in digitalized business environments, where humans and machines directly interact in data-driven processes. As a consequence, digital management is progressively transforming into Artificial Management, thereby reshaping how organizations design, execute, and control strategic and operational activities in the era of Digital Transformation.

Against this backdrop, Artificial Management can be defined as follows (Kollmann/Kollmann 2025): In the context of Digital Transformation, 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, organization, delegation, coordination, employee management and control.

Practical manifestations of Artificial Management are already emerging:

• When AI systems proactively predict customer needs and trigger automated fulfillment processes without explicit orders (Artificial Analytics). Example: If Amazon deploys AI systems to proactively ship products to customers based on predictive analytics—before an explicit order is placed—this represents Artificial Management in the form of Artificial Analytics.
• When an AI system is formally appointed to executive functions within a company, controlling processes and issuing instructions (Artificial Leadership). Example: When NetDragon Websoft appoints an AI system as the head of the company, responsible for managing processes and issuing instructions, this illustrates Artificial Leadership.
• When AI dynamically determines individualized willingness-to-pay in real-time digital pricing systems (Artificial Business). Example: If Booking.com uses AI in customer dialogues to dynamically determine maximum willingness to pay, this exemplifies Artificial Business.
• When AI autonomously develops new product ideas or business concepts, we enter the realm of Artificial Entrepreneurship, where human creativity is partially or entirely substituted by algorithmic generation.
• These developments signal the emergence of a new dimension in corporate organization, management logic, and business model innovation. As data increasingly forms the basis for strategic and operational decision-making, AI algorithms become embedded in production systems, transaction processes, governance structures, and entrepreneurial activities.

Objectives of the Special Issue

This Special Issue aims to explore the theoretical foundations, empirical evidence, and managerial implications of Artificial Management in the context of Digital Business and Digital Entrepreneurship. Specifically, we seek to examine how AI technologies are transforming managerial authority, decision architectures, organizational design, business processes, and entrepreneurial dynamics. Contributions may adopt conceptual, empirical, methodological, or interdisciplinary approaches and may address micro-, meso-, or macro-level perspectives.

We invite the submission of high-quality, original research contributions addressing (but not limited to) the following themes:

• Artificial Transformation of Digital Business: Structural shifts in digital business models through AI integration; AI-driven platform governance; algorithmic ecosystems; data-based competitive advantage.
• Artificial Analysis of Digital Business Processes: AI-driven analytics in strategic and operational management; predictive and prescriptive decision systems; algorithmic performance measurement and control.
• Artificial Business Processes in Procurement, Sales, and Trading: Intelligent supply chain automation; dynamic pricing mechanisms; AI-driven negotiation systems; automated transaction management.
• Artificial Leadership with AI as a (Co-)CEO: Algorithmic governance structures; human–AI hybrid leadership models; AI as decision authority; ethical, legal, and organizational implications of AI-led firms.
• Artificial Entrepreneurship with AI as a (Co-)Founder: AI-generated opportunity recognition; automated venture creation; AI-based business model innovation; implications for entrepreneurial cognition and creativity.

Both quantitative and qualitative approaches, as well as mixed-methods research, design science, computational studies, and forward-looking conceptual frameworks are encouraged. All submissions must provide rigorous theoretical grounding and clear implications for both research and practice.

Concluding Perspective

Artificial Management is not merely a technological extension of digitalization; it represents a structural shift in the locus of managerial authority. The transition from human-centric management to hybrid or AI-dominant governance systems challenges foundational assumptions of leadership, responsibility, creativity, and strategic control. This Special Issue aims to establish Artificial Management as a distinct research field within digital business and digital entrepreneurship. By bringing together interdisciplinary perspectives, we seek to develop robust theoretical foundations, empirical insights, and normative frameworks that help scholars and practitioners understand and shape the future of management in the age of Artificial Intelligence.

Literature:

Kollmann, T. & Kollmann, K. (2025): Artificial Management: The Evolution for Corporate Management, netCAMPUS/netSTART 2025.

Kollmann, T. (2025). What is Artificial Entrepreneurship? The Influence of AI for the Creative Destruction of Schumpeter. Research & Development, 6(1), 7-29. https://doi.org/10.11648/j.rd.20250601.12.

Kollmann, T., Kollmann, K., & Kollmann, N. (2023): Artificial Leadership: Digital Transformation as a Leadership Task between the Chief Digital Officer and Artificial Intelligence, in: International Journal of Business Science and Applied Management , Vol. 18, Nr. 1, S. 76-95.https://doi.org/10.69864/ijbsam.18-1.172.

Kollmann, T., Kollmann, K. & Kollmann, N. (2023): Artificial Leadership: The Revolution for Corporate Management, netCAMPUS/netSTART 2023.

Kollmann, T., Kleine-Stegemann, L., de Cruppe, K. & Then-Bergh, C. (2022): Eras of Digital Entrepreneurship. Business & Information Systems Engineering, Vol. 64, 15–31 (2022). https://doi.org/10.1007/s12599-021-00728-6.

Prof. Dr. Tobias Kollmann
Guest Editor

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• artificial management
• artificial leadership
• artificial business
• artificial entrepreneurship
• artificial transformation
• AI-driven decision-making
• AI-driven platform governance
• AI-based business model innovations
• AI-driven management processes
• AI-driven entrepreneurship processes