TY - GEN

T1 - Modeling of Autonomous Artificial Intelligence Systems for Corporate Management

AU - Романова, Анна Сергеевна

PY - 2026/7/2

Y1 - 2026/7/2

N2 - The paper presents a reference model for development and implementation of autonomous artificial intelligence systems for corporate management. The primary categories of autonomous systems in corporate management are multifunctional command centers, personalized virtual systems, and humanoid robots. In the near future, we can expect the emergence of new systems that combine digital factories with virtual agents or humanoid robots. The proposed model is based on computational law (law as computation), a dedicated operational context (separate from the general operational context used by humans), controlled generation of synthetic training data, machine learning algorithms, and game theory. The model justifies the development of an ethical and legally compliant operational digital brain at an industrial scale. The model allows testing the hypothesis of “machine consciousness continuity,” where blockchain stores accumulated experience and digital twins retain internal models of reality. To the best of the author’s knowledge, this is the first model to implement a dedicated operational context for autonomous artificial intelligence systems. The model establishes a connection between the informed consent of all stakeholders interested in the corporation’s success and the practical implementation of artificial intelligence systems.

AB - The paper presents a reference model for development and implementation of autonomous artificial intelligence systems for corporate management. The primary categories of autonomous systems in corporate management are multifunctional command centers, personalized virtual systems, and humanoid robots. In the near future, we can expect the emergence of new systems that combine digital factories with virtual agents or humanoid robots. The proposed model is based on computational law (law as computation), a dedicated operational context (separate from the general operational context used by humans), controlled generation of synthetic training data, machine learning algorithms, and game theory. The model justifies the development of an ethical and legally compliant operational digital brain at an industrial scale. The model allows testing the hypothesis of “machine consciousness continuity,” where blockchain stores accumulated experience and digital twins retain internal models of reality. To the best of the author’s knowledge, this is the first model to implement a dedicated operational context for autonomous artificial intelligence systems. The model establishes a connection between the informed consent of all stakeholders interested in the corporation’s success and the practical implementation of artificial intelligence systems.

KW - Androids

KW - Artificial intelligence

KW - Autonomous systems

KW - Computational law

KW - Corporate governance

KW - Ethics

KW - Game theory

KW - Synthetic data

UR - https://www.mendeley.com/catalogue/8a5bece4-a657-34c7-bbf1-765863ebe43f/

U2 - 10.1007/978-3-032-24784-1_26

DO - 10.1007/978-3-032-24784-1_26

M3 - Conference contribution

SN - 978-3-032-24783-4

T3 - Advances in Science, Technology & Innovation

SP - 257

EP - 261

BT - Artificial Intelligence Powered Ethical Systems, Generative Intelligence, and Societal Futures. AIR 2024.

PB - Springer Nature

CY - Cham

Y2 - 10 December 2024

ER -