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Organizational theory has evolved from the classical school of the industrial age—where humans operated technical systems—to the neo-classical school of the digital age—where people collaborate facilitated by technical systems. Despite contemporary organizations exhibiting cyborglike characteristics through intricate human–machine relationships, organizational theory remains fundamentally human-centric. The emergence of Non-Human Knowledge Workers challenges this view.
Organizational theory has evolved from the classical school of the industrial age—where humans operated technical systems—to the neo-classical school of the digital age—where people collaborate facilitated by technical systems. Despite contemporary organizations exhibiting cyborglike characteristics through intricate human–machine relationships, organizational theory remains fundamentally human-centric. The emergence of Non-Human Knowledge Workers challenges this view. To see how, we may view the organization through three lenses: as a network (how we collaborate), as a system (how we adapt), and as technology (how we can design based on these new principles).
Traditional hierarchies and static structures have been made redundant as digitalisation necessitates self-organization, cross-functional collaboration, and real-time adaptation. Wirearchy—a conceptualization of organizations as networks built around purpose and knowledge—epitomizes the new model of organizational design where distributed power and digital communication enable knowledge-driven, decentralized decisions.
“Emergent networks matter more than prescribed ones.”
Within any organization there are two networks: prescribed (documented roles and processes) and emergent (the informal interactions and relationships that happen in the white space of the organizational chart). Especially in knowledge-intensive companies, emergent networks matter more than prescribed ones.
Where do AI systems fit in? As AI transitions to Non-Human Knowledge Workers, it shifts from hard infrastructure owned by IT to soft infrastructure led by HR. Soft infrastructure is the non-physical support that makes organizations work. It can be illustrated as five layers: Individual (cognition and behaviour), Interpersonal (interactions and relationships), Group (roles and team dynamics), Organizational (values, policies, structure), and Societal (the wider cultural and regulatory context). These layers are about to be inseparable from the question of AI.
In this sense, NHKWs differ from other AI agents in that they are full participants in the organization’s inner workings, including the white spaces of the organizational chart.
Both humans and organizations can be described as information and communication systems—gathering, processing, and exchanging information for various purposes. The term Artificial Information System (AIS) distinguishes engineered systems from natural ones. Systems Theory provides the framework for managing the complexity of such systems, whether biological, social, technological, or a combination thereof, by understanding the interdependent parts that make up a whole.
“This decentralization enhances communication efficiency and capacity to handle complex problems.”
An agent is any entity capable of acting autonomously within a specific context, physical or digital. Multi-Agent Systems (MAS) comprise multiple agents—human or artificial—that work to solve tasks that individual agents could not. While single-agent systems are simpler to design and manage, MAS offer several advantages in complex and distributed problem solving.
Since multi-agent systems perform tasks in parallel they work more efficiently than single-agent systems handling tasks sequentially. Additionally, dynamic task allocation and distributed knowledge enable agents to coordinate tasks, adapt to new information and make local decisions without relying on a central decision maker. This decentralization enhances communication efficiency and capacity to handle complex problems. As a result, MAS excel in both collaborative and competitive contexts.
In collaborative contexts, agents with complementary skills cooperate to achieve common objectives, forming communities that enhance collective performance. In competitive contexts, agents model complex group behaviors with simple interactions leading to sophisticated emergent phenomena. In both contexts, it is an evolutionary process that can lead to novel strategies unattainable by single-agent systems.
Organizational technology is a conceptual framework describing the actors, tasks, expertise, methods, and systems by which inputs are transformed into goods and services in the process of value creation.
Tasks refer to activities involved in the value transformation process. Discrete units of value creation—the steps that convert inputs to outputs (research, drafting, reviewing, deciding, fulfilling). Tasks are the “work surface”.
Techne (expertise) refers to specialized knowledge and skills possessed by individual employees and the organization as a whole, which is required to carry out certain tasks. The know-how—tacit and explicit—required to execute tasks to standard. Techne lives in people’s heads, in models’ learned weights, and in organizational norms.
Techniques (methods) refers to the codified ways techne is applied: procedures, checklists, playbooks, prompts, evaluation rubrics, QA gates. Techniques make expertise portable and improvable.
Technical Systems refers to physical and non-physical tools part of the enabling environment. These systems route information and actions to the right actors at the right time. Technical Core typically refers to the actors that perform the organization’s essential work.
“Organizations no longer need to be designed around human limitations, instead organizations may be reimagined as ecosystems that mobilize the collective intelligence of humanity and technology.”
The convergence of technological breakthroughs in Non-Human Knowledge Workers transitions AI from Technical Systems, associated with hardware and software tools, to Technical Core, previously associated with humans. As the technical core becomes a design parameter organizations no longer need to be designed around human limitations, instead organizations may be reimagined as ecosystems that mobilize the collective intelligence of humanity and technology.
