Overlapping Technological Propagations: How Industrial Change Reaches the Systemic Level

1. Introduction

Technological change is commonly interpreted through inventions, general-purpose technologies, industrial revolutions or techno-economic paradigms. These approaches identify historical clusters of innovation, pervasive infrastructures and the complementary organizational and institutional adjustments associated with major transformations [1,2,3,4,5]. Sociotechnical-transition research has further shown that technologies, practices, institutions and infrastructures evolve together and that transitions may involve several interacting regimes and systems [6,7,8].

These traditions explain different dimensions of technological change. General-purpose technology theory addresses pervasiveness and complementary innovation. Diffusion research investigates the spread of adoption across populations of potential users [9,10,11]. Studies of organizational complementarity explain why technical adoption often requires changes in skills, procedures and decision structures [12,13]. Production-network research shows how local disturbances can generate aggregate consequences through intersectoral connections [14,15]. Multi-system transition studies examine competition, integration and spillovers among simultaneously changing sociotechnical systems [16,17,18].

Taken separately, however, these approaches do not generally provide a causal account that begins with a change in the technical delegability of a function, follows the transformation of its consequences across organizational and economic levels, and explains how a later change can alter an earlier transformation that has not yet stabilized. This is the problem addressed in this article.

The analysis begins from the function rather than from the technology as an indivisible object. Section 2 defines functions independently of the human, organizational or technical arrangements through which they are performed.

Technological development changes the boundary between functions that require existing forms of human or organizational execution and functions that can be technically delegated. Task-based research has examined related changes in the allocation of activities between labour and capital, including substitution, complementarity and the creation of new tasks [19,20,21]. Yet technical possibility does not by itself constitute either organizational or systemic transformation. Its consequences depend on how the capability is adopted, combined with complementary assets and incorporated into a wider structure of interdependencies.

When an organization reallocates a function, it may change costs, timing, scale, information flows, competencies and decision rights. These changes can affect suppliers, customers, competitors, workers, infrastructure providers and regulators. Their consequences may therefore reach actors that neither introduced nor directly adopted the originating technology. The effect experienced by each actor also need not reproduce the effect experienced by the original adopter.

This article calls the transmission and transformation of such consequences systemic propagation. Unlike diffusion, it extends beyond adoption: the population of adopters and the population of affected actors need not coincide.

A change reaches the systemic level when its consequences become part of the constraints, opportunities or decision conditions encountered by multiple interdependent actors, including non-adopters.

Research on interdependence and production networks shows why systemic consequences cannot be inferred from adoption alone. Their reach and form depend on complementarities, feedback, the position of affected actors and the configuration of their connections [14,15,22,23,24]. Technological propagation has an additional property: it can modify organizational boundaries, network connections, standards and decision structures. It does not merely travel through a system; it can transform the system through which it travels.

Propagation also requires time. New capabilities therefore often emerge while the consequences of earlier innovations remain unfinished. Propagations overlap when a new change in functional delegability enters before an earlier propagation has relatively stabilized and causally alters its trajectory. The later propagation may amplify, redirect, combine with, absorb or inhibit the earlier one.

Artificial intelligence makes this analytical problem particularly visible. AI capabilities are entering organizations whose restructuring around computing, digital networks, cloud infrastructures and platforms remains incomplete. Rapid AI adoption can therefore coexist with incomplete organizational and systemic transformation: adoption measures who is using the capability, whereas propagation analysis traces how its consequences alter organizations, infrastructures, markets and institutions, including conditions faced by non-adopters. Understanding AI-driven transformation therefore requires not only examining the diffusion or direct effects of AI, but also explaining how its consequences interact with technological and organizational transformations already under way.

Technological propagations are also influenced by events and processes that do not originate in the same functional change. Wars, natural disasters, climate change, migration, labour scarcity and industrial policies can modify the resources, connections, rules and incentives through which a propagation unfolds. The article refers to these influences as trajectory-modifying forces. Their inclusion makes explicit that technical capability opens possible trajectories but does not autonomously determine their selection or systemic outcome.

1.1. Conceptual Method and Analytical Strategy

The article uses mechanism-based conceptual synthesis. It brings adjacent literatures on technological diffusion, general-purpose technologies, organizational complementarity, production networks and sociotechnical transitions into a common analytical sequence. The purpose is not to aggregate their conclusions into a comprehensive review, but to identify an explanatory gap between functional technical possibility and system-wide consequences and to construct the minimum concepts required to connect those levels [25].

The argument proceeds through analytical differentiation and mechanism reconstruction. It distinguishes adoption from consequences, identifies the stages and feedbacks through which consequences change form, and derives a typology of interactions between unfinished propagations. Historical episodes are used as plausibility illustrations rather than as tests. The resulting propositions are therefore intended to guide subsequent historical, comparative, organizational and network-based investigation, not to establish universal empirical regularities in advance.

The article does not propose a general mathematical model or another comprehensive framework of technological change. It develops a mechanism-based conceptual explanation. Section 2 restates the unitary interpretation of the Industrial Revolution adopted here. Section 3 distinguishes propagation from diffusion, technological waves and sociotechnical transitions. Section 4 reconstructs the recursive mechanism connecting functional delegability to systemic conditions. Section 5 examines overlapping propagations, trajectory-modifying forces and a compact historical illustration. Section 6 discusses relationships to established approaches, implications and limitations. Section 7 concludes.

2. The Industrial Revolution as a Unitary Process

This article adopts a unitary interpretation of the Industrial Revolution as the long-run expansion of technically delegable functions. It does not deny the historical significance of steam power, electricity, mass production, electronic computing, digital networks or artificial intelligence. Nor does it reject periodizations based on technological revolutions and techno-economic paradigms [1,3,4,5]. It treats these configurations as distinguishable phases within a continuing process rather than as entirely separate industrial revolutions.

The unity of that process does not derive from the continuous development of one technology or from an invariant institutional structure. Steam engines, electric motors, computers and artificial-intelligence systems differ radically in their material operation and immediate applications. At a more abstract level, however, they participate in a common historical movement: each expands the range of transformations that can be assigned to technical systems and thereby modifies the allocation of activity among people, machines and organizations.

2.1. Function and Delegability

A function is defined here as a delimited transformation in which an admissible set of inputs is processed, under specified conditions, to produce a required output. The definition deliberately abstracts from the actor or mechanism performing it. The same function may be executed by an individual, distributed among organizational roles, embedded in a mechanical device or implemented computationally.

For example, quality control may be performed by a worker, divided between production and inspection roles or assigned partly to sensors and software. The analytical unit may also be a closely connected set of functions: distinguishing them serves causal reconstruction and does not imply that they become delegable separately in practice.

This mechanism-independent definition makes it possible to compare technologies that would otherwise appear incommensurable. A mechanical loom, an electric motor, an accounting application and a machine-learning system do not perform the same operations. Each nevertheless changes production by making one or more functions technically executable through a different arrangement.

Functional delegability indicates that the technical execution of a function has become possible without preserving its previous allocation. It does not imply complete automation or the elimination of human participation. A function may be only partially delegated, may require supervision or may remain embedded in a larger process containing non-delegable components.

The concept is related to task-based analysis. Autor et al. [19] distinguish activities according to their susceptibility to codification and computerization, while Acemoglu and Restrepo [20,21] examine displacement from some tasks and reinstatement through the creation of others. Functional delegability operates at a different analytical level: it identifies a technical possibility before determining whether a function will be assigned to labour, capital or a hybrid arrangement.

2.2. From Technical Possibility to Organizational Reallocation

A demonstrated capability does not prescribe how an organization will use it. Adoption depends on costs, complementary assets, available competencies, regulation, routines and expectations. A technically delegable function may remain humanly executed, be partially reassigned or be reorganized in several competing ways.

Propagation requires organizational activation: adoption, incorporation into a process or a credible anticipatory response that changes decisions before widespread use. Functional delegability is therefore an originating technical possibility, not a sufficient cause of systemic propagation. Technical demonstration alone opens a possibility but does not yet transmit consequences through the system.

When delegation occurs, its effects rarely remain confined to the function directly affected. Related procedures must be redesigned, responsibilities redistributed and information formatted or transmitted differently. New functions may be created to integrate, supervise or maintain the technical system. Delegation can replace existing execution, complement it, increase scale or frequency, change organizational location, enable a previously impracticable activity or create supervisory and coordinative functions.

Research on complementarities shows that technology, work organization, skills and decision structures often need to change together [12,13,26]. David’s analysis of electrification illustrates that replacing a central power source did not immediately produce the full benefits later associated with electric production. Those benefits required a reorganization of factory layouts, machinery and workflows [27].

Functional delegability is therefore the origin of a potential transformation; organizational reallocation is its first realization. Neither is sufficient to establish that systemic change has occurred.

2.3. From Organization to System

Organizations are connected through productive, competitive, informational, infrastructural and institutional relationships. When functional reallocation changes costs, timing, scale, quality or information flows, connected actors may face new conditions even if they do not adopt the originating technology.

A system is defined here as the analytically delimited configuration of interdependent actors, organizations, infrastructures and institutional arrangements within which these consequences are traced. It may correspond to a production network, sector, labour market, infrastructure or broader economic configuration. In empirical applications, this analytical perimeter must be specified before assessing whether propagation has reached the systemic level. Systemic therefore describes a relation within a specified perimeter, not merely a large scale; global reach is a possible result, not part of the definition.

Systemic significance is not simply a function of scale or adoption rate. A large internal reorganization may remain organizationally bounded. Conversely, a limited innovation introduced at a strategically connected point may generate extensive effects. Production-network research demonstrates that aggregate consequences depend partly on the position of affected actors and the structure of their interdependencies [14,15].

A change becomes systemic when its consequences alter constraints, opportunities or decision conditions shared by a plurality of interdependent actors. The unity proposed here is analytical rather than teleological. It lies in the continuing expansion and reallocation of technically delegable functions, while historical discontinuities arise from the technologies involved, the functions they affect and the systems through which their consequences unfold.

3. Diffusion, Transition and Propagation

Technological waves, diffusion processes, sociotechnical transitions and systemic propagations describe different dimensions of technological change. A technological wave identifies a historically recognizable concentration of technologies, infrastructures, investment patterns and organizational principles. Diffusion describes the spread of adoption. A sociotechnical transition concerns the reconfiguration of technologies, practices, institutions and actors. Propagation concerns the causal movement and transformation of consequences.

3.1. Diffusion and Propagation

Diffusion research investigates who adopts an innovation, when adoption occurs and which incentives, information channels or constraints determine its rate [9,10,11,28]. Adoption is often necessary for an innovation to produce significant effects, but it does not identify the boundaries of those effects.

Diffusion concerns the spread of adoption. Propagation concerns the transmission and transformation of consequences.

An innovation can diffuse without producing equivalent systemic transformation. Conversely, a capability adopted by relatively few but strategically positioned actors may change prices, standards, access conditions or infrastructure requirements for an entire sector. The population of adopters and the population of affected actors therefore need not coincide, and diffusion and propagation need not proceed at the same speed.

Table 1. Diffusion and systemic propagation. 

Analytical dimension	Diffusion	Systemic propagation
Primary object	Adoption or use of a technology	Consequences generated by a change in functional delegability
Principal question	Who adopts, when and at what rate?	How are consequences transmitted, transformed and made systemic?
Relevant population	Potential and actual adopters	Adopters and non-adopters affected through interdependencies
Transmission	Spread of a comparatively identifiable innovation	Causal sequence whose effects can change form across actors and levels
Systemic threshold	No necessary threshold beyond adoption	Shared constraints, opportunities or decision conditions are altered
Possible divergence	Wide diffusion with limited restructuring	Limited adoption with extensive systemic consequences

Table 1. Diffusion and systemic propagation. 

Analytical dimension	Diffusion	Systemic propagation
Primary object	Adoption or use of a technology	Consequences generated by a change in functional delegability
Principal question	Who adopts, when and at what rate?	How are consequences transmitted, transformed and made systemic?
Relevant population	Potential and actual adopters	Adopters and non-adopters affected through interdependencies
Transmission	Spread of a comparatively identifiable innovation	Causal sequence whose effects can change form across actors and levels
Systemic threshold	No necessary threshold beyond adoption	Shared constraints, opportunities or decision conditions are altered
Possible divergence	Wide diffusion with limited restructuring	Limited adoption with extensive systemic consequences

3.2. Definition and Analytical Boundary

Systemic propagation is the process through which the direct effects of a change in functional delegability are transmitted and transformed across organizational and economic interdependencies, eventually altering shared constraints, opportunities or decision conditions for multiple actors.

The object being propagated is neither the technology itself nor an invariant effect. It is a sequence of consequences. A cost reduction for an adopter may become competitive pressure for another firm, a change in tasks for workers, additional demand for infrastructure or a new problem for regulators.

Not every consequence extending beyond the original adopter constitutes systemic change. The decisive transition occurs when consequences cease to be merely an internal option of the adopter and become part of the environment encountered by other actors. Systemic does not mean universal, irreversible or beneficial. Effects may remain uneven, be subsequently redirected and generate concentration, bottlenecks or vulnerability as well as productivity and opportunity.

3.3. Propagation, Waves and Transitions

Waves describe historically recognizable configurations; propagations describe unfolding causal processes. A wave can contain several propagations originating in different functions, while a propagation can cross the conventional boundary between waves because its organizational or institutional consequences continue after a new configuration emerges.

The multi-level perspective explains transitions through interactions among niches, regimes and broader landscape conditions [6]. Multi-system studies examine competition, integration, symbiosis and spillovers among simultaneously changing systems [7,16,17]. Deep-transition research extends the analysis to transformations involving multiple sociotechnical systems and shared rules over long periods [8,29].

Propagation does not replace these objects of analysis. Transition studies ask how sociotechnical configurations change; propagation analysis asks how consequences originating in a functional change travel across and between those configurations.

3.4. Relative Stabilization

A propagation may be considered relatively stabilized when the principal organizational arrangements, infrastructures and rules generated in response to the originating functional change are no longer undergoing substantial reconfiguration because of that change. Relative stabilization is compatible with continued use, incremental improvement and residual effects. A propagation remains unfinished when its principal complementarities, standards, infrastructures or organizational arrangements are still being substantially revised.

4. The Recursive Mechanism of Systemic Propagation

Systemic propagation begins when a change in functional delegability is incorporated into an organizational arrangement and generates consequences extending beyond it. The mechanism contains five components: change in functional delegability; organizational reallocation; transmission across interdependencies; transformation of consequences; and emergence of systemic conditions.

These components do not form a rigid chronological sequence. Feedback connects them, and a propagation may weaken or stop before reaching the systemic level. Existing systemic conditions influence which technical possibilities are adopted, while acute perturbations, structural pressures and intentional interventions may affect every component.

For analytical purposes, propagation can be observed at four connected levels: (1) the function whose technical delegability changes; (2) the organization or production process in which execution is reallocated; (3) interorganizational, sectoral and infrastructural networks through which consequences are transmitted; and (4) systemic and institutional conditions shared by multiple actors. These levels identify locations of transformation, not a one-way ladder: responses at the network or institutional level can feed back into organizational choices and the further development or use of the originating capability.

4.1. Organizational Reallocation and Transmission

When an organization adopts a capability, it reallocates execution among human, technical and organizational components. Because functions are interdependent, the reallocation usually modifies more than the directly delegated activity. It can change operations, decision rights, competencies, information, production location and the functions required for supervision and coordination.

Organizational reallocation then changes relations with other parts of the system. Effects may be transmitted through production, competition, labour markets, information flows, infrastructure, standards, finance and institutions. Production-network research demonstrates that aggregate effects depend on the position of affected actors, network topology and availability of substitutes [14,15].

4.2. Transformation, Feedback and Systemic Conditions

The consequence experienced by a connected actor is not necessarily the consequence experienced by the adopter. A reduction in production costs may become price pressure for competitors, differently timed demand for suppliers, reduced margins for intermediaries, new competency requirements for workers or a regulatory problem. The consequence changes form during transmission.

A consequence becomes systemic when it changes conditions shared by multiple interdependent actors. Indicators include reorganization by non-adopters, new standards becoming conditions of participation, infrastructure becoming a widespread competitive constraint, changing skill requirements, redesigned regulation and redirected investment.

The components of the mechanism influence one another. Organizational experience may stimulate further technical development; infrastructure constraints may redirect applications; and regulation may prevent some reallocations while encouraging others. The same technical capability can therefore produce different consequences in differently connected systems, and limited adoption at a strategically positioned point can have effects disproportionate to its initial scale. Research on feedback and interdependence helps characterize these possibilities [22,23,24,30], without treating industrial change as equivalent to a formal network model.

4.3. Modification of the Propagation Structure

Technological propagation differs from transmission through an unchanged network because innovation can alter the structure carrying its consequences. A platform may remove intermediaries, create dependencies and centralize information. An artificial system may change organizational hierarchies and the distribution of expertise. A production technology may replace suppliers, generate interfaces or relocate activities.

Technological propagation does not merely travel through a system; it can modify the system through which it travels.

Not every propagation reaches the systemic level. It can remain localized or be interrupted by missing investment, insufficient infrastructure, incompatible standards, regulation, competing technologies or another process that changes conditions before stabilization.

5. Overlapping Propagations

Systemic propagation requires time. Organizations must discover viable applications, develop competencies and redesign connected functions. Infrastructure, regulation, education and standards may adjust more slowly still. Before these changes have stabilized, further capabilities can enter the system.

Propagations overlap when a new change in functional delegability enters a system before an earlier propagation has relatively stabilized and alters its trajectory. The relevant unit is not the relationship between two technologies in isolation, but the effect exerted by one unfolding propagation on another.

5.1. Why Overlap Is Structurally Likely

Technical capabilities can develop faster than organizations restructure around them; organizations can adjust faster than shared infrastructure and institutions; and different propagations move through different channels. Software-based capabilities may spread rapidly, while transformations dependent on physical infrastructure require longer periods. The chronological sequence of invention therefore need not correspond to the sequence of systemic realization.

Technological acceleration must also be distinguished from systemic acceleration. A system may acquire capabilities at increasing speed while becoming less able to stabilize the corresponding organizational arrangements.

5.2. Five Effects on an Unfinished Propagation

A later propagation can alter an unfinished propagation through five analytically distinguishable interaction modes, summarized in Table 2.

These analytical interaction modes are neither mutually exclusive nor exhaustive and are not intended as a complete taxonomy of technological interactions. They identify the dominant mode affecting a specified consequence, channel, group of actors and temporal phase, not the state of the entire system. A later propagation may amplify an infrastructure while inhibiting applications built upon it, and its dominant effect may change over time.

5.3. Relationship to Multi-System Research

Transition studies examine how configurations of technologies, actors, practices, infrastructures and rules are reconstituted, and multi-system research considers directionality, transition phase and competitive or complementary relationships [18]. A propagation is a different analytical object: it is a causal trajectory originating in a change in functional delegability. It may cross several sociotechnical systems, while several propagations may interact within the same system. The contribution developed here is to trace such a trajectory across organizational and systemic levels and to explain how it can alter an earlier trajectory before relative stabilization.

5.4. Contextual Forces and Propagation Trajectories

An unfinished propagation may be altered not only by another technological propagation but also by trajectory-modifying forces: acute events, structural pressures or intentional interventions that change the resources, constraints, connections or incentives through which it unfolds.

Acute perturbations include wars, earthquakes, extreme weather events, pandemics, financial crises and supply interruptions. Natural disasters affecting suppliers can impose substantial losses on connected firms, particularly when inputs are difficult to replace [31]. Evidence from the Great East Japan Earthquake shows how a geographically concentrated event can propagate through supply chains and produce aggregate consequences [32].

Structural pressures include climate change, demographic ageing, migration, persistent labour scarcity, urbanization and changes in energy or resource availability. Their cumulative effects progressively alter the conditions under which functional delegation becomes relevant.

Intentional interventions include industrial policies, subsidies, regulation, public investment, standards, migration policies, trade restrictions and educational programmes. They can change resources, connections, rules, incentives and expectations. Industrial policy may finance complementary infrastructure, redirect a trajectory towards selected applications, facilitate combinations or inhibit alternatives [33].

War combines acute perturbation and intentional intervention. It can interrupt supply chains while directing research, procurement and investment. United States wartime R&D during the Second World War continued to shape inventive activity and the postwar innovation system [34].

Environmental pressures can influence the direction of innovation. Energy prices redirect inventive activity towards efficient technologies [35], while environmental policies and relative returns influence whether innovation develops along cleaner or more damaging trajectories [36].

Labour scarcity and migration reveal recursive interaction. Labour availability can affect adoption of labour-substituting technologies [37], while demographic ageing and shortages have been associated with robot adoption and automation-related innovation [38]. The termination of the Bracero programme contracted agricultural labour supply and stimulated related innovation [39].

Including these forces avoids technological determinism. Functional delegability opens possible trajectories; it does not determine which one will occur. Realized propagation is coproduced by organizational choices, interdependencies, resources, institutions, policies and environmental, demographic or geopolitical pressures.

5.5. A compact Historical Illustration

The sequence connecting electrification, electronic computing, digital networks and artificial intelligence provides a compact illustration. It is not an empirical test, a complete reconstruction or an attempt to exemplify every interaction mode in the typology.

Electrification changed the delegability and spatial organization of mechanical functions, but its systemic consequences required factories to be redesigned around distributed power, new workflows and production control [27]. Electronic computing entered an economy whose reorganization around electricity and mass production had not produced a final or uniform configuration. Computers delegated calculation and data processing, while their effects depended on standardizing information, redesigning administrative procedures and developing competencies.

Digital networks subsequently changed the consequences of computing. Isolated processing became connected capacity. Networking amplified computing, combined processing with communication, redirected digitization towards coordination and absorbed many earlier functions into networked services and platforms. Networks also created new intermediaries and dependencies and altered the system through which computing propagated.

Artificial intelligence is entering this incompletely stabilized digital configuration. Many organizations have not finished redesigning processes around existing information systems, cloud infrastructure and platforms. AI nevertheless expands the range of analytical, linguistic, predictive and coordinative functions that can be delegated. Recent evidence reinforces the importance of separating rapid adoption from completed systemic transformation: generative AI has diffused quickly, while observed organizational effects include task reorganization, new oversight and integration activities, and uneven or still-limited aggregate labour-market effects [40,41]. This pattern is consistent with earlier work emphasizing that AI may, like other general-purpose technologies, require complementary investments in processes, skills and organizational capital before its broader productivity effects are realized [42].

Its propagation may amplify the value of data and computing infrastructure; redirect digitization from procedural automation towards probabilistic generation and decision support; combine models, platforms, computing and organizational data; absorb established software functions into broader systems; and inhibit earlier investments by making applications or competencies obsolete before expected benefits are realized.

The sequence demonstrates why technological eras do not imply completed transformations. Computing developed through infrastructures inherited from electrification. Networks changed computing before its consequences had stabilized. Artificial intelligence now acts on unfinished propagations of computing and networking.

6. Discussion

The proposed account shifts attention from technologies and historical periods to causal trajectories generated by changes in functional delegability. Its contribution is not to replace established theories but to connect insights developed at different analytical levels.

6.1. Relationship to Established Approaches

General-purpose technology theory explains pervasiveness, improvement and complementary innovation [2,43]. Propagation analysis examines the process separating technical potential from systemic realization.

Technological-revolution theories identify coherent historical configurations [3,4,5]. Propagation distinguishes the visible configuration from causal processes contributing to it. A wave can contain several propagations, and a propagation can cross wave boundaries.

Task-based approaches explain substitution, complementarity and new tasks [19,20,21]. Functional delegability identifies the prior technical possibility; propagation follows consequences beyond the employment relationship and adopting organization.

Production-network and systemic research shows how aggregate consequences depend on interdependence, actor position and network structure [14,15,22,23,24]. The present account adds that propagation can change the structure carrying its consequences.

Sociotechnical-transition research examines configurations of technologies, practices, institutions and infrastructures and already recognizes multi-system interaction. The addition proposed here is a functional and causal connection among an originating change, organizational realization, systemic effects and an earlier unfinished trajectory.

6.2. Analytical and Empirical Implications

Systemic propagation separates adoption from consequences, connects analytical levels, treats the transformation of effects as part of the mechanism and introduces temporal interaction. It also yields three empirically examinable expectations.

First, systemic reach should depend less on adoption counts alone than on the position of adopters, the substitutability of affected inputs and the topology of interdependence. Second, the result of overlap should depend on when the later capability enters and whether its complementary assets are compatible with those of the earlier propagation. Third, contextual forces should alter trajectories through observable changes in resources, connections, rules or incentives rather than by operating as unexplained external shocks.

For artificial intelligence, this distinction has an immediate implication: adoption rates alone are an incomplete indicator of systemic impact. AI can alter the value and direction of earlier digital investments, reshape complementary tasks and organizational arrangements, and change conditions faced by non-adopters through competition, infrastructure, standards and labour markets. Assessing AI-driven transformation therefore requires tracing propagated consequences as well as measuring diffusion.

These expectations suggest a common empirical protocol: identify the originating function and organizational reallocation; trace interdependencies and transformed consequences; determine whether shared systemic conditions emerge; and locate other active propagations and contextual forces. Historical case studies can reconstruct sequences, organizational comparisons can examine divergent reallocations, and network analysis can trace transmission channels and systemic reach.

6.3. Organizational and Policy Implications

Rapid improvement in technical capabilities does not guarantee coherent organizational adaptation. Successive innovations may repeatedly change the target of reorganization and reduce the value of complementary investments that have not matured.

For organizations, the relevant decision is not simply whether to adopt a technology, but how the new capability interacts with a reorganization already under way. Decision makers should identify which complementary investments have not yet matured and how the new capability changes their value, compatibility or direction. Contextual conditions may also be temporary or persistent.

For policymakers, adoption rates provide an incomplete measure. Policies modify propagation by changing resources, connections, rules and expectations. Their effects may include amplification and combination, but also lock-in, inhibition of alternatives and premature obsolescence.

6.4. Scope and Limitations

The account is conceptual rather than mathematical. It offers a compact historical illustration rather than an empirical test. The five effects are neither mutually exclusive nor necessarily exhaustive. The boundary between organizational and systemic change remains partly dependent on the scope of inquiry. Trajectory-modifying forces also constitute a broad category whose three classes operate through different mechanisms.

Not every change in functional delegability produces systemic propagation. Capabilities may remain unused, localized or blocked. Explaining selection requires comparative investigation. The article therefore provides a circumscribed mechanism-based account rather than a comprehensive framework or new periodization of industrial history.

7. Conclusion

The article has proposed interpreting the Industrial Revolution as a unitary historical process based on the continuing expansion of technically delegable functions. This interpretation places distinct technological configurations within a common process in which the allocation of functions among people, organizations and technical systems is repeatedly transformed.

A change in functional delegability is only the origin of a potential transformation. Its consequences become systemic through organizational reallocation, transmission across interdependencies and transformation as different actors respond. Propagation differs from diffusion because it concerns consequences, including those experienced by non-adopters.

The process is recursive and open. Technological propagation can modify the connections and decision structures through which it proceeds, and its consequences depend on the interdependencies and timing involved. Its trajectory is also affected by wars, natural disasters, climate change, migration, labour scarcity and industrial policies.

Because propagation requires time, a new capability frequently enters before an earlier transformation has stabilized. The interaction may amplify, redirect, combine with, absorb or inhibit the previous trajectory.

The account does not replace theories of general-purpose technologies, technological revolutions or sociotechnical transitions. It operates at a different scale. Waves identify historical configurations; transitions describe changes in sociotechnical systems; propagation reconstructs a causal movement from functional delegability to systemic conditions and across interacting unfinished trajectories.

Artificial intelligence makes this problem especially salient because it is propagating through economic and organizational structures that are still being transformed by earlier developments in computing, networking and platformization.

What appears retrospectively as a succession of industrial revolutions may therefore be understood as the visible historical pattern produced by multiple propagations in an open and changing system. The relevant question is not only which technology follows another, but how a new functional capability enters a system already in transformation—and how technological interactions, political choices, structural pressures and unexpected shocks change what that capability ultimately becomes.