Introduction

In recent years, a digital logic has been gaining ground within the personnel management system. Decisions are increasingly made on the basis of data, while part of managerial functions is being transferred to algorithms.

The changes taking place require a reconsideration of conventional ideas about the role of both the human being and HR within an organization. To understand the scale of these changes, it is important to trace how personnel management has developed as a whole.

For this purpose, I have compiled a table showing how the role of the human being in the organization and approaches to managing people have changed over time. For the analysis, I decided to take the period from 1970 to 2030.

Why does the timeline begin with the 1970s?

In my view, this was the period when personnel management began to emerge as a separate function within the organization and started to take shape as an independent field.

So, before us is Table 3.It reflects how the key elements of managing people in an organization changed across different periods of time.

The table includes the following parameters:

• HR status within the organization;
• Control;
• Evaluation of work;
• Employee autonomy;
• Measurement of results;
• Organizational environment;
• Management automation;
• Role of the human being in the organization.

Each of the selected parameters, in my view, characterizes a specific aspect of the management system and makes it possible to trace how it changed at different stages.

The first parameter - HR status within the organization — will be examined separately, as it reflects the place of this function within the overall management system. The remaining parameters will be grouped into several thematic blocks and examined in their interconnection.

Parameter No. 1: HR Status in the Organization

This indicator demonstrates what position the personnel management function occupied and what role it played in managerial decision-making over time.

Chronological Dynamics

The 1970s - The Era of Record-Keeping

The personnel department performs purely administrative functions: registration, documentation, and disciplinary control. It does not participate in decision-making and effectively acts as a recorder of management decisions.

The 1980s - Implementation of Standards

Headcount planning and productivity control are added to basic record-keeping. The HR function becomes involved in labor cost control but does not yet influence the overall management strategy.

The 1990s - Operational Department

Amid economic instability, HR gains operational status, focusing on hiring, onboarding, and layoffs. The department handles tactical, hands-on tasks aimed at maintaining organizational stability during periods of turbulence.

The 2000s - The Service Model

The growth of corporations and their territorial expansion create a need for unified processes. In response to this demand, leading consulting firms develop management standards and metric systems, which are then transferred to HR specialists within large corporations. Gradually, these metrics spread more widely and are adopted by other organizations. HR systematizes recruitment, evaluation, and motivation, but continues to operate within a pre-defined, top-down model. As a result, the service status of the HR function becomes firmly established.

The 2010s - Strategic Partnership

The concept of the “strategic HR role” emerges. Organizational design, corporate culture, and employee engagement are added to the existing set of HR functions.

HR is invited to participate in discussions of strategic issues. However, in most companies, this status remains largely declarative — a partnership on paper rather than in actual decision-making.

The 2020s - Digital Transition

The pandemic triggered accelerated digitalization and sharply changed work formats. HR was forced to move rapidly toward remote and hybrid models of work.

The importance of management systems, data analysis, and digital coordination tools increased significantly. HR moved into a predominantly digital environment.

2026 - The New Reality

The idea of “strategic partnership” loses much of its practical meaning. Part of the HR function is transferred to algorithms.

HR returns to a service role — but now it serves not only the managerial level, but also the organization’s digital systems.

Conclusions

What conclusions can be drawn from this point?

First, management methods within organizations change, and only after that does the HR function transform — not the other way around. HRM within an organization adapts to its existing management model.

When management is built on control and regulations, the personnel management department performs administrative tasks. As management moves toward more complex models based on data, processes, and algorithms, the role of HRM changes as well.

The influence of the personnel management function depends on how deeply it is embedded in the organization’s existing management system and how actively it participates in its implementation.

Why educational programs in human resource management continue to promote the postulate of HR’s primacy over other organizational functions is a question to which I have no answer.

Block 1. Work Organization

Next, we proceed to analyze the parameters reflecting the organization of work. This block includes:

• control;
• the focus of performance evaluation;
• the degree of employee autonomy.

These indicators, in my view, clearly demonstrate a unified management system. Their integration into a single block is necessary to show the complex transition of the organization from direct administrative management of people to remote management of processes.

Parameter No. 2: Control

Control mechanisms show how task execution is monitored within an organization. The table shows a clear transition from physical observation — timesheets and visual checks — to digital and predictive monitoring.

While control was previously exercised directly by a supervisor, today it is implemented through information systems. The organization records not only activity in task trackers and KPI fulfillment, but also behavioral patterns.

By 2026, control becomes predictive: the system analyzes the course of task execution and forecasts potential failures before they occur. It is expected that by 2030 we will transition to automatic coordination, where control will become “invisible” because it will be fully integrated into work tools and algorithms.

Parameter No. 3: Focus of Performance Evaluation

This indicator reflects what exactly the organization considers a “result” in a given period.

Based on the table, we can see how the focus shifts from tracking time — Input — and output volumes — Output — to financial indicators, and then to the quality of processes and created value.

In the modern model of the 2020s, the priority becomes cognitive focus: what is evaluated is no longer merely mechanical execution, but the employee’s mental effort and intellectual contribution.

By 2030, the primary object of evaluation will be systemic contribution — the direct impact of an employee’s actions on the aggregate result and overall resilience of the organization.

For example, the work of a logistics specialist is evaluated not only by the number of shipments, but also by the ability to optimize routes and reduce delays. In the future, the object of evaluation will be how effectively they can prevent systemic failures across the company’s entire value chain.

Parameter No. 4: Employee Autonomy

This parameter reflects the degree of human agency in decision-making.

The path of employee autonomy has gone through a cycle from rigid job instructions in the 1970s to a high level of self-organization in the 2010s. However, in the modern digital environment, the vector has changed. Full freedom has been replaced by hybrid autonomy, followed by the “algorithmic corridor” — activity within boundaries set by the system, that is, autonomy within an AI system.

In the future, agency will cease to belong exclusively to the human. The system will define the boundaries of the permissible, creating a kind of “digital cage,” where decisions are made by the human only from the options proposed by the system.

Ultimately, the system is likely to gradually appropriate the right to define the field of choice. In this model, the human will be assigned the role of an executor within predefined AI parameters.

Conclusions for the Block

1. From Actions to Processes: Work organization is shifting from the control of physical actions to the management of the course of the process. Control is becoming permanent yet invisible.
2. Preemptive Logic: The system records not only the final result, but also the entire dynamics of its formation, allowing the system to operate preemptively.
3. The Reversal of Autonomy: The trend toward maximum employee autonomy is being replaced by the rigid frameworks of algorithms. Freedom of choice formally remains, but the set of available options is now formed and distributed by the digital system, which is gradually appropriating part of human agency. 

Block 2. Management Infrastructure

This block includes the parameters of result measurement and management automation. These indicators reflect the mechanisms and tools through which management is implemented within an organization.

Parameter No. 5. Result Measurement

The essence of this indicator lies in understanding what results employees produce and how well these results correspond to the assigned tasks.

From the table, we can see that at the early stages, results were recorded through paper timesheets, work orders, stopwatches, and accounting records. With the development of digital tools, measurement began to shift into information systems: access control systems (ACS), ERP platforms, trackers, Big Data, and AI analytics.

A transition has occurred from point-based recording to continuous process measurement. This makes it possible to manage the achievement of results more effectively: to identify deviations at early stages, eliminate bottlenecks, and ensure predictability.

Today, evaluation is based on data collected continuously through Big Data and AI analytics. In 2026, end-to-end real-time analytics becomes part of the management infrastructure. This makes it possible to see an objective picture of employees’ work and to make proactive decisions quickly.

By 2030, data will transform from a recording tool into a management mechanism through the implementation of automated self-adjusting evaluation. In this model, the system will identify deviations in real time and partially correct the process without direct human involvement.

Parameter No. 7. Level of Management Automation

Automation is necessary to reduce the dependence of decisions on the human factor. Its goal is to ensure fast, accurate, and predictable management.

The table shows how management is gradually shifting from the human being to digital infrastructure. Management automation has evolved from manual data collection, then through basic computing systems, to local PC databases, end-to-end IT record-keeping, and cloud ecosystems.

In the 2020s, predictive AI dominates, and by 2026, the stage of autonomous AI agents begins. By 2030, automation will presumably reach the level of end-to-end digital integration.

The role of the supervisor changes accordingly. They are no longer the sole source of management decisions.

Automation gradually withdraws part of the management function and transfers it to algorithms. As a result, control, deviation analysis, partial process correction, and decision support will increasingly be carried out not directly by the supervisor, but through digital infrastructure.

Key Conclusions

• The transition to continuous monitoring has become a fundamental shift from one-time recording of results to constant measurement of the process. By 2030, evaluation will presumably become self-adjusting and will correct work in real time.
• Management is shifting from the supervisor to digital infrastructure and autonomous AI agents. The role of the manager is transforming: they will manage people less and less, and increasingly focus on configuring the management system.
• Infrastructure automation and end-to-end digital integration will be aimed at creating an uninterrupted management environment. The system will independently identify deviations, reduce the influence of the subjective factor, and strive to maximize the predictability of business processes.

Block 3. Social Indicators

This block includes parameters such as the internal organizational environment and the place of the human being within it.

Parameter No. 6. Internal Organizational Environment

The organizational environment describes the conditions in which people work: how decisions are made, how power is distributed, and how interaction among participants in the organization is structured.

We can see that the environment does not remain unchanged: over time, there is a transition from a rigid hierarchical and bureaucratic structure to more flexible, project-based, and network forms of organization.

Since the 2020s, the organizational environment has become more distributed: work is increasingly less tied to a specific location, while interaction is increasingly carried out through digital systems. By 2026, the environment becomes decentralized: tasks are distributed through platforms, coordination is increasingly implemented through digital tools, and formal structure gradually gives way to more flexible, project-based forms of interaction.

By 2030, a new digital reality is expected to emerge, in which processes, data, and participant interaction are integrated into a single system. Within this system, participants will interact continuously, while changes in processes will be recorded and adjusted in real time.

Parameter No. 8. The Role of the Employee in the Organization

As the internal environment of the organization changes, so does the position of the human being within it. The evolution of the employee’s role reflects a transition from the mechanical execution of tasks to the inclusion of the human being in the digital environment as a functional element.

Let us distinguish three key stages of this transformation:

1. The industrial and post-industrial era - the human being as a resource

At the initial stages, the employee is a staff unit and an executor of functions. Their role is reduced first to the production of goods, then to ensuring profit, and later to the accumulation of individual knowledge. At this stage, the human being still remains an autonomous subject whom the organization hires for their competencies and talent — that is, as human capital.

2. The transitional period, the current stage - the human being as a process

With the development of flexible, project-based structures, the focus shifts: the employee ceases to be merely an “owner of competencies” and becomes an active participant in processes. What comes to the forefront is not their knowledge, skills, and abilities, but their capacity to interact within a network.

3. The new digital reality, 2030 - the human being as an element of the network

At this point of transformation, the human being is viewed as a carrier of a behavioral model. The system analyzes and directs their actions, turning personal experience into a predictable algorithm. There is a transition from subjectivity to the status of an element of the digital network. The employee gradually loses part of their autonomy and becomes a functional node that generates data and operates within a self-regulating ecosystem.

Key Conclusions

• By 2030, a technological replacement of the managerial hierarchy may take place: part of the power previously attached to positions and management levels will shift to a digital ecosystem operating in real time.
• There is also a gradual alienation of subjectivity. The human being ceases to be viewed as “capital” and is increasingly described as a functional element of the network, whose experience is translated into data and behavioral models.
• The priority of the system over the individual is increasing. Efficiency is now measured not only by personal results, but also by the quality of a person’s integration into a behavioral model.
• The price of such manageability is the growing dependence of employees on data generated by the system and the gradual atrophy of independent thinking, professional judgment, and the ability to make decisions.

Final Summary

We have completed the review of the dynamics of changes in the organizational management system from 1970 to 2030. As a summary, the following can be highlighted:

1. Primacy of the system. The influence of the personnel management service is determined by the extent to which it is embedded in the organization’s existing management system. First, management methods within organizations change, and only then does the HR function transform — not the other way around.
2. From control to process. Work organization is shifting from the recording of isolated actions to continuous management of how work is performed and how results are formed. Control becomes invisible, but total.
3. The decline of autonomy. The trend toward maximum employee freedom is being reversed. Absolute independence is replaced by an “algorithmic corridor” or a “digital cage.” The boundaries of decision-making are set by the system: it defines the permissible options for action and choice scenarios, gradually appropriating part of human agency.
4. Data as an actor. By 2030, data ceases to be merely a report. It turns into an active tool that corrects work in real time. The management infrastructure shifts into an “autopilot” mode, minimizing the human factor.
5. Transformation of leadership. The role of the manager changes radically: from a “controller,” they become an “architect of algorithms.” They no longer manage people directly, but instead design the logic of the system and monitor the algorithms themselves.
6. Evaluation through the “digital footprint.” For the employee, this transformation means an environment in which their professionalism is evaluated exclusively through digital indicators, while the space for initiative is replaced by a rigid scenario.
7. Technological replacement of power. By 2030, the classical hierarchy may be definitively replaced by a digital ecosystem operating in real time.
8. Alienation of agency. There is a transition from the human being as “capital” to the human being as a functional node of the network. Personal experience is translated into an algorithm, while the priority of the system over the individual becomes absolute.
9. The price of alienation of agency. The result of total efficiency is employees’ growing dependence on data generated by the system and the gradual atrophy of independent thinking, judgment, and the ability to make decisions.

This article reflects the author’s professional position and interpretation of changes in the personnel management system. It does not claim to be the ultimate truth, but rather represents an attempt to develop an analytical model based on the author’s experience, observation of management practices, and analysis of long-term trends.

References and Theoretical Framework

1. Taylor, F. W. The Principles of Scientific Management. New York: Harper & Brothers, 1911.
2. Weber, M. Economy and Society: An Outline of Interpretive Sociology. Berkeley: University of California Press,1978. Original work published in 1922.
3. Drucker, P. F. The Practice of Management. New York: Harper & Row, 1954.
4. Ashby, W. R. An Introduction to Cybernetics. London: Chapman & Hall, 1956.
5. Becker, G. S. Human Capital: A Theoretical and Empirical Analysis, with Special Reference to Education. New York: National Bureau of Economic Research, 1964.
6. Mintzberg, H. The Structuring of Organizations: A Synthesis of the Research. Englewood Cliffs: Prentice-Hall, 1979.
7. Castells, M. The Rise of the Network Society. Oxford: Blackwell Publishers, 1996.
8. Ulrich, D. Human Resource Champions: The Next Agenda for Adding Value and Delivering Results. Boston: Harvard Business School Press, 1997.
9. Kaplan, R. S., Norton, D. P. The Balanced Scorecard: Translating Strategy into Action. Boston: Harvard Business School Press, 1996.
10. Davenport, T. H., Harris, J. G. Competing on Analytics: The New Science of Winning. Boston: Harvard Business School Press, 2007.
11. Lee, M. K., Kusbit, D. Metsky, E. Dabbish, L. “Working with Machines: The Impact of Algorithmic and Data-Driven Management on Human Workers.” In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, 1603–1612, 2015.
12. Rosenblat, A., Stark, L. “Algorithmic Labor and Information Asymmetries: A Case Study of Uber’s Drivers.” International Journal of Communication, 10, 3758–3784, 2016.
13. Zuboff, S. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. New York: PublicAffairs, 2019.
14. Kellogg, K. C., Valentine, M. A., Christin, A. “Algorithms at Work: The New Contested Terrain of Control.” Academy of Management Annals, 14(1), 366–410, 2020

Additional Sources: Regional Context / CIS

15. Щедровицкий, Г. П. Избранные труды. Москва: Школа культурной политики, 1995.
16. Пригожин, А. И. Методы развития организаций. Москва: МЦФЭР, 2003.
17. Базаров, Т. Ю., Еремин, Б. Л., ред. Управление персоналом: учебник для вузов. 2-е изд., перераб. и доп. Москва: ЮНИТИ, 2002.
18. Кибанов, А. Я., ред. Управление персоналом организации. Москва: ИНФРА-М, 1997.
19. Клейнер, Г. Б. “Системная экономика как платформа развития современной экономической теории.” Вопросы экономики, №6, 2013, с. 4–28.