JAKARTA, JurnalPost.com — The presence of artificial intelligence or artificial intelligence (AI) in the workplace has raised major questions about the future of management. As technology becomes increasingly capable of scheduling, monitoring work, analyzing data, and assisting in decision-making, do organizations still need managers?
This question cannot be answered simply by looking at AI's ability to replace administrative tasks. The ongoing shift touches on more fundamental issues: how organizations divide labor, distribute authority, and coordinate human activity.
An INSEAD study on Organizational Technology (OrgTech) shows that technology does not just change how work is done, but also influences the design of the organization itself. The role of the manager, long synonymous with supervision and control, is facing new demands.
These findings align with various reports from McKinsey, Gartner, and the World Economic Forum (WEF) showing that AI usage continues to expand. However, increased technology adoption has not always resulted in comparable organizational effectiveness or financial gains.
In other words, the main challenge for organizations is not merely determining which tasks can be delegated to machines, but redesigning the relationship between humans, technology, and decision-making processes.
When Technology Changes How Organizations Coordinate
For years, managers were considered essential to ensure work proceeded according to plan. Managers divided tasks, monitored performance, resolved interpersonal issues, and relayed information from leadership to teams.
However, some of these functions can now be supported by technology.
Collaboration tools like Jira, Asana, and Slack allow team members to track project progress, share information, and resolve coordination issues without always relying on direct instructions from superiors.
AI development expands these capabilities. Systems no longer just record work; they can help identify delays, route information to relevant parties, and provide action recommendations.
In an INSEAD Knowledge article on September 24, 2026, Phanish Puranam, along with Piyush Gulati and Arianna Marchetti, explained that OrgTech can influence both vertical and horizontal coordination.
In vertical coordination, technology enhances a manager's ability to oversee and control work. In horizontal coordination, technology helps employees collaborate directly without excessive intervention from superiors.
Both can lead to leaner organizational structures. However, the consequences are not always the same.
Organizations that use AI to strengthen oversight may become increasingly centralized. Conversely, organizations that leverage it to support collaboration have the potential to grant employees greater autonomy.
Therefore, the use of technology does not automatically result in a more democratic or effective organization. The final outcome depends on how the technology is implemented.
Middle Managers Face Pressure
These changes in work methods are beginning to affect organizational demand for management positions.
Gartner, in projections published in October 2024, estimated that by 2026, about 20 percent of organizations will use AI to streamline structures, with a reduction of more than half of middle management positions in organizations that implement these changes.
This figure is a projection, not evidence that such large-scale reductions have already occurred universally.
Nevertheless, the trend of companies reducing management layers is already visible in several labor studies.
Korn Ferry, through its Workforce 2025 report, found that 41 percent of surveyed workers stated their organizations had cut management layers. Some 37 percent of respondents felt directionless due to the reduced presence of managers.
These findings highlight an issue often overlooked in organizational restructuring.
Reducing the number of managers may lower operational costs. However, when coordination, coaching, and communication functions are not well redesigned, organizations risk facing internal confusion.
Administrative work may be offloaded to technology, but the need for leadership, conflict resolution, and human development does not automatically disappear.
AI Usage Grows, But Results Are Uneven
A McKinsey survey titled The State of AI in 2026: On the Road to ROI published on August 25, 2026, shows an increase in AI usage within organizations.
Nearly nine out of ten respondents reported routine AI use in at least one business function. Meanwhile, 44 percent stated their organizations had scaled AI implementation across the enterprise, up from 38 percent the previous year.
The use of AI agents is also growing faster in large companies.
Some 40 percent of respondents from organizations with annual revenues exceeding $1 billion reported that they had increased the use of AI agents in one or more business functions. In smaller organizations, the figure reached 22 percent.
However, this increased usage has not been fully matched by financial success.
McKinsey found that only 37 percent of respondents attributed some impact on operating profit or earnings before interest and taxes (EBIT) to AI usage.
In fact, the group of high-performing organizations reporting an AI impact of at least 5 percent on EBIT, accompanied by significant benefits, included only about 6 percent of respondents.
This data reveals a gap between the technology's ability to improve individual productivity and its success in generating change at the organizational level.
The issue is not just whether a company has used AI, but whether the technology truly makes work processes more effective.
Managers Have the Opportunity to Become Teachers and Human-AI Coordinators
Amid these changes, INSEAD offers a perspective on the potential emergence of managerial functions that differ from conventional patterns.
In a discussion on OrgTech published by INSEAD Knowledge on August 20, 2026, Phanish Puranam proposed two potential developments for the manager's role. Both remain conceptual possibilities, not yet established forms of future organizations.
First, the manager as an educator or teacher within the organization.
The manager's function is no longer limited to ensuring work is completed on target, but evolves into helping team members build critical thinking skills, evaluate information, and make decisions.
As routine work is increasingly assisted by machines, the value of human leadership may lie in its ability to develop the capacity of others.
Managers need to ensure team members are not only able to use AI but also understand the results provided, recognize errors, and question technological recommendations when necessary.
Second, the manager as a coordinator of human-AI relationships.
In this function, the manager is responsible for managing the division of labor between humans and intelligent systems.
Managers must understand which decisions can be automated, when an issue requires human judgment, and what mechanisms are needed when a system does not produce an adequate decision.
This function demands new skills in technology governance, decision-making, risk management, and cross-functional coordination.
These changes show that the future of management cannot be prepared for solely through digital tool training. Organizations also need to strengthen leadership competencies and human judgment.
Critical Thinking Skills Become Increasingly Important
Increasing reliance on AI carries the risk of weakening employee skills if technology use is not accompanied by competency development.
Gartner estimates that by 2026, the decline in critical thinking skills due to generative AI use will drive 50 percent of global organizations to implement non-AI-assisted skills assessments.
This projection highlights the importance of ensuring that human capabilities do not become entirely dependent on automated systems.
Meanwhile, the Future of Jobs Report 2025 from the WEF estimates that about 39 percent of the skills used by workers will change or experience a decline in relevance by 2030.
Some 63 percent of employers also identify the skills gap as a major barrier to business transformation.
Amid these developments, technological skills such as AI, data analysis, and cybersecurity are expected to be in higher demand.
However, human competencies such as analytical thinking, creativity, leadership, resilience in the face of change, and the ability to work together remain crucial.
This serves as a reminder that human resource development must not stop at the ability to operate technology.
Organizations must also maintain employees' ability to think independently, make ethical judgments, and understand the impact of decisions on others.
AI Success Is Determined by Organizational Design
Many organizations begin AI transformation by purchasing software or implementing automation systems. However, technological sophistication does not always guarantee success.
McKinsey research in 2026 found that nearly three-quarters of high-performing organizations had fundamentally redesigned workflows after implementing AI.
Conversely, only about a quarter of respondents from other organizations reported similar changes.
This difference shows that successful AI implementation is closely related to an organization's ability to adjust business processes, responsibility structures, and decision-making mechanisms.
Gartner also warns that more than 40 percent of agentic AI projects have the potential to be canceled by the end of 2027 due to high costs, unclear business benefits, or weak risk controls.
Thus, AI should not be treated as a single solution for all management problems.
Technology needs to be integrated with organizational needs, work culture, and clear accountability mechanisms.
Without such processes, automation can actually create new problems, ranging from decisions that are difficult to justify to a decrease in employee trust in the system.
Revisiting Peter Senge's Learning Organization
Management transformation in the AI era can also be analyzed through the concept of the learning organization developed by Peter Senge.
Through five disciplines of organizational learning, Senge emphasizes the importance of the ability of individuals and groups to continue learning, understand system interconnections, and build a shared vision.
This concept remains relevant as work relationships begin to involve intelligent technology.
In the aspect of mental models, organizations need to review the assumption that all activities must be directly supervised by humans.
In the aspect of personal mastery, individuals are required to continuously develop competencies, including the ability to understand and evaluate AI usage.
Meanwhile, systems thinking invites organizations to view the relationships between humans, technology, rules, and business processes as a unified whole that influences one another.
The discipline of shared vision becomes important so that AI transformation is not only understood as a leadership efficiency agenda but also as a common goal.
As for team learning , it emphasizes the need for dialogue and collective learning to find the most effective collaboration patterns between humans and machines.
These five disciplines provide a framework for understanding that AI transformation is not just a technological change, but a comprehensive organizational learning process.
The Future of Work Is Not as Simple as Humans Versus Machines
Concerns about job losses due to AI need to be placed in the context of broader labor market changes.
The WEF, in its Future of Jobs Report 2025 estimates that various technological, economic, demographic, and environmental changes could create 170 million new jobs by 2030, while displacing about 92 million jobs.
Overall, these projections result in a net addition of about 78 million jobs. This figure includes various global transformation factors, not just the impact of AI.
On the other hand, a 2026 McKinsey survey found that 39 percent of respondents expected AI to cause workforce reductions in their organizations within the following year.
However, only 14 percent of respondents from AI-using organizations reported that the technology had contributed to a decrease in the total number of workers in the previous year.
The difference between expectations and realization shows that the impact of AI on employment is still evolving and does not always proceed as predicted.
In facing these changes, upskilling is one of the key strategies. The WEF notes that 85 percent of surveyed employers plan to prioritize workforce upskilling in the 2025–2030 period.
This means that organizations should not just consider the efficiency of worker numbers. They also need to design transition processes that allow the workforce to adapt to new roles.
Redefining the Meaning of Leadership
The development of AI brings organizations to the need to review the meaning of leadership.
If technology is capable of taking over some reporting, scheduling, and monitoring activities, then a manager's value can no longer be measured solely by the amount of administrative work they successfully control.
The manager's role is increasingly related to the ability to build trust, develop team competencies, resolve complex issues, and ensure organizational decisions maintain a clear direction and responsibility.
AI usage also needs to be balanced with governance that ensures humans retain the ability to judge, correct, and be accountable for decisions.
In this context, organizations that successfully adapt are not necessarily those with the most advanced technology or the leanest structures.
The advantage may actually arise from the ability to combine technological efficiency with human knowledge, creativity, and judgment.
Ultimately, AI does not immediately eliminate the need for managers. However, this technology demands that organizations rewrite managerial functions, competencies, and responsibilities.
The future of management is not just a matter of determining who is superior between humans and machines, but how both can work in a system that is complementary, adaptive, and remains human-oriented.
References:
INSEAD Knowledge. (2026). How Technology Is Changing the Work of Management; Beyond Automation: How AI Is Changing Management.
McKinsey & Company. (2026). The State of AI in 2026: On the Road to ROI.
Gartner. (2024–2026). Publications regarding predictions on organizational structure changes, critical thinking skills, and agentic AI governance.
World Economic Forum. (2025). The Future of Jobs Report 2025.
Korn Ferry. (2025). Workforce 2025: Power Shifts.
Senge, P. M. (1990). The Fifth Discipline: The Art and Practice of the Learning Organization.
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