Human as a decision maker in the digital era Free

This issue of The Learning Organization contains a variety of papers related to organizational learning and learning organizations. Their topics include information technology (IT) adoption and digital transformation (DX) (Bagchi & Sharma, 2025; Chen, Wang, & Seidle, 2025; Ribeiro et al. 2025). sustainability (Showkat & Nagina, 2025), organizational citizenship behavior (OCB; Bhardwaj, Sharma, & Savita, 2025; Tran, 2025) and inter-organizational learning (Lørum, Skyvulstad, Eri-Montsma, & Smith, 2025). These may seem to address completely different issues. However, these studies all imply the importance of the role of people − managers, leaders and members − in various situations of organizational management. In other words, each paper explicitly or implicitly reveals the roles and functions of people who proactively engage in organizational learning. From this, it can be read that the importance of people is not decreasing, but rather increasing, as a result of the progress of DX and the development of artificial intelligence (AI).

In the following, a summary and individual implications of each of the above papers will be discussed. Finally, integrated implications regarding the role of people in contemporary and future management in the “digital era” will be presented.

Various futures are predicted regarding the development and spread of digital technology and AI. On one hand, some predict that AI will reach “singularity” and surpass humans. There is also the view that AI will take away human jobs. On the other hand, others believe that AI will not take away human jobs, but only change the position and role of humans in society. In a similar event in history, for example, when office automation led to the widespread use of personal computers (PCs), some predicted that many office workers would lose their jobs. In reality, however, we witnessed that people’s tasks only shifted to other roles that utilize PCs. In parallel, the quantity and quality of output required increased as PCs improved job efficiency. As a result, no one now claims that PCs have increased unemployment.

Ribeiro, Melo, Muniz, de Souza, & Canever (2025) address changes in a workplace in the transition from Industry 4.0 (I4.0) to Industry 5.0 (I5.0). I4.0 has promoted digitization in the workplace and contributed to improved productivity. I5.0 is oriented toward building a more sustainable, human-centered and resilient industry while improving sustainability. What lies ahead is the improvement of quality of life (QOL) and social responsibility (Ribeiro et al., 2025). In other words, while I4.0 is technology-oriented, I5.0 is more value-oriented (Ribeiro et al., 2025).

Ribeiro et al. (2025) examined a case of the implementation of I4.0 and I5.0 in a Brazilian glass manufacturer. The findings revealed that even as digital transformation (DX) progressed in I5.0 implementation, various workers played important roles and were respected at key positions in the workplace. Namely, while DX changed work practices, the significance of humans did not diminish. Rather, human knowledge and its sharing became more important. In particular, the importance of workers’ tacit knowledge was strongly recognized in the case examined by Ribeiro et al. (2025). Notably, digital technology was not well suited to handling tacit knowledge compared to explicit knowledge. The words “Assembly lines are still sociotechnical systems” (Ribeiro et al., 2025, p. 385) are striking.

DX not only makes business operations more efficient but also brings opportunities for companies and society, such as the emergence of new business models. In this process, the importance of humans as holders of tacit knowledge will increase even further.

Chen et al. (2025) conducted an extensive survey on digital transformation (DX) adoption in Taiwanese companies and found that “management innovation” contributes to promoting DX adoption and digital maturity. Here, management innovation consists of three functions: nurturing a corporate culture encouraging trial-and-error, creating digital-technology-related job functions and setting up a new division to oversee the transformation. While all of these are important, this Implications for Practitioners (IfP) focuses on the culture that encourages trial and error.

Implementing DX is a kind of organizational learning in that it changes existing organizational behavior (Huber, 1991). In this process, the digital technology to be implemented is not perfect from the beginning and requires adaptation to the context. Failure and negligence of the adaptation process create serious problems for the organization concerned (Bagchi & Sharma, 2025).

In other words, realizing digital maturity requires experiential learning (Kolb, 1984) through trial and error and feedback (Chen et al., 2025). Moreover, the function of trial and error is not limited to promoting learning in question. Organizational culture that encourages trial and error mitigates members’ anxiety about failure (Chen et al., 2025), which will encourage experiential learning in the future.

When implementing digital technology, it is very rare that the technology perfectly fits the practical context right from the start. In many cases, trial and error is essential for adaptation. Hence, in terms of encouraging trial and error, DX is strongly influenced by culture (Chen et al. (2025), which seems to be far from digital technology.

Bagchi & Sharma (2025) examined the case of a steel blade manufacturer’s failure to implement enterprise resource planning (ERP). ERP is a system to manage a company’s business resources (human resources, material, money and information) in an integrated manner to improve business efficiency. ERP aims to centralize data that each unit (finance, sales, inventory management, production, human resources, etc.) individually manages for more effective use. The company that Bagchi & Sharma (2025) studied aimed to improve its business operations by implementing two ERP modules: an inventory management system and a customer relationship system. The ERP project was led by an external consultant. The implementation, however, did not produce the expected results.

The reason for the failure was a one-size-fits-all IT implementation that ignored the context in which the company’s practices were situated. For example, the consultant ignored the fact that different tax rates apply to different foreign customers, which is obvious to all concerned. In other words, the consultant attempted to implement “industry best practice” as they believed in it, without making any effort to understand the business and context of the company. Bagchi & Sharma (2025) call this “a template-based implementation” (p. 427) detached from company-specific processes and practices. Surprisingly, such an ERP that ignored real business practices not only undermined customer trust but also created dissonance within the company and even led to mass employee turnover.

Bagchi & Sharma (2025) argue that in ERP implementation, managers need to apply both the bird’s-eye view and the ant’s-eye view in an integrated manner. In other words, it is important to have both a holistic view and an attitude of looking closely at the details. This is in line with “systems thinking” − the most important discipline of the learning organization (Senge, 1990).

As this case illustrates, IT is not unconditionally effective. Its effectiveness depends on the context. Hence, contextual knowledge is essential for smooth and effective IT implementation. In this process, it is humans who have a broad and deep understanding of the context and can adjust the technology accordingly. We must not regard technologies as infallible but must adapt them to reality by ourselves.

Showkat & Nagina (2025) examined the relationship between learning organizations and environmental sustainability practices (STP) in the Indian tourism sector. They found that learning organizations (Senge, 1990) contribute to implementing sustainability practices and improving their effectiveness. Specifically, Showkat & Nagina (2025; Table 1) focused on the following learning organization characteristics (LOCs): emphasis on and encouragement of learning (including joint learning), open discussion, empowerment of members and collaboration with external partners. They found that these characteristics contribute to promoting STPs in local communities and the tourism sector. In addition, outcomes such as reduced environmental impact, well-being and economic development of local communities and economic sustainability and development of the tourism sector are engendered.

Upon implementing a new practice, we tend to focus only on the practice itself and its outcomes. In contrast, Showkat & Nagina (2025) found the importance of fostering learning organizations as a prerequisite for facilitating the implementation of practices and improving their effectiveness.

In other words, the benefits of LOCs extend beyond the focal organization’s boundary to local communities, the industrial sector and the global environment. Needless to say, the role of the leader in each aspect of the learning organization (encouraging learning and open discussion, empowering members and working with external partners) is important. We should look again at the importance of leaders who “plow” the fields of the learning organization when sowing the seeds of new practices.

Bhardwaj et al. (2025) quantitatively examined the relationship between employee empowerment, commitment and OCB among front-line employees of Indian retail businesses. OCB refers to pro-organizational behavior not prescribed by a formal job description, which includes support, guidance and mentoring of colleagues in need.

There are two types of empowerment for employees. On one hand, structural empowerment (SE) “deals with the organizational setting that enables employees to achieve the goals, that is, access to information, resources and development opportunities” (Bhardwaj et al., 2025, p. 460). In other words, it entails formal and institutional empowerment. On the other hand, psychological empowerment (PE) is “an individual’s belief in their ability to influence their work environment, make meaningful contribution and achieve desired outcomes” (Bhardwaj et al., 2025, p. 462). In contrast to SE, PE is informal and subjective.

Bhardwaj et al. (2025) found that SE and PE both increase commitment and encourage OCB, improving performance through OCB. From another point of view, this result implies that over-management may negatively impact operational performance. Remember, redundancy is important in knowledge creation and innovation. Innovation is generated through empowered and spontaneous collaboration, usually outside job descriptions, rather than managed and planned collaboration (Nonaka & Takeuchi, 1995).

Bhardwaj et al. (2025) also found the effect of commitment on OCB. However, there may be another effect in the opposite direction; the experience of being helped or mentored through another person’s OCB would further enhance that person’s commitment. Thus, empowerment, commitment and OCB are not in a one-way relationship, but in a spiral relationship, in which empowerment triggers the start of the spiral. Management should empower employees and promote the spiral of collaboration and learning.

Tran (2025) examined the relationship between leadership and OCB as well as the mediating effects of organizational justice and person-organization fit (P-O fit) between these factors.

Among them, organizational justice is “a range of ethical activities in an organization that aims to create a fair, equitable and positive workplace” (Tran, 2025, p. 485). At the most fundamental level, organizational justice is classified into procedural and distributive justice. Of these, procedural justice is related to maintaining opportunities for involvement in decision-making. Distributive justice concerns the fair distribution of rewards and other distribution results (e.g. Parker, Baltes, & Christiansen, 1997). However, in the analysis of Tran (2025), both are integrated and fed into the model as a single construct.

As a leadership style, Tran (2025) assumes a classical two-dimensional model (e.g. Likert, 1961): task-oriented leadership and relationship-oriented leadership. Of these, task-oriented leadership aims at improving organizational productivity and achieving goals. It includes actions such as defining roles and assigning the right person to the right job. Relationship-oriented leadership, on the other hand, is oriented toward job satisfaction, well-being and empathy among employees (Tran, 2025). For this purpose, leaders strive to foster a supportive working culture.

The essence of Tran’s (2025) findings is as follows. First, task-oriented leadership promotes OCB among members. Second, relationship-oriented leadership promotes OCB at both the organizational and individual levels. Third, organizational justice mediates the relationship between relationship-oriented leadership and individual-level OCB.

These results suggest that relational leadership can be more important than task-oriented leadership in achieving organizational goals. Its underlying mechanisms are as follows. Relationship-oriented leadership enhances members’ perception of fairness in the organization to which they belong, increasing members’ OCB. Needless to say, it leads to improving task performance, even if the leader is not “task-oriented.” In other words, relationship-oriented leadership promotes task performance as well as, or even better than, task-oriented leadership. This finding is impressive.

This result is also consistent with the abovementioned Bhardwaj et al.’s (2025) assertion that psychological empowerment, rather than structural empowerment, strengthens OCB. Hence, to achieve organizational goals, leaders should build supportive relationships with their members.

Lørum et al. (2025) analyzed inter-organizational learning (IOL) in a Norwegian integrated health-care service. They examined the transfer of elderly and fragile patients from 13 municipalities (primary care) to one hospital (specialized care). In their analysis, the framework of Engeström’s (2016) activity system, consisting of subject, object, instruments, outcome, rules, community and division of labor, was referred to.

The results revealed the functions of “contradictions” in IOL, i.e. interdepartmental conflicts, and the importance of leadership. Regarding contradictions, in this case, there existed a difference in perspectives between primary care and the central hospital, and learning occurred through overcoming this difference. This finding supports Engeström’s (2016) idea of the activity system; according to Engeström (2016), contradictions and conflicts in the learning process are the source of new ideas and solutions. In other words, challenges to existing practices and conflicts between different perspectives facilitate learning.

In addition to that, Lørum et al. (2025) found the importance of leadership in IOL. Hence, they propose adding leadership as a new element to Engeström’s activity system. Integrated health-care services involve diverse organizations, such as the central hospital, municipalities and external committees. Furthermore, its management structure is fragmented. To integrate such fragmented structures and achieve their goals, a leader who can motivate and manage the entire organization is needed (Lørum et al., 2025).

From this finding, I would like to stress that it is the human leader who can take on the role of overseeing this group of functions. AI cannot play this role. AI refers to a vast amount of data, including similar cases in the past, and suggests solutions that seem appropriate. However, AI cannot perform the following functions required of leaders. First, AI cannot be accountable or responsible. Second, AI cannot understand fear and anxiety (e.g. in this case, understanding and judging the patient’s anxiety).

In addition, can AI be trusted by people? For example, in Lørum et al. (2025) case, if AI had made decisions on the patients’ transfer, could the patients have trusted the decision and had faith in the AI? Patients would have wanted human physicians’ voices for their final decision.

Of course, human leaders can take great advantage of referring to AI’s suggestions. Using AI will increase the probability of correct decisions. However, ultimately, it is the human leader who can decide and lead the organization and associated learning with responsibility and accountability.

Papers on this issue examined a variety of topics. At first glance, these may appear to have no commonality. However, all of these papers depict the importance of the roles of human managers, leaders and members in diverse organizational activities.

It is people who lead DX with tacit knowledge, trial and error and adoption to context (Bagchi & Sharma, 2025; Chen et al., 2025; Ribeiro et al., 2025). It is people who empower and motivate members and activate learning (Bhardwaj et al., 2025; Showkat & Nagina, 2025; Tran, 2025). Moreover, it is people who can be responsible and accountable, who sometimes understand people’s fears and anxieties, who coordinate between organizations and who can give orders to their members (Lørum et al., 2025).

Some argue that AI will eventually surpass humans. However, each paper in this issue reminds us of the importance and role of human presence. In particular, I emphasize the following characteristics of AI. First, AI is emotionless (this is the answer ChatGPT gave me!). AI may be able to simulate emotions, such as anxiety or fear. However, it is not showing tears with emotion, but only “pretending” to do so according to the result of emotionless calculation. In particular, AI cannot feel fear or cannot make decisions based on fear. It cannot understand people’s fears and anxieties. Second, it cannot take responsibility. Even if it takes on the appearance of taking responsibility by “apologizing,” for example, it will not resonate with anyone’s emotions.

The classic manga by the great Japanese cartoonist Osamu Tezuka, “Phoenix: A Tale of the Future” (Tezuka, 2002), illustrates a future (31st century) in which national governments leave policy decision-making to AIs. In this story, the resolutions of disputes among countries were delegated to AIs possessed by each country. As a result of debates and negotiations among AIs, the AIs concluded that war was the only solution. The governments acquiesced to the decision, and an all-out nuclear war broke out, destroying the human race. This story shows the characteristics of AI (lack of emotion and irresponsibility) and criticizes blind dependence on AI.

Only human beings can direct the future of organizations, societies and mankind with emotion and responsibility. We must be the ultimate decision makers.