Organizational Strategy in the AI Era 1: Five Leadership Roles and Organizational Transformation

Success in the AI era is not about 'technology'

Hello, this is Hirose.

The speed of generative AI's evolution is permeating the business landscape far beyond our imagination. Many companies are positioning AI as the most important theme in their management strategy and are investing heavily. However, behind the hype, there is an increasing chorus of voices saying, 'We introduced AI, but for some reason, we aren't seeing the results we expected,' or 'They talk about productivity improvement, but I don't really feel like anything has changed.'

In fact, this challenge is not limited to AI. In the history of past digital transformations (DX), such as ERP implementation or internet adoption, the introduction of technology itself was not the cause of failure; rather, 'the inability of organizations and leadership to adapt to technological change' was the biggest barrier.

This fundamental issue is also sharply pointed out in the Harvard Business Review article '5 Critical Skills Leaders Need in the Age of AI,' which suggests that for companies to create true value in the AI era, it is necessary to fundamentally transform the roles and capabilities of leaders as well.

In this Note, I will focus on the '5 Critical Skills' proposed by the HBR article for user companies utilizing AI, especially for senior leaders who should lead the transformation, and delve into the core of the matter from the following three points.

1. What are the 'new roles of leaders' in the AI era as indicated by the 5 skills?

2. Why are conventional skill sets no longer sufficient, and why are these 5 necessary (management theory backing)?

3. How can senior leaders acquire and practice these skills (concrete actions and cultural transformation)?

To turn AI from a mere tool into a source of 'strategic advantage,' what should we do as leaders now? Let's think about it together.

1. Five New Roles for Leaders

If the key to success in the AI era lies not in 'technology' but in 'organizational and leadership transformation,' leaders must break away from past success experiences and update their roles themselves. The five skills proposed by the HBR article specifically define five new 'roles' required of leadership.

Leaders are no longer people who strictly 'inspect and manage' the inside of an organization. Instead, they are required to have multifaceted capabilities to 'incorporate external knowledge, design organizations, lead teams, develop members, and lead by example.'

The following is an overview of the five new roles that senior leaders should take on.

1.1 Knowledge Explorer

• Definition of the role
  Cross organizational boundaries—including industry, regulators, startups, and technologists—to acquire tacit knowledge about the true potential and risks of AI from diverse networks.

• Difference from conventional leadership
  Moving away from inward-looking knowledge gathering (in-house analyst reports and industry information gathering).

1.2 Organizational Designer

• Definition of the role
  Become a 'designer' who goes beyond cost reduction to fundamentally rethink business processes using AI and redesign organizational structures and corporate culture.

• Difference from conventional leadership
  Moving away from being a technology implementation manager who just adds AI to existing processes.

1.3 Conductor of Collaboration

• Definition of the Role
  Treat humans and AI as flexible teammates, and "conduct" the balance of inputs, especially in high-risk decision-making. Ensure psychological safety and create a space for collaboration.

• Difference from Traditional Leadership
  Moving away from being a "user" who merely receives AI as a data analysis tool.

1.4 Nurturer of Talent

• Definition of the Role
  Instead of strictly managing subordinates as an "inspector," act as a "coach" to provide the environment and guidance for members to experiment with, learn, and reskill for new ways of working in the AI era.

• Difference from Traditional Leadership
  A shift from top-down supervisors to collaboration and development.

1.5 Exemplar of Practice

• Definition of the Role
  Beyond just talking about AI, use AI daily in your own work and personal life, and make those practices visible to colleagues. Create social proof within the organization to accelerate transformation.

• Difference from Traditional Leadership
  Moving away from managers who only give instructions or top-down postures that only manage impressions.

1.6 The Necessity of the Five Roles

The background to why these roles are required of leaders is a common challenge that many companies fall into: "failure to create value through AI."

The reason AI adoption does not succeed is not a lack of technical performance. An HBR paper argues that the cause is the following three organizational challenges.

1. Fear and Ignorance of AI
   Employees fear AI and do not leverage its potential.

2. Process Incompatibility
   AI is merely "tacked on" to existing legacy processes and does not correspond to the organization's way of working or value proposition.

3. Lack of Leadership Action
   Leaders do not fully understand the potential of AI and are failing to lead team collaboration and transformation.

In other words, the five new roles are a code of conduct for leaders in the AI era, designed to pinpoint and overcome the factors behind AI adoption failure. From Chapter 2 onwards, we will categorize these five roles into three areas: "organizational strategy," "team management," and "behavioral change," and delve into specific principles of action.

2. Organizational Strategy

In the AI era, what a leader must first take on is input from the organization's external environment and the transformation of its internal structure. This is also an act of balancing "exploration of knowledge" and "exploitation of knowledge," known as ambidextrous management, which is essential for growing an organization.

Role 1: Explorer of Knowledge

When we hear "AI literacy," we tend to imagine acquiring technical knowledge, but what is required of senior leaders is managerial insight into "what AI will bring to their business and what risks it entails."

This cannot be obtained solely through in-house analyst reports or gathering information within the industry. As HBR papers suggest, leaders must become "explorers of knowledge."

Theoretical background for why knowledge exploration is essential
In management science, "social proof" and "acquisition of tacit knowledge" are among the factors that accelerate the adoption of new technologies.

• Participating in diverse networks (acquiring non-redundant information)
  If you remain within existing closed industry circles, the information you obtain becomes redundant, and no new perspectives are born. Only by engaging in dialogue with diverse stakeholders such as other industries, startups, regulatory authorities, and engineers can you obtain "non-redundant information," that is, fresh insights.

• Acquisition of tacit knowledge
  The true value of AI is only understood through tacit knowledge—such as specific application methods and raw experiences of successes and failures—that is not written in manuals or specifications. Leaders must "observe" how trusted peers are utilizing AI through such networks and acquire tacit knowledge through "dialogue."

Action principles to practice
Senior leaders have a responsibility not only to expand their own networks but also to intentionally have their teams participate in networking events with other industries and companies to raise AI literacy across the entire company.

Role 2: Organizational Architect

A leader who has understood the true potential of AI as an "explorer of knowledge" must take on the next role of "architect (organizational designer)." This means redesigning the "foundation" of old organizational processes, structures, and culture so that AI can function.

The mechanism behind AI investment failure
The biggest reason many companies cannot extract value from AI is not because "the technology is inferior," but because "they are grafting AI onto legacy processes." Placing AI on top of outdated processes only increases complexity and does not generate true value.

Decades of research have consistently shown that complementary organizational changes are essential to gain the true benefit of increased productivity from AI implementation.

From cost reduction to "rethinking value creation"
An "organizational architect" must lead transformation from the following three perspectives.

1. Rethinking processes
   Make decisions on where to automate, where to augment human judgment, and where to leave tasks entirely to humans. Rather than simple personnel reduction, fundamentally rethink business processes.

2. Creating new value
   Focus on AI-driven hyper-personalization and the construction of new business models that were previously impossible.

3. Upgrading roles
   While having AI agents handle simple chores, perform organizational role redesign to upgrade employee tasks to "higher-value roles."

Transformation is one with "culture"
Organizational design is not limited to physical structural changes. Outdated processes often reinforce old norms and culture. Leaders must have the authority and resolve to execute bold organizational designs, such as integrating responsibility for strategy, transformation, and technology, and fulfill their role as architects who extract the true value of AI through structural transformation.

3. Team Management

In this chapter, we focus on the roles of "conductor" and "nurturer" to maximize team power in the AI era. In particular, the core themes are human-AI collaboration and the construction of psychological safety, which serves as its foundation.

Role 3: Conductor of Collaboration

The greatest transformation brought about by AI is the decision-making process itself. AI is no longer just a data entry tool, but has taken on the role of a "flexible teammate" that performs complex financial forecasting and strategic analysis. The leader, or "conductor of collaboration," must design and manage this new collaborative environment.

The "choreography" of human-AI collaboration
What is required of senior leaders is the ability to consciously "choreograph" the balance of human and algorithmic inputs, such as the following.

1. Designing the role of AI
   Improve the quality of decision-making by consciously designing and managing AI's role, not only by using it as a "recommender" or "analyst," but also by having it intentionally challenge group consensus as a "devil's advocate."

2. Leveraging Speed and Abundance
   Directly incorporate the 'abundant and rapid evidence-based' insights provided by AI into senior team discussions, enabling multi-faceted trade-off debates that could not have been reached by humans alone.

Psychological Safety is the Foundation of Collaboration
Psychological safety is the most important factor in ensuring the success of human-AI collaboration, especially in high-risk decision-making.

• An Environment that Allows AI Criticism
  It is essential to have an environment where the team can verify and point out to each other whether the conclusions and recommendations produced by AI are correct and free from hallucinations without fear. If a leader shows an attitude of treating AI proposals as absolute, the team will become unable to share mistakes, and the introduction of AI will result in increased risk.

• Clarification of Final Responsibility
  Leaders must clearly demonstrate that the responsibility for final decision-making lies with humans, and must encourage the team to freely explore scenarios and learn from failures together.

Role 4: Talent Developer

The introduction of AI frees employees from simple tasks, but at the same time, it requires reskilling for 'new skills.' Here, the leader's role fundamentally changes from 'inspector' to 'coach'.

Transition from 'Inspection Culture' to 'Coaching Culture'
As years of research have shown, the skills required of modern managers have shifted significantly from traditional 'supervision' to 'collaboration, coaching, and influence'.

Senior leaders need to destroy the 'inspection culture' that has become a long-standing custom—that is, the culture of strictly interrogating subordinates through exhaustive forecasting tasks and reporting meetings.

• Investing Time and Resources into Coaching
  By leaving forecasting to AI with real-time digital dashboards, managers are freed from data collection and inspection tasks. Instruct them to redirect the freed-up time toward customer engagement and coaching subordinates.

• Coach for New Ways of Working
  Just because AI reduces busy work does not mean employees will automatically acquire new skills. Leaders must act as 'coaches' who teach and embed new ways of working to complement AI, and must continue to provide the psychological safety necessary to encourage failure and experimentation.

'Talent Developer' is one of the most important roles for cultivating the soil of growth so that the team does not fear working in the AI era and continues to evolve.

4. Behavioral Change

If the previous three roles (Knowledge Explorer, Organizational Designer, Collaboration Conductor/Talent Developer) were about building the foundation of strategy, organization, and team in the AI era, the final role is for lighting a fire and moving the entire organization on that foundation.

It is the role of a 'Role Model' where the leader personally masters AI and clearly demonstrates that attitude to the organization.

Role 5: Role Model

Senior leaders need to not only talk about the benefits of AI but also demonstrate their seriousness through their own actions. As the HBR paper points out, despite the fact that many leaders are more positive about AI than their employees, there is a reality that they are not actually using AI as much as they claim to be. This is one of the biggest factors hindering organizational transformation.

Strategic Significance of 'Using It Every Day'
The best way for a leader to remain relevant in the AI era is to 'use AI every day, both personally and professionally.' This action has the following dual strategic significance.

1. Acquisition of Aesthetic Eye (Discernment)
   By using AI themselves, leaders enhance their ability to spot 'Workslop.' Workslop is content that looks sophisticated but has no substance. The 'managerial discernment' to judge whether reports or project proposals created by AI are based on truly valuable insights or are just superficially dressed up can only be cultivated through practice.

2. Building Social Proof
   There is immeasurable value in utilizing AI in a leader's daily work and making hands-on AI usage visible to colleagues and the team.

'Social Proof' to Accelerate Transformation
People adopt new technology most when they see 'trusted peers and superiors using it.' By showing a stance of taking the lead in trying AI, failing, and gaining learning, the following message is conveyed to the entire organization.

• Curiosity, agility, and even mistakes are all part of this transformation journey.

• Leaders themselves bear the initial costs of adoption (the costs of learning and failure).

The personal practice of senior leaders is not merely a hobby; it serves as a powerful motivation to accelerate organizational transformation and acts as a catalyst that irreversibly drives behavioral change across the entire organization.

5. Conclusion: Recommendations for Strategic Advantage

Through this Note, we have confirmed that success for leaders in the AI era depends not on the amount invested in technology, but on "leadership and organizational transformation." To maximize the potential offered by AI and build a true strategic advantage over competitors, leaders must take on the following five new roles.

1. Organizational Strategy

   • Role 1: Explorer of Knowledge

   • Role 2: Architect of the Organization

2. Team Management

   • Role 3: Conductor of Collaboration

   • Role 4: Nurturer of Talent

3. Behavioral Change

   • Role 5: Exemplar of Practice

These five roles are designed to overcome the fundamental challenges that hinder AI adoption: "lack of knowledge," "process maladaptation," and "team fear and distrust."

Leaders must move away from the short-term perspective of mere cost efficiency and set high goals for creating "new customer value that would have been impossible without AI."

AI does not bring value simply by spending money on tools and infrastructure. To succeed in "Organizational Strategy in the AI Era," senior leaders are required to consciously adopt these five new roles and be prepared to transform the core of the organization. This determination and practice are the only ways to elevate your company's AI investment from a "cost" to a "true strategic advantage."

I hope this Note is helpful to you.
Thank you for reading until the end today as well.

Sequel

Reference Information