Purchase this article as a standalone PDF with full colour magazine layout

Introduction: A Leadership Crisis, a Democratization Opportunity

Leadership today is under intense scrutiny. Despite sustained investment in development programs, many executives and HR leaders still report low satisfaction with leadership pipelines and real-world leadership performance. As Haslam, Alvesson, and Reicher (2024) argue, this paradox stems from organizations clinging to outdated ideas, which they term “zombie leadership,” that prioritize charisma, status, and positional authority over collaboration, reflection, and purpose. These legacy ideas remain embedded in organizational cultures and leadership selection processes.

In contrast, new modes of development are emerging, offering a more grounded, accessible approach. AI coaching tools are part of this w, wave, providing leaders with a unique opportunity: on-demand, confidential, and judgment-free reflective conversations. Rather than delivering content or evaluations, these tools help users slow down, surface inner dilemmas, and clarify meaning. This can support leaders who often seek spaces to articulate unfiltered concerns and deepen their awareness, which is something organizational systems often fail to provide.

Zombie leadership” that prioritizes charisma, status, and positional authority over collaboration, reflection, and purpose.

The shift toward AI coaching reflects a democratization opportunity (Malafronte, 2025). Where traditional coaching remains costly and exclusive, AI coaching offers scale without compromising psychological safety.

This shift is not only theoretical: pioneering platforms such as Pocket Confidant AI, Rypple.ai, and Magify. AI demonstrates how AI can bring reflective dialogue into everyday leadership practice, turning coaching into a resource, accessible not only across organizations but also directly in the hands of practitioners and professionals. In this sense, AI coaching has the potential to circulate both inside organizational systems and beyond them, supporting individual growth without always being mediated by corporate structures or compliance constraints. At the same time, the development of ICF Global AI Coaching Standards provides a framework to ensure that this expansion is grounded in ethics, dignity, and trust.

AI coaching is not a distant possibility but an already expanding domain that is reshaping leadership development.

These initiatives mirror a rapidly accelerating market trajectory: the global coaching platform market is currently estimated at $3.7B in 2024 and projected to reach $10.4B by 2034 (CAGR ~10.9%) (Market.us). Other analysts model similar growth patterns $3.8B in 2025 rising to $11.1B by 2035 (CAGR 11.2%, FMIBlog) and $2.6B in 2024 to $6.8B by 2031 (CAGR 14.3%, Persistence Market Research), indicating a consistent 10–14% annual growth band. For “online coaching platforms” specifically, projections suggest growth from $3.2B in 2024 to $11.7B by 2032 (CAGR ~14%, Business Research Insights). Together, these data points confirm that AI coaching is not a distant possibility but an already expanding domain that is reshaping leadership development. Against this backdrop, the PhD studies this article draws upon explore how AI coaching may not only augment leadership competencies but help redefine what leadership competence itself means in practice.

1. From Competencies Models to Competency Augmentation
Traditional competencies frameworks were built for stability, not uncertainty. They assume leadership is about possessing the right traits or mastering predetermined behaviours. But as the world changes faster than models can adapt, organizations are realizing that adaptive competence, the ability to learn and adapt in context, matters more than any static checklist.

Our study revealed that AI coaching helps leaders augment their existing capacities by creating space to process real challenges, not only simulating them. For example, one participant from the energy sector highlighted how AI allowed them to hold back judgment, reflect, and think more intentionally:

“I moderated my mindset. I delayed my judgment until more information was provided. It’s all about taking the time to think.”

This “pause and think” function has been lost in many fast-paced work environments. Leaders often feel pressured to decide and move on, and sometimes do move on without really knowing where they are going. AI coaching reinstates reflective space, , key driver of competence in practice. Leaders began to notice how their own reactions shaped team behaviour, strategic decisions, and communication breakdowns.

The AI Coaching conversation triggered reflective processing that reshaped perceptions and intentions. Leaders began shifting from fixed views to more curious, relational, and expansive ones.

Crucially, this development happened not through instruction, but through cognitive support: the AI helped leaders become more aware of some of their patterns, clarify values, and rehearse new reasoning, building capability in the flow of work. This shows that leadership competence can be rehearsed, not prescribed.

If you are a leader or manager, ask yourself: What if my organization’s leaders or team members were self-coaching with AI, how many could we develop and make more competent?

2. Mindset Change in the Flow of Conversation
Leadership development begins at the level of mindsets: the schemas, inner cognitive and affective programs (‘affective’ being anything that affects your moods and emotions) that filter reality, influence emotions, and dictate behaviours. Such internal lenses determine how leaders interpret success, failure, ambiguity, conflict, and pretty much any situation that emerges in their day-to-day work. In one of our studies, we followed mid-level leaders through repeated AI coaching conversations and not only found a schema change unfolding through each of the conversations but also a direct integration and use of the new schema in the flow of their work.

At first, some of the leaders approached the AI Coach with scepticism, but across sessions, they became more open and expressive, uncovering unconscious beliefs that were limiting their leadership. For instance, they allowed themselves to name inner fears, recognize how past experiences shaped their discomfort within specific situations, share honest opinions about colleagues or organizational decisions; things that are often kept secret in everyday leadership life, even when a human coach is hired and paid by their organization. This reframing allows leaders to re-engage in work situations with more awareness of their complexities, more confidence, more capacity to hold previously bothering elements, and more agency to enact leadership.

As one of the leaders explained:

“The AI coach gave me the impression of understanding what I wanted to speak about. It gave me confidence.”

This aligns with Lev Vygotsky’s (a renowned Russian psychologist) notion of development as a “living through” of meaningful experience. The AI Coaching conversation triggered reflective processing that reshaped perceptions and intentions. Leaders began shifting from fixed views to more curious, relational, and expansive ones.

Listening and questioning are known for being the most powerful developmental forces at work.

Moreover, we observed that mindset change was iterative. Repeated exposure to coaching questions led to deeper insight. Some leaders reported recognizing self-limiting thought patterns, adopting more complex frames, and experimenting with new approaches; this is what coaching is meant to generate with coachees, and it is now possible to achieve with AI Coaching.

If you are a leader or manager, ask yourself: What if my organization’s leaders or team members were self-coaching with AI? How much faster and easier would it be to get better mindsets?

3. Reflectivity and the leaders’ orientations

One under-discussed dimension of digital coaching is the emergence of the skilled coachee in our context, a leader who becomes adept at engaging AI coaching as a personal development or learning tool. In one of our studies, we saw how frequent users of AI coaching began to structure their thinking, manage emotions better, and even look forward to reflective sessions. They developed a rhythm bringing topics, reviewing past decisions, and measuring their own growth.

A senior leader described:

“I was able to find confidence in my ability to support others through change and clarity in how to get started. I now feel as though I know where to begin and am less overwhelmed by the outcome.”

Another used the AI Coach to reflect on their approach to delegation and team trust, eventually recognizing a pattern of micromanagement driven by perfectionism. They were not given a solution; they surfaced it by reflecting in dialogue.

These cases suggest that AI coaching can help embed developmental habits into everyday work, which is precisely what decades of research in leader development advocate. Leaders started journalling, pausing before decisions, and checking assumptions with greater intentionality. The AI coaches acted like a mirror, reinforcing reflection and accountability without human pressure.

This shift also supports organizational resilience. When more leaders become reflective learners, they contribute to learning cultures and environments where insight flows in every direction, not just top-down.

If you are a leader or manager, ask yourself: What if my organization’s leaders or team members were self-coaching with AI, how much learning, well-being, and agency could it spark across the organization?

4. AI vs Human Coaching: A Complement, Not a Competitor

A recurring concern is whether AI coaching competes with or undermines human coaching. Our study suggests otherwise. We found that leaders used both AI coaching and human coaching differently: AI coaching for regular deliberate thinking, tactical clarity, and emotional regulation, and human coaching for relational depth, identity work, and values clarification.

One leader captured these insights when engaging with the AI coach:

“How my strengths have changed since I’ve gotten older.” We also observed that AI coaching prepared leaders to go deeper in human coaching. It helped them sort thoughts, frame issues, and arrive ready to reflect with precision. In this way, AI coaching serves as a bridge, removing surface noise and surfacing core issues.

Several coaches we interacted with also welcomed this development. They felt that AI coaching democratized access to reflection and freed them to focus on transformational work with clients who were already reflective and self-aware.

This reinforces a blended vision where AI coaching supports the development of reflective capacity, while human coaches focus on deeper behavioural change.

However, the possibility does remain for leaders to only seek their meaning-making in full autonomy with AI coaches; this is still the challenge we see emerging with AI coaching.

If you are a leader or manager, ask yourself: What if my organization’s leaders or team members were self-coaching with many leaders and managers' support, and how many human coaches would we need to coach our entire organization?

5. From Coaching Conversations to a Theory of Leader Competence Development

When analyzed in aggregate, AI coaching conversations reveal more than personal insight; they point to a framework for how leader competence develops. Across cases, we observed three key shifts:

1. Emotional regulation: Leaders began calming emotional triggers and responding with intention.

2. Cognitive restructuring: Leaders reframed issues, clarified perspectives, and challenged limiting beliefs.

3. Relational reframing: Some leaders began seeing others differently, less as adversaries, more as partners.

These mechanisms echo the patterns found in research on competence development from an organizational perspective. Organizations are evolving from mechanical systems into dialogical spaces, where identity, shared cognition, and dynamic interpretation matter more than rigid roles or procedures.

This means that organizational life is no longer just about compliance with established routines, but about the continuous co-creation of meaning through interaction. Identity is shaped less by titles or fixed positions and more by a felt sense of belonging and purpose. Shared cognition arises when teams align their perspectives and build collective understanding, allowing them to respond to uncertainty with agility. Dynamic interpretation reflects the fact that norms and procedures are always adapted in practice, shaped by dialogue rather than imposed in isolation. In this light, organizational competence depends less on rigid hierarchies and more on reflective, adaptive, and collaborative practices that help people navigate complexity together.

AI coaching opens value opportunities not to automate coaching, but to amplify its presence in the daily lives of leaders.

For leadership, this requires a shift from directing and controlling to listening, facilitating, and enabling sense-making across the system. Leaders must be able to hold space for dialogue, foster trust, and invite diverse interpretations, so that meaning and direction emerge collectively rather than being dictated from above (which most often leads to frustrations and mistakes). The emerging view of leaders and managers as “coaches” or “facilitators of dialogue” is part of this required shift towards organizations that can make processes less constraining and more developmental, that is to say, capable of enacting empowerment at all levels.

AI coaching supports this evolution by creating coaching conversations at scale. It gives each individual a private space to think, while contributing to collective clarity, provided the data is used ethically.

Leaders began to align their thoughts and emotions with others, discuss assumptions more openly, and foster reflection in their teams. In this sense, AI coaching becomes a driver of cultural learning, not just individual growth.

6. What Leaders Change Through AI Coaching: Patterns Across Cases
Drawing from multiple cases in the PhD thesis, we catalogued what leaders actually change when engaging in AI coaching. The findings were tangible:

• Emotional clarity: Leaders went from stress to calm, anger to understanding.

› They listen more.

• New mental frames: They adopted more realistic, hopeful, and collaborative outlooks.

› They become more aware of their fears, decrease control, and increase autonomy.

• Behavioural focus: They set actions, made decisions, and restructured meetings.

› They trust more, they delegate better.

• Interpersonal awareness: They grew curious about others’ needs and became less reactive.

› They improve communication, decrease confusion, and increase clarity and alignment.

• System thinking: Some leaders began addressing structural barriers, e.g., misaligned KPIs, unclear roles, or lack of feedback loops.

› They improve processes, they facilitate organizational efficiency.

These examples show the granular transformation AI coaching enables. Leaders did not just become more “competent, they became more present, aware, and proactive in context.

7. Towards a Formula for Developing Leaders with AI Coaching
Based on our synthesis, we offer a five-part model for AI-supported leader development:
AI-supported leader development:
1. Expectations: Leaders begin with varying openness; some seek help, others empowerment.

2. Schema change: AI coaching challenges and reveals patterns, triggering ng internal shift.

3. Agency building: With repeated use, leaders direct their own learning with increasing competency.

4. Organizational framing: Uptake depends on how AI coaching is introduced, explained, and supported by the organization and its leaders.

5. Ethical enablement: Adopting industry standards (ICF, 2021) ensures dignity, safety, and trust in the coaching process.

New tools do not just support competence, they help redefine work itself. AI coaching enables organizing activity, allowing reflection to shape how decisions are made, teams are led, and strategy is translated into practice.

Listening and questioning are known for being the most powerful developmental forces at work. AI coaching can help organizations and their leaders listen deeply, privately, and continuously, not to control people, but to empower them and facilitate organizational competence.

Conclusion: Coaching for the Many, Leadership by the Many

AI coaching is not a substitute for human insight; it is a structure for human growth. It brings reflective space to more people, more often, and at lower cost. In doing so, it rebalances leadership development, making it more democratic, contextual, and real.

That is why AI coaching opens value opportunities not to automate coaching, but to amplify its presence in the daily lives of leaders. Reflection is too important to be reserved for the few.

As leadership becomes more distributed, so too must leadership development. The question now is not whether AI will change how we coach but whether we will use it to unlock the full depth of human competence across organizations.

Competence that listens before acting is a competence that includes others and creates spaces where people want to contribute and grow.

If we embrace this opportunity, we do not just develop better leaders. We reinvent work itself into something meaningful, reflective, and alive.