Enterprise AI coaching is moving from experiment to infrastructure.

Why This Research Matters

As organizations explore how generative AI reshapes learning, leadership, and execution, one question remains central: How does AI coaching function inside real organizational ecosystems?

Until recently, there has been limited peer-reviewed academic research examining this transformation in practice.

A newly published study in Behavioral Sciences provides independent academic analysis of AI coaching adoption within a professional coaching firm, offering insight into how AI reshapes roles, identity, and value creation across the enterprise coaching landscape.

This research contributes to the broader discussion around automation, augmentation, and the evolution of workplace coaching.

About the Study

The research, “AI in the Coach’s Chair: How Professional Coaches Navigate Identity and Role Ambiguity in Response to AI Adoption by Their Coaching Firm,” was conducted by:

• Dr. Gil Bozer, Sapir Academic College

• Prof. Dr. Silja Kotte, Aschaffenburg University of Applied Sciences

The paper was published in 2026 in MDPI’s peer-reviewed journal Behavioral Sciences.

The qualitative field study examines real-world organizational adoption of AI coaching and explores how AI-based coaching reshapes professional roles, boundaries, and value creation across the enterprise coaching ecosystem.

Importantly, the study focuses not on whether AI coaching “works” in isolation, but on how it functions within the broader organizational coaching market and how it may catalyze the evolution of workplace coaching models.

Key Findings from the Research

1. AI Coaching Can Operate Independently at Scale

The authors identify a “division of delivery” model in which AI coaching operates autonomously for structured, everyday employee needs, such as reflection, goal clarity, action planning, and follow-up, without requiring direct human oversight.

This positions AI coaching as a scalable, stand-alone organizational capability rather than a niche experimental tool.

2. AI Augments Human Coaches Rather Than Replaces Them

The research highlights blended models where AI automates routine elements of coaching delivery while augmenting human coaches in complex, executive, or emotionally nuanced contexts.

Rather than a replacement dynamic, the findings describe a structural evolution in how coaching is delivered across organizations.

3. Psychological Safety Emerges as a Key Advantage

Participants in the study experienced AI coaching as neutral and non-judgmental.

In some cases, this enabled more candid reflection than traditional human-mediated settings, particularly within organizational environments where hierarchical dynamics can influence openness.

4. AI Coaching Catalyzes Market Evolution

The study frames AI coaching not merely as a tool, but as a catalyst for professional renewal and ecosystem evolution.

The adoption of AI coaching triggered role ambiguity and identity work among professional coaches, a process that ultimately led to new blended human-AI coaching models and adaptive professional growth.

Pandatron’s Perspective

“Organizations don’t need more programs or gated interventions,” said Pandatron CEO Dima Syrotkin.
“This research shows how AI can operate independently at scale, automate parts of coaching delivery, and augment human expertise, while also supporting coach development. Pandatron is built to serve as organizational infrastructure for reflection and action, available to every employee with a company-managed device.”

Pandatron builds on these research insights by offering a stand-alone enterprise AI platform that supports everyday employee reflection and execution, while also enabling organizations to evolve their broader coaching and development ecosystem.

By embedding AI coaching directly into the flow of work, organizations can:

• Extend coaching beyond elite programs

• Automate structured reflection and follow-up

• Support both employees and professional coaches

• Scale development without linear cost growth

Read the Full Peer-Reviewed Study

The full open-access article is available via MDPI’s Behavioral Sciences journal:

🔗 Access the Article: https://www.mdpi.com/2076-328X/16/2/211

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If your organization is exploring how AI can support reflection, adoption, and execution at scale:

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