Resources

Panelists

  • JONATHAN HODGE -  President & CEO of Advantage Performance Group, Jon has helped organizations navigate transformation, complexity, and high-stakes decision-making. His work spans industries, equipping leaders to accelerate performance, build high-impact teams, and align leadership strategies with business goals. He holds an International Coaching Federation (ICF) certification through Georgetown University’s Institute of Transformational Leadership.
  • CHRISTINE TAO - Christine co-founded Sounding Board and now leads BTS's Scaled Coaching Center of Excellence, where she helps global organizations embed digital human coaching into their broader talent and leadership strategies to scale beyond the C-suite. 
  • SHEILA BOYSEN-ROTELLI - Sheila leads AI Coaching Strategy as Head of Global Coach Quality and Capability at BTS and is a Master Certified Executive Coach. She sets the strategic direction for AI coaching across the portfolio, ensuring alignment with coaching science, ethics, and global standards while creating a cohesive AI + human coaching experience that enables scale, consistency, and market differentiation. She is also a recognized thought leader, contributing author, and advisor shaping the future of AI in coaching.

Summary

Organizations are moving from executive-only coaching to integrated ecosystems spanning all leadership levels, combining traditional executive coaching, tech-enabled scaled coaching, and AI coaching tools. The most mature organizations build intentional architectures that match coaching modality to leader level, business challenges, and developmental needs. AI coaching is not replacing human coaches but enabling always-on practice, reflection, and role-play support in moments of need, particularly between human coaching sessions.

Current state of coaching adoption - organizational approaches (poll results):

  • 32% primarily focus coaching on senior leaders

  • 28% report ad hoc or inconsistent approaches

  • Combined 60% still concentrate coaching at senior levels rather than scaled deployment 1

AI adoption status (poll results):

  • Largest segments are piloting/testing use cases and curious but haven't started

  • Market shift began summer 2024, crystallizing into specific use cases by year-end

  • Organizations now moving from general-purpose AI to fit-for-purpose applications

Drivers of scaled coaching growth

  • Technology and access:
    •    COVID accelerated digital, tech-enabled coaching beyond senior leaders
    •    Technology making coaching more accessible across organizational levels 

  • Business environment:
    •    Pace of change increasing faster than traditional development models can support
    •    Leaders navigating more ambiguity, complexity, and competing priorities 
    •    Urgency for AI transformation driving faster leadership development timelines 
    •    Organizations demanding development that creates sustainable behavior change, not just momentary insight 

What coaching delivers

  • Core value proposition:
    •    Combines personalized goal attainment with organizational strategy alignment
    •    Meets individuals where they are to support identity shifts and belief changes, not just skill transfer 
    •    Supports integration of learning into real situations and decisions 
    •    Creates synergy between personal impact and business goals at scale 

Leadership capability trends

  • Consistent core needs:
    •    Clear communication, direction-setting, empathy, and team development remain foundational
    •    Capabilities themselves haven't shifted significantly 

    Evolving context    :
    •    Leaders must activate capabilities faster under ambiguity and shifting priorities 
    •    Coaching serves as activation intervention for rapid capability deployment 
    •    Key themes: navigating ambiguity, resilience, adaptability, communication during uncertainty 
    •    Managing up, across, and down while learning new technologies themselves 

Best-in-class scaling architecture

  • Ecosystem approach (not single modality):
    •    Organizations building coaching ecosystems across traditional executive, tech-enabled scaled, and AI coaching
    •    Natural segmentation by leader level: senior leaders, mid-level, first-level, democratized access 

  • Modality matching:
    •    Senior executives: Highly individualized, transformational work on enterprise leadership, complexity, succession, strategic influence 
    •    Mid-level and first-level: Scaled human coaching combining consistency, structure, reflection, and self-awareness at volume 
    •    Broad populations: AI coaching for always-on practice, role-play, reflection, in-moment support between human sessions or where human coaching unavailable 

  • Strategic considerations:
    •    Start with business needs and work backwards 
    •    Consider programmatic vs. individualized needs 
    •    Define use cases clearly before selecting solutions 

AI coaching: Where it fits

  • Six distinct roles (not one thing):
    •    Learning partner 
    •    Practice partner (high-value use case for pre-interaction rehearsal) 
    •    Reflection support through open-ended questions 
    •    Real-time support in moment of need 
    •    Different interventions for different moments with transparent role-switching 

  • Not a replacement for ChatGPT/Copilot:
    •    General LLMs lack intentional coaching architecture and guardrails 
    •    Purpose-built AI coaching requires distinct design for developmental outcomes

  • Appropriate applications:
    •    Pre-conversation practice and role-play in low-stakes environment 
    •    Between human coaching sessions for continuous support
    •    Populations without human coach access 
    •    Across all leadership levels, not just frontline 

Ethical guardrails and data protection

  • Required protections:
    •    Data belongs to individual user, not shared with organization in identifiable form
    •    Aggregate, anonymized insights only (same as human coaching standards) 
    •    Alignment with ICF and EMCC ethical principles 
    •    Persistent memory that travels with user without restarting context 

  • Bias mitigation:
    •    Architecture must balance challenge and support, not just agree with user 
    •    Users can select tone preference (challenge vs. support lean) while maintaining balance 
    •    Multiple layers of protection against bias built into tool design
    •    Not all AI tools follow instructions well; intentional construction required 

Implementation and adoption best practices

  • Overcome adoption barriers:
    •    Integrate AI coaching into existing developmental experiences rather than standalone deployment 
    •    Bring practice opportunities into programs where leaders already engaged 
    •    Exposure and trial within structured experiences drives continued use beyond program
    •    Connect to overall leadership development systems, not isolated tools 

  • Increase usage:
    •    Persistent memory so users don't start from scratch each session 
    •    Bring tools into flow of work where coaching needed 
    •    Integration with human coaching experiences

  • For organizations with internal LLMs:
    •    Customize system prompts to prevent over-agreement and encourage challenge 
    •    Recognize general LLMs don't automatically provide coach-like support despite helpfulness
    •    Building effective coaching agents requires significant skill and intention

Vendor selection criteria

Assessment framework being provided:
•    Checklist of criteria for evaluating AI coaching providers 
•    Evaluate which tools have proper guardrails and developmental architecture 
•    Distinguish truly valuable developmental tools from general AI applications 

Pending confirmation
•    Organizations still defining strategies for coaching dissemination beyond senior levels 
•    Market continues rapid evolution in 3-6 month increments