It’s no secret that in 2026 artificial intelligence (AI) adoption has become a boardroom priority. However, while organizations are investing heavily in AI tools, many are still underestimating the human side of transformation.

For this reason, coaching is becoming an increasingly important part of AI implementation strategies and, for coaching to gain real traction, leaders first need buy-in and financial backing from key stakeholders.

For years, organizations have found it difficult to measure the return on investment (ROI) of coaching effectively. Traditional learning measurement methods often focus heavily on participation metrics alone, leaving gaps in the deeper impact story. For example, organizations often measure engagement in the program, satisfaction scores, quality of relationships with coaches or self-assessment surveys — and that is where they stop. Participation and satisfaction alone rarely tell the full story, and deeper impact analysis is required to justify further investment. That’s because the most meaningful outcomes of coaching tend to emerge over time as a compound effect, influencing individual performance, team dynamics and broader business results.

Thus, coaching’s value is not simply transactional. It unfolds over time through behavior change, improved decision-making and shifts in leadership dynamics that ripple throughout an organization. That means organizations evaluating coaching purely through short-term metrics risk missing its broader impact. For L&D leaders, demonstrating these longer-term business outcomes is critical not only for proving coaching’s value, but also for securing the investment and stakeholder buy-in needed to scale hybrid human-AI coaching initiatives as part of a broader AI transformation strategy.

Stages of Coaching Impact

At the beginning of a coaching program or initiative, organizations are most likely to see high-level leading indicators of success, such as participation rates, engagement, confidence levels and self-reported progress. These metrics matter because they indicate whether employees are leaning into the process and beginning to build trust in the support available to them. This is a fantastic start on the road to the business outcomes that tend to emerge later.

As coaching programs mature within a team or organization, program managers can begin to measure coaching against more traditionally understood business metrics, such as employee retention, succession readiness, performance trends, promotion rates and more. Looking retrospectively at these indicators often provides a far clearer picture of impact while also surfacing metrics that can be further factored into a more traditional ROI approach.

This can be particularly relevant in the context of AI transformation. One of the biggest barriers to successful AI adoption is not the technology itself, but human hesitation around it. Some employees may fear replacement, lack confidence in using new tools or feel overwhelmed by the pace of change. Others may want to use these tools but simply don’t know where to start or how to effectively integrate them. Managers often face additional pressure, needing to lead teams through uncertainty while simultaneously facing their own potentially limiting beliefs and adapting their ways of working.

This is where coaching can have a real impact. During periods of organizational change, coaching becomes far more than a development perk. It becomes a strategic enabler of transformation. Effective coaching helps increase adoption of new initiatives, reduce resistance to change, build confidence and strengthen resilience across teams.

In the case of AI, coaching can help leaders and employees move from anxiety to action.

AI Coaching Has Changed the Game

AI coaching has fundamentally changed the accessibility and scalability of coaching programs. Traditionally, coaching has been reserved for senior leaders or high-potential employees because of cost and time constraints. AI coaching removes many of those barriers by providing employees with always-on, personalized support that can be accessed in the flow of work. Whether it is before a difficult conversation, during a period of change or when reflecting on leadership challenges, AI coaching can meet employees in the moment.

Crucially, organizations must resist the temptation to turn to AI coaching as a one-size-fits-all solution. Currently, AI coaching is not best positioned as a replacement for human coaching, but rather as an augmentation of it. For many organizations, the sweet spot is a hybrid approach that combines the empathy, nuance and strategic guidance of human coaches with the scale, consistency and immediacy of AI coaching tools. This allows organizations to democratize access to coaching while still providing deeper human support where it matters most. In the context of transformation initiatives, this blend can significantly accelerate adoption and behavioral change across the organization.

Coaching’s Compound Effect

Coaching also helps organizations address one of the most overlooked aspects of transformation: the downstream impact of leadership behavior.

When managers become more confident, adaptable and open to change, those behaviors influence the people around them. Teams often mirror the attitudes and emotional responses of leaders. A manager who embraces new ways with curiosity and confidence is far more likely to foster a culture where employees feel safe to experiment and learn. This creates a multiplier effect.

Correcting the Misconception

In some organizations, coaching remains associated with underperformance or corrective action, something employees are offered when there is a problem to fix. This misconception can limit engagements, damage organizational trust and reduce the strategic value organizations extract from coaching initiatives.

The businesses seeing the greatest success are the businesses using coaching as it is intended. Rather than positioning it as remedial support, these organizations are embedding coaching into talent development, transformation programs, and growth strategies. In these organizations, coaching is viewed as an accelerator for performance, adaptability, and innovation. It is a benefit for employees who are ready and willing to grow and develop into their next version of success.

For organizations trying to gain buy-in for AI coaching initiatives, the key is therefore to move the conversation away from short-term participation metrics and toward long-term business impact. Success can then be defined by whether leaders became more adaptable, whether teams embraced change faster, whether productivity improved and whether the organization became more resilient during transformation.