What if one of coaching's contributions to AI transformation goes beyond partnering with people and teams navigating change, and offers a process architecture for transformation itself?
Organizations around the world are investing heavily in AI. They are selecting tools, developing governance frameworks, and training employees to use new technologies.
Yet a common challenge continues to show up.
Despite access to AI tools, many organizations face the challenge of turning experimentation into everyday practice and finally capturing business value, even when employees are given enough reasons to be curious and start testing.
Let's consider that the missing piece isn't another, better AI tool, or another training session.
Working in leadership and talent development, I've noticed an interesting parallel: the journey teams go through when adopting AI closely resembles the journey coaches accompany their clients on. Not because AI adoption is coaching, but because both involve partnering with people to move them from uncertainty to meaningful action. Teams are the experts of their own working process - they know best where and in what way AI should be integrated.
This made me revisit one of Erickson Coaching International's most recognized frameworks: the Solution-Focused Coaching Arrow. What struck me was not the coaching techniques themselves, but the underlying architecture.
A good coach starts by accompanying the client through topic exploration, rather than jumping to solutions
One of the principles I have always appreciated in coaching is its sequence. Coaching doesn't begin by pushing the client to search for answers. Instead, the conversation follows a deliberate progression:
Explore the topic and the current reality
Clarify the desired outcome
Reflect on why it matters
Create new perspectives
Commit to action
Reflect on value and celebrate progress
The process is designed to guide thinking toward concrete actions, leading to results that actually make a difference. That same principle may have something valuable to offer organizations committed to AI adoption.
From coaching conversations to AI adoption
This observation became the starting point for designing an AI adoption framework that follows the same logic as the coaching journey - not by coaching employees in the traditional sense, but by stimulating and structuring how teams think about change.
The parallels are striking:
Establish Rapport becomes understanding the current workflow.
Clarify the Outcome becomes defining the business challenge.
Create an Experience becomes exploring possibilities where AI can generate real business value.
Formulating Action Steps become designing and testing a practical AI use case.
Review Value becomes learning from the experiment.
Celebrate Progress becomes reinforcing adoption and continuous improvement.
The objective is not to replicate a coaching session. The objective is to create a process that supports teams in moving thoughtfully from awareness to action.
A new role: AI adoption facilitators
Facilitating AI adoption calls for different roles at different moments:
Sometimes we need to be detectives, actively digging in to understand how work is really done.
Sometimes challengers, directly pushing back on assumptions that no longer serve the organization.
Sometimes architects, designing the exercises and questions that help the team surface and define the right challenge for themselves, before moving to solutions.
Sometimes facilitators, actively driving experimentation forward, without prescribing every answer.
This feels remarkably similar to coaching.
Not because facilitators become coaches, but because both focus on enabling quality thinking rather than handingover immediate answers.
That doesn't mean staying at arm's length. It's worth being clear about what's actually being handed over and what isn't. The adoption facilitator owns the process: asking the right questions at the right time, challenging assumptions, systematizing the thinking process, and holding the team accountable for what they commit to. The team owns the content: which problem matters most, which use case to test, what the solution actually looks like. The facilitator's ownership of the process is active work - it's not neutral, and it's not optional. What stays out of the facilitator's scope is deciding, on the team's behalf, what the answer is.
Look at a parallel in a management context: a “coaching style” does not mean running formal coaching sessions with direct reports. It refers to a set of competencies and a way of thinking: curiosity over certainty, questions over instructions. And it isn't about restricting how people think or steering them toward a predetermined answer. It's a systemic approach to quality thinking: building the conditions where the people closest to the work can find the solution that actually fits it.
AI transformation is often described as a technology initiative.
In reality, it is equally a process of research, experimentation, and learning.
People need space to explore, question, experiment, and build confidence before new ways of working become sustainable.
Technology provides capability.
Process provides structure.
Thinking architecture creates adoption.
And this is where coaching has something important to contribute - not only as a way to partner people through challenges during change, but as a quality-thinking process architecture for organizational transformation.As AI becomes part of everyday work, organizations may benefit not only from technical expertise, but also from frameworks that help people move from understanding to experimentation, to meaningful action.
Because successful AI adoption doesn't begin with the right tool alone, but with a well-scoped challenge and a solution-oriented way of thinking.
ABOUT ANA
Ana Jebirashvili is an Erickson Certified Professional Coach, AI Adoption Facilitator, and L&D Consultant and Trainer. She combines her work in leadership and talent development with her academic experience as an Assistant Professor and PhD Candidate.
Ana supports individuals and organizations navigating leadership development, talent growth, and the evolving opportunities and challenges of AI adoption. Her work brings together coaching, learning, and practical development to help people and organizations approach change with greater clarity and intention.
To follow and connect with Ana on LinkedIn, visit her profile.