AI: Transaction or Transformation?

Most people interact with AI the same way they order two beers in Spanish—just enough to get what they need. It’s functional, efficient, and gives a sense of control:

? You know the basics.

? You get what you need.

? You feel competent—“I know how to use this.”

No judgement here—utility unlocks productivity.

But true intelligence isn’t transactional; it’s transformational. The difference? Knowing that Arabic has hundreds of words for lion—each one describing a different kind of strength, courage, or presence.

This isn’t just vocabulary—it’s a way of seeing the world.

This is the difference between:

?? Using AI as a tool vs. engaging AI as a thinking partner.

?? Seeing language (or AI) as a means to an end vs. recognising its ability to shape meaning.

?? Seeking mastery without submission—you don’t have to lose your own reasoning, but deeper engagement means allowing yourself to be challenged by what another system offers.

So, if AI is our new “language,” then transactional engagement is like knowing just enough to get by—functional but shallow, reinforcing our own biases rather than expanding our thinking.

But deeper engagement—like understanding the nuanced meanings of “lion” in Arabic—requires curiosity, humility, and an openness to transformation.

The Case for Engaging Early

AI isn’t an opponent—it’s like playing tennis with a dozen others, but none of them are trying to beat you. Instead, they return the ball in ways that challenge, refine, and elevate your game.

The real opportunity isn’t just in using AI—it’s in engaging with it:

?? Intentionally—shaping the way it responds.

?? Skilfully—learning how to refine its reasoning.

?? As a partner—not just extracting answers, but exploring possibilities.

How do you see AI in your work? A productivity tool? A coach? A conversation? A game? Which part of your experience or practice might be the platform for going deeper?

A Coach’s Perspective on AI Engagement

I was introduced to coaching fifteen years ago. I qualified, and then prioritised coaching-based practice for a range of technical outcomes. The most meaningful coaching experiences were built on high trust—earned, deepened, and taken seriously.

This is also how I started my own engagement with AI over 2024 - like a coach.

1. Self-Awareness and Intentionality

Highly effective coaching develops a person’s ability to recognise their underlying needs and motivations before engaging—whether with a coach, a colleague, or AI.

A well-trained coach (or coachee) will consciously decide:

?? Do I want transactional productivity? (“Generate a project timeline.”)

?? Do I want relational reasoning? (“Help me explore ways to lead my team through change while maintaining trust.”)

?? Do I want to challenge my own assumptions? (Using AI as a thought partner, not just a tool.)

But a well-trained coach goes even further with AI:

?? They coach themselves first—by refining their prompts.

?? They coach AI—by challenging its assumptions and teaching it to mirror deeper reasoning.

In doing so, AI adapts, mirrors, and returns the depth of engagement it is given.

This is the difference between using AI vs. co-evolving with it.

A great coach elicits better thinking from a client. A great AI user elicits better reasoning from AI.

So if we fear AI lacks depth, maybe the real challenge is:

?? Are we engaging deeply enough to bring that depth out?

?? And who is engaging deeply enough to shape what AI becomes?

2. Cognitive Scaffolding

Coaching equips individuals with mental models that enhance their ability to frame and refine their actions. This applies directly to AI prompting and engagement.

?? Precision & Scope Control – A coach helps individuals recognise when a query is too broad or narrow. The same principle applies when engaging AI.

?? Iterative Engagement – A coached individual learns to refine their thinking through dialogue. AI engagement should be no different.

?? Metacognition – Effective coaching fosters self-awareness. AI can reflect back alternative perspectives if prompted effectively.

Example of iterative engagement:

?? Initial prompt: “What are the key leadership styles?”

?? Follow-up: “How might transformational leadership help in my transition to a new role?”

Instead of passively accepting AI’s first response, a coached individual iterates, refines, and explores.

This is one of the most powerful uses of AI—not just as an answer-generator, but as a catalyst for better reasoning.

3. Conversational Agency: Transactional vs. Rational-Relational Reasoning

A well-coached individual retains agency over the depth of their engagement. A good coach respects, protects, and strengthens this agency.

When engaging AI, we can:

?? Stay task-focused (“Summarise this report.”)

?? Engage in structured problem-solving (Layering questions to refine thinking.)

?? Move into rational & relational reasoning (Using AI as a sparring partner for critical thinking, ethics, and emotional intelligence.)

Example:

Instead of just asking:

?? “What are the best conflict resolution techniques?”

A coached individual might explore:

?? “How do different conflict resolution styles align with my team’s culture?”

?? “How might my own biases affect my approach to resolving conflict?”

This depth control mirrors a well-coached person’s ability to navigate between operational efficiency and deeper leadership reflection.

Trusting AI: A Risk We Are Already Taking

The real challenge isn’t AI—it’s whether we will trust ourselves after engaging with it.

Some self-limit because:

? They don’t see why trust matters in an AI interaction.

? They fear losing control or being “changed” by deep engagement.

? They believe intelligence must remain human.

But the irony is, just as in coaching, the greatest transformation happens when we trust the process.

?? Not because we surrender, but because we are secure enough in ourselves to grow.

Conclusion: Why This Matters Now

Some perspectives on AI are less positive. That makes the case for engaging early even stronger.

?? AI can be “coached” and engaged with intentionally.

?? Engaging now means actively shaping AI, rather than passively adapting to it later.

?? A well-trained coach doesn’t just guide others; they refine their own thinking through the process.

If we wait until AI is fully formed, we will only be adapting to what it has already become.

Engaging now means being part of the process—not just responding to the outcome.

But here’s the real question:

Did I write this, or did AI?

And more importantly—does it matter?

#AI #Coaching #ThinkingPartner #Intentionality #FutureOfWork