Membres
Chrysalis MG Consulting | AI ADOPTION: Leading through change we don't fully understand!
As an executive coach working with regional leaders for 12 years, I keep seeing the same pattern with AI
As an executive coach working with regional leaders for 12 years, I keep seeing the same pattern with AI: capability arrives, resources follow, time passes, then the real question emerges, not "did we adopt it?" but “how did we lead it?”
AI as genuine advantage The UAE leads the world in AI adoption, backed by nearly a decade of state planning since 2017. This is the result of a decade of planning, starting with the world's first Minister of State for AI in 2017 & continuing through the National Strategy for AI 2031. Regulation is accelerating adoption (i.e. agentic AI). The constraint leaders face today is not a lack of resources, but the ability to respond to change.
The capability gap There is a pattern I notice for transformations I witnessed, long before AI. Investment moves quickly. Confidence progresses slower. It happens because organizations often build the capability before they've built the leadership capacity to hold it. That gap temds to surface later.
Who is actually carrying the transition? The greatest struggle rarely sits at the top, where strategy and enthusiasm are thriving. It is the middle managment who is struggling to translate that into daily workflow. If managers can't operate AI with confidence, strategy dies there, quietly and without much support.
A leadership capability gap, not a technology gap There is no shortage of access to AI. The main gap lies with leaders' confidence in trusting, questioning and owning AI-driven decisions they can't fully verify themselves. Many built careers on being the most knowledgeable person in the room; that tends to disappear. AI is expected to shape half of business decisions by 2027, not a future requirement, but next year's job description.
How does success look like?
The UAE's early lead came from government strategy and capital; both are firmly in place. What is needed now is execution discipline: managers who operationalize AI daily, leaders who explain decisions rather than delegate them away.
My recommendations:
- Shift from "know it all" to "learn it all." In my article (07/09/26: Leading through ambiguity and uncertainty), I explain how to make effective decisions without having the full picture and be able to say so honestly. Leaders must also separate understanding from ownership; they don't need to build the model to own the decision, just grasp its implications and limits.
- Extend support to middle management to navigate through uncertainty. I run peer coaching circles, monthly sessions based on “live” co-creation, neuroscience and transformational coaching, where leader and teams discuss progress, decisions, and change reactions honestly.
Sustained over 6–12 months, it builds more trust and clarity than a one-time program. The successful organizations won't be the ones with the biggest budget, but the ones with leaders who shift their mindset to lead their teams under uncertainty.
