The Real Test of AI: Can We Change Fast Enough?
I have spent the past few years watching AI move from a quiet experiment in labs to a force reshaping every kind of work I know. I have seen it in the private sector, in government spaces, and most recently in humanitarian work. What stands out to me is not how powerful the tools are but how slow institutions can be to change around them.
Technology is not the problem. Transformation is.
Every major leap in AI has felt like a wave.
The first wave was about perception, when machines learned to see, hear, and recognize patterns.
The second was about generation, when they learned to create, writing, translating, and designing with us.
The third, the one we live in now, is about reasoning. Machines can plan, analyze, and make decisions with a level of structure that almost feels human.
And the fourth is already forming on the horizon, where intelligence meets motion, with robots, automation, and physical AI working alongside people in the real world.
Each wave has forced us to ask new questions about trust, ethics, and control. But underneath it all, I have noticed something simple: progress depends less on the tools and more on the systems that hold them.
Across humanitarian organizations, AI is being used quietly. People are testing it in the background to write reports, translate data, or build small prototypes. Most of them do it on their own time, using personal accounts, because the systems around them move too slowly. There are no policies, no strategies, and often no leadership guidance.
I see it as resilience. Humanitarians, like people everywhere, are adapting faster than the systems that employ them. The innovation is already alive; it is just waiting for structure, support, and recognition.
To make that possible, we need more than adoption. We need readiness.
And readiness is not a software problem. It is a systems problem.
From what I have seen, five elements make the difference:
Innovation that welcomes experimentation.
Infrastructure that protects data and enables scale.
Ecosystems that connect teams and tools instead of isolating them.
Partnerships that bridge humanitarian needs and technology expertise.
Openness that shares lessons, failures, and progress with others.
These are not buzzwords. They are the architecture of transformation.
Even the strongest framework needs leadership because tools can automate, but only people can align.
Leadership is what turns systems into movements. It is what builds trust, invites curiosity, and gives direction when the world changes faster than policy can catch up.
I keep returning to this thought: AI will not change the humanitarian world by itself. It will only do so when our leadership, culture, and institutions are ready to change with it.
That is the real test of our time.
When I think about leadership in moments like this, I do not see it as authority or control. I see it as presence. Leadership today means creating the conditions for others to learn, explore, and adapt safely. It means listening before deciding, enabling before directing, and shaping culture before strategy.
In an age of reasoning machines, the most important thing we can do as leaders is remember what makes us human. Curiosity, empathy, and courage are not soft skills. They are the very foundations of transformation.
Because in the end, technology will keep evolving. The question is, will we?
Ali Al Mokdad
