Every organisation now faces the same question. How do you adopt AI fast enough to stay relevant, without moving so fast that you break the things that must not break? For a group with an established operating business, that tension is not abstract. It is the line between innovation and exposure, and you do not get to cross it twice.

Al Liwan’s answer is Al Liwan Labs.

Al Liwan Labs is a wholly-owned entity whose job is to develop and test AI capabilities at arm’s length from the core operating business. The point of the arm’s length is simple: the business adopts only what has been proven, and never has to move faster than it safely should. The Lab can experiment freely precisely because it sits outside that operating business, not inside it.

Why now, and why here. The UAE has embraced agentic AI at the level of the state. Hundreds of senior officials are being trained, and the declared target is for half of government services to be delivered through AI agents within two years. When the public sector moves at that speed, the private sector has to keep pace simply to interface with it. In Abu Dhabi, AI adoption is not a someday project. It is happening, and the institutions that will matter are the ones building the capability now rather than commissioning a study about it.

The harder problem is not capability. It is control. I have spent a long time arguing that enterprise AI runs between two failure modes. On one side, unsupervised agents taking over where they should not, especially where the stakes are highest. On the other, a human-in-the-loop requirement so heavy that it becomes a brake nobody can release, and the promised productivity never arrives. Both fail, in opposite directions. The whole discipline of the coming years is learning to calibrate the space in between, and to do it in a way you can actually defend to all stakeholders. Al Liwan Labs is where we do this work in practice rather than on a presentation slide.

What this is, and what it is not. Labs is a deliberate experiment, not a reorganisation and not a mandate imposed on anyone’s day-to-day. We build and test agentic workflows in a ring-fenced setting, compliant by construction, and only what survives that testing is offered to the wider group. Over time AI will reach every division, and each will be able to embrace it at its own pace. Nobody is asked to run before the ground is checked.

An invitation. I want to build Labs in conversation, not in a vacuum. If you are a technology provider building toward more capable and more autonomous systems, a researcher working on AI governance and its guarantees, or an operator who has felt both of those failure modes first-hand, I would like to compare notes. The unsupervised future is coming whether or not we are ready for it. The interesting work is making it one we can actually stand behind.