Workforce data and analytics

I've been reading this recently: "Gulf organizations set to redesign jobs as AI adoption accelerates" (Consultancy-me.com), which covers research from Procapita Group's practice. It is worth reading in full, but one figure in particular stayed with me: AI adoption across the region has risen from 62% two years ago to 84% in 2025.

A twenty-two point jump in two years is fast by any standard. What interested me more, though, was the framing the research puts around it.

The story is redesign, not reduction

The assumption that tends to dominate conversations about AI and employment is that automation removes jobs. The research suggests something more demanding is happening in the Gulf: work is being redesigned task by task and role by role, with workforce reallocation occurring at a scale most organisations have not prepared for.

The report cites one global organisation that restructured 16,000 roles specifically to align employee capabilities with AI-supported ways of working. That is not a headcount exercise. That is a capability exercise, and it is a fundamentally harder one.

You cannot redesign what you have not mapped

Here is the uncomfortable implication for anyone responsible for people in this region.

Redesigning roles at any meaningful scale requires knowing what your workforce can actually do today. Not job titles. Not what the job description said when someone was hired three years ago. Actual, current capability — including the things people have learned informally and the things they list on a CV but have not practised in years.

Most organisations I speak with in the GCC cannot answer that question without a manual exercise that takes weeks and is out of date by the time it finishes. The skills data either does not exist, or it sits in a system nobody has updated since implementation.

This is why I would argue workforce analytics has stopped being a nice-to-have. If role redesign is coming — and the adoption figures suggest it already is — then a current, trustworthy picture of workforce capability is the prerequisite for doing it well. It is not the follow-up project.

Adoption figures measure tools, not change

There is a second trap worth naming. High adoption statistics are satisfying to report and easy to misread.

Eighty-four percent adoption tells you people have access to a tool and are using it. It tells you very little about whether the work itself has changed — whether processes were rebuilt around the technology, whether decision rights moved, whether anybody's role is genuinely different from what it was before the licence was purchased.

The organisations getting real value are measuring the second thing. That is considerably harder, and considerably more useful.

A planning problem before a technology problem

My honest view is that most of this sits with workforce planning rather than with technology teams.

The questions that matter are not which platform to buy. They are: which roles in our organisation are most exposed to redesign in the next two years? Where do we already hold the capability to absorb that change, and where would we be starting from nothing? What does our workforce need to be able to do in three years, and how far is that from where we are today?

Those are answerable questions. They require data most organisations already partly hold, and a willingness to look at it honestly.

The pressure is still manageable in most organisations in this region. That will not always be true, and the ones building the picture now will be glad they did.