Forty percent of ASEAN GBS organisations have implemented AI. Almost none can show the board a number that proves it worked. Here's why implementation and measurement are not the same milestone, and what actually closes the gap.

Finance AI deployments fail most often at the training stage, not the technology. Roland Berger data shows only 37% of ASEAN GBS organisations with an AI vision have started reskilling their people. Capability has to be built before the tool lands, because the twelve-month ROI timeline leaves no room for a team still learning six months after go-live.

Stop at ‘readiness’ and you stall. Learn how to build a real GBS AI roadmap that drives execution—starting with the right processes and accountable owners.

What an AI Readiness Assessment Actually Reveals, And Why Leaders Are Surprised The first thing an AI readiness assessment tends to surface is not a technology problem. It is a process problem that has been running for years with nobody looking directly at it. That is the finding most GBS leaders do not expect. They go in focused on AI capability, tools, platforms, and use cases. What comes back is a diagnosis of the operational foundation those tools would have to run on. An

74% of GBS organisations have an AI vision. Most don't have an honest picture of where they actually stand. Before budget is committed or vendors are selected, there is one question that determines whether any of it will work.

Something shifted in the last twelve months. The conversation between GBS leaders and corporate headquarters stopped being about whether AI was coming and became about what you have done with it. If you lead a GBS function across southeast asia, you have probably felt this already. A request for an update. A slide deck due before the quarterly review. A question that sounds simple but is not: what is AI actually delivering for us? Most GBS leaders are not ready to answer that