Leaders see AI success, workers see friction

He distinguishes between “blue money” outcomes – time saved, such as using a chat assistant to draft an email in seconds – and “green money” outcomes that grow revenue, cut costs or reduce risk. Many organisations focus on single-agent use cases that lift individual productivity, he said, rather than redesigning whole workflows with measurable results.

“What I’m saying is employees at all levels should be metriced in a way where they all meet at the same outcome. And that’s how you get everyone singing from the same hymnbook, so to speak,” Tidey said.

The data supports the point. Ninety-one per cent of respondents reported at least one measurable improvement from AI in the past 12 months, but the average was just 3.1 of 10 outcome areas. Executives were 19 percentage points more likely than workers to report revenue growth from AI.

Bigger businesses report more AI adoption, weaker execution

Half of enterprise respondents described AI as organisation-wide or fully embedded, compared with 42 per cent in small and mid-sized organisations. Yet enterprises scored 61.7 on the index against 64.9 for smaller organisations, and lower across all 10 dimensions measured. The widest gaps were in workflow integration (58.8 versus 63.5) and cross-functional coordination (61.3 versus 65.7).

“Organisations are throwing more and more tools at problems, and then the problem is they’re not actually able to bring all of that together and have people working from the same place meaningfully,” Tidey said. “Smaller organisations, people know what their workflows look like. They’re probably sat next to the person that they’re running that workflow with in the office. In these bigger organisations, that’s just not the case.”