AI boosts capacity, but firms lag on work redesign

Vertage has published research showing a wide gap between how business leaders and workers view the impact of artificial intelligence on organisational capacity. The study found that 71% of decision-makers said AI had increased capacity, compared with 43% of workers.

The findings accompany a broader claim from the HR technology company that many large organisations are adopting AI faster than they are redesigning work around it.

The report, based on a survey of 800 enterprise decision-makers and 1,200 workers across six markets, argues that businesses are increasingly organising work around outcomes rather than roles or headcount. It found that 74% of enterprises define significant work around outcomes, yet only 15% are considered ready to deliver consistently under what Vertage calls an "outcome-ready" model.

That gap matters because the most advanced companies reported stronger results across several measures. Outcome-ready businesses recorded customer satisfaction of 91%, compared with 67% elsewhere. They also reported stronger delivery of strategic goals, at 86% versus 65%, and faster conversion of opportunities into value, at 85% versus 64%.

The study also pointed to a cultural divide. In organisations classed as outcome-ready, 69% of employees said they understood their contribution and could adapt how they worked. In other businesses, the figure was 34%.

AI and Work

One of the clearest findings was the mismatch between management and staff over whether AI is creating useful time or simply changing workflows without delivering obvious benefits for employees.

Vertage said the gap suggests many employers have automated tasks without deciding how to use the resulting capacity. In practice, businesses may be adding AI tools while leaving existing structures, reporting lines and performance measures largely intact.

The company described this as a work design issue rather than a technology problem. The report said employers must decide when a task should be handled by employees, specialist contractors, external partners or AI systems, rather than assume every new demand requires another hire.

"AI adoption no longer separates strong businesses from the rest. Outcome readiness does," said Edzard Overbeek, Group Chief Executive Officer at Vertage.

Overbeek linked that argument to a wider shift in management practice.

"The strongest businesses organize people, partners and AI around a clear result, and they keep human judgment at the center," he said.

Readiness Measures

To assess how far organisations have moved towards this model, Vertage introduced an outcome-readiness index designed by Opinium. The framework breaks readiness into three areas: structural, operational and cultural.

Structural readiness refers to how ownership, investment and decision-making are organised around results. Operational readiness covers how companies deploy employees, specialists, suppliers, partners and AI together. Cultural readiness concerns whether staff have enough clarity, trust and authority to adapt their work.

The survey suggested that more advanced companies were more likely to plan delivery through a single strategy spanning employees, partners, suppliers and AI. That was true for 57% of outcome-ready businesses, compared with 40% overall. They were also more likely to measure the full cost of delivering outcomes, at 55% versus 31% across the wider sample.

A quote from one enterprise leader interviewed for the study illustrated that approach: "I don't care how many people you put on the dance floor - the dance needs to look like this," said one enterprise leader interviewed for the report.

Culture Question

Vertage's findings place notable weight on culture, especially at a time when companies are under pressure to deploy AI quickly while also reassuring staff about changes to jobs and workflows.

The report cited examples from customer case studies in which cross-functional teams were given authority to deliver defined outcomes in 90-day sprints. In another business, employees were expected to challenge AI output so they could catch errors earlier.

"Outcome readiness starts with culture," said Overbeek. "People need to understand the result, know where they can challenge and feel trusted to use their judgment. That clarity helps businesses make better choices about how work gets done."

Sarah White, Founder and Managing Director at Lemon, which contributed to the research, said the main lesson was not simply that few businesses have reached an advanced stage.

"The most important takeaway from this research isn't that only a small percentage of organizations are outcome ready. It's that the vast majority are navigating a fundamental change in how work is organized. No business needs to have the entire future operating model figured out today. What matters is understanding where the gaps exist and beginning to make deliberate changes," said White.

The research covered respondents in the United States, the United Kingdom and Ireland, Australia, India, Belgium and the Netherlands. It also included interviews with senior leaders responsible for procurement, technology, workforce strategy, transformation or major project delivery.