AI adoption outpaces workplace redesign, Vertage warns

Vertage has published research showing a gap between how business leaders and workers view the effect of artificial intelligence on organisational capacity. The study also found that only 15% of enterprises are classed as ready to deliver outcome-based work consistently.

The report is based on a survey of 800 enterprise decision-makers and 1,200 workers across six markets. It found that 71% of decision-makers believed AI had increased organisational capacity, compared with 43% of workers. The 28-point gap suggests many companies are introducing automation faster than they are redesigning work around it.

Three in four enterprises now define significant work around outcomes rather than roles or headcount. Even so, a much smaller group had reached what Vertage described as an advanced level of outcome readiness.

Businesses in that group reported stronger results on several measures. Some 91% reported higher customer satisfaction, compared with 67% elsewhere, while 86% said they were delivering strategic goals more strongly, against 65% for other businesses. The report also found that 85% of outcome-ready organisations were faster at converting opportunities into value, compared with 64% of the wider sample.

Readiness gap

The research frames outcome readiness as a broader operating model rather than a narrow technology issue. It says organisations that perform better tend to organise ownership, investment and decision-making around results, while combining employees, external specialists, suppliers and AI in a single delivery system.

The report identified three dimensions of outcome readiness: structural, operational and cultural. Structurally, outcome-ready businesses are more likely to plan delivery through a single strategy spanning employees, partners, suppliers and AI, with 57% doing so compared with 40% overall.

On measurement, 55% of outcome-ready businesses track the full cost of delivering outcomes, compared with 31% across the wider market. The report suggests that difference affects how leaders decide whether to build skills internally, use outside partners, hire flexible talent or automate tasks.

Employee understanding also appeared to differ sharply. Some 69% of employees in outcome-ready businesses understood their contribution and could adapt how they worked, compared with 34% elsewhere.

That cultural divide is central to the report's conclusions. It argues that AI on its own is not separating stronger businesses from weaker ones. The greater divide lies in whether organisations have clarity over desired results and the authority structures needed to deliver them.

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

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

Culture focus

The findings also point to the growing role of management culture in AI adoption. Businesses that gave staff clear goals, trust and room to challenge outputs were better placed to turn extra AI-enabled capacity into useful work rather than unused time.

In the qualitative part of the research, senior leaders described models in which cross-functional teams were given authority to deliver defined outcomes over short cycles. Another example cited in the report involved making it part of employees' roles to challenge AI-generated output to catch errors earlier.

Overbeek said culture was the starting point for any attempt to redesign work effectively around outcomes.

"Outcome readiness starts with culture," Overbeek said.

"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," he said.

The report comes as employers continue to test where AI fits inside large organisations, particularly in procurement, workforce planning and service delivery. The findings suggest many businesses may be treating AI deployment as a productivity initiative without making corresponding changes to job design, accountability and decision rights.

Sarah White, Founder and Managing Director, Lemon, an independent strategy and research firm that contributed to the report, said the main lesson was not simply that few organisations were advanced in outcome readiness.

"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," White said.

The survey covered respondents in the United States, the United Kingdom and Ireland, Australia, India, Belgium and the Netherlands. It focused on large organisations with at least 1,000 employees, or 2,000 in the United States.