Only 29% of transformations consistently deliver expected value
HR leaders are being asked to support faster adoption of AI and other workplace technologies while managing skills gaps, employee workload and change fatigue. Only 29% of corporate transformations consistently achieve the value they were designed to deliver, according to Kearney's Transformation Study 2026.
Resistance to change emerged as the most commonly cited implementation barrier, ahead of budget constraints, timelines and technology. The finding suggests that organisations may be investing heavily in transformation infrastructure without giving the same attention to whether employees are prepared and able to work differently.
That issue is becoming more significant as companies expand their use of artificial intelligence. More than 80% of executives surveyed said fewer than half of their AI initiatives were delivering measurable financial impact. For HR teams, the results point to a gap between making technology available and building the workforce capability required to use it effectively.
"Companies have become much better at designing and launching transformations, but they haven't made the same progress in getting organisations to adopt them," said Jennifer McGee, Kearney partner and lead author of the report.
"That's the paradox: we have more technology, more sophisticated transformation methods, and more investment than ever, yet consistent value realisation is still elusive. The next transformation advantage won't come from better strategy alone; it will come from mastering adoption."
Kearney's findings also indicate that transformation remains largely leadership-driven. Nearly three-quarters of respondents said strategy, priorities and sequencing were set primarily by senior leadership, while only 12% said leaders intentionally slowed transformation to protect organisational readiness.
That creates a potential challenge for HR leaders managing how much change employees can absorb while continuing to meet existing performance expectations. Kearney's research argues that adoption needs to be considered at the design stage rather than treated as an implementation issue after decisions have already been made.
The consultancy identified four areas for organisations to consider from the outset: employee motivation, opportunities for people to contribute to shaping change, workforce capacity to absorb it and the capabilities employees will need.
"Adoption isn't what happens after a transformation is designed. It has to shape the transformation from the beginning. That means designing around what motivates people, giving the organisation a meaningful role in shaping change, creating capacity to absorb it, and building capabilities before they are needed. When those elements come too late, organisations spend the rest of the transformation trying to overcome resistance they helped create,” McGee said.
Capability-building was also associated with materially different outcomes. Organisations that embedded it from the beginning of a transformation were nearly three times more likely to realise the value they expected, according to the study.
That finding is particularly relevant to AI implementation. HRD has previously examined how gaps in training can constrain AI productivity gains, while separate coverage has highlighted the role of skills and psychological safety during AI-driven workforce transformation.
Bryan Arcati, Kearney partner and co-author of the report, said workforce preparation would become increasingly important as organisations expand their use of AI.
"AI is making human-shaped transformation more urgent, not less. At a time when most leaders aren't seeing measurable financial impact from the majority of their AI initiatives, it's clear that digital capability alone isn't enough. The organisations that close that gap will be the ones that build capabilities before implementation: equipping leaders to redesign work, helping employees build confidence and judgment in using AI, and reinforcing new ways of working every day,” Arcati said.
