Before AI Reshapes Your Workforce, Understand How Work Truly Gets Done

Kerry Brown, Transformation Evangelist at Celonis, is a strategist and thought leader who helps companies achieve organizational excellence.

​A concerning pattern is emerging in corporate workforce planning. Organizations often reduce headcount based on assumptions about what AI can handle, only to discover that the work—or the expertise needed to perform it—cannot be replaced as easily as expected. Gartner and Forrester have projected that roughly half of the job cuts made in the name of AI will be reversed. ​

AI absolutely provides the opportunity to reduce repetitive work, improve performance and enable employees to focus on higher-value activities. As companies increasingly explore organizational transformation or process reimagination, due to market pressures or M&A transactions, realizing transformation’s full potential requires a clear understanding of how work actually gets done.​

The challenge is rarely technology alone. Transformation initiatives are often missing business context: the exceptions, subtleties, nuances, informal handoffs and judgment calls that shape how work happens in practice. These rarely appear in process maps, job descriptions or organizational charts. Without true visibility, leaders risk making workforce decisions based on an oversimplified view.​

The simplest conclusion is that AI has been oversold, but recent reversals in hiring point to a different problem: decisions being made without a full view of the work, expertise and institutional knowledge. In my 20 years working in digital transformation at major enterprises, I have repeatedly seen that work described on paper differs from what people actually do.​

From Broad Assumptions To Evidence-Led Capacity Planning

With this context, leaders can replace broad headcount assumptions with a practical three-step framework with workforce performance as a central goal:​