The work that arrives before the gain
IBM Institute for Business Value and Oxford Economics ran two surveys covering 1,500 human resources executives and 8,800 employees. 80 percent of executives said AI creates more work in validating recommendations, correcting errors, supplying context, and managing exceptions. 42 percent of employees said AI adds to their workload or leaves their effort unrecognized.[1]
These tasks are the oversight work that allows the tool to be used safely in daily operations. 43 percent of employees said they are blamed when AI goes wrong, while 41 percent of human resources executives said employees may not feel safe challenging an output. When authority and responsibility sit in different hands, a speed gain can place a new error burden on the worker.[1]
Override authority changes the productivity account
Where human resources shared responsibility for deciding which choices remained human-led, 76 percent of employees reported feeling safe questioning or overriding an AI recommendation. The figure was 43 percent where human resources was merely advisory. This association does not establish causation, but it makes voice in work design a measurable distinction.[1]
Measuring productivity only through faster completion omits validation, correction, and exception handling. Companies should disclose the hours these tasks consume, who receives them, and whether challenging an output carries a performance penalty. The surveys measure perceptions rather than actual working hours, so they cannot establish the size of the burden by themselves. Teams can watch weekly validation and correction hours by task type and team, while recording challenges and subsequent performance reviews separately. When output accelerates, the labor that makes it reliable belongs in the ledger.[1]