AI can increase productivity. It can’t increase human capacity

Artificial intelligence (AI) has the potential to boost productivity by automating tasks and providing leaders with capabilities that previously required more time and resources. However, this does not necessarily lead to an increase in human capacity. Despite AI's ability to draft emails, analyze information, and automate administrative work, many workers still report lacking sufficient time or energy to complete their tasks.

This discrepancy exists because AI does not directly address human limitations in terms of complexity, pressure, change, and decision-making.

Leaders need to recognize the difference between productivity and human capacity. Productivity focuses on how much we can produce, while human capacity refers to how much complexity, pressure, change, and decision-making a person can sustainably handle while maintaining effective performance. AI can expand human capacity, but organizations must take responsibility for enhancing it.

For instance, if an executive saves five hours each week through AI, those hours could be spent on additional meetings, decisions, targets, or deliverables. In this case, productivity has increased, but human capacity has not. Human beings have cognitive, emotional, and attentional limits, and under sustained pressure, our judgment can deteriorate. We may become more reactive, listen differently, and struggle with strategic thinking due to constant focus on immediate tasks.

Organizations must consider human performance beyond productivity when implementing AI strategies. Leaders must possess the ability to access their best judgment under pressure, maintain clarity amidst abundant information, regulate their responses to stress, and foster confidence and stability within their teams. These factors become increasingly critical as AI accelerates the speed of information delivery and decision-making expectations.

To make the most of AI investments, organizations should prioritize reinvesting the capacity AI provides back into people. This includes supporting strategic thinking, customer conversations, developing employees, experimentation, and creating space for deep thinking. Measuring AI's return on investment should extend beyond the amount of additional work people can produce; instead, it should focus on making better use of their human capability.