Julie A. Stone: The Hidden Cost of AI Productivity: Are Companies Depleting the Capacity They Need to Perform?
Every productivity case for artificial intelligence (AI) rests on an expectation: that time saved on a task translates into greater productivity. Julie A. Stone thinks companies need to examine the assumptions behind that expectation – and the human cost of meeting it. Organizations can measure faster and greater output without understanding whether the conditions behind it support sustained performance.
Recent research gives that concern substance. A Boston Consulting Group (BCG) study of 1,488 U.S. workers, published in the March 5, 2026, issue of the Harvard Business Review under the title “When Using AI Leads to ‘Brain Fry,'” examined mental fatigue associated with excessive use or constant monitoring of AI tools. The researchers connected this strain to more errors, decision overload, and intentions to quit. Stone asks leaders to consider whether employees have the cognitive capacity to think, evaluate, and exercise judgment, which are all requirements for strong performance and sound business outcomes. Are working conditions preserving that capacity, or are productivity expectations drawing it down?
Where Does the Saved Time Go?
A draft that once took two hours may now take ten minutes. But producing the draft is only part of the work. When AI produces it faster, the people reviewing, interpreting, and acting on it can also be expected to move faster than they did before AI entered the workflow. “A person may produce a draft in minutes, but someone still needs to evaluate it, put it in context, make a decision, and take responsibility for the result,” Stone says.
An eight-month study at a U.S. technology company, featured in the February 9, 2026, issue of the Harvard Business Review, illustrates this pattern. U.C. Berkeley Haas researchers found that broader tasks and parallel AI-assisted workflows made workdays denser and more cognitively demanding. Employees described feeling busier, more stretched, and less able to disconnect. The researchers warned that constant switching and reduced recovery could impair judgment and increase errors over time. “The task may take less time, but that does not mean the thinking around it should,” Stone says. “Are organizations creating room for better thinking, or simply increasing the productivity they expect without fully appreciating the cognitive capacity that additional work requires?”
Meeting the Target While Depleting Capacity
Stone distinguishes between achieving a result and understanding what it took to achieve it. A team can meet its targets by routinely working evenings and weekends, packing their calendars, or taking shortcuts and making sacrifices that delay other projects while leaving people without enough time to think and recover. “Sometimes an extra push is necessary,” she says. “But when it becomes routine, the result can hide what it took to achieve it.”
Stone goes on to argue: “Cognitive capacity is finite and fluctuating. It is the internal resource people draw on to think, evaluate, solve problems, and exercise judgment. Working conditions influence how much is available and whether people can replenish and sustain it.” That capacity depends on having time to think, being able to focus, and having the physical and mental health to do both well. A calendar filled with meetings leaves little room for concentrated work. Repeated interruptions make complex thinking harder. Work that regularly extends into evenings and weekends can crowd out sleep, movement, and recovery – the very things that help people remain ready to contribute. Eventually, quality may slip, opportunities may be missed, or your best people may leave. The conditions draining their capacity may have started long before, without anyone recognizing the pattern or having an opportunity to address it.
What Else Could People Contribute?
There is another cost to conditions that keep people constantly catching up: the contribution the organization never receives. “When people spend their available attention keeping up, they have less of it for improving a process, spotting a risk, developing a new idea, or learning to use AI well,” Stone says. A team may meet its targets, while contributing less than it could under better conditions. Business results rarely reveal that missed potential. Stone asks executives to consider what they achieved, what it took, and what else their people could have contributed.
The Signals Leaders Can Examine Now
Leaders can explore both sustainability and missed opportunity through a few practical questions:
When meetings fill the day, is focused work being pushed into the evening?
As AI speeds up tasks, are people handling more decisions and broader responsibilities within shorter timelines?
What are people skipping to keep pace: careful reviews, conversations, testing assumptions, or opportunities to learn and improve?
Is evening and weekend work increasing, and is there meaningful recovery after intense stretches?
What is the team doing to meet its goals that it could not sustain for another three months?
“No single answer necessarily points to a problem,” Stone says. “But patterns over time show leaders where to investigate and how to create conditions that replenish capacity and make it sustainable.” Examined alongside business results, these trends can act as an organizational capacity fuel gauge:
Do reserves need replenishing?
Is the current pace sustainable?
Is there room for unexpected demands?
The trend matters more than hitting a fixed capacity target. Depending on what they find, leaders may need to clarify priorities, rebalance demands, redistribute work, or protect time for focused thinking and recovery. Sometimes that includes introducing what Stone calls productive friction: a deliberate pause to question an assumption or examine a consequential decision before moving ahead. That pause can prevent rework and improve what follows. “The answer isn’t simply to do less work,” Stone says. “It is to work smarter and create the conditions for your people to apply their capabilities where they matter most.”
As AI becomes ubiquitous, Stone argues, a company’s people will become the competitive advantage. Ensuring they have the capacity to sustain performance – and the reserve to learn, adapt, and innovate – should be at the top of every executive team’s list.
Follow Julie A. Stone on LinkedIn for more insights on human contribution, AI-enabled productivity, and sustained organizational performance.
