AI is reshaping how employees manage their time. Here’s the reality today.
AI is creating some serious confusion around time management in the workplace. Depending on the headlines you’re reading, you’re likely to be convinced that it’s either freeing up employees’ time by at least a full working day per week, or that it’s creating additional hours of work.
So, which one is it? A time management problem in which employees engage in performance theater, hiding the actual amount of hours they’re saving by leveraging AI assistance? Or the flipside, in which AI creates additional workload due to its unreliable outputs and constant need for human oversight and governance?
As is often the case, two things can be true at once.
A recent survey of 6,000 full-time digital workers conducted by Glean’s Work AI Institute highlights each side of the coin. On one side, there’s a distinct and emerging behavior referred to by Glean as “botsitting.” Botsitting, as CIO notes, stands for “all the unrecognized work that goes into making AI actually usable.” While another behavior, with a less savory name, involves shipping AI-generated work that is simply not up to snuff. Whether unverified, untrustworthy, or just plain bad, it’s work that has been delivered with little to no human oversight. Both behaviors lead to additional work.
Alarmingly, 69% of workers using AI admitted to shipping low-quality work, and more than 40% said they sometimes deliver work they wouldn’t even be able to explain or defend if asked. Meanwhile, nearly 30% pass the buck and blame AI for mistakes in their work. That’s even more startling when the numbers show that 75% of the same workers said they save about 11 hours per week with AI. Could that time savings stem from a lack of human oversight?
This tracks with a recent BetterUp survey, which found that nearly 54% of managers report receiving AI workslop, “content that appears polished but lacks real substance.” Moreover, it turns out many employees trained in AI are using it in ways that potentially create regulatory problems for their organizations. A recent LexisNexis report found that 74% of AI-savvy employees use unauthorized tools, versus just 17% of untrained employees.
Situations like this signal a clear culture disconnect within the organization. Employees look to company leaders to set the tone, and if AI red lines are not communicated often and with clarity, employees are more likely to use AI in ways that benefit them personally, potentially putting the organization at risk. Recent research from SSRN notes a 2025 study that found a significant governance gap: “While 89% of organizations have implemented some form of policies or controls to restrict or monitor AI access to sensitive data, only 52% claim to have comprehensive controls in place.”
A recent Gallup study of 23,717 U.S. employees backs this sentiment when it found that managerial support of AI use plays an undeniable role in how employees use it. “Employees also report several concerns that may discourage them from using AI even when tools are available. Questions about usefulness, ethics and data security, along with established work habits, can influence whether employees experiment with AI and how frequently they incorporate it into their work,” the report notes. Gallup also revealed that nearly 50% of employees do not agree that their organizations have clear guidelines and policies on how to use AI safely and securely. As Gallup points out, these findings “suggest that concerns about the usefulness and the ethics of AI remain the most significant barriers to initial adoption.”
These numbers signal a clear need for better governance policies and ongoing awareness of those policies for employees. Company leaders should make it easy for their teams to access AI red lines, encourage experimentation within these boundaries, and create accountability around final outputs/deliverables. In terms of whether or not AI is truly a time saver, it will largely depend on your industry and how AI is genuinely being deployed. That said, human oversight remains imperative and should not be cut to justify productivity gains at the cost of low-quality outcomes.
What we’ve experienced so far at Brightly in our AI-assisted work is not that it’s collectively saving our employees days worth of time but is instead improving product quality. Leveraging AI in strategic ways that provide support to our teams rather than using it to cut back on hours or talent has resulted in fewer support issues.
In one of my recent conversations with our Development Director, Erik Harman, he noted how helpful this strategy has been in arming our developers with robust insights and empowering them to ideate in ways they otherwise may have overlooked. “Using AI as a sounding board to gain insight into uncommented or older code, or even as a new-to-a-codebase developer, being able to quickly gain an understanding of what is going on, what changes need to be made, and also being able to have AI look for what you’ve missed, is invaluable,” Erik said. “But AI can be wrong, that’s why we still keep humans in the loop.”
To Erik’s point, leaders grappling with the grey area between AI and productivity gains versus losses can benefit from emphasizing the importance of quality over time saved. Employees at every level should understand the critical factor of human oversight and should always be able to explain and defend their work.